LMU BioDB 2017 - User contributions [en]

Page Desiigner

2017-12-15T19:36:37Z

Mbalducc: /* Mary */

[[Category:Page Desiigner]]
[[Category:Group Projects]]

==Page Design Team Members==
Coder: [[User:ArashLari|Arash Lari]]
 
Project Manager/ Quality Assurance: [[User:hhinsch|Hayden Hinsch]]
 
Data Analyst: [[User:Mbalducc|Mary Balducci]]
 
Designer: [[User:Nicolekalcic|Nicole Kalcic]]

==Page Desiigner Deliverables Page==

[[Page Desiigner Deliverables Page]]

==Team Schedule==
[[Page Desiigner Schedule]]

==Page Desiigner Uploaded Files==

[[Media:MaryHaydenWeek12JournalClubPresentation.pptx ‎]]
 
[[File:Data Driven Design.zip]]
 
[[File:Pagedesignprototype.zip]]
 
[[File:BiodbPageDesignFinalPresentation_.pptx]]

==Page Layout==
*<code>Below are a series of rough ideas we will use to create the layout of the page</code>
[[File:ACT1screenshot.png|500px]]
*We will be using a layout similar to the ACT1 gene page.
[[File:Sketchofpagedesign.png]]
*This is a rough sketch of what the page will look like.
*The section labeled '''description''' on the sketch will include the following:
**Gene ID from each database
**Description/Function (ensembl)
*Within the dropdown menus we will be incorporating the following:
**DNA Sequence (ensembl)
**Protein Sequence (UniProt)
**Locus tag (NCBI)
**Also Known As (NCBI)
**Consensus Sequence (JASPAR)
**Regulation (SGD)
**Interaction (SGD)
**Similar Proteins (UniProt)
**Gene Ontology (SGD)
**JASPAR
***Matrix ID
***Class Heat shock factors
***Family HSF factors
***Sequence Logo
***Frequency Matrix
*A zip file containing the html file of prototype page can be downloaded by clicking the <code>pagedesignprototype.zip</code> link below.
[[File:Pagedesignprototype.zip]]

==Annotated Bibliography==
===Mary's contribution:===
Pizzaro, Jewett, Nielson, Agosin. (2008) Growth Temperature Exerts Differential Physiological and Transcriptional Responses in Laboratory and Wine Strains of Saccharomyces Cerevisiae. "Applied and Environmental Microbiology", 74, 6358-6368, doi:10.1128/AEM.00602-08
*PubMed Abstract: https://www.ncbi.nlm.nih.gov/pubmed/18723660
*PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2570279/
*HTML format: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2570279/
*PDF format: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2570279/pdf/0602-08.pdf
*Copyright: 2008 American Society for Microbiology. It is open access.
*Publisher: American Society for Microbiology. This is a scientific society.
*Availability: Online and in print
*Did LMU pay a fee for this article: No
*I could not find the data associated with this article.

Homma, Iwahashi, Komatsu. (2003) Yeast Gene Expression During Growth at Low Temperature. ''Cryobiology'', 46, doi: 10.1016/S0011-2240(03)00028-2
*PubMed abstract: https://www.ncbi.nlm.nih.gov/pubmed/12818212
*PubMed Central:
*HTML format: http://www.sciencedirect.com/science/article/pii/S0011224003000282?via%3Dihub
*PDF format: https://ac.els-cdn.com/S0011224003000282/1-s2.0-S0011224003000282-main.pdf?_tid=aa7fa05e-c5d2-11e7-88ae-00000aacb361&acdnat=1510289609_6ec25501ce7af9dcc6b521ef8a024164
*Copyright 2003 Elsevier Science (USA). It is open access.
*Publisher: Elsevier. This is a for-profit publisher
*Availability: Online and in print
*Did LMU pay a fee for this article: No
*I could not find the data associated with this article.

===Hayden's Contribution===

Dahlquist, K. D., Fitzpatrick, B. G., Camacho, E. T., Entzminger, S. D., & Wanner, N. C. (2015). Parameter Estimation for Gene Regulatory Networks from Microarray Data: Cold Shock Response in Saccharomyces cerevisiae. Bulletin of Mathematical Biology, 77(8), 1457–1492. http://doi.org/10.1007/s11538-015-0092-6
* PubMed Abstract: https://www.ncbi.nlm.nih.gov/pubmed/26420504
* PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4636536/
* Publisher Full Text (HTML): https://link.springer.com/article/10.1007/s11538-015-0092-6
* Publisher Full Text (PDF): https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4636536/pdf/11538_2015_Article_92.pdf
* Copyright: The Author(s) 2015. Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
* Publisher: Bulletin of Mathematical Biology(scientific society)
* Availability: Online
* Did LMU pay a fee for this article: No
* Data: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4636536/bin/11538_2015_92_MOESM1_ESM.zip

Ando, A., Nakamura, T., Murata, Y., Takagi, H. and Shima, J. (2007), Identification and classification of genes required for tolerance to freeze–thaw stress revealed by genome-wide screening of Saccharomyces cerevisiae deletion strains. FEMS Yeast Research, 7: 244–253. doi:10.1111/j.1567-1364.2006.00162.x
* PubMed Abstract: https://www.ncbi.nlm.nih.gov/pubmed/16989656
* PubMed Central: N/A
* Publisher Full Text (HTML): https://academic.oup.com/femsyr/article/7/2/244/616825?searchresult=1
* Publisher Full Text (PDF): http://onlinelibrary.wiley.com/doi/10.1111/j.1567-1364.2006.00162.x/epdf
* Copyright: Copyright © 2007, Oxford University Press; Open Access after time has elapsed: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. You must ask permission from the publisher to use the article.
* Publisher: Published by Oxford University Press(respected open access organization)
* Availability: Online and in print
* Did LMU pay a fee for this article: No
* Data: I couldn't find any supplementary data other than the data provided in the article.

==Journal Club Presentations==
===Powerpoint Slides and Respective Articles===
[[File:Data Driven Design.zip]]
* Liikkanen, L. (2017). The Data-Driven Design Era in Professional Web Design. Accessed November 13, 2017, from http://delivery.acm.org/10.1145/3130000/3121355/p52-liikkanen.pdf?ip=157.242.223.254&id=3121355&acc=ACTIVE%20SERVICE&key=80B0E63637265656%2E958C566062FD1C18%2E4D4702B0C3E38B35%2E4D4702B0C3E38B35&CFID=829067610&CFTOKEN=20249523&__acm__=1510614806_1e8b314e23f771f9b139d99596801365
 
[[Media:MaryHaydenWeek12JournalClubPresentation.pptx ‎]]
*Pizzaro, Jewett, Nielson, Agosin. (2008) Growth Temperature Exerts Differential Physiological and Transcriptional Responses in Laboratory and Wine Strains of Saccharomyces Cerevisiae. "Applied and Environmental Microbiology", 74, 6358-6368, doi:10.1128/AEM.00602-08

==Executive Summaries==

===[[Week 11]] Executive Summaries===
====Arash====
This week, I worked on researching the given article and the development terms within it as well as prepare a presentation on the article. I also began thinking of some page layout ideas with Nicole to prepare to implement in the coming weeks. All of this information could be found on my Week 11 page: [[ArashLari_Week_11|ArashLari Week 11]].
[[User:ArashLari|ArashLari]] ([[User talk:ArashLari|talk]]) 02:09, 14 November 2017 (PST)
====Mary====
This week, I worked on creating an annotated bibliography. The articles I found were primary sources about experiments done involving cold shock on yeast, and the use of microarrays to show results. I used multiple databases to find these articles, and while doing so I learned what key words got me the results closest to what I wanted. While writing the annotated bibliography, I also learned more about the articles, such as when they were written, who published them, what kind of publisher they are, and other information. All of this is recorded in my [[mbalducc Week 11| Week 11]] page.

[[User:Mbalducc|Mbalducc]] ([[User talk:Mbalducc|talk]]) 23:03, 13 November 2017 (PST)

====Nicole====
This past week, I read the article ''The Data-Driven Design Era in Professional Web Design'' by L.A. Liikkanen. This allowed me to complete my individual journal: an informative outline of the article and list of ten definitions. Arash and I worked together to complete a 15 minute presentation that we are going to give on Tuesday. The presentation gives an overview of our individual journals and what we each learned. You can access more information on what I did this week here: [[Nicolekalcic Week 11]].
[[User:Nicolekalcic|Nicolekalcic]] ([[User talk:Nicolekalcic|talk]]) 01:27, 14 November 2017 (PST)
====Hayden====
This week I created part of the annotated bibliography we will be using for our final project. I conducted searched for "yeast cold shock microarray" articles and found which two articles I was going to use for the bibliography. The majority of the time this week was spent on finding the information needed for the annotated bibliography which can be found below on this page. More detailed information can be found on my [[hhinsch Week 11]] page. This week I became proficient in finding reliable article to use for our final project. This week we also created the group's template and wiki page. [[User:Hhinsch|Hhinsch]] ([[User talk:Hhinsch|talk]]) 22:43, 13 November 2017 (PST)

===[[Week 12]] Executive Summaries===
====Arash====
This week was rather light compared to the previous week. We mostly set up the files on our personal computers, which was convenient because as a computer science major I already had most of the necessary files. Nicole and I talked about some preliminary designs and set up a rough schedule that we'll make concrete after the break. This can be found on my week 12 page [[ArashLari Week 12] | Arash Lari Week 12]. [[User:ArashLari|ArashLari]] ([[User talk:ArashLari|talk]]) 20:43, 20 November 2017 (PST)

====Mary====
This week I read an article about an experiment done on wine and lab strains of yeast in different temperatures. The experimenters used DNA microarrays to determine which genes were affected by the change in temperatures and which were different based on the different strains of yeast. While reading the article, I can across words I had never seen before, so I also found and recorded the definitions of these words. I then made an outline of the article, to use as a basis for my presentation with our project manager, [[user:hhinsch| Hayden]]. All of this is on my [[mbalducc Week 12| Week 12]] page.

[[User:Mbalducc|Mbalducc]] ([[User talk:Mbalducc|talk]]) 19:51, 19 November 2017 (PST)

====Nicole====
Because Arash and I presented last week, we didn't have a heavy work load this week. Arash explained a lot of technical things to me, and we completed the first coding milestones and talked about design possibilities. I officially have a GitHub (nicolekal). I also downloaded the software I needed but didn't have onto my laptop. A full update can be found on: [[Nicolekalcic Week 12] | Nicole Kalcic Week 12]. [[User:Nicolekalcic|Nicolekalcic]] ([[User talk:Nicolekalcic|talk]]) 23:45, 20 November 2017 (PST)

====Hayden====
This week I worked with Mary specifically in order to complete our journal club presentation. As a group we worked together to make corrections to the [[Page Desiigner]] group page in order to complete the deliverables for this week. Mary and I created a schedule for our group along with helpful links. As a class we decided we will be using WhatsApp to communicate. I spent most of this week outlining the article (it was a pretty difficult read) and defining terms on my [[hhinsch Week 12]] page. [[User:Hhinsch|Hhinsch]] ([[User talk:Hhinsch|talk]]) 17:42, 20 November 2017 (PST)

===[[Week 14]] Executive Summaries===
====Arash====
This week I worked on implementing our designs for the web page. Nicole and Hayden helped come up with some design ideas. We ended up deciding that ACT1 was a very well designed page and that it would be best to follow the format of that page. There's only a few things left to do but our portion of the project is nearly complete, the generic version of every gene's page needs just a few finishing touches. [[User:ArashLari|ArashLari]] ([[User talk:ArashLari|talk]]) 18:19, 4 December 2017 (PST)

====Mary====
This week I finished the Week 10 assignment, using YEASTRACT and GRNsight. I specifically chose one profile from the STEM results to use in YEASTRACT to find transcription factors that regulate a cluster of genes. First I uploaded the genes from profile #22 into YEASTRACT to find 20 significant transcription factors that regulate them. Then, I used Excel to get rid of the transcription factors that were not related to other transcription factors. Once I had those, I imported them into GRNsight to create a map of the transcription factors and their relations to each other. I took a screenshot of this map and uploaded it to my [[mbalducc Week 14| Week 14]] page.

[[User:Mbalducc|Mbalducc]] ([[User talk:Mbalducc|talk]]) 19:14, 4 December 2017 (PST)

====Nicole====

====Hayden====
This week I served as a "floater". I worked with Nicole and Arash in order to come up with how the page design prototype would look. We decided to use the ACT1 design along with Nicole's sketch in order to find a balance between aesthetic and function. The design we used is downloadable from this page and my [[hhinsch Week 14]] page. My [[hhinsch Week 14]] page has some more information regarding why we chose our current prototype design. I also spoke with Mary to make sure she knew I was there to help with her deliverables if needed. I also spent time with the other QA's this week in order to familiarize myself with the deliverables of the other groups. This was necessary for me to make sure we added everything to the page that is required. I uploaded images to my [hhinsch Week 14]] page as well as this page in order to further clarify our thought process behind the page prototype. [[User:Hhinsch|Hhinsch]] ([[User talk:Hhinsch|talk]]) 20:16, 4 December 2017 (PST)

==Team Progress Reflections==

===[[Week 11]] Team Progress Reflections===

====Nicole====
# What worked?
#* We all work well in our positions. Arash and I worked together recently, so it was easy to coordinate what we are going to do as coder and designer. Everyone was open to opinions on the page and team name. Also, everyone communicated what they were having trouble finishing.
# What didn't work?
#* Like Mary said, we weren't able to meet in person. We planned out our meetup during class, but Friday ended up being a busy day for everyone.
# What will I do next to fix what didn't work?
#* Next week I will make sure to check in more with my partners. Even if we don't meet up, it is important to make sure everyone is caught up on the assignment and their individual parts.
====Mary====
# What worked?
#*I think as a team, we did a good job communicating and figuring out what needed to be done, and who would do each part.
# What didn't work?
#*We did not meet up outside of class. We had planned to, but we all ended up having conflicts so we couldn't meet.
# What will I do next to fix what didn't work?
#*I think this can be fixed just by making sure we all communicate in other ways, which is what we did. Through text messages we were able to talk about the assignment and help each other.
====Hayden====
# What worked?
#*We are all doing well communicating and completing our deliverables as individuals and as a group.
# What didn't work?
#*Everything worked well in regards to the group, but I did have some trouble finding all the information needed to create an annotated bibliography for the articles I used. Google Scholar gave me way too many results, and PubMed did not have a lot of articles that were either free or LMU had paid for.
# What will I do next to fix what didn't work?
#*I will continue to ask questions in class. I also feel more confident about finding useful articles after the completion of this assignment, so it shouldn't be a problem.
[[User:Hhinsch|Hhinsch]] ([[User talk:Hhinsch|talk]]) 22:44, 13 November 2017 (PST)

====Arash====

# What worked?
#*We were good at maintaining our own individual tasks and keeping each other updated via text message.

# What didn't work?
#*We were unable to schedule time to meet and work effectively.

# What will I do next to fix what didn't work?
#*Hopefully we will have lighter course loads and more free time for the next assignment, but besides that we will begin working sooner and try to work in person more than digitally.

===[[Week 12]] Team Progress Reflections===

====Arash====
# What worked?
#*I think we all got a better grasp of the assignment and time management for the assignment. We have a clear idea where we're headed.
# What didn't work?
#* I wish we had more time to dedicate to this class, as often our schedules don't line up.
# What will I do next to fix what didn't work?
#*We'll try to be more proactive about all our tasks so they don't pile up. I'm planning on starting some work during the thanksgiving break to lighten the load afterwards.
====Mary====
# What worked?
#*I think that this week I felt more comfortable with the project as a whole. I also liked presenting after the other guilds because I got to see their presentations to get a better idea of what we should include in ours.
# What didn't work?
#*I wish that I had more time to read the article and make the presentation. I felt that I didn't understand the article completely, and had to read it a few times to be happy with the way that I understood it and formed my outline of it. Because of this, I couldn't spend as much time as I would've wanted on making the presentation.
# What will I do next to fix what didn't work?
#*I will try to spend more time on the entire project, instead of just one part.

====Nicole====
#What Worked?
#*Arash and I communicated via text and had a better idea of what we needed to do earlier on in the week, which made it easier to progress and do quality, time efficient work.
#What didn't work?
#*We weren't all able to meet in person. I don't know if this was a huge issue this week, but scheduling conflicts might become more of a problem in December.
#What will I do next week to fix what didn't work?
#*Next week I will try to make plans with the group on Tuesday. I am assuming everyone is going out of town for Thanksgiving, but perhaps we can make certain dates within the week to have things done by so the rest of the group can look over the work.

====Hayden====
#What Worked?
#*This week we were a little more prepared to work together and complete the deliverables. As time goes by the end goal is becoming more apparent.
#What didn't work?
#*I spent a lot of time reading the article multiple times and it is still a bit confusing to me. A lot of the vocabulary wasn't even found in the dictionaries we provided and a lot of the information needed a lot of background knowledge to comprehend.
#What will I do next week to fix what didn't work?
#*Next week I will try and do the bulk of the assignment earlier in the week rather than on the weekend, so I may have more time to understand the material.[[User:Hhinsch|Hhinsch]] ([[User talk:Hhinsch|talk]]) 21:09, 20 November 2017 (PST)

===[[Week 14]] Team Progress Reflections===

====Arash====
# What worked?
#* Our design idea turned out pretty nicely, and was not that difficult to implement.
# What didn't work?
#* Coming up with what the final aesthetics will look like.
# What will I do next to fix what didn't work?
#* We will discuss the matter in class with the professors and our fellow students to see what works best for everyone.

====Mary====
#What worked?
#*Using YEASTRACT, Excel, and GRNsight to create a map of significant transcription factors in the profile I chose.
#What didn't work?
#*I have not fixed Weeks 8 and 10 as much as I would have wanted to.
#What will I do next to fix what didn't work?
#*Take more time, make sure I do things right the first time so I don't have to back and fix them later.

====Hayden====
# What worked?
#* We did a pretty good job getting everything done we needed to get done this week in a timely fashion while dealing with adversity.
# What didn't work?
#* We still need to complete the prototype and add the other groups' deliverables to our page.
# What will I do next to fix what didn't work?
#* We just simply need to take a final assessment of the deliverables as well as gather feedback from the entire class regarding the final layout of the page.

====Nicole====
# What worked?
#* We completed the basic structure of the page, and everyone was able to finish their work in time despite my absence on Thursday.
# What didn't work?
#* We haven't finalized anything yet, or implemented any information into the page.
# What will I do next to fix what didn't work?
#* We will talk with everyone in class, including the Dahlquist and Dionisio in order to make final decisions moving into Week 15.

===[[Week 15]] Team Progress Reflections===
====Arash====
This week I worked on adding the finishing touches to our info.html file in order to make the information easier to digest and nicer to look at. I also worked on my parts of the group presentation and report, which basically entailed me writing out, in detail, everything I did for the GRNsight project. I also wrote an individual statement of work that I emailed to the professors.
[[User:ArashLari|ArashLari]] ([[User talk:ArashLari|talk]]) 22:44, 14 December 2017 (PST)
[[ArashLari_Week_15|ArashLari Week 15]]
====Hayden====
This week I helped complete the final presentation for our team as well as the final paper. I made sure all of the deliverables were accurately produced as well as formulates the final presentation and final paper layout. In regards to what worked and what didn't work, everything was completed on time and we all communicated fairly effectively so I don't have anything to note on. Our deliverables can be found on my [[Page Desiigner Deliverables Page]] page. A More detailed summary of work can be found on my [[hhinsch Week 15]] page. [[User:Hhinsch|Hhinsch]] ([[User talk:Hhinsch|talk]]) 06:21, 15 December 2017 (PST)

====Mary====
This week I finished analyzing the data from Dr. Dahlquist's lab. I used YEASTRACT and GRNSight to create a gene regulation matrix of the significant transcription factors and then made them into a visual map which showed the interactions between the genes. I also help create a powerpoint for our team so that we could present on the work that we've done in the last few weeks. My [[mbalducc Week 15|Week 15]] page outlines this as well.

[[User:Mbalducc|Mbalducc]] ([[User talk:Mbalducc|talk]]) 11:36, 15 December 2017 (PST)

====Nicole====
This week, I helped format the presentation. I also completed my part of the group paper. In addition, I created a logo for GRNSight on Adobe Illustrator. Arash wanted a bar for the top of the page that had a small logo on it. This was done as a scalable vector graphic and then emailed to Arash.
[[User:Nicolekalcic|Nicolekalcic]] ([[User talk:Nicolekalcic|talk]]) 10:32, 15 December 2017 (PST)
{{Pagedesiigner}}

Page Desiigner Deliverables Page

2017-12-12T04:49:49Z

Mbalducc: /* Data Analyst Deliverables */ changed input file

== Deliverables Checklist ==

# Organized Team deliverables wiki page (or other media (CD or flash drive) with table of contents)
# Group Report (''.doc'', ''.docx'' or ''.pdf'' file)
# Individual statements of work, assessments, reflections (wiki page, ''.doc'', ''.docx'', ''.pdf'', or e-mailed to both Dr. Dahlquist and Dr. Dionisio)
# Group PowerPoint presentation (given on Tuesday, December 12, ''.ppt'', ''.pptx'' or ''.pdf'' file)
# Code (GitHub pull request)
#* Each team should coordinate in performing a final integration and integration testing iteration (see [[Coder]] milestone for details) which the Interaction and Integration team then submits to the ''original'' GRNsight GitHub repository as a single, unified pull request from the class project’s fork
# Supply a README that summarizes the functionality of your team's new feature (''.txt'' or ''.md'', ''one README per team'')
# Excel spreadsheet with ANOVA results/stem formatting (''.xlsx'')
# PowerPoint of screenshots of stem results (''.pptx'')
# Gene List and GO List files from each significant profile (''.txt'' compressed together in a ''.zip'' file)
# YEASTRACT "rank by TF" results (''.xlsx'')
# GRNmap input workbook (with network adjacency matrix, ''.xlsx'')
# GRNmap output workbook (''.xlsx'')
# Electronic notebook corresponding to these the microarray results files ([[Week 8]], [[Week 10]], and Weeks 11-15) support ''reproducible research'' so that all manipulations of the data and files are documented so that someone else could begin with your starting file, follow the protocol, and obtain your results.

===Data Analyst Deliverables===
#[[Media:Mbalducc_week8_dCIN5.zip|Excel file for the ANOVA of dCIN5]]
#[[media:Mbalducc_STEMprofiles.pdf| PowerPoint of STEM profiles and Gene Regulatory Network from GRNsight]]
#[[media:Mbalduccgene&GOlists.zip|Gene lists and GO lists]]
#[[media:Mbalducc_Profile_22_yeastract_data.xlsx| Excel Sheet of Profile #22 from YEASTRACT "Rank by TF" results]]
#[[media:17-genes_19-edges_team-hAPI_Sigmoid_estimation.xlsx|GRNmap input Workbook]]
#[[media:Mbalducc_GRNmapoutputfiles.zip|GRNmap output files]]

'''My electronic notebooks that outline the process I followed:'''
*[[mbalducc Week 8|Week 8]]
*[[mbalducc Week 10|Week 10]]
*[[mbalducc Week 11|Week 11]]
*[[mbalducc Week 12|Week 12]]
*[[mbalducc Week 14|Week 14]]

[[User:Mbalducc|Mbalducc]] ([[User talk:Mbalducc|talk]]) 12:39, 11 December 2017 (PST)

{{pagedesiigner}}

Page Desiigner Deliverables Page

2017-12-11T20:39:01Z

Mbalducc: /* Data Analyst Deliverables */ added signature

== Deliverables Checklist ==

# Organized Team deliverables wiki page (or other media (CD or flash drive) with table of contents)
# Group Report (''.doc'', ''.docx'' or ''.pdf'' file)
# Individual statements of work, assessments, reflections (wiki page, ''.doc'', ''.docx'', ''.pdf'', or e-mailed to both Dr. Dahlquist and Dr. Dionisio)
# Group PowerPoint presentation (given on Tuesday, December 12, ''.ppt'', ''.pptx'' or ''.pdf'' file)
# Code (GitHub pull request)
#* Each team should coordinate in performing a final integration and integration testing iteration (see [[Coder]] milestone for details) which the Interaction and Integration team then submits to the ''original'' GRNsight GitHub repository as a single, unified pull request from the class project’s fork
# Supply a README that summarizes the functionality of your team's new feature (''.txt'' or ''.md'', ''one README per team'')
# Excel spreadsheet with ANOVA results/stem formatting (''.xlsx'')
# PowerPoint of screenshots of stem results (''.pptx'')
# Gene List and GO List files from each significant profile (''.txt'' compressed together in a ''.zip'' file)
# YEASTRACT "rank by TF" results (''.xlsx'')
# GRNmap input workbook (with network adjacency matrix, ''.xlsx'')
# GRNmap output workbook (''.xlsx'')
# Electronic notebook corresponding to these the microarray results files ([[Week 8]], [[Week 10]], and Weeks 11-15) support ''reproducible research'' so that all manipulations of the data and files are documented so that someone else could begin with your starting file, follow the protocol, and obtain your results.

===Data Analyst Deliverables===
#[[Media:Mbalducc_week8_dCIN5.zip|Excel file for the ANOVA of dCIN5]]
#[[media:Mbalducc_STEMprofiles.pdf| PowerPoint of STEM profiles and Gene Regulatory Network from GRNsight]]
#[[media:Mbalduccgene&GOlists.zip|Gene lists and GO lists]]
#[[media:Mbalducc_Profile_22_yeastract_data.xlsx| Excel Sheet of Profile #22 from YEASTRACT "Rank by TF" results]]
#[[media:Mbalducc_profile 22_RegulationMatrix_Documented_2017.xlsx|GRNmap input Workbook]]
#[[media:Mbalducc_GRNmapoutputfiles.zip|GRNmap output files]]

'''My electronic notebooks that outline the process I followed:'''
*[[mbalducc Week 8|Week 8]]
*[[mbalducc Week 10|Week 10]]
*[[mbalducc Week 11|Week 11]]
*[[mbalducc Week 12|Week 12]]
*[[mbalducc Week 14|Week 14]]

[[User:Mbalducc|Mbalducc]] ([[User talk:Mbalducc|talk]]) 12:39, 11 December 2017 (PST)

{{pagedesiigner}}

Page Desiigner Deliverables Page

2017-12-08T17:44:56Z

Mbalducc: /* Data Analyst Deliverables */ added output files

== Deliverables Checklist ==

# Organized Team deliverables wiki page (or other media (CD or flash drive) with table of contents)
# Group Report (''.doc'', ''.docx'' or ''.pdf'' file)
# Individual statements of work, assessments, reflections (wiki page, ''.doc'', ''.docx'', ''.pdf'', or e-mailed to both Dr. Dahlquist and Dr. Dionisio)
# Group PowerPoint presentation (given on Tuesday, December 12, ''.ppt'', ''.pptx'' or ''.pdf'' file)
# Code (GitHub pull request)
#* Each team should coordinate in performing a final integration and integration testing iteration (see [[Coder]] milestone for details) which the Interaction and Integration team then submits to the ''original'' GRNsight GitHub repository as a single, unified pull request from the class project’s fork
# Supply a README that summarizes the functionality of your team's new feature (''.txt'' or ''.md'', ''one README per team'')
# Excel spreadsheet with ANOVA results/stem formatting (''.xlsx'')
# PowerPoint of screenshots of stem results (''.pptx'')
# Gene List and GO List files from each significant profile (''.txt'' compressed together in a ''.zip'' file)
# YEASTRACT "rank by TF" results (''.xlsx'')
# GRNmap input workbook (with network adjacency matrix, ''.xlsx'')
# GRNmap output workbook (''.xlsx'')
# Electronic notebook corresponding to these the microarray results files ([[Week 8]], [[Week 10]], and Weeks 11-15) support ''reproducible research'' so that all manipulations of the data and files are documented so that someone else could begin with your starting file, follow the protocol, and obtain your results.

===Data Analyst Deliverables===
#[[Media:Mbalducc_week8_dCIN5.zip|Excel file for the ANOVA of dCIN5]]
#[[media:Mbalducc_STEMprofiles.pdf| PowerPoint of STEM profiles and Gene Regulatory Network from GRNsight]]
#[[media:Mbalduccgene&GOlists.zip|Gene lists and GO lists]]
#[[media:Mbalducc_Profile_22_yeastract_data.xlsx| Excel Sheet of Profile #22 from YEASTRACT "Rank by TF" results]]
#[[media:Mbalducc_profile 22_RegulationMatrix_Documented_2017.xlsx|GRNmap input Workbook]]
#[[media:Mbalducc_GRNmapoutputfiles.zip|GRNmap output files]]

'''My electronic notebooks that outline the process I followed:'''
*[[mbalducc Week 8|Week 8]]
*[[mbalducc Week 10|Week 10]]
*[[mbalducc Week 11|Week 11]]
*[[mbalducc Week 12|Week 12]]
*[[mbalducc Week 14|Week 14]]
{{pagedesiigner}}

File:Mbalducc GRNmapoutputfiles.zip

2017-12-08T17:44:33Z

Mbalducc:

Mbalducc Week 15

2017-12-07T23:55:14Z

Mbalducc: /* Electronic Notebook */ adde notes

=Electronic Notebook=
*This week, I checked with Dr. Dahlquist to make sure that my Gene Regulation data was good to be put into a weighted model in GRNsight.
*I also uploaded all of my current deliverables onto the [[Page Desiigner Deliverables Page]].
*Ran my files through MatLab to obtain an output file to load into GRNsight to that weights and expression changes could be viewed in the GRNmap.

=Acknowledgements=
I worked with the other members of the [[Data Analysis]]: [[User:Aporras1|Antonio Porras]], [[User:dbashour|Dina Bashoura]], and [[User:Emmatyrnauer|Emma Tyrnauer]] on this assignment. We spoke in class and over text about what we needed to do for the project.

=References=

LMU BioDB 2017. (2017). Week 15 Retrieved December 7, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_15

Mbalducc Week 15

2017-12-07T23:14:20Z

Mbalducc: added acknowledgements and ref

=Electronic Notebook=
*This week, I checked with Dr. Dahlquist to make sure that my Gene Regulation data was good to be put into a weighted model in GRNsight.
*I also uploaded all of my current deliverables onto the [[Page Desiigner Deliverables Page]].
*

=Acknowledgements=
I worked with the other members of the [[Data Analysis]]: [[User:Aporras1|Antonio Porras]], [[User:dbashour|Dina Bashoura]], and [[User:Emmatyrnauer|Emma Tyrnauer]] on this assignment. We spoke in class and over text about what we needed to do for the project.

=References=

LMU BioDB 2017. (2017). Week 15 Retrieved December 7, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_15

Mbalducc Week 15

2017-12-07T23:09:55Z

Mbalducc: added notes

Template:Mbalducc

2017-12-07T23:05:08Z

Mbalducc: /* Other Pages */ added pages

= Other Pages =

=== Individual Journals ===

[[user:mbalducc|Mary Balducci]]

[[mbalducc Week 2|Week 2 Journal]]

[[mbalducc Week 3|Week 3 Journal]]

[[mbalducc Week 4|Week 4 Journal]]

[[The Comprehensive Antibiotic Resistance Database|Week 5 Journal]]

[[mbalducc Week 6| Week 6 Journal]]

[[mbalducc Week 7|Week 7 Journal]]

[[mbalducc Week 8|Week 8 Journal]]

[[mbalducc Week 9|Week 9 Journal]]

[[mbalducc Week 10|Week 10 Journal]]

[[mbalducc Week 11|Week 11 Journal]]

[[mbalducc Week 12|Week 12 Journal]]

No Assignment Week 13

[[mbalducc Week 14|Week 14 Journal]]

[[mbalducc Week 15|Week 15 Journal]]

=== Assignments ===

[[Week 1|Week 1 Assignment]]

[[Week 2|Week 2 Assignment]]

[[Week 3|Week 3 Assignment]]

[[Week 4|Week 4 Assignment]]

[[Week 5|Week 5 Assignment]]

[[Week 6|Week 6 Assignment]]

[[Week 7|Week 7 Assignment]]

[[Week 8|Week 8 Assignment]]

[[Week 9|Week 9 Assignment]]

[[Week 10|Week 10 Assignment]]

[[Week 11|Week 11 Assignment]]

[[Week 12|Week 12 Assignment]]

No Assignment Week 13

[[Week 14|Week 14 Assignment]]

[[Week 15|Week 15 Assignment]]

=== Shared Journals ===

[[Class Journal Week 1]]

[[Class Journal Week 2]]

[[Class Journal Week 3]]

[[Class Journal Week 4]]

[[Class Journal Week 5]]

[[Class Journal Week 6]]

[[Class Journal Week 7]]

[[Class Journal Week 8]]

[[Class Journal Week 9]]

[[Class Journal Week 10]]

[[Page Desiigner]]

[[Category: Journal Entry]]

Page Desiigner Deliverables Page

2017-12-06T01:32:05Z

Mbalducc: /* Data Analyst Deliverables */

== Deliverables Checklist ==

# Organized Team deliverables wiki page (or other media (CD or flash drive) with table of contents)
# Group Report (''.doc'', ''.docx'' or ''.pdf'' file)
# Individual statements of work, assessments, reflections (wiki page, ''.doc'', ''.docx'', ''.pdf'', or e-mailed to both Dr. Dahlquist and Dr. Dionisio)
# Group PowerPoint presentation (given on Tuesday, December 12, ''.ppt'', ''.pptx'' or ''.pdf'' file)
# Code (GitHub pull request)
#* Each team should coordinate in performing a final integration and integration testing iteration (see [[Coder]] milestone for details) which the Interaction and Integration team then submits to the ''original'' GRNsight GitHub repository as a single, unified pull request from the class project’s fork
# Supply a README that summarizes the functionality of your team's new feature (''.txt'' or ''.md'', ''one README per team'')
# Excel spreadsheet with ANOVA results/stem formatting (''.xlsx'')
# PowerPoint of screenshots of stem results (''.pptx'')
# Gene List and GO List files from each significant profile (''.txt'' compressed together in a ''.zip'' file)
# YEASTRACT "rank by TF" results (''.xlsx'')
# GRNmap input workbook (with network adjacency matrix, ''.xlsx'')
# GRNmap output workbook (''.xlsx'')
# Electronic notebook corresponding to these the microarray results files ([[Week 8]], [[Week 10]], and Weeks 11-15) support ''reproducible research'' so that all manipulations of the data and files are documented so that someone else could begin with your starting file, follow the protocol, and obtain your results.

===Data Analyst Deliverables===
#[[Media:Mbalducc_week8_dCIN5.zip|Excel file for the ANOVA of dCIN5]]
#[[media:Mbalducc_STEMprofiles.pdf| PowerPoint of STEM profiles and Gene Regulatory Network from GRNsight]]
#[[media:Mbalduccgene&GOlists.zip|Gene lists and GO lists]]
#[[media:Mbalducc_Profile_22_yeastract_data.xlsx| Excel Sheet of Profile #22 from YEASTRACT "Rank by TF" results]]
#[[media:Mbalducc_profile 22_RegulationMatrix_Documented_2017.xlsx|GRNmap input Workbook]]
#GRNmap output workbook

'''My electronic notebooks that outline the process I followed:'''
*[[mbalducc Week 8|Week 8]]
*[[mbalducc Week 10|Week 10]]
*[[mbalducc Week 11|Week 11]]
*[[mbalducc Week 12|Week 12]]
*[[mbalducc Week 14|Week 14]]
{{pagedesiigner}}

Page Desiigner Deliverables Page

2017-12-06T01:29:24Z

Mbalducc: /* Data Analyst Deliverables */ added deliverables

== Deliverables Checklist ==

# Organized Team deliverables wiki page (or other media (CD or flash drive) with table of contents)
# Group Report (''.doc'', ''.docx'' or ''.pdf'' file)
# Individual statements of work, assessments, reflections (wiki page, ''.doc'', ''.docx'', ''.pdf'', or e-mailed to both Dr. Dahlquist and Dr. Dionisio)
# Group PowerPoint presentation (given on Tuesday, December 12, ''.ppt'', ''.pptx'' or ''.pdf'' file)
# Code (GitHub pull request)
#* Each team should coordinate in performing a final integration and integration testing iteration (see [[Coder]] milestone for details) which the Interaction and Integration team then submits to the ''original'' GRNsight GitHub repository as a single, unified pull request from the class project’s fork
# Supply a README that summarizes the functionality of your team's new feature (''.txt'' or ''.md'', ''one README per team'')
# Excel spreadsheet with ANOVA results/stem formatting (''.xlsx'')
# PowerPoint of screenshots of stem results (''.pptx'')
# Gene List and GO List files from each significant profile (''.txt'' compressed together in a ''.zip'' file)
# YEASTRACT "rank by TF" results (''.xlsx'')
# GRNmap input workbook (with network adjacency matrix, ''.xlsx'')
# GRNmap output workbook (''.xlsx'')
# Electronic notebook corresponding to these the microarray results files ([[Week 8]], [[Week 10]], and Weeks 11-15) support ''reproducible research'' so that all manipulations of the data and files are documented so that someone else could begin with your starting file, follow the protocol, and obtain your results.

===Data Analyst Deliverables===
#[[Media:Mbalducc_week8_dCIN5.zip|Excel file for the ANOVA of dCIN5]]
#[[media:Mbalducc_STEMprofiles.pdf| PowerPoint of STEM profiles and Gene Regulatory Network from GRNsight]]
#[[media:Mbalduccgene&GOlists.zip|Gene lists and GO lists]]
#[[media:Mbalducc_Profile_22_yeastract_data.xlsx| Excel Sheet of Profile #22 from YEASTRACT "Rank by TF" results]]
#[[media:Mbalducc_profile 22_RegulationMatrix_Documented_2017.xlsx|GRNmap input Workbook]]
#

'''My electronic notebooks that outline the process I followed:'''
*[[mbalducc Week 8|Week 8]]
*[[mbalducc Week 10|Week 10]]
*[[mbalducc Week 11|Week 11]]
*[[mbalducc Week 12|Week 12]]
*[[mbalducc Week 14|Week 14]]
{{pagedesiigner}}

Page Desiigner Deliverables Page

2017-12-06T01:26:02Z

Mbalducc: added deliverables

== Deliverables Checklist ==

# Organized Team deliverables wiki page (or other media (CD or flash drive) with table of contents)
# Group Report (''.doc'', ''.docx'' or ''.pdf'' file)
# Individual statements of work, assessments, reflections (wiki page, ''.doc'', ''.docx'', ''.pdf'', or e-mailed to both Dr. Dahlquist and Dr. Dionisio)
# Group PowerPoint presentation (given on Tuesday, December 12, ''.ppt'', ''.pptx'' or ''.pdf'' file)
# Code (GitHub pull request)
#* Each team should coordinate in performing a final integration and integration testing iteration (see [[Coder]] milestone for details) which the Interaction and Integration team then submits to the ''original'' GRNsight GitHub repository as a single, unified pull request from the class project’s fork
# Supply a README that summarizes the functionality of your team's new feature (''.txt'' or ''.md'', ''one README per team'')
# Excel spreadsheet with ANOVA results/stem formatting (''.xlsx'')
# PowerPoint of screenshots of stem results (''.pptx'')
# Gene List and GO List files from each significant profile (''.txt'' compressed together in a ''.zip'' file)
# YEASTRACT "rank by TF" results (''.xlsx'')
# GRNmap input workbook (with network adjacency matrix, ''.xlsx'')
# GRNmap output workbook (''.xlsx'')
# Electronic notebook corresponding to these the microarray results files ([[Week 8]], [[Week 10]], and Weeks 11-15) support ''reproducible research'' so that all manipulations of the data and files are documented so that someone else could begin with your starting file, follow the protocol, and obtain your results.

===Data Analyst Deliverables===
#[[Media:Mbalducc_week8_dCIN5.zip|Excel file for the ANOVA of dCIN5]]
#[[media:Mbalducc_STEMprofiles.pdf| PowerPoint of STEM profiles and Gene Regulatory Network from GRNsight]]
#[[media:Mbalduccgene&GOlists.zip|Gene lists and GO lists]]
#[[media:Mbalducc_Profile_22_yeastract_data.xlsx| Excel Sheet of Profile #22 from YEASTRACT "Rank by TF" results]]
#[[media:Mbalducc_profile 22_RegulationMatrix_Documented_2017.xlsx|GRNmap input Workbook]]
#
{{pagedesiigner}}

Page Desiigner Deliverables Page

2017-12-06T01:22:29Z

Mbalducc: added deliverables

File:Mbalduccgene&GOlists.zip

2017-12-06T01:21:44Z

Mbalducc:

Mbalducc Week 14

2017-12-05T23:52:29Z

Mbalducc: /* Files */ changed file

==Files==
[[media:Mbalducc_Profile_22_yeastract_data.xlsx| Excel Sheet of Profile #22 TF from YEASTRACT]]

[[media:Mbalducc_STEMprofiles.pdf| PowerPoint of STEM profiles and Gene Regulatory Network from GRNsight]]

[[media:Mbalducc_profile 22_RegulationMatrix_Documented_2017.xlsx]]

==Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes==
# Opened the gene list in Excel for the one of the significant profiles from my stem analysis. I chose a cluster with a clear cold shock/recovery up/down or down/up pattern.
#* Copied the list of gene IDs onto my clipboard.
# Launched a web browser and went to the [http://www.yeastract.com/ YEASTRACT database].
#* On the left panel of the window, clicked on the link to [http://www.yeastract.com/formrankbytf.php ''Rank by TF''].
#* Pasted my list of genes from my cluster into the box labeled ''ORFs/Genes''.
#* Checked the box for ''Check for all TFs''.
#* Accepted the defaults for the Regulations Filter (Documented, DNA binding plus expression evidence)
#* Did '''''not''''' apply a filter for "Filter Documented Regulations by environmental condition".
#* Ranked genes by TF using: The % of genes in the list and in YEASTRACT regulated by each TF.
#* Clicked the ''Search'' button.
# Answered the following questions:
#* In the results window that appears, the p values colored green are considered "significant", the ones colored yellow are considered "borderline significant" and the ones colored pink are considered "not significant". '''''How many transcription factors are green or "significant"?'''''
#**43 are green or "significant".
#* '''''Copied the table of results from the web page and pasteed it into a new Excel workbook to preserve the results.'''''
#** '''''Uploaded the Excel file to OWW or Box and linked to it in my electronic lab notebook.'''''
#** '''''Is your transcription factor on the list? If so, what is their "% in user set", "% in YEASTRACT", and "p value".''''' (Note that this doesn't apply to the wt strain).
#***My transcription factor, Cin5 was on the list. Here is the data associated with it:
#****% in user set: 40.68%
#****% in YEASTRACT: 3.30%
#****p-value: 0.001495074628175
#*List of 20 significant transcription factors:
#*#Aft2p
#*#Mga2p
#*#Gis1p
#*#Hot1p
#*#Sut1p
#*#Zap1p
#*#Mig1p
#*#Hap2p
#*#Sut2p
#*#Bas1p
#*#Pho2p
#*#Opi1p
#*#Ert1p
#*#Oaf1p
#*#Sfp1p
#*#Mig3p
#*#Rlm1p
#*#Sum1p
#*#Ace2p
#*#Pho4p
#* Went back to the YEASTRACT database and followed the link to ''[http://www.yeastract.com/formgenerateregulationmatrix.php Generate Regulation Matrix]''.
#* Copied and pasted the list of transcription factors I identified (plus the transcription factor deleted in my strain: Cin5p) into both the "Transcription factors" field and the "Target ORF/Genes" field.
#* I used the "Regulations Filter" options of "Documented", "'''Only''' DNA binding evidence"
#** Clicked the "Generate" button.
#** In the results window that appeared, I clicked on the link to the "Regulation matrix (Semicolon Separated Values (CSV) file)" that appeared and saved it to my Desktop. I renamed this file with a meaningful name so that I could distinguish it from the other files I will generate.

=== Visualizing My Gene Regulatory Networks with GRNsight===

# Followed these steps for each of the three files I generated:
#* Opened the file in Excel. It did not open properly in Excel because a semicolon was used as the column delimiter instead of a comma. To fix this, I select the entire Column A. Then went to the "Data" tab and selected "Text to columns". In the Wizard that appeared, I selected "Delimited" and click "Next". In the next window, I selected "Semicolon", and clicked "Next". In the next window, I left the data format at "General", and clicked "Finish". This now looked like a table with the names of the transcription factors across the top and down the first column and all of the zeros and ones distributed throughout the rows and columns. This is called an "adjacency matrix." If there is a "1" in the cell, that means there is a connection between the transcription factor in that row with that column.
#* Saved this file in Microsoft Excel workbook format (.xlsx).
#* Checked to see that all of the transcription factors in the matrix were connected to at least one of the other transcription factors by making sure that there was at least one "1" in a row or column for that transcription factor. If a factor is not connected to any other factor, I deleted its row and column from the matrix. I made sure that I still had somewhere between 15 and 30 transcription factors in my network after this pruning.
#** I only deleted the transcription factor if there were all zeros in its column '''AND''' all zeros in its row. Visualizing the matrix in GRNsight (below) helped me find these easily.
#* For this adjacency matrix to be usable in GRNmap (the modeling software) and GRNsight (the visualization software), I needed to transpose the matrix. I Inserted a new worksheet into my Excel file and named it "network". Went back to the previous sheet and selected the entire matrix and copied it. Went to my new worksheet and clicked on the A1 cell in the upper left. Selected "Paste special" from the "Home" tab. In the window that appeared, I checked the box for "Transpose". This pasted my data with the columns transposed to rows and vice versa. This was necessary because I wanted the transcription factors that are the "regulatORS" across the top and the "regulatEES" along the side.
#* The labels for the genes in the columns and rows needed to match. Thus, I deleted the "p" from each of the gene names in the columns. I adjusted the case of the labels to make them all upper case.
#* In cell A1, I copied and pasted the text "rows genes affected/cols genes controlling".
#* Finally, for ease of working with the adjacency matrix in Excel, I wanted to alphabetize the gene labels both across the top and side.
#** I selected the area of the entire adjacency matrix.
#** I clicked the Data tab and clicked the custom sort button.
#** I sorted Column A alphabetically, being sure to exclude the header row.
#** Next I sorted row 1 from left to right, excluding cell A1. In the Custom Sort window, click on the options button and select sort left to right, excluding column 1.
#* Saved the workbook.
# Next I visualized what these gene regulatory networks look like with the GRNsight software.
#* I went to the [http://dondi.github.io/GRNsight/ GRNsight] home page.
#* I selected the menu item File > Open and select the regulation matrix .xlsx file that has the "network" worksheet in it that you formatted above. GRNsight created a graph of the network, I screenshot this and added it to my PowerPoint.

==Acknowledgements==
I worked with the rest of the [[Data Analysis]] guild: [[User:Aporras1|Antonio Porras]], [[User:dbashour|Dina Bashoura]], and [[User:Emmatyrnauer|Emma Tyrnauer]] on this assignment. We spoke in class and created a group chat so we could ask each other questions and help each other as we worked on the project. I also used the instructions from the [[Week 10]] assignment. I edited the instructions slightly so they would be specific to the profile I chose and the procedure I followed.

==References==

GRNsight. (2017). Home. Retrieved November 30, 2017 from http://dondi.github.io/GRNsight/

LMU BioDB 2017. (2017). Week 10 Retrieved November 28, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10

YEASTRACT. Generate Regulation Matrix. Retrieved November 30, 2017, from http://www.yeastract.com/formgenerateregulationmatrix.php

YEASTRACT. Rank by TF. Retrieved November 30, 2017, from http://www.yeastract.com/formrankbytf.php

{{template:mbalducc}}

File:Mbalducc STEMprofiles.pdf

2017-12-05T23:51:48Z

Mbalducc:

Mbalducc Week 14

2017-12-05T23:48:27Z

Mbalducc: /* Files */ changed file

==Files==
[[media:Mbalducc_Profile_22_yeastract_data.xlsx| Excel Sheet of Profile #22 TF from YEASTRACT]]

[[media:mbalducc_STEM.pdf| PowerPoint of STEM profiles and Gene Regulatory Network from GRNsight]]

[[media:Mbalducc_profile 22_RegulationMatrix_Documented_2017.xlsx]]

==Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes==
# Opened the gene list in Excel for the one of the significant profiles from my stem analysis. I chose a cluster with a clear cold shock/recovery up/down or down/up pattern.
#* Copied the list of gene IDs onto my clipboard.
# Launched a web browser and went to the [http://www.yeastract.com/ YEASTRACT database].
#* On the left panel of the window, clicked on the link to [http://www.yeastract.com/formrankbytf.php ''Rank by TF''].
#* Pasted my list of genes from my cluster into the box labeled ''ORFs/Genes''.
#* Checked the box for ''Check for all TFs''.
#* Accepted the defaults for the Regulations Filter (Documented, DNA binding plus expression evidence)
#* Did '''''not''''' apply a filter for "Filter Documented Regulations by environmental condition".
#* Ranked genes by TF using: The % of genes in the list and in YEASTRACT regulated by each TF.
#* Clicked the ''Search'' button.
# Answered the following questions:
#* In the results window that appears, the p values colored green are considered "significant", the ones colored yellow are considered "borderline significant" and the ones colored pink are considered "not significant". '''''How many transcription factors are green or "significant"?'''''
#**43 are green or "significant".
#* '''''Copied the table of results from the web page and pasteed it into a new Excel workbook to preserve the results.'''''
#** '''''Uploaded the Excel file to OWW or Box and linked to it in my electronic lab notebook.'''''
#** '''''Is your transcription factor on the list? If so, what is their "% in user set", "% in YEASTRACT", and "p value".''''' (Note that this doesn't apply to the wt strain).
#***My transcription factor, Cin5 was on the list. Here is the data associated with it:
#****% in user set: 40.68%
#****% in YEASTRACT: 3.30%
#****p-value: 0.001495074628175
#*List of 20 significant transcription factors:
#*#Aft2p
#*#Mga2p
#*#Gis1p
#*#Hot1p
#*#Sut1p
#*#Zap1p
#*#Mig1p
#*#Hap2p
#*#Sut2p
#*#Bas1p
#*#Pho2p
#*#Opi1p
#*#Ert1p
#*#Oaf1p
#*#Sfp1p
#*#Mig3p
#*#Rlm1p
#*#Sum1p
#*#Ace2p
#*#Pho4p
#* Went back to the YEASTRACT database and followed the link to ''[http://www.yeastract.com/formgenerateregulationmatrix.php Generate Regulation Matrix]''.
#* Copied and pasted the list of transcription factors I identified (plus the transcription factor deleted in my strain: Cin5p) into both the "Transcription factors" field and the "Target ORF/Genes" field.
#* I used the "Regulations Filter" options of "Documented", "'''Only''' DNA binding evidence"
#** Clicked the "Generate" button.
#** In the results window that appeared, I clicked on the link to the "Regulation matrix (Semicolon Separated Values (CSV) file)" that appeared and saved it to my Desktop. I renamed this file with a meaningful name so that I could distinguish it from the other files I will generate.

=== Visualizing My Gene Regulatory Networks with GRNsight===

# Followed these steps for each of the three files I generated:
#* Opened the file in Excel. It did not open properly in Excel because a semicolon was used as the column delimiter instead of a comma. To fix this, I select the entire Column A. Then went to the "Data" tab and selected "Text to columns". In the Wizard that appeared, I selected "Delimited" and click "Next". In the next window, I selected "Semicolon", and clicked "Next". In the next window, I left the data format at "General", and clicked "Finish". This now looked like a table with the names of the transcription factors across the top and down the first column and all of the zeros and ones distributed throughout the rows and columns. This is called an "adjacency matrix." If there is a "1" in the cell, that means there is a connection between the transcription factor in that row with that column.
#* Saved this file in Microsoft Excel workbook format (.xlsx).
#* Checked to see that all of the transcription factors in the matrix were connected to at least one of the other transcription factors by making sure that there was at least one "1" in a row or column for that transcription factor. If a factor is not connected to any other factor, I deleted its row and column from the matrix. I made sure that I still had somewhere between 15 and 30 transcription factors in my network after this pruning.
#** I only deleted the transcription factor if there were all zeros in its column '''AND''' all zeros in its row. Visualizing the matrix in GRNsight (below) helped me find these easily.
#* For this adjacency matrix to be usable in GRNmap (the modeling software) and GRNsight (the visualization software), I needed to transpose the matrix. I Inserted a new worksheet into my Excel file and named it "network". Went back to the previous sheet and selected the entire matrix and copied it. Went to my new worksheet and clicked on the A1 cell in the upper left. Selected "Paste special" from the "Home" tab. In the window that appeared, I checked the box for "Transpose". This pasted my data with the columns transposed to rows and vice versa. This was necessary because I wanted the transcription factors that are the "regulatORS" across the top and the "regulatEES" along the side.
#* The labels for the genes in the columns and rows needed to match. Thus, I deleted the "p" from each of the gene names in the columns. I adjusted the case of the labels to make them all upper case.
#* In cell A1, I copied and pasted the text "rows genes affected/cols genes controlling".
#* Finally, for ease of working with the adjacency matrix in Excel, I wanted to alphabetize the gene labels both across the top and side.
#** I selected the area of the entire adjacency matrix.
#** I clicked the Data tab and clicked the custom sort button.
#** I sorted Column A alphabetically, being sure to exclude the header row.
#** Next I sorted row 1 from left to right, excluding cell A1. In the Custom Sort window, click on the options button and select sort left to right, excluding column 1.
#* Saved the workbook.
# Next I visualized what these gene regulatory networks look like with the GRNsight software.
#* I went to the [http://dondi.github.io/GRNsight/ GRNsight] home page.
#* I selected the menu item File > Open and select the regulation matrix .xlsx file that has the "network" worksheet in it that you formatted above. GRNsight created a graph of the network, I screenshot this and added it to my PowerPoint.

==Acknowledgements==
I worked with the rest of the [[Data Analysis]] guild: [[User:Aporras1|Antonio Porras]], [[User:dbashour|Dina Bashoura]], and [[User:Emmatyrnauer|Emma Tyrnauer]] on this assignment. We spoke in class and created a group chat so we could ask each other questions and help each other as we worked on the project. I also used the instructions from the [[Week 10]] assignment. I edited the instructions slightly so they would be specific to the profile I chose and the procedure I followed.

==References==

GRNsight. (2017). Home. Retrieved November 30, 2017 from http://dondi.github.io/GRNsight/

LMU BioDB 2017. (2017). Week 10 Retrieved November 28, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10

YEASTRACT. Generate Regulation Matrix. Retrieved November 30, 2017, from http://www.yeastract.com/formgenerateregulationmatrix.php

YEASTRACT. Rank by TF. Retrieved November 30, 2017, from http://www.yeastract.com/formrankbytf.php

{{template:mbalducc}}

File:Mbalducc profile 22 RegulationMatrix Documented 2017.xlsx

2017-12-05T23:48:04Z

Mbalducc:

Mbalducc Week 14

2017-12-05T23:31:11Z

Mbalducc: /* Files */ added file

==Files==
[[media:Mbalducc_Profile_22_yeastract_data.xlsx| Excel Sheet of Profile #22 TF from YEASTRACT]]

[[media:mbalducc_STEM.pdf| PowerPoint of STEM profiles and Gene Regulatory Network from GRNsight]]

[[media:Mbalducc_RegulationMatrix_Documented_profile_22.xlsx]]

==Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes==
# Opened the gene list in Excel for the one of the significant profiles from my stem analysis. I chose a cluster with a clear cold shock/recovery up/down or down/up pattern.
#* Copied the list of gene IDs onto my clipboard.
# Launched a web browser and went to the [http://www.yeastract.com/ YEASTRACT database].
#* On the left panel of the window, clicked on the link to [http://www.yeastract.com/formrankbytf.php ''Rank by TF''].
#* Pasted my list of genes from my cluster into the box labeled ''ORFs/Genes''.
#* Checked the box for ''Check for all TFs''.
#* Accepted the defaults for the Regulations Filter (Documented, DNA binding plus expression evidence)
#* Did '''''not''''' apply a filter for "Filter Documented Regulations by environmental condition".
#* Ranked genes by TF using: The % of genes in the list and in YEASTRACT regulated by each TF.
#* Clicked the ''Search'' button.
# Answered the following questions:
#* In the results window that appears, the p values colored green are considered "significant", the ones colored yellow are considered "borderline significant" and the ones colored pink are considered "not significant". '''''How many transcription factors are green or "significant"?'''''
#**43 are green or "significant".
#* '''''Copied the table of results from the web page and pasteed it into a new Excel workbook to preserve the results.'''''
#** '''''Uploaded the Excel file to OWW or Box and linked to it in my electronic lab notebook.'''''
#** '''''Is your transcription factor on the list? If so, what is their "% in user set", "% in YEASTRACT", and "p value".''''' (Note that this doesn't apply to the wt strain).
#***My transcription factor, Cin5 was on the list. Here is the data associated with it:
#****% in user set: 40.68%
#****% in YEASTRACT: 3.30%
#****p-value: 0.001495074628175
#*List of 20 significant transcription factors:
#*#Aft2p
#*#Mga2p
#*#Gis1p
#*#Hot1p
#*#Sut1p
#*#Zap1p
#*#Mig1p
#*#Hap2p
#*#Sut2p
#*#Bas1p
#*#Pho2p
#*#Opi1p
#*#Ert1p
#*#Oaf1p
#*#Sfp1p
#*#Mig3p
#*#Rlm1p
#*#Sum1p
#*#Ace2p
#*#Pho4p
#* Went back to the YEASTRACT database and followed the link to ''[http://www.yeastract.com/formgenerateregulationmatrix.php Generate Regulation Matrix]''.
#* Copied and pasted the list of transcription factors I identified (plus the transcription factor deleted in my strain: Cin5p) into both the "Transcription factors" field and the "Target ORF/Genes" field.
#* I used the "Regulations Filter" options of "Documented", "'''Only''' DNA binding evidence"
#** Clicked the "Generate" button.
#** In the results window that appeared, I clicked on the link to the "Regulation matrix (Semicolon Separated Values (CSV) file)" that appeared and saved it to my Desktop. I renamed this file with a meaningful name so that I could distinguish it from the other files I will generate.

=== Visualizing My Gene Regulatory Networks with GRNsight===

# Followed these steps for each of the three files I generated:
#* Opened the file in Excel. It did not open properly in Excel because a semicolon was used as the column delimiter instead of a comma. To fix this, I select the entire Column A. Then went to the "Data" tab and selected "Text to columns". In the Wizard that appeared, I selected "Delimited" and click "Next". In the next window, I selected "Semicolon", and clicked "Next". In the next window, I left the data format at "General", and clicked "Finish". This now looked like a table with the names of the transcription factors across the top and down the first column and all of the zeros and ones distributed throughout the rows and columns. This is called an "adjacency matrix." If there is a "1" in the cell, that means there is a connection between the transcription factor in that row with that column.
#* Saved this file in Microsoft Excel workbook format (.xlsx).
#* Checked to see that all of the transcription factors in the matrix were connected to at least one of the other transcription factors by making sure that there was at least one "1" in a row or column for that transcription factor. If a factor is not connected to any other factor, I deleted its row and column from the matrix. I made sure that I still had somewhere between 15 and 30 transcription factors in my network after this pruning.
#** I only deleted the transcription factor if there were all zeros in its column '''AND''' all zeros in its row. Visualizing the matrix in GRNsight (below) helped me find these easily.
#* For this adjacency matrix to be usable in GRNmap (the modeling software) and GRNsight (the visualization software), I needed to transpose the matrix. I Inserted a new worksheet into my Excel file and named it "network". Went back to the previous sheet and selected the entire matrix and copied it. Went to my new worksheet and clicked on the A1 cell in the upper left. Selected "Paste special" from the "Home" tab. In the window that appeared, I checked the box for "Transpose". This pasted my data with the columns transposed to rows and vice versa. This was necessary because I wanted the transcription factors that are the "regulatORS" across the top and the "regulatEES" along the side.
#* The labels for the genes in the columns and rows needed to match. Thus, I deleted the "p" from each of the gene names in the columns. I adjusted the case of the labels to make them all upper case.
#* In cell A1, I copied and pasted the text "rows genes affected/cols genes controlling".
#* Finally, for ease of working with the adjacency matrix in Excel, I wanted to alphabetize the gene labels both across the top and side.
#** I selected the area of the entire adjacency matrix.
#** I clicked the Data tab and clicked the custom sort button.
#** I sorted Column A alphabetically, being sure to exclude the header row.
#** Next I sorted row 1 from left to right, excluding cell A1. In the Custom Sort window, click on the options button and select sort left to right, excluding column 1.
#* Saved the workbook.
# Next I visualized what these gene regulatory networks look like with the GRNsight software.
#* I went to the [http://dondi.github.io/GRNsight/ GRNsight] home page.
#* I selected the menu item File > Open and select the regulation matrix .xlsx file that has the "network" worksheet in it that you formatted above. GRNsight created a graph of the network, I screenshot this and added it to my PowerPoint.

==Acknowledgements==
I worked with the rest of the [[Data Analysis]] guild: [[User:Aporras1|Antonio Porras]], [[User:dbashour|Dina Bashoura]], and [[User:Emmatyrnauer|Emma Tyrnauer]] on this assignment. We spoke in class and created a group chat so we could ask each other questions and help each other as we worked on the project. I also used the instructions from the [[Week 10]] assignment. I edited the instructions slightly so they would be specific to the profile I chose and the procedure I followed.

==References==

GRNsight. (2017). Home. Retrieved November 30, 2017 from http://dondi.github.io/GRNsight/

LMU BioDB 2017. (2017). Week 10 Retrieved November 28, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10

YEASTRACT. Generate Regulation Matrix. Retrieved November 30, 2017, from http://www.yeastract.com/formgenerateregulationmatrix.php

YEASTRACT. Rank by TF. Retrieved November 30, 2017, from http://www.yeastract.com/formrankbytf.php

{{template:mbalducc}}

File:Mbalducc RegulationMatrix Documented profile 22.xlsx

2017-12-05T23:30:47Z

Mbalducc:

Mbalducc Week 10

2017-12-05T23:25:15Z

Mbalducc: /* Acknowledgments */ added specifics about instructions

=Files=
[[media:MB_dCIN5_Profile_GeneLists.zip| dCIN5 Profile Gene Lists]]

[[media:MB_dCIN5_ProfileGOlists.zip| dCIN5 Profile GO Lists]]

=Clustering and GO Term Enrichment with STEM=

#'''Prepared microarray data file for loading into STEM'''
#*Downloaded: [[Media:Mbalducc_week8_dCIN5.zip|Excel file for the ANOVA of dCIN5]]
#* Inserted a new worksheet into my Excel workbook, named it "dCIN5_stem".
#* Selected all of the data from rmy "dCIN5_ANOVA" worksheet and Paste special > paste values into my "dCIN5_stem" worksheet.
#** My leftmost column had the column header "Master_Index". Renamed this column to "SPOT". Column B was named "ID". Renamed this column to "Gene Symbol". Deleted the column named "Standard_Name".
#** Filtered the data on the B-H corrected p value to be > 0.05 (that's '''greater than''' in this case).
#*** Once the data was filtered, selected all of the rows (except for my header row) and deleted the rows by right-clicking and choosing "Delete Row" from the context menu. Undid the filter. '''''Record of the number of genes left in my electronic notebook.'''''
#****After deleting the genes with B-H p-values > 0.05, there were 1463 genes left.
#** Deleted all of the data columns '''''EXCEPT''''' for the Average Log Fold change columns for each timepoint (for example, wt_AvgLogFC_t15, etc.).
#** Renamed the data columns with just the time and units (for example, 15m, 30m, etc.).
#** Saved my work. Then used ''Save As'' to save this spreadsheet as Text (Tab-delimited) (*.txt). Clicked OK to the warnings and closed my file.
#*** Also turned on file extensions.
# '''Downloaded and extracted the STEM software.''' [http://www.cs.cmu.edu/~jernst/stem/ Click here to go to the STEM web site].
#* Clicked on the [http://www.andrew.cmu.edu/user/zivbj/stemreg.html download link], registered, and downloaded the <code>stem.zip</code> file to my Desktop.
#* Unzipped the file.
#* This created a folder called <code>stem</code>. Inside the folder, double-clicked on the <code>stem.jar</code> to launch the STEM program.
# '''Running STEM'''
## In section 1 (Expression Data Info) of the the main STEM interface window, clicked on the ''Browse...'' button to navigate to and selected my file.
##* Clicked on the radio button ''No normalization/add 0''.
##* Checked the box next to ''Spot IDs included in the data file''.
## In section 2 (Gene Info) of the main STEM interface window, selected ''Saccharomyces cerevisiae (SGD)'', from the drop-down menu for Gene Annotation Source. Selected ''No cross references'', from the Cross Reference Source drop-down menu. Selected ''No Gene Locations'' from the Gene Location Source drop-down menu.
## In section 3 (Options) of the main STEM interface window, made sure that the Clustering Method says "STEM Clustering Method" and did not change the defaults for Maximum Number of Model Profiles or Maximum Unit Change in Model Profiles between Time Points.
## In section 4 (Execute) clicked on the yellow Execute button to run STEM.
# '''Viewing and Saving STEM Results'''
## A new window opened called "All STEM Profiles (1)". Each box corresponds to a model expression profile. Colored profiles have a statistically significant number of genes assigned; they are arranged in order from most to least significant p value. Profiles with the same color belong to the same cluster of profiles. The number in each box is simply an ID number for the profile.
##* Clicked on the button that says "Interface Options...". At the bottom of the Interface Options window that appears below where it says "X-axis scale should be:", clicked on the radio button that says "Based on real time". Then closed the Interface Options window.
##*Took a screenshot of this window (on a PC, simultaneously press the <code>Alt</code> and <code>PrintScreen</code> buttons to save the view in the active window to the clipboard) and paste it into a PowerPoint presentation to save my figures.
## Clicked on each of the SIGNIFICANT profiles (the colored ones) to open a window showing a more detailed plot containing all of the genes in that profile.
###This step could not be done on a Mac, when the significant profiles were clicked on a blank white page was all that appeared, so this step was carried out on a different computer.
##* Took a screenshot of each of the individual profile windows and saved the images in my PowerPoint presentation.
##**The first significant profile showed in detail, so we could screenshot it, but the six other significant profiles only should a blank white page when clicked on.
##**On a different computer, we were able to view every plot in detail and take screenshots, so the issue seems to be with the Macs we were using.
##* At the bottom of each profile window, there were two yellow buttons "Profile Gene Table" and "Profile GO Table". For each of the profiles, clicked on the "Profile Gene Table" button to see the list of genes belonging to the profile. In the window that appeared, clicked on the "Save Table" button and saved the file to my desktop. Made my filename descriptive of the contents, e.g. "dCIN5_profile#_genelist.txt", where I replaced the number symbol with the actual profile number.
##** Uploaded these files to the wiki and linked to them on my individual journal page.
##* For each of the significant profiles, clicked on the "Profile GO Table" to see the list of Gene Ontology terms belonging to the profile. In the window that appeared, clicked on the "Save Table" button and saved the file to my desktop. Made my filename descriptive of the contents, "dCIN5_profile#_GOlist.txt", where I replaced the number symbol with the actual profile number.
##** Uploaded these files to the wiki and linked to them on my individual journal page.
# '''Analyzing and Interpreting STEM Results'''
## Selected '''''one''''' of the profiles I saved in the previous step for further interpretation of the data. Answered the following:
##* '''''Why did you select this profile? In other words, why was it interesting to you?'''''
##**I chose this profile because I thought it looked interesting due to the two increases in expression change at 15 and 60 minutes
##* '''''How many genes belong to this profile?'''''
##**28.6 genes belong to this profile.
##* '''''How many genes were expected to belong to this profile?'''''
##**67 genes were expected to belong to this profile.
##* '''''What is the p value for the enrichment of genes in this profile?''''' Bear in mind that we just finished computing p values to determine whether each individual gene had a significant change in gene expression at each time point. This p value determines whether the number of genes that show this particular expression profile across the time points is significantly more than expected.
##**The p value for the enrichment of genes in this profile is 2.7E-11
##* Opened the GO list file I saved for this profile in Excel. This list shows all of the Gene Ontology terms that are associated with genes that fit this profile. Select the third row and then choose from the menu Data > Filter > Autofilter. Filter on the "p-value" column to show only GO terms that have a p value of < 0.05. '''''How many GO terms are associated with this profile at p < 0.05?''''' The GO list also has a column called "Corrected p-value". This correction is needed because the software has performed thousands of significance tests. Filter on the "Corrected p-value" column to show only GO terms that have a corrected p value of < 0.05. '''''How many GO terms are associated with this profile with a corrected p value < 0.05?'''''
##**13 terms are associated with the profile at p < 0.05.
##**0 terms are associated with the profile at the corrected value 0.05.
##* Select 6 Gene Ontology terms from my filtered list (either p < 0.05 or corrected p < 0.05). The terms I selected are (with their definitions from the [http://geneontology.org/ Gene Ontology Consortium]):
##**nucleoplasm part (GO:0044451): Any constituent part of the nucleoplasm, that part of the nuclear content other than the chromosomes or the nucleolus.
##**nucleobase-containing compound catabolic process (GO:0034655): The chemical reactions and pathways resulting in the breakdown of nucleobases, nucleosides, nucleotides and nucleic acids.
##**peptidyl-amino acid modification (GO:0018193): The alteration of an amino acid residue in a peptide.
##**RNA catabolic process (GO:0006401): The chemical reactions and pathways resulting in the breakdown of RNA, ribonucleic acid, one of the two main type of nucleic acid, consisting of a long, unbranched macromolecule formed from ribonucleotides joined in 3',5'-phosphodiester linkage.
##**organic cyclic compound catabolic process (GO:1901361): The chemical reactions and pathways resulting in the breakdown of organic cyclic compound.
##**establishment of RNA localization (GO:0051236): The directed movement of RNA to a specific location.
##** Each member of the group will be reported on his or her own cluster in their presentation next week. You should take care to choose terms that are the most significant, but that are also not too redundant. For example, "RNA metabolism" and "RNA biosynthesis" are redundant with each other because they mean almost the same thing.
##*** Note whether the same GO terms are showing up in multiple clusters.
##**'''''Look up the definitions for each of the terms at [http://geneontology.org http://geneontology.org]. In my final presentation, you will discuss the biological interpretation of these GO terms. In other words, why does the cell react to cold shock by changing the expression of genes associated with these GO terms? Also, what does this have to do with the transcription factor being deleted (for the Δgln3 and Δswi4 groups)?'''''
##** To easily look up the definitions, go to [http://geneontology.org http://geneontology.org].
##** Copy and paste the GO ID (e.g. GO:0044848) into the search field at center top of the page called "Search GO Data".
##** In the [http://amigo.geneontology.org/amigo/medial_search?q=GO%3A0044848 results] page, click on the button that says "Link to detailed information about <term>, in this case "biological phase"".
##** The definition will be on the next results page, e.g. [http://amigo.geneontology.org/amigo/term/GO:0044848 here].

=Summary=
The purpose of this process was to narrow the results down to only the significant data. We filtered the data to only the genes with B-H corrected p-values of <0.05. We then used those results in the STEM program to fins the significant genes. Running STEM gave us 7 significant profiles. I chose to analyze profile #38. This profile contained 28.6 genes, out of an expected 67. This profile also had a list of 13 gene ontology terms connected to it (when the p value was filtered to <0.05), 6 of which I chose to focus on and define so that I can present on them later.

=Acknowledgments=

I worked with my homework partner, [[User:Simonwro120|Simon Wroblewski]] on this assignment. We worked together in class during the work sessions and spoke outside of class about the assignment as well. I also took the instructions from the [[Week 10]] assignment page and modified them slightly to be specific to my analysis.

While I worked with the people noted above, this individual journal entry was completed by me and not copied from another source.

=References=

Gene Ontology Consortium. Retrieved November 6, 2017, from http://geneontology.org/

LMU BioDB 2017. (2017). Week 10 Retrieved October 31, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10

{{template:mbalducc}}

Mbalducc Week 8

2017-12-05T23:20:18Z

Mbalducc: /* Sanity Check: Number of genes significantly changed */

=Microarray Data Analysis Lab Notebook=

I analyzed the strain dCIN5, there were 4 replicates per data point.

5871 replacements were made when I deleted the NAs from the spreadsheet.

[[Media:Mbalducc_week8_dCIN5.zip|Excel file for the ANOVA of dCIN5]]

[[Media:BIOL367_F17_dCIN5_p-value_slide_MB.pptx|Table for Comparing dCIN5 with WT]]

==Statistical Data Analysis Part 1==
# Created a new worksheet, naming it dCIN5_ANOVA".
# Copied the first three columns containing the "MasterIndex", "ID", and "Standard Name" from the "Master_Sheet" worksheet for the strain dCIN5 and pasted it into my new worksheet. Copied the columns containing the data for dCIN5 and pasted it into my new worksheet.
# At the top of the first column to the right of my data, created five column headers of the form dCIN5_AvgLogFC_(TIME) where (TIME) is 15, 30, 60, 90, and 120.
# In the cell below the dCIN5_AvgLogFC_t15 header, typed =AVERAGE(D2:G2) and hit enter.
# Then highlighted all the data in row 2 associated with dCIN5 and t15, pressed the closing paren key (shift 0),and pressed the "enter" key.
# This cell now contained the average of the log fold change data from the first gene at t=15 minutes.
# Clicked on this cell and positioned my cursor at the bottom right corner. I saw the cursor change to a thin black plus sign (not a chubby white one). When it did, double clicked, and the formula is copied to the entire column of 6188 other genes.
# Repeated steps (4) through (8) with the t30, t60, t90, and the t120 data.
# In the first empty column to the right of the dCIN5_AvgLogFC_t120 calculation, created the column header dCIN5_ss_HO.
# In the first cell below this header, typed =SUMSQ(D2:W2)
# Highlighted all the LogFC data in row 2 for the dCIN5 (but not the AvgLogFC), pressed the closing paren key (shift 0), and pressed the "enter" key.
# In the next empty column to the right of dCIN5_ss_HO, created the column headers dCIN5_ss_(TIME) as in (3).
# Made a note of how many data points I had at each time point for my strain. For dCIN5, there are 4 data points for each time point. There are 20 total data points.
# In the first cell below the header dCIN5_ss_t15, typed <code>=SUMSQ(D2:G2)-COUNTA(D2:G2)*X2^2</code> and hit enter.
#* The <code>COUNTA</code> function counts the number of cells in the specified range that have data in them (i.e., does not count cells with missing values).
#* Upon completion of this single computation, used the Step (7) trick to copy the formula throughout the column.
# Repeated this computation for the t30 through t120 data points.
# In the first column to the right of dCIN5_ss_t120, created the column header dCIN5_SS_full.
# In the first row below this header, typed <code>=sum(AD2:AH2)</code> and hit enter.
# In the next two columns to the right, created the headers dCIN5_Fstat and dCIN5_p-value.
# Recalled the number of data points from (13): 20.
# In the first cell of the dCIN5_Fstat column, typed <code>=((20-5)/5)*(AC2-AI2>)/AI2</code> and hit enter.
#* Copied to the whole column.
# In the first cell below the dCIN5_p-value header, typed <code>=FDIST(AJ2,5,20-5)</code>. Copied to the whole column.
# Performed a quick sanity check to see if I did all of these computations correctly.
#* Clicked on cell A1 and clicked on the Data tab. Selected the Filter icon (looks like a funnel). Little drop-down arrows appeared at the top of each column. This enabled me to filter the data according to criteria I set.
#* Clicked on the drop-down arrow on my dCIN5_p-value column. Selected "Number Filters". In the window that appeared, set a criterion that filtered my data so that the p value had to be less than 0.05.
#* Excel now only displayed the rows that corresponded to data meeting that filtering criterion. A number appeared in the lower left hand corner of the window giving me the number of rows that meet that criterion.

==== Calculate the Bonferroni and p value Correction ====

# I performed adjustments to the p value to correct for the [https://xkcd.com/882/ multiple testing problem]. Labelled the next two columns to the right with the same label, dCIN5_Bonferroni_p-value.
# Typed the equation <code>=AK2*6189</code>, Upon completion of this single computation, used the Step (10) trick to copy the formula throughout the column.
# Replaced any corrected p value that is greater than 1 by the number 1 by typing the following formula into the first cell below the second dCIN5_Bonferroni_p-value header: <code>=IF(AL2>1,1,AL2)</code>. Used the Step (10) trick to copy the formula throughout the column.

==== Calculate the Benjamini & Hochberg p value Correction ====

# Inserted a new worksheet named "dCIN5_ANOVA_B-H".
# Copied and pasted the "MasterIndex", "ID", and "Standard Name" columns from my previous worksheet into the first three columns of the new worksheet.
# Used Paste special > Paste values. Copied my unadjusted p values from my ANOVA worksheet and pasted it into Column D.
# Selected all of columns A, B, C, and D. Sorted by ascending values on Column D. Clicked the sort button from A to Z on the toolbar, in the window that appeared, sorted by column D, smallest to largest.
# Typed the header "Rank" in cell E1. Created a series of numbers in ascending order from 1 to 6189 in this column. This was the p value rank, smallest to largest. Typed "1" into cell E2 and "2" into cell E3. Selected both cells E2 and E3. Double-clicked on the plus sign on the lower right-hand corner of my selection to fill the column with a series of numbers from 1 to 6189.
# Typed dCIN5_B-H_p-value in cell F1. Typed the following formula in cell F2: <code>=(D2*6189)/E2</code> and pressed enter. Copied that equation to the entire column.
# Typed "dCIN5_B-H_p-value" into cell G1.
# Typed the following formula into cell G2: <code>=IF(F2>1,1,F2)</code> and pressed enter. Copied that equation to the entire column.
# Selected columns A through G. Sorted them by my MasterIndex in Column A in ascending order.
# Copied column G and used Paste special > Paste values to paste it into the next column on the right of your ANOVA sheet.

* '''''Zipped and uploaded the .xlsx file that I have created to the wiki.'''''

==== Sanity Check: Number of genes significantly changed ====

* Opened my dCIN5_ANOVA worksheet.
* Selected row 1 and selected the menu item Data > Filter > Autofilter. This will enabled me to filter the data according to criteria I set.
* Clicked on the drop-down arrow for the unadjusted p value. Set a criterion to filter my data so that the p value has to be less than 0.05.

** '''''How many genes have p < 0.05? and what is the percentage (out of 6189)?'''''
***2290 genes have p < 0.05. The percentage out of 6189 is 37%.
** '''''How many genes have p < 0.01? and what is the percentage (out of 6189)?'''''
***1380 genes have p < 0.01. The percentage is 22%.
** '''''How many genes have p < 0.001? and what is the percentage (out of 6189)?'''''
***691 genes have p < 0.001. The percentage is 11%.
** '''''How many genes have p < 0.0001? and what is the percentage (out of 6189)?'''''
***358 genes have p < 0.0001. The percentage is 6%.

* I have just performed 6189 hypothesis tests. Another way to state what we are seeing with p < 0.05 is that we would expect to see this a gene expression change for at least one of the timepoints by chance in about 5% of our tests, or 309 times. Since we have more than 309 genes that pass this cut off, we know that some genes are significantly changed. However, we don't know ''which'' ones. To apply a more stringent criterion to our p values, we performed the Bonferroni and Benjamini and Hochberg corrections to these unadjusted p values. The Bonferroni correction is very stringent. The Benjamini-Hochberg correction is less stringent. To see this relationship, filter your data to determine the following:
** '''''How many genes are p < 0.05 for the Bonferroni-corrected p value? and what is the percentage (out of 6189)?'''''
***151 genes are p < 0.05. The percentage is 2%.
** '''''How many genes are p < 0.05 for the Benjamini and Hochberg-corrected p value? and what is the percentage (out of 6189)?'''''
***1453 genes are p < 0.05. The percentage is 23%.
* In summary, the p value cut-off should not be thought of as some magical number at which data becomes "significant". Instead, it is a moveable confidence level. If we want to be very confident of our data, use a small p value cut-off. If we are OK with being less confident about a gene expression change and want to include more genes in our analysis, we can use a larger p value cut-off.
* We will compare the numbers we get between the wild type strain and the other strains studied, organized as a table. Use this [[Media:BIOL367_F17_sample_p-value_slide.pptx | sample PowerPoint slide]] to see how your table should be formatted. Upload your slide to the wiki.
** Note that since the wild type data is being analyzed by one of the groups in the class, it will be sufficient for this week to supply just the data for your strain. We will do the comparison with wild type at a later date.
* Comparing results with known data: the expression of the gene ''NSR1'' (ID: YGR159C)is known to be induced by cold shock. '''''Find ''NSR1'' in your dataset. What is its unadjusted, Bonferroni-corrected, and B-H-corrected p values? What is its average Log fold change at each of the time points in the experiment?''''' Does ''NSR1'' change expression due to cold shock in this experiment?
**Unadjusted p-value: 6.37596E-08
**Bonferroni-corrected: 0.000394608
**B-H corrected: 2.19227E-05
**AvgLogFC t15: 4.070048368
**AvgLogFC t30: 3.611460213
**AvgLogFC t60: 4.298496857
**AvgLogFC t90: -2.900930452
**AvgLogFC t120: -0.931494963
**The NSR1 gene does change expression due to cold shock in the dCIN5 experiment.
* For fun, find "your favorite gene" (from your web page) in the dataset. '''''What is its unadjusted, Bonferroni-corrected, and B-H-corrected p values? What is its average Log fold change at each of the timepoints in the experiment?''''' Does your favorite gene change expression due to cold shock in this experiment?
**My favorite gene is HSF1
**Unadjusted p-value: 0.004551209
**Bonferroni-corrected: 1
**B-H corrected: 0.025723684
**AvgLogFC t15: -1.230282375
**AvgLogFC t30: -1.272313728
**AvgLogFC t60: -1.500144335
**AvgLogFC t90: -0.075703512
**AvgLogFC t120: 0.422687452
**HSF1 does appear to change expression due to cold shock in the dCIN5 experiment.

==== Summary Paragraph ====

In this experiment, data for the expression of yeast genes in cold shock with the deletion of CIN5 were analyzed. There were 5 time points, each corresponding to different temperatures, first the cold shock, then the recovery. The data shows the log fold change for the expression of each gene at each time point. From this data, the p-values were found for each gene. Then the Bonferroni corrected and B-H corrected p-values were found. The Bonferroni correction gave the most strict results, with only 151 genes (2% of the total) having a p-value of less than 0.05. This is compared to the B-H adjusted, which showed 1453 genes (23% of the total) having a p-value of less than 0.05, and compared to the unadjusted p-value, where 2290 genes (37% of the total) had p-values of less than 0.05.
The data was compared to a gene which is known to change expression during cold shock: NSR1. Our data shows that the NSR1 still did respond to cold shock in our strain, dCIN5. The gene HSF1 (my favorite gene) was also looked at. This gene did not appear to change expression in response to cold shock in the strain dCIN5.

=Acknowledgements=

I worked with my homework partner, [[User:Simonwro120|Simon Wroblewski]], on this assignment. We worked together in class and compared results for our formulas in Excel. We also spoke outside of class to compare what we were doing to make sure we were both getting the same results for the same strain, dCIN5. I also used the instructions from the [[Week 8]] page in my journal, edited to show that I did them in the past.

While I worked with the people noted above, this individual journal entry was completed by me and not copied from another source.

[[User:Mbalducc|Mbalducc]] ([[User talk:Mbalducc|talk]]) 15:32, 22 October 2017 (PDT)

=References=

LMU BioDB 2017. (2017). Week 8. Retrieved October 19, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_8

{{template:mbalducc}}

Mbalducc Week 8

2017-12-05T23:18:14Z

Mbalducc: /* Microarray Data Analysis Lab Notebook */

=Microarray Data Analysis Lab Notebook=

I analyzed the strain dCIN5, there were 4 replicates per data point.

5871 replacements were made when I deleted the NAs from the spreadsheet.

[[Media:Mbalducc_week8_dCIN5.zip|Excel file for the ANOVA of dCIN5]]

[[Media:BIOL367_F17_dCIN5_p-value_slide_MB.pptx|Table for Comparing dCIN5 with WT]]

==Statistical Data Analysis Part 1==
# Created a new worksheet, naming it dCIN5_ANOVA".
# Copied the first three columns containing the "MasterIndex", "ID", and "Standard Name" from the "Master_Sheet" worksheet for the strain dCIN5 and pasted it into my new worksheet. Copied the columns containing the data for dCIN5 and pasted it into my new worksheet.
# At the top of the first column to the right of my data, created five column headers of the form dCIN5_AvgLogFC_(TIME) where (TIME) is 15, 30, 60, 90, and 120.
# In the cell below the dCIN5_AvgLogFC_t15 header, typed =AVERAGE(D2:G2) and hit enter.
# Then highlighted all the data in row 2 associated with dCIN5 and t15, pressed the closing paren key (shift 0),and pressed the "enter" key.
# This cell now contained the average of the log fold change data from the first gene at t=15 minutes.
# Clicked on this cell and positioned my cursor at the bottom right corner. I saw the cursor change to a thin black plus sign (not a chubby white one). When it did, double clicked, and the formula is copied to the entire column of 6188 other genes.
# Repeated steps (4) through (8) with the t30, t60, t90, and the t120 data.
# In the first empty column to the right of the dCIN5_AvgLogFC_t120 calculation, created the column header dCIN5_ss_HO.
# In the first cell below this header, typed =SUMSQ(D2:W2)
# Highlighted all the LogFC data in row 2 for the dCIN5 (but not the AvgLogFC), pressed the closing paren key (shift 0), and pressed the "enter" key.
# In the next empty column to the right of dCIN5_ss_HO, created the column headers dCIN5_ss_(TIME) as in (3).
# Made a note of how many data points I had at each time point for my strain. For dCIN5, there are 4 data points for each time point. There are 20 total data points.
# In the first cell below the header dCIN5_ss_t15, typed <code>=SUMSQ(D2:G2)-COUNTA(D2:G2)*X2^2</code> and hit enter.
#* The <code>COUNTA</code> function counts the number of cells in the specified range that have data in them (i.e., does not count cells with missing values).
#* Upon completion of this single computation, used the Step (7) trick to copy the formula throughout the column.
# Repeated this computation for the t30 through t120 data points.
# In the first column to the right of dCIN5_ss_t120, created the column header dCIN5_SS_full.
# In the first row below this header, typed <code>=sum(AD2:AH2)</code> and hit enter.
# In the next two columns to the right, created the headers dCIN5_Fstat and dCIN5_p-value.
# Recalled the number of data points from (13): 20.
# In the first cell of the dCIN5_Fstat column, typed <code>=((20-5)/5)*(AC2-AI2>)/AI2</code> and hit enter.
#* Copied to the whole column.
# In the first cell below the dCIN5_p-value header, typed <code>=FDIST(AJ2,5,20-5)</code>. Copied to the whole column.
# Performed a quick sanity check to see if I did all of these computations correctly.
#* Clicked on cell A1 and clicked on the Data tab. Selected the Filter icon (looks like a funnel). Little drop-down arrows appeared at the top of each column. This enabled me to filter the data according to criteria I set.
#* Clicked on the drop-down arrow on my dCIN5_p-value column. Selected "Number Filters". In the window that appeared, set a criterion that filtered my data so that the p value had to be less than 0.05.
#* Excel now only displayed the rows that corresponded to data meeting that filtering criterion. A number appeared in the lower left hand corner of the window giving me the number of rows that meet that criterion.

==== Calculate the Bonferroni and p value Correction ====

# I performed adjustments to the p value to correct for the [https://xkcd.com/882/ multiple testing problem]. Labelled the next two columns to the right with the same label, dCIN5_Bonferroni_p-value.
# Typed the equation <code>=AK2*6189</code>, Upon completion of this single computation, used the Step (10) trick to copy the formula throughout the column.
# Replaced any corrected p value that is greater than 1 by the number 1 by typing the following formula into the first cell below the second dCIN5_Bonferroni_p-value header: <code>=IF(AL2>1,1,AL2)</code>. Used the Step (10) trick to copy the formula throughout the column.

==== Calculate the Benjamini & Hochberg p value Correction ====

# Inserted a new worksheet named "dCIN5_ANOVA_B-H".
# Copied and pasted the "MasterIndex", "ID", and "Standard Name" columns from my previous worksheet into the first three columns of the new worksheet.
# Used Paste special > Paste values. Copied my unadjusted p values from my ANOVA worksheet and pasted it into Column D.
# Selected all of columns A, B, C, and D. Sorted by ascending values on Column D. Clicked the sort button from A to Z on the toolbar, in the window that appeared, sorted by column D, smallest to largest.
# Typed the header "Rank" in cell E1. Created a series of numbers in ascending order from 1 to 6189 in this column. This was the p value rank, smallest to largest. Typed "1" into cell E2 and "2" into cell E3. Selected both cells E2 and E3. Double-clicked on the plus sign on the lower right-hand corner of my selection to fill the column with a series of numbers from 1 to 6189.
# Typed dCIN5_B-H_p-value in cell F1. Typed the following formula in cell F2: <code>=(D2*6189)/E2</code> and pressed enter. Copied that equation to the entire column.
# Typed "dCIN5_B-H_p-value" into cell G1.
# Typed the following formula into cell G2: <code>=IF(F2>1,1,F2)</code> and pressed enter. Copied that equation to the entire column.
# Selected columns A through G. Sorted them by my MasterIndex in Column A in ascending order.
# Copied column G and used Paste special > Paste values to paste it into the next column on the right of your ANOVA sheet.

* '''''Zipped and uploaded the .xlsx file that I have created to the wiki.'''''

==== Sanity Check: Number of genes significantly changed ====

* Opened my dCIN5_ANOVA worksheet.
* Selected row 1 and selected the menu item Data > Filter > Autofilter. This will enabled me to filter the data according to criteria I set.
* Clicked on the drop-down arrow for the unadjusted p value. Set a criterion to filter my data so that the p value has to be less than 0.05.

** '''''How many genes have p < 0.05? and what is the percentage (out of 6189)?'''''
***2290 genes have p < 0.05. The percentage out of 6189 is 37%.
** '''''How many genes have p < 0.01? and what is the percentage (out of 6189)?'''''
***1380 genes have p < 0.01. The percentage is 22%.
** '''''How many genes have p < 0.001? and what is the percentage (out of 6189)?'''''
***691 genes have p < 0.001. The percentage is 11%.
** '''''How many genes have p < 0.0001? and what is the percentage (out of 6189)?'''''
***358 genes have p < 0.0001. The percentage is 6%.

* I have just performed 6189 hypothesis tests. Another way to state what we are seeing with p < 0.05 is that we would expect to see this a gene expression change for at least one of the timepoints by chance in about 5% of our tests, or 309 times. Since we have more than 309 genes that pass this cut off, we know that some genes are significantly changed. However, we don't know ''which'' ones. To apply a more stringent criterion to our p values, we performed the Bonferroni and Benjamini and Hochberg corrections to these unadjusted p values. The Bonferroni correction is very stringent. The Benjamini-Hochberg correction is less stringent. To see this relationship, filter your data to determine the following:
** '''''How many genes are p < 0.05 for the Bonferroni-corrected p value? and what is the percentage (out of 6189)?'''''
***151 genes are p < 0.05. The percentage is 2%.
** '''''How many genes are p < 0.05 for the Benjamini and Hochberg-corrected p value? and what is the percentage (out of 6189)?'''''
***1453 genes are p < 0.05. The percentage is 23%.
* In summary, the p value cut-off should not be thought of as some magical number at which data becomes "significant". Instead, it is a moveable confidence level. If we want to be very confident of our data, use a small p value cut-off. If we are OK with being less confident about a gene expression change and want to include more genes in our analysis, we can use a larger p value cut-off.
* We will compare the numbers we get between the wild type strain and the other strains studied, organized as a table. Use this [[Media:BIOL367_F17_sample_p-value_slide.pptx | sample PowerPoint slide]] to see how your table should be formatted. Upload your slide to the wiki.
** Note that since the wild type data is being analyzed by one of the groups in the class, it will be sufficient for this week to supply just the data for your strain. We will do the comparison with wild type at a later date.
* Comparing results with known data: the expression of the gene ''NSR1'' (ID: YGR159C)is known to be induced by cold shock. '''''Find ''NSR1'' in your dataset. What is its unadjusted, Bonferroni-corrected, and B-H-corrected p values? What is its average Log fold change at each of the time points in the experiment?''''' Does ''NSR1'' change expression due to cold shock in this experiment?
**Unadjusted p-value: 6.37596E-08
**Bonferroni-corrected: 0.000394608
**B-H corrected: 2.19227E-05
**AvgLogFC t15: 4.070048368
**AvgLogFC t30: 3.611460213
**AvgLogFC t60: 4.298496857
**AvgLogFC t90: -2.900930452
**AvgLogFC t120: -0.931494963
**The NSR1 gene does change expression due to cold shock in the dCIN5 experiment.
* For fun, find "your favorite gene" (from your web page) in the dataset. '''''What is its unadjusted, Bonferroni-corrected, and B-H-corrected p values? What is its average Log fold change at each of the timepoints in the experiment?''''' Does your favorite gene change expression due to cold shock in this experiment?
**My favorite gene is HSF1
**Unadjusted p-value: 0.004551209
**Bonferroni-corrected: 1
**B-H corrected: 0.025723684
**AvgLogFC t15: -1.230282375
**AvgLogFC t30: -1.272313728
**AvgLogFC t60: -1.500144335
**AvgLogFC t90: -0.075703512
**AvgLogFC t120: 0.422687452
**HSF1 does not appear to change due to heat shock.

==== Summary Paragraph ====

In this experiment, data for the expression of yeast genes in cold shock with the deletion of CIN5 were analyzed. There were 5 time points, each corresponding to different temperatures, first the cold shock, then the recovery. The data shows the log fold change for the expression of each gene at each time point. From this data, the p-values were found for each gene. Then the Bonferroni corrected and B-H corrected p-values were found. The Bonferroni correction gave the most strict results, with only 151 genes (2% of the total) having a p-value of less than 0.05. This is compared to the B-H adjusted, which showed 1453 genes (23% of the total) having a p-value of less than 0.05, and compared to the unadjusted p-value, where 2290 genes (37% of the total) had p-values of less than 0.05.
The data was compared to a gene which is known to change expression during cold shock: NSR1. Our data shows that the NSR1 still did respond to cold shock in our strain, dCIN5. The gene HSF1 (my favorite gene) was also looked at. This gene did not appear to change expression in response to cold shock in the strain dCIN5.

=Acknowledgements=

I worked with my homework partner, [[User:Simonwro120|Simon Wroblewski]], on this assignment. We worked together in class and compared results for our formulas in Excel. We also spoke outside of class to compare what we were doing to make sure we were both getting the same results for the same strain, dCIN5. I also used the instructions from the [[Week 8]] page in my journal, edited to show that I did them in the past.

While I worked with the people noted above, this individual journal entry was completed by me and not copied from another source.

[[User:Mbalducc|Mbalducc]] ([[User talk:Mbalducc|talk]]) 15:32, 22 October 2017 (PDT)

=References=

LMU BioDB 2017. (2017). Week 8. Retrieved October 19, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_8

{{template:mbalducc}}

Mbalducc Week 14

2017-12-05T23:13:36Z

Mbalducc: added my template

==Files==
[[media:Mbalducc_Profile_22_yeastract_data.xlsx| Excel Sheet of Profile #22 TF from YEASTRACT]]

[[media:mbalducc_STEM.pdf| PowerPoint of STEM profiles and Gene Regulatory Network from GRNsight]]

==Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes==
# Opened the gene list in Excel for the one of the significant profiles from my stem analysis. I chose a cluster with a clear cold shock/recovery up/down or down/up pattern.
#* Copied the list of gene IDs onto my clipboard.
# Launched a web browser and went to the [http://www.yeastract.com/ YEASTRACT database].
#* On the left panel of the window, clicked on the link to [http://www.yeastract.com/formrankbytf.php ''Rank by TF''].
#* Pasted my list of genes from my cluster into the box labeled ''ORFs/Genes''.
#* Checked the box for ''Check for all TFs''.
#* Accepted the defaults for the Regulations Filter (Documented, DNA binding plus expression evidence)
#* Did '''''not''''' apply a filter for "Filter Documented Regulations by environmental condition".
#* Ranked genes by TF using: The % of genes in the list and in YEASTRACT regulated by each TF.
#* Clicked the ''Search'' button.
# Answered the following questions:
#* In the results window that appears, the p values colored green are considered "significant", the ones colored yellow are considered "borderline significant" and the ones colored pink are considered "not significant". '''''How many transcription factors are green or "significant"?'''''
#**43 are green or "significant".
#* '''''Copied the table of results from the web page and pasteed it into a new Excel workbook to preserve the results.'''''
#** '''''Uploaded the Excel file to OWW or Box and linked to it in my electronic lab notebook.'''''
#** '''''Is your transcription factor on the list? If so, what is their "% in user set", "% in YEASTRACT", and "p value".''''' (Note that this doesn't apply to the wt strain).
#***My transcription factor, Cin5 was on the list. Here is the data associated with it:
#****% in user set: 40.68%
#****% in YEASTRACT: 3.30%
#****p-value: 0.001495074628175
#*List of 20 significant transcription factors:
#*#Aft2p
#*#Mga2p
#*#Gis1p
#*#Hot1p
#*#Sut1p
#*#Zap1p
#*#Mig1p
#*#Hap2p
#*#Sut2p
#*#Bas1p
#*#Pho2p
#*#Opi1p
#*#Ert1p
#*#Oaf1p
#*#Sfp1p
#*#Mig3p
#*#Rlm1p
#*#Sum1p
#*#Ace2p
#*#Pho4p
#* Went back to the YEASTRACT database and followed the link to ''[http://www.yeastract.com/formgenerateregulationmatrix.php Generate Regulation Matrix]''.
#* Copied and pasted the list of transcription factors I identified (plus the transcription factor deleted in my strain: Cin5p) into both the "Transcription factors" field and the "Target ORF/Genes" field.
#* I used the "Regulations Filter" options of "Documented", "'''Only''' DNA binding evidence"
#** Clicked the "Generate" button.
#** In the results window that appeared, I clicked on the link to the "Regulation matrix (Semicolon Separated Values (CSV) file)" that appeared and saved it to my Desktop. I renamed this file with a meaningful name so that I could distinguish it from the other files I will generate.

=== Visualizing My Gene Regulatory Networks with GRNsight===

# Followed these steps for each of the three files I generated:
#* Opened the file in Excel. It did not open properly in Excel because a semicolon was used as the column delimiter instead of a comma. To fix this, I select the entire Column A. Then went to the "Data" tab and selected "Text to columns". In the Wizard that appeared, I selected "Delimited" and click "Next". In the next window, I selected "Semicolon", and clicked "Next". In the next window, I left the data format at "General", and clicked "Finish". This now looked like a table with the names of the transcription factors across the top and down the first column and all of the zeros and ones distributed throughout the rows and columns. This is called an "adjacency matrix." If there is a "1" in the cell, that means there is a connection between the transcription factor in that row with that column.
#* Saved this file in Microsoft Excel workbook format (.xlsx).
#* Checked to see that all of the transcription factors in the matrix were connected to at least one of the other transcription factors by making sure that there was at least one "1" in a row or column for that transcription factor. If a factor is not connected to any other factor, I deleted its row and column from the matrix. I made sure that I still had somewhere between 15 and 30 transcription factors in my network after this pruning.
#** I only deleted the transcription factor if there were all zeros in its column '''AND''' all zeros in its row. Visualizing the matrix in GRNsight (below) helped me find these easily.
#* For this adjacency matrix to be usable in GRNmap (the modeling software) and GRNsight (the visualization software), I needed to transpose the matrix. I Inserted a new worksheet into my Excel file and named it "network". Went back to the previous sheet and selected the entire matrix and copied it. Went to my new worksheet and clicked on the A1 cell in the upper left. Selected "Paste special" from the "Home" tab. In the window that appeared, I checked the box for "Transpose". This pasted my data with the columns transposed to rows and vice versa. This was necessary because I wanted the transcription factors that are the "regulatORS" across the top and the "regulatEES" along the side.
#* The labels for the genes in the columns and rows needed to match. Thus, I deleted the "p" from each of the gene names in the columns. I adjusted the case of the labels to make them all upper case.
#* In cell A1, I copied and pasted the text "rows genes affected/cols genes controlling".
#* Finally, for ease of working with the adjacency matrix in Excel, I wanted to alphabetize the gene labels both across the top and side.
#** I selected the area of the entire adjacency matrix.
#** I clicked the Data tab and clicked the custom sort button.
#** I sorted Column A alphabetically, being sure to exclude the header row.
#** Next I sorted row 1 from left to right, excluding cell A1. In the Custom Sort window, click on the options button and select sort left to right, excluding column 1.
#* Saved the workbook.
# Next I visualized what these gene regulatory networks look like with the GRNsight software.
#* I went to the [http://dondi.github.io/GRNsight/ GRNsight] home page.
#* I selected the menu item File > Open and select the regulation matrix .xlsx file that has the "network" worksheet in it that you formatted above. GRNsight created a graph of the network, I screenshot this and added it to my PowerPoint.

==Acknowledgements==
I worked with the rest of the [[Data Analysis]] guild: [[User:Aporras1|Antonio Porras]], [[User:dbashour|Dina Bashoura]], and [[User:Emmatyrnauer|Emma Tyrnauer]] on this assignment. We spoke in class and created a group chat so we could ask each other questions and help each other as we worked on the project. I also used the instructions from the [[Week 10]] assignment. I edited the instructions slightly so they would be specific to the profile I chose and the procedure I followed.

==References==

GRNsight. (2017). Home. Retrieved November 30, 2017 from http://dondi.github.io/GRNsight/

LMU BioDB 2017. (2017). Week 10 Retrieved November 28, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10

YEASTRACT. Generate Regulation Matrix. Retrieved November 30, 2017, from http://www.yeastract.com/formgenerateregulationmatrix.php

YEASTRACT. Rank by TF. Retrieved November 30, 2017, from http://www.yeastract.com/formrankbytf.php

{{template:mbalducc}}

Page Desiigner

2017-12-05T03:17:36Z

Mbalducc: /* Week 14 Team Progress Reflections */

[[Category:Page Desiigner]]
[[Category:Group Projects]]

==Page Design Team Members==
Coder: [[User:ArashLari|Arash Lari]]
 
Project Manager/ Quality Assurance: [[User:hhinsch|Hayden Hinsch]]
 
Data Analyst: [[User:Mbalducc|Mary Balducci]]
 
Designer: [[User:Nicolekalcic|Nicole Kalcic]]

==Team Schedule==
[[Page Desiigner Schedule]]

==Page Desiigner Uploaded Files==

[[Media:MaryHaydenWeek12JournalClubPresentation.pptx ‎]]
 
[[File:Data Driven Design.zip]]

==Page Layout==
*<code>Below are a series of rough ideas we will use to create the layout of the page</code>
[[File:ACT1screenshot.png|500px]]
*We will be using a layout similar to the ACT1 gene page.
[[File:Sketchofpagedesign.png]]
*This is a rough sketch of what the page will look like.
*The section labeled '''description''' on the sketch will include the following:
**Gene ID from each database
**Description/Function (ensembl)
*Within the dropdown menus we will be incorporating the following:
**DNA Sequence (ensembl)
**Protein Sequence (UniProt)
**Locus tag (NCBI)
**Also Known As (NCBI)
**Consensus Sequence (JASPAR)
**Regulation (SGD)
**Interaction (SGD)
**Similar Proteins (UniProt)
**Gene Ontology (SGD)
**JASPAR
***Matrix ID
***Class Heat shock factors
***Family HSF factors
***Sequence Logo
***Frequency Matrix

==Annotated Bibliography==
===Mary's contribution:===
Pizzaro, Jewett, Nielson, Agosin. (2008) Growth Temperature Exerts Differential Physiological and Transcriptional Responses in Laboratory and Wine Strains of Saccharomyces Cerevisiae. "Applied and Environmental Microbiology", 74, 6358-6368, doi:10.1128/AEM.00602-08
*PubMed Abstract: https://www.ncbi.nlm.nih.gov/pubmed/18723660
*PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2570279/
*HTML format: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2570279/
*PDF format: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2570279/pdf/0602-08.pdf
*Copyright: 2008 American Society for Microbiology. It is open access.
*Publisher: American Society for Microbiology. This is a scientific society.
*Availability: Online and in print
*Did LMU pay a fee for this article: No
*I could not find the data associated with this article.

Homma, Iwahashi, Komatsu. (2003) Yeast Gene Expression During Growth at Low Temperature. ''Cryobiology'', 46, doi: 10.1016/S0011-2240(03)00028-2
*PubMed abstract: https://www.ncbi.nlm.nih.gov/pubmed/12818212
*PubMed Central:
*HTML format: http://www.sciencedirect.com/science/article/pii/S0011224003000282?via%3Dihub
*PDF format: https://ac.els-cdn.com/S0011224003000282/1-s2.0-S0011224003000282-main.pdf?_tid=aa7fa05e-c5d2-11e7-88ae-00000aacb361&acdnat=1510289609_6ec25501ce7af9dcc6b521ef8a024164
*Copyright 2003 Elsevier Science (USA). It is open access.
*Publisher: Elsevier. This is a for-profit publisher
*Availability: Online and in print
*Did LMU pay a fee for this article: No
*I could not find the data associated with this article.

===Hayden's Contribution===

Dahlquist, K. D., Fitzpatrick, B. G., Camacho, E. T., Entzminger, S. D., & Wanner, N. C. (2015). Parameter Estimation for Gene Regulatory Networks from Microarray Data: Cold Shock Response in Saccharomyces cerevisiae. Bulletin of Mathematical Biology, 77(8), 1457–1492. http://doi.org/10.1007/s11538-015-0092-6
* PubMed Abstract: https://www.ncbi.nlm.nih.gov/pubmed/26420504
* PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4636536/
* Publisher Full Text (HTML): https://link.springer.com/article/10.1007/s11538-015-0092-6
* Publisher Full Text (PDF): https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4636536/pdf/11538_2015_Article_92.pdf
* Copyright: The Author(s) 2015. Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
* Publisher: Bulletin of Mathematical Biology(scientific society)
* Availability: Online
* Did LMU pay a fee for this article: No
* Data: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4636536/bin/11538_2015_92_MOESM1_ESM.zip

Ando, A., Nakamura, T., Murata, Y., Takagi, H. and Shima, J. (2007), Identification and classification of genes required for tolerance to freeze–thaw stress revealed by genome-wide screening of Saccharomyces cerevisiae deletion strains. FEMS Yeast Research, 7: 244–253. doi:10.1111/j.1567-1364.2006.00162.x
* PubMed Abstract: https://www.ncbi.nlm.nih.gov/pubmed/16989656
* PubMed Central: N/A
* Publisher Full Text (HTML): https://academic.oup.com/femsyr/article/7/2/244/616825?searchresult=1
* Publisher Full Text (PDF): http://onlinelibrary.wiley.com/doi/10.1111/j.1567-1364.2006.00162.x/epdf
* Copyright: Copyright © 2007, Oxford University Press; Open Access after time has elapsed: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. You must ask permission from the publisher to use the article.
* Publisher: Published by Oxford University Press(respected open access organization)
* Availability: Online and in print
* Did LMU pay a fee for this article: No
* Data: I couldn't find any supplementary data other than the data provided in the article.

==Journal Club Presentations==
===Powerpoint Slides and Respective Articles===
[[File:Data Driven Design.zip]]
* Liikkanen, L. (2017). The Data-Driven Design Era in Professional Web Design. Accessed November 13, 2017, from http://delivery.acm.org/10.1145/3130000/3121355/p52-liikkanen.pdf?ip=157.242.223.254&id=3121355&acc=ACTIVE%20SERVICE&key=80B0E63637265656%2E958C566062FD1C18%2E4D4702B0C3E38B35%2E4D4702B0C3E38B35&CFID=829067610&CFTOKEN=20249523&__acm__=1510614806_1e8b314e23f771f9b139d99596801365
 
[[Media:MaryHaydenWeek12JournalClubPresentation.pptx ‎]]
*Pizzaro, Jewett, Nielson, Agosin. (2008) Growth Temperature Exerts Differential Physiological and Transcriptional Responses in Laboratory and Wine Strains of Saccharomyces Cerevisiae. "Applied and Environmental Microbiology", 74, 6358-6368, doi:10.1128/AEM.00602-08

==Executive Summaries==

===[[Week 11]] Executive Summaries===
====Arash====
This week, I worked on researching the given article and the development terms within it as well as prepare a presentation on the article. I also began thinking of some page layout ideas with Nicole to prepare to implement in the coming weeks. All of this information could be found on my Week 11 page: [[ArashLari_Week_11|ArashLari Week 11]].
[[User:ArashLari|ArashLari]] ([[User talk:ArashLari|talk]]) 02:09, 14 November 2017 (PST)
====Mary====
This week, I worked on creating an annotated bibliography. The articles I found were primary sources about experiments done involving cold shock on yeast, and the use of microarrays to show results. I used multiple databases to find these articles, and while doing so I learned what key words got me the results closest to what I wanted. While writing the annotated bibliography, I also learned more about the articles, such as when they were written, who published them, what kind of publisher they are, and other information. All of this is recorded in my [[mbalducc Week 11| Week 11]] page.

[[User:Mbalducc|Mbalducc]] ([[User talk:Mbalducc|talk]]) 23:03, 13 November 2017 (PST)

====Nicole====
This past week, I read the article ''The Data-Driven Design Era in Professional Web Design'' by L.A. Liikkanen. This allowed me to complete my individual journal: an informative outline of the article and list of ten definitions. Arash and I worked together to complete a 15 minute presentation that we are going to give on Tuesday. The presentation gives an overview of our individual journals and what we each learned. You can access more information on what I did this week here: [[Nicolekalcic Week 11]].
[[User:Nicolekalcic|Nicolekalcic]] ([[User talk:Nicolekalcic|talk]]) 01:27, 14 November 2017 (PST)
====Hayden====
This week I created part of the annotated bibliography we will be using for our final project. I conducted searched for "yeast cold shock microarray" articles and found which two articles I was going to use for the bibliography. The majority of the time this week was spent on finding the information needed for the annotated bibliography which can be found below on this page. More detailed information can be found on my [[hhinsch Week 11]] page. This week I became proficient in finding reliable article to use for our final project. This week we also created the group's template and wiki page. [[User:Hhinsch|Hhinsch]] ([[User talk:Hhinsch|talk]]) 22:43, 13 November 2017 (PST)

===[[Week 12]] Executive Summaries===
====Arash====
This week was rather light compared to the previous week. We mostly set up the files on our personal computers, which was convenient because as a computer science major I already had most of the necessary files. Nicole and I talked about some preliminary designs and set up a rough schedule that we'll make concrete after the break. This can be found on my week 12 page [[ArashLari Week 12] | Arash Lari Week 12]. [[User:ArashLari|ArashLari]] ([[User talk:ArashLari|talk]]) 20:43, 20 November 2017 (PST)

====Mary====
This week I read an article about an experiment done on wine and lab strains of yeast in different temperatures. The experimenters used DNA microarrays to determine which genes were affected by the change in temperatures and which were different based on the different strains of yeast. While reading the article, I can across words I had never seen before, so I also found and recorded the definitions of these words. I then made an outline of the article, to use as a basis for my presentation with our project manager, [[user:hhinsch| Hayden]]. All of this is on my [[mbalducc Week 12| Week 12]] page.

[[User:Mbalducc|Mbalducc]] ([[User talk:Mbalducc|talk]]) 19:51, 19 November 2017 (PST)

====Nicole====
Because Arash and I presented last week, we didn't have a heavy work load this week. Arash explained a lot of technical things to me, and we completed the first coding milestones and talked about design possibilities. I officially have a GitHub (nicolekal). I also downloaded the software I needed but didn't have onto my laptop. A full update can be found on: [[Nicolekalcic Week 12] | Nicole Kalcic Week 12]. [[User:Nicolekalcic|Nicolekalcic]] ([[User talk:Nicolekalcic|talk]]) 23:45, 20 November 2017 (PST)

====Hayden====
This week I worked with Mary specifically in order to complete our journal club presentation. As a group we worked together to make corrections to the [[Page Desiigner]] group page in order to complete the deliverables for this week. Mary and I created a schedule for our group along with helpful links. As a class we decided we will be using WhatsApp to communicate. I spent most of this week outlining the article (it was a pretty difficult read) and defining terms on my [[hhinsch Week 12]] page. [[User:Hhinsch|Hhinsch]] ([[User talk:Hhinsch|talk]]) 17:42, 20 November 2017 (PST)

===[[Week 14]] Executive Summaries===
====Arash====
This week I worked on implementing our designs for the web page. Nicole and Hayden helped come up with some design ideas. We ended up deciding that ACT1 was a very well designed page and that it would be best to follow the format of that page. There's only a few things left to do but our portion of the project is nearly complete, the generic version of every gene's page needs just a few finishing touches. [[User:ArashLari|ArashLari]] ([[User talk:ArashLari|talk]]) 18:19, 4 December 2017 (PST)

====Mary====
This week I finished the Week 10 assignment, using YEASTRACT and GRNsight. I specifically chose one profile from the STEM results to use in YEASTRACT to find transcription factors that regulate a cluster of genes. First I uploaded the genes from profile #22 into YEASTRACT to find 20 significant transcription factors that regulate them. Then, I used Excel to get rid of the transcription factors that were not related to other transcription factors. Once I had those, I imported them into GRNsight to create a map of the transcription factors and their relations to each other. I took a screenshot of this map and uploaded it to my [[mbalducc Week 14| Week 14]] page.

[[User:Mbalducc|Mbalducc]] ([[User talk:Mbalducc|talk]]) 19:14, 4 December 2017 (PST)

====Nicole====

====Hayden====

==Team Progress Reflections==

===[[Week 11]] Team Progress Reflections===

====Nicole====
# What worked?
#* We all work well in our positions. Arash and I worked together recently, so it was easy to coordinate what we are going to do as coder and designer. Everyone was open to opinions on the page and team name. Also, everyone communicated what they were having trouble finishing.
# What didn't work?
#* Like Mary said, we weren't able to meet in person. We planned out our meetup during class, but Friday ended up being a busy day for everyone.
# What will I do next to fix what didn't work?
#* Next week I will make sure to check in more with my partners. Even if we don't meet up, it is important to make sure everyone is caught up on the assignment and their individual parts.
====Mary====
# What worked?
#*I think as a team, we did a good job communicating and figuring out what needed to be done, and who would do each part.
# What didn't work?
#*We did not meet up outside of class. We had planned to, but we all ended up having conflicts so we couldn't meet.
# What will I do next to fix what didn't work?
#*I think this can be fixed just by making sure we all communicate in other ways, which is what we did. Through text messages we were able to talk about the assignment and help each other.
====Hayden====
# What worked?
#*We are all doing well communicating and completing our deliverables as individuals and as a group.
# What didn't work?
#*Everything worked well in regards to the group, but I did have some trouble finding all the information needed to create an annotated bibliography for the articles I used. Google Scholar gave me way too many results, and PubMed did not have a lot of articles that were either free or LMU had paid for.
# What will I do next to fix what didn't work?
#*I will continue to ask questions in class. I also feel more confident about finding useful articles after the completion of this assignment, so it shouldn't be a problem.
[[User:Hhinsch|Hhinsch]] ([[User talk:Hhinsch|talk]]) 22:44, 13 November 2017 (PST)

====Arash====

# What worked?
#*We were good at maintaining our own individual tasks and keeping each other updated via text message.

# What didn't work?
#*We were unable to schedule time to meet and work effectively.

# What will I do next to fix what didn't work?
#*Hopefully we will have lighter course loads and more free time for the next assignment, but besides that we will begin working sooner and try to work in person more than digitally.

===[[Week 12]] Team Progress Reflections===

====Arash====
# What worked?
#*I think we all got a better grasp of the assignment and time management for the assignment. We have a clear idea where we're headed.
# What didn't work?
#* I wish we had more time to dedicate to this class, as often our schedules don't line up.
# What will I do next to fix what didn't work?
#*We'll try to be more proactive about all our tasks so they don't pile up. I'm planning on starting some work during the thanksgiving break to lighten the load afterwards.
====Mary====
# What worked?
#*I think that this week I felt more comfortable with the project as a whole. I also liked presenting after the other guilds because I got to see their presentations to get a better idea of what we should include in ours.
# What didn't work?
#*I wish that I had more time to read the article and make the presentation. I felt that I didn't understand the article completely, and had to read it a few times to be happy with the way that I understood it and formed my outline of it. Because of this, I couldn't spend as much time as I would've wanted on making the presentation.
# What will I do next to fix what didn't work?
#*I will try to spend more time on the entire project, instead of just one part.

====Nicole====
#What Worked?
#*Arash and I communicated via text and had a better idea of what we needed to do earlier on in the week, which made it easier to progress and do quality, time efficient work.
#What didn't work?
#*We weren't all able to meet in person. I don't know if this was a huge issue this week, but scheduling conflicts might become more of a problem in December.
#What will I do next week to fix what didn't work?
#*Next week I will try to make plans with the group on Tuesday. I am assuming everyone is going out of town for Thanksgiving, but perhaps we can make certain dates within the week to have things done by so the rest of the group can look over the work.

====Hayden====
#What Worked?
#*This week we were a little more prepared to work together and complete the deliverables. As time goes by the end goal is becoming more apparent.
#What didn't work?
#*I spent a lot of time reading the article multiple times and it is still a bit confusing to me. A lot of the vocabulary wasn't even found in the dictionaries we provided and a lot of the information needed a lot of background knowledge to comprehend.
#What will I do next week to fix what didn't work?
#*Next week I will try and do the bulk of the assignment earlier in the week rather than on the weekend, so I may have more time to understand the material.[[User:Hhinsch|Hhinsch]] ([[User talk:Hhinsch|talk]]) 21:09, 20 November 2017 (PST)

===[[Week 14]] Team Progress Reflections===

====Arash====
# What worked?
#* Our design idea turned out pretty nicely, and was not that difficult to implement.
# What didn't work?
#* Coming up with what the final aesthetics will look like.
# What will I do next to fix what didn't work?
#* We will discuss the matter in class with the professors and our fellow students to see what works best for everyone.

====Mary====
#What worked?
#*Using YEASTRACT, Excel, and GRNsight to create a map of significant transcription factors in the profile I chose.
#What didn't work?
#*I have not fixed Weeks 8 and 10 as much as I would have wanted to.
#What will I do next to fix what didn't work?
#*Take more time, make sure I do things right the first time so I don't have to back and fix them later.
{{Pagedesiigner}}

Page Desiigner

2017-12-05T03:14:43Z

Mbalducc: /* Mary */

[[Category:Page Desiigner]]
[[Category:Group Projects]]

==Page Design Team Members==
Coder: [[User:ArashLari|Arash Lari]]
 
Project Manager/ Quality Assurance: [[User:hhinsch|Hayden Hinsch]]
 
Data Analyst: [[User:Mbalducc|Mary Balducci]]
 
Designer: [[User:Nicolekalcic|Nicole Kalcic]]

==Team Schedule==
[[Page Desiigner Schedule]]

==Page Desiigner Uploaded Files==

[[Media:MaryHaydenWeek12JournalClubPresentation.pptx ‎]]
 
[[File:Data Driven Design.zip]]

==Page Layout==
*<code>Below are a series of rough ideas we will use to create the layout of the page</code>
[[File:ACT1screenshot.png|500px]]
*We will be using a layout similar to the ACT1 gene page.
[[File:Sketchofpagedesign.png]]
*This is a rough sketch of what the page will look like.
*The section labeled '''description''' on the sketch will include the following:
**Gene ID from each database
**Description/Function (ensembl)
*Within the dropdown menus we will be incorporating the following:
**DNA Sequence (ensembl)
**Protein Sequence (UniProt)
**Locus tag (NCBI)
**Also Known As (NCBI)
**Consensus Sequence (JASPAR)
**Regulation (SGD)
**Interaction (SGD)
**Similar Proteins (UniProt)
**Gene Ontology (SGD)
**JASPAR
***Matrix ID
***Class Heat shock factors
***Family HSF factors
***Sequence Logo
***Frequency Matrix

==Annotated Bibliography==
===Mary's contribution:===
Pizzaro, Jewett, Nielson, Agosin. (2008) Growth Temperature Exerts Differential Physiological and Transcriptional Responses in Laboratory and Wine Strains of Saccharomyces Cerevisiae. "Applied and Environmental Microbiology", 74, 6358-6368, doi:10.1128/AEM.00602-08
*PubMed Abstract: https://www.ncbi.nlm.nih.gov/pubmed/18723660
*PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2570279/
*HTML format: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2570279/
*PDF format: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2570279/pdf/0602-08.pdf
*Copyright: 2008 American Society for Microbiology. It is open access.
*Publisher: American Society for Microbiology. This is a scientific society.
*Availability: Online and in print
*Did LMU pay a fee for this article: No
*I could not find the data associated with this article.

Homma, Iwahashi, Komatsu. (2003) Yeast Gene Expression During Growth at Low Temperature. ''Cryobiology'', 46, doi: 10.1016/S0011-2240(03)00028-2
*PubMed abstract: https://www.ncbi.nlm.nih.gov/pubmed/12818212
*PubMed Central:
*HTML format: http://www.sciencedirect.com/science/article/pii/S0011224003000282?via%3Dihub
*PDF format: https://ac.els-cdn.com/S0011224003000282/1-s2.0-S0011224003000282-main.pdf?_tid=aa7fa05e-c5d2-11e7-88ae-00000aacb361&acdnat=1510289609_6ec25501ce7af9dcc6b521ef8a024164
*Copyright 2003 Elsevier Science (USA). It is open access.
*Publisher: Elsevier. This is a for-profit publisher
*Availability: Online and in print
*Did LMU pay a fee for this article: No
*I could not find the data associated with this article.

===Hayden's Contribution===

Dahlquist, K. D., Fitzpatrick, B. G., Camacho, E. T., Entzminger, S. D., & Wanner, N. C. (2015). Parameter Estimation for Gene Regulatory Networks from Microarray Data: Cold Shock Response in Saccharomyces cerevisiae. Bulletin of Mathematical Biology, 77(8), 1457–1492. http://doi.org/10.1007/s11538-015-0092-6
* PubMed Abstract: https://www.ncbi.nlm.nih.gov/pubmed/26420504
* PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4636536/
* Publisher Full Text (HTML): https://link.springer.com/article/10.1007/s11538-015-0092-6
* Publisher Full Text (PDF): https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4636536/pdf/11538_2015_Article_92.pdf
* Copyright: The Author(s) 2015. Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
* Publisher: Bulletin of Mathematical Biology(scientific society)
* Availability: Online
* Did LMU pay a fee for this article: No
* Data: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4636536/bin/11538_2015_92_MOESM1_ESM.zip

Ando, A., Nakamura, T., Murata, Y., Takagi, H. and Shima, J. (2007), Identification and classification of genes required for tolerance to freeze–thaw stress revealed by genome-wide screening of Saccharomyces cerevisiae deletion strains. FEMS Yeast Research, 7: 244–253. doi:10.1111/j.1567-1364.2006.00162.x
* PubMed Abstract: https://www.ncbi.nlm.nih.gov/pubmed/16989656
* PubMed Central: N/A
* Publisher Full Text (HTML): https://academic.oup.com/femsyr/article/7/2/244/616825?searchresult=1
* Publisher Full Text (PDF): http://onlinelibrary.wiley.com/doi/10.1111/j.1567-1364.2006.00162.x/epdf
* Copyright: Copyright © 2007, Oxford University Press; Open Access after time has elapsed: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. You must ask permission from the publisher to use the article.
* Publisher: Published by Oxford University Press(respected open access organization)
* Availability: Online and in print
* Did LMU pay a fee for this article: No
* Data: I couldn't find any supplementary data other than the data provided in the article.

==Journal Club Presentations==
===Powerpoint Slides and Respective Articles===
[[File:Data Driven Design.zip]]
* Liikkanen, L. (2017). The Data-Driven Design Era in Professional Web Design. Accessed November 13, 2017, from http://delivery.acm.org/10.1145/3130000/3121355/p52-liikkanen.pdf?ip=157.242.223.254&id=3121355&acc=ACTIVE%20SERVICE&key=80B0E63637265656%2E958C566062FD1C18%2E4D4702B0C3E38B35%2E4D4702B0C3E38B35&CFID=829067610&CFTOKEN=20249523&__acm__=1510614806_1e8b314e23f771f9b139d99596801365
 
[[Media:MaryHaydenWeek12JournalClubPresentation.pptx ‎]]
*Pizzaro, Jewett, Nielson, Agosin. (2008) Growth Temperature Exerts Differential Physiological and Transcriptional Responses in Laboratory and Wine Strains of Saccharomyces Cerevisiae. "Applied and Environmental Microbiology", 74, 6358-6368, doi:10.1128/AEM.00602-08

==Executive Summaries==

===[[Week 11]] Executive Summaries===
====Arash====
This week, I worked on researching the given article and the development terms within it as well as prepare a presentation on the article. I also began thinking of some page layout ideas with Nicole to prepare to implement in the coming weeks. All of this information could be found on my Week 11 page: [[ArashLari_Week_11|ArashLari Week 11]].
[[User:ArashLari|ArashLari]] ([[User talk:ArashLari|talk]]) 02:09, 14 November 2017 (PST)
====Mary====
This week, I worked on creating an annotated bibliography. The articles I found were primary sources about experiments done involving cold shock on yeast, and the use of microarrays to show results. I used multiple databases to find these articles, and while doing so I learned what key words got me the results closest to what I wanted. While writing the annotated bibliography, I also learned more about the articles, such as when they were written, who published them, what kind of publisher they are, and other information. All of this is recorded in my [[mbalducc Week 11| Week 11]] page.

[[User:Mbalducc|Mbalducc]] ([[User talk:Mbalducc|talk]]) 23:03, 13 November 2017 (PST)

====Nicole====
This past week, I read the article ''The Data-Driven Design Era in Professional Web Design'' by L.A. Liikkanen. This allowed me to complete my individual journal: an informative outline of the article and list of ten definitions. Arash and I worked together to complete a 15 minute presentation that we are going to give on Tuesday. The presentation gives an overview of our individual journals and what we each learned. You can access more information on what I did this week here: [[Nicolekalcic Week 11]].
[[User:Nicolekalcic|Nicolekalcic]] ([[User talk:Nicolekalcic|talk]]) 01:27, 14 November 2017 (PST)
====Hayden====
This week I created part of the annotated bibliography we will be using for our final project. I conducted searched for "yeast cold shock microarray" articles and found which two articles I was going to use for the bibliography. The majority of the time this week was spent on finding the information needed for the annotated bibliography which can be found below on this page. More detailed information can be found on my [[hhinsch Week 11]] page. This week I became proficient in finding reliable article to use for our final project. This week we also created the group's template and wiki page. [[User:Hhinsch|Hhinsch]] ([[User talk:Hhinsch|talk]]) 22:43, 13 November 2017 (PST)

===[[Week 12]] Executive Summaries===
====Arash====
This week was rather light compared to the previous week. We mostly set up the files on our personal computers, which was convenient because as a computer science major I already had most of the necessary files. Nicole and I talked about some preliminary designs and set up a rough schedule that we'll make concrete after the break. This can be found on my week 12 page [[ArashLari Week 12] | Arash Lari Week 12]. [[User:ArashLari|ArashLari]] ([[User talk:ArashLari|talk]]) 20:43, 20 November 2017 (PST)

====Mary====
This week I read an article about an experiment done on wine and lab strains of yeast in different temperatures. The experimenters used DNA microarrays to determine which genes were affected by the change in temperatures and which were different based on the different strains of yeast. While reading the article, I can across words I had never seen before, so I also found and recorded the definitions of these words. I then made an outline of the article, to use as a basis for my presentation with our project manager, [[user:hhinsch| Hayden]]. All of this is on my [[mbalducc Week 12| Week 12]] page.

[[User:Mbalducc|Mbalducc]] ([[User talk:Mbalducc|talk]]) 19:51, 19 November 2017 (PST)

====Nicole====
Because Arash and I presented last week, we didn't have a heavy work load this week. Arash explained a lot of technical things to me, and we completed the first coding milestones and talked about design possibilities. I officially have a GitHub (nicolekal). I also downloaded the software I needed but didn't have onto my laptop. A full update can be found on: [[Nicolekalcic Week 12] | Nicole Kalcic Week 12]. [[User:Nicolekalcic|Nicolekalcic]] ([[User talk:Nicolekalcic|talk]]) 23:45, 20 November 2017 (PST)

====Hayden====
This week I worked with Mary specifically in order to complete our journal club presentation. As a group we worked together to make corrections to the [[Page Desiigner]] group page in order to complete the deliverables for this week. Mary and I created a schedule for our group along with helpful links. As a class we decided we will be using WhatsApp to communicate. I spent most of this week outlining the article (it was a pretty difficult read) and defining terms on my [[hhinsch Week 12]] page. [[User:Hhinsch|Hhinsch]] ([[User talk:Hhinsch|talk]]) 17:42, 20 November 2017 (PST)

===[[Week 14]] Executive Summaries===
====Arash====
This week I worked on implementing our designs for the web page. Nicole and Hayden helped come up with some design ideas. We ended up deciding that ACT1 was a very well designed page and that it would be best to follow the format of that page. There's only a few things left to do but our portion of the project is nearly complete, the generic version of every gene's page needs just a few finishing touches. [[User:ArashLari|ArashLari]] ([[User talk:ArashLari|talk]]) 18:19, 4 December 2017 (PST)

====Mary====
This week I finished the Week 10 assignment, using YEASTRACT and GRNsight. I specifically chose one profile from the STEM results to use in YEASTRACT to find transcription factors that regulate a cluster of genes. First I uploaded the genes from profile #22 into YEASTRACT to find 20 significant transcription factors that regulate them. Then, I used Excel to get rid of the transcription factors that were not related to other transcription factors. Once I had those, I imported them into GRNsight to create a map of the transcription factors and their relations to each other. I took a screenshot of this map and uploaded it to my [[mbalducc Week 14| Week 14]] page.

[[User:Mbalducc|Mbalducc]] ([[User talk:Mbalducc|talk]]) 19:14, 4 December 2017 (PST)

====Nicole====

====Hayden====

==Team Progress Reflections==

===[[Week 11]] Team Progress Reflections===

====Nicole====
# What worked?
#* We all work well in our positions. Arash and I worked together recently, so it was easy to coordinate what we are going to do as coder and designer. Everyone was open to opinions on the page and team name. Also, everyone communicated what they were having trouble finishing.
# What didn't work?
#* Like Mary said, we weren't able to meet in person. We planned out our meetup during class, but Friday ended up being a busy day for everyone.
# What will I do next to fix what didn't work?
#* Next week I will make sure to check in more with my partners. Even if we don't meet up, it is important to make sure everyone is caught up on the assignment and their individual parts.
====Mary====
# What worked?
#*I think as a team, we did a good job communicating and figuring out what needed to be done, and who would do each part.
# What didn't work?
#*We did not meet up outside of class. We had planned to, but we all ended up having conflicts so we couldn't meet.
# What will I do next to fix what didn't work?
#*I think this can be fixed just by making sure we all communicate in other ways, which is what we did. Through text messages we were able to talk about the assignment and help each other.
====Hayden====
# What worked?
#*We are all doing well communicating and completing our deliverables as individuals and as a group.
# What didn't work?
#*Everything worked well in regards to the group, but I did have some trouble finding all the information needed to create an annotated bibliography for the articles I used. Google Scholar gave me way too many results, and PubMed did not have a lot of articles that were either free or LMU had paid for.
# What will I do next to fix what didn't work?
#*I will continue to ask questions in class. I also feel more confident about finding useful articles after the completion of this assignment, so it shouldn't be a problem.
[[User:Hhinsch|Hhinsch]] ([[User talk:Hhinsch|talk]]) 22:44, 13 November 2017 (PST)

====Arash====

# What worked?
#*We were good at maintaining our own individual tasks and keeping each other updated via text message.

# What didn't work?
#*We were unable to schedule time to meet and work effectively.

# What will I do next to fix what didn't work?
#*Hopefully we will have lighter course loads and more free time for the next assignment, but besides that we will begin working sooner and try to work in person more than digitally.

===[[Week 12]] Team Progress Reflections===

====Arash====
# What worked?
#*I think we all got a better grasp of the assignment and time management for the assignment. We have a clear idea where we're headed.
# What didn't work?
#* I wish we had more time to dedicate to this class, as often our schedules don't line up.
# What will I do next to fix what didn't work?
#*We'll try to be more proactive about all our tasks so they don't pile up. I'm planning on starting some work during the thanksgiving break to lighten the load afterwards.
====Mary====
# What worked?
#*I think that this week I felt more comfortable with the project as a whole. I also liked presenting after the other guilds because I got to see their presentations to get a better idea of what we should include in ours.
# What didn't work?
#*I wish that I had more time to read the article and make the presentation. I felt that I didn't understand the article completely, and had to read it a few times to be happy with the way that I understood it and formed my outline of it. Because of this, I couldn't spend as much time as I would've wanted on making the presentation.
# What will I do next to fix what didn't work?
#*I will try to spend more time on the entire project, instead of just one part.

====Nicole====
#What Worked?
#*Arash and I communicated via text and had a better idea of what we needed to do earlier on in the week, which made it easier to progress and do quality, time efficient work.
#What didn't work?
#*We weren't all able to meet in person. I don't know if this was a huge issue this week, but scheduling conflicts might become more of a problem in December.
#What will I do next week to fix what didn't work?
#*Next week I will try to make plans with the group on Tuesday. I am assuming everyone is going out of town for Thanksgiving, but perhaps we can make certain dates within the week to have things done by so the rest of the group can look over the work.

====Hayden====
#What Worked?
#*This week we were a little more prepared to work together and complete the deliverables. As time goes by the end goal is becoming more apparent.
#What didn't work?
#*I spent a lot of time reading the article multiple times and it is still a bit confusing to me. A lot of the vocabulary wasn't even found in the dictionaries we provided and a lot of the information needed a lot of background knowledge to comprehend.
#What will I do next week to fix what didn't work?
#*Next week I will try and do the bulk of the assignment earlier in the week rather than on the weekend, so I may have more time to understand the material.[[User:Hhinsch|Hhinsch]] ([[User talk:Hhinsch|talk]]) 21:09, 20 November 2017 (PST)

===[[Week 14]] Team Progress Reflections===

====Arash====
# What worked?
#* Our design idea turned out pretty nicely, and was not that difficult to implement.
# What didn't work?
#* Coming up with what the final aesthetics will look like.
# What will I do next to fix what didn't work?
#* We will discuss the matter in class with the professors and our fellow students to see what works best for everyone.
{{Pagedesiigner}}

Mbalducc Week 14

2017-12-01T01:53:58Z

Mbalducc: /* Files */

==Files==
[[media:Mbalducc_Profile_22_yeastract_data.xlsx| Excel Sheet of Profile #22 TF from YEASTRACT]]

[[media:mbalducc_STEM.pdf| PowerPoint of STEM profiles and Gene Regulatory Network from GRNsight]]

==Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes==
# Opened the gene list in Excel for the one of the significant profiles from my stem analysis. I chose a cluster with a clear cold shock/recovery up/down or down/up pattern.
#* Copied the list of gene IDs onto my clipboard.
# Launched a web browser and went to the [http://www.yeastract.com/ YEASTRACT database].
#* On the left panel of the window, clicked on the link to [http://www.yeastract.com/formrankbytf.php ''Rank by TF''].
#* Pasted my list of genes from my cluster into the box labeled ''ORFs/Genes''.
#* Checked the box for ''Check for all TFs''.
#* Accepted the defaults for the Regulations Filter (Documented, DNA binding plus expression evidence)
#* Did '''''not''''' apply a filter for "Filter Documented Regulations by environmental condition".
#* Ranked genes by TF using: The % of genes in the list and in YEASTRACT regulated by each TF.
#* Clicked the ''Search'' button.
# Answered the following questions:
#* In the results window that appears, the p values colored green are considered "significant", the ones colored yellow are considered "borderline significant" and the ones colored pink are considered "not significant". '''''How many transcription factors are green or "significant"?'''''
#**43 are green or "significant".
#* '''''Copied the table of results from the web page and pasteed it into a new Excel workbook to preserve the results.'''''
#** '''''Uploaded the Excel file to OWW or Box and linked to it in my electronic lab notebook.'''''
#** '''''Is your transcription factor on the list? If so, what is their "% in user set", "% in YEASTRACT", and "p value".''''' (Note that this doesn't apply to the wt strain).
#***My transcription factor, Cin5 was on the list. Here is the data associated with it:
#****% in user set: 40.68%
#****% in YEASTRACT: 3.30%
#****p-value: 0.001495074628175
#*List of 20 significant transcription factors:
#*#Aft2p
#*#Mga2p
#*#Gis1p
#*#Hot1p
#*#Sut1p
#*#Zap1p
#*#Mig1p
#*#Hap2p
#*#Sut2p
#*#Bas1p
#*#Pho2p
#*#Opi1p
#*#Ert1p
#*#Oaf1p
#*#Sfp1p
#*#Mig3p
#*#Rlm1p
#*#Sum1p
#*#Ace2p
#*#Pho4p
#* Went back to the YEASTRACT database and followed the link to ''[http://www.yeastract.com/formgenerateregulationmatrix.php Generate Regulation Matrix]''.
#* Copied and pasted the list of transcription factors I identified (plus the transcription factor deleted in my strain: Cin5p) into both the "Transcription factors" field and the "Target ORF/Genes" field.
#* I used the "Regulations Filter" options of "Documented", "'''Only''' DNA binding evidence"
#** Clicked the "Generate" button.
#** In the results window that appeared, I clicked on the link to the "Regulation matrix (Semicolon Separated Values (CSV) file)" that appeared and saved it to my Desktop. I renamed this file with a meaningful name so that I could distinguish it from the other files I will generate.

=== Visualizing My Gene Regulatory Networks with GRNsight===

# Followed these steps for each of the three files I generated:
#* Opened the file in Excel. It did not open properly in Excel because a semicolon was used as the column delimiter instead of a comma. To fix this, I select the entire Column A. Then went to the "Data" tab and selected "Text to columns". In the Wizard that appeared, I selected "Delimited" and click "Next". In the next window, I selected "Semicolon", and clicked "Next". In the next window, I left the data format at "General", and clicked "Finish". This now looked like a table with the names of the transcription factors across the top and down the first column and all of the zeros and ones distributed throughout the rows and columns. This is called an "adjacency matrix." If there is a "1" in the cell, that means there is a connection between the transcription factor in that row with that column.
#* Saved this file in Microsoft Excel workbook format (.xlsx).
#* Checked to see that all of the transcription factors in the matrix were connected to at least one of the other transcription factors by making sure that there was at least one "1" in a row or column for that transcription factor. If a factor is not connected to any other factor, I deleted its row and column from the matrix. I made sure that I still had somewhere between 15 and 30 transcription factors in my network after this pruning.
#** I only deleted the transcription factor if there were all zeros in its column '''AND''' all zeros in its row. Visualizing the matrix in GRNsight (below) helped me find these easily.
#* For this adjacency matrix to be usable in GRNmap (the modeling software) and GRNsight (the visualization software), I needed to transpose the matrix. I Inserted a new worksheet into my Excel file and named it "network". Went back to the previous sheet and selected the entire matrix and copied it. Went to my new worksheet and clicked on the A1 cell in the upper left. Selected "Paste special" from the "Home" tab. In the window that appeared, I checked the box for "Transpose". This pasted my data with the columns transposed to rows and vice versa. This was necessary because I wanted the transcription factors that are the "regulatORS" across the top and the "regulatEES" along the side.
#* The labels for the genes in the columns and rows needed to match. Thus, I deleted the "p" from each of the gene names in the columns. I adjusted the case of the labels to make them all upper case.
#* In cell A1, I copied and pasted the text "rows genes affected/cols genes controlling".
#* Finally, for ease of working with the adjacency matrix in Excel, I wanted to alphabetize the gene labels both across the top and side.
#** I selected the area of the entire adjacency matrix.
#** I clicked the Data tab and clicked the custom sort button.
#** I sorted Column A alphabetically, being sure to exclude the header row.
#** Next I sorted row 1 from left to right, excluding cell A1. In the Custom Sort window, click on the options button and select sort left to right, excluding column 1.
#* Saved the workbook.
# Next I visualized what these gene regulatory networks look like with the GRNsight software.
#* I went to the [http://dondi.github.io/GRNsight/ GRNsight] home page.
#* I selected the menu item File > Open and select the regulation matrix .xlsx file that has the "network" worksheet in it that you formatted above. GRNsight created a graph of the network, I screenshot this and added it to my PowerPoint.

==Acknowledgements==
I worked with the rest of the [[Data Analysis]] guild: [[User:Aporras1|Antonio Porras]], [[User:dbashour|Dina Bashoura]], and [[User:Emmatyrnauer|Emma Tyrnauer]] on this assignment. We spoke in class and created a group chat so we could ask each other questions and help each other as we worked on the project. I also used the instructions from the [[Week 10]] assignment. I edited the instructions slightly so they would be specific to the profile I chose and the procedure I followed.

==References==

GRNsight. (2017). Home. Retrieved November 30, 2017 from http://dondi.github.io/GRNsight/

LMU BioDB 2017. (2017). Week 10 Retrieved November 28, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10

YEASTRACT. Generate Regulation Matrix. Retrieved November 30, 2017, from http://www.yeastract.com/formgenerateregulationmatrix.php

YEASTRACT. Rank by TF. Retrieved November 30, 2017, from http://www.yeastract.com/formrankbytf.php

Mbalducc Week 14

2017-12-01T01:53:11Z

Mbalducc: added ppt file

==Files==
[[media:Mbalducc_Profile_22_yeastract_data.xlsx| Excel Sheet of Profile #22 TF from YEASTRACT]]

[[media:mbalducc_STEM.pdf]]

==Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes==
# Opened the gene list in Excel for the one of the significant profiles from my stem analysis. I chose a cluster with a clear cold shock/recovery up/down or down/up pattern.
#* Copied the list of gene IDs onto my clipboard.
# Launched a web browser and went to the [http://www.yeastract.com/ YEASTRACT database].
#* On the left panel of the window, clicked on the link to [http://www.yeastract.com/formrankbytf.php ''Rank by TF''].
#* Pasted my list of genes from my cluster into the box labeled ''ORFs/Genes''.
#* Checked the box for ''Check for all TFs''.
#* Accepted the defaults for the Regulations Filter (Documented, DNA binding plus expression evidence)
#* Did '''''not''''' apply a filter for "Filter Documented Regulations by environmental condition".
#* Ranked genes by TF using: The % of genes in the list and in YEASTRACT regulated by each TF.
#* Clicked the ''Search'' button.
# Answered the following questions:
#* In the results window that appears, the p values colored green are considered "significant", the ones colored yellow are considered "borderline significant" and the ones colored pink are considered "not significant". '''''How many transcription factors are green or "significant"?'''''
#**43 are green or "significant".
#* '''''Copied the table of results from the web page and pasteed it into a new Excel workbook to preserve the results.'''''
#** '''''Uploaded the Excel file to OWW or Box and linked to it in my electronic lab notebook.'''''
#** '''''Is your transcription factor on the list? If so, what is their "% in user set", "% in YEASTRACT", and "p value".''''' (Note that this doesn't apply to the wt strain).
#***My transcription factor, Cin5 was on the list. Here is the data associated with it:
#****% in user set: 40.68%
#****% in YEASTRACT: 3.30%
#****p-value: 0.001495074628175
#*List of 20 significant transcription factors:
#*#Aft2p
#*#Mga2p
#*#Gis1p
#*#Hot1p
#*#Sut1p
#*#Zap1p
#*#Mig1p
#*#Hap2p
#*#Sut2p
#*#Bas1p
#*#Pho2p
#*#Opi1p
#*#Ert1p
#*#Oaf1p
#*#Sfp1p
#*#Mig3p
#*#Rlm1p
#*#Sum1p
#*#Ace2p
#*#Pho4p
#* Went back to the YEASTRACT database and followed the link to ''[http://www.yeastract.com/formgenerateregulationmatrix.php Generate Regulation Matrix]''.
#* Copied and pasted the list of transcription factors I identified (plus the transcription factor deleted in my strain: Cin5p) into both the "Transcription factors" field and the "Target ORF/Genes" field.
#* I used the "Regulations Filter" options of "Documented", "'''Only''' DNA binding evidence"
#** Clicked the "Generate" button.
#** In the results window that appeared, I clicked on the link to the "Regulation matrix (Semicolon Separated Values (CSV) file)" that appeared and saved it to my Desktop. I renamed this file with a meaningful name so that I could distinguish it from the other files I will generate.

=== Visualizing My Gene Regulatory Networks with GRNsight===

# Followed these steps for each of the three files I generated:
#* Opened the file in Excel. It did not open properly in Excel because a semicolon was used as the column delimiter instead of a comma. To fix this, I select the entire Column A. Then went to the "Data" tab and selected "Text to columns". In the Wizard that appeared, I selected "Delimited" and click "Next". In the next window, I selected "Semicolon", and clicked "Next". In the next window, I left the data format at "General", and clicked "Finish". This now looked like a table with the names of the transcription factors across the top and down the first column and all of the zeros and ones distributed throughout the rows and columns. This is called an "adjacency matrix." If there is a "1" in the cell, that means there is a connection between the transcription factor in that row with that column.
#* Saved this file in Microsoft Excel workbook format (.xlsx).
#* Checked to see that all of the transcription factors in the matrix were connected to at least one of the other transcription factors by making sure that there was at least one "1" in a row or column for that transcription factor. If a factor is not connected to any other factor, I deleted its row and column from the matrix. I made sure that I still had somewhere between 15 and 30 transcription factors in my network after this pruning.
#** I only deleted the transcription factor if there were all zeros in its column '''AND''' all zeros in its row. Visualizing the matrix in GRNsight (below) helped me find these easily.
#* For this adjacency matrix to be usable in GRNmap (the modeling software) and GRNsight (the visualization software), I needed to transpose the matrix. I Inserted a new worksheet into my Excel file and named it "network". Went back to the previous sheet and selected the entire matrix and copied it. Went to my new worksheet and clicked on the A1 cell in the upper left. Selected "Paste special" from the "Home" tab. In the window that appeared, I checked the box for "Transpose". This pasted my data with the columns transposed to rows and vice versa. This was necessary because I wanted the transcription factors that are the "regulatORS" across the top and the "regulatEES" along the side.
#* The labels for the genes in the columns and rows needed to match. Thus, I deleted the "p" from each of the gene names in the columns. I adjusted the case of the labels to make them all upper case.
#* In cell A1, I copied and pasted the text "rows genes affected/cols genes controlling".
#* Finally, for ease of working with the adjacency matrix in Excel, I wanted to alphabetize the gene labels both across the top and side.
#** I selected the area of the entire adjacency matrix.
#** I clicked the Data tab and clicked the custom sort button.
#** I sorted Column A alphabetically, being sure to exclude the header row.
#** Next I sorted row 1 from left to right, excluding cell A1. In the Custom Sort window, click on the options button and select sort left to right, excluding column 1.
#* Saved the workbook.
# Next I visualized what these gene regulatory networks look like with the GRNsight software.
#* I went to the [http://dondi.github.io/GRNsight/ GRNsight] home page.
#* I selected the menu item File > Open and select the regulation matrix .xlsx file that has the "network" worksheet in it that you formatted above. GRNsight created a graph of the network, I screenshot this and added it to my PowerPoint.

==Acknowledgements==
I worked with the rest of the [[Data Analysis]] guild: [[User:Aporras1|Antonio Porras]], [[User:dbashour|Dina Bashoura]], and [[User:Emmatyrnauer|Emma Tyrnauer]] on this assignment. We spoke in class and created a group chat so we could ask each other questions and help each other as we worked on the project. I also used the instructions from the [[Week 10]] assignment. I edited the instructions slightly so they would be specific to the profile I chose and the procedure I followed.

==References==

GRNsight. (2017). Home. Retrieved November 30, 2017 from http://dondi.github.io/GRNsight/

LMU BioDB 2017. (2017). Week 10 Retrieved November 28, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10

YEASTRACT. Generate Regulation Matrix. Retrieved November 30, 2017, from http://www.yeastract.com/formgenerateregulationmatrix.php

YEASTRACT. Rank by TF. Retrieved November 30, 2017, from http://www.yeastract.com/formrankbytf.php

File:Mbalducc STEM.pdf

2017-12-01T01:52:39Z

Mbalducc:

Mbalducc Week 14

2017-12-01T01:51:15Z

Mbalducc: /* Visualizing Your Gene Regulatory Networks with GRNsight */ typo

==Files==
[[media:Mbalducc_Profile_22_yeastract_data.xlsx| Excel Sheet of Profile #22 TF from YEASTRACT]]

==Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes==
# Opened the gene list in Excel for the one of the significant profiles from my stem analysis. I chose a cluster with a clear cold shock/recovery up/down or down/up pattern.
#* Copied the list of gene IDs onto my clipboard.
# Launched a web browser and went to the [http://www.yeastract.com/ YEASTRACT database].
#* On the left panel of the window, clicked on the link to [http://www.yeastract.com/formrankbytf.php ''Rank by TF''].
#* Pasted my list of genes from my cluster into the box labeled ''ORFs/Genes''.
#* Checked the box for ''Check for all TFs''.
#* Accepted the defaults for the Regulations Filter (Documented, DNA binding plus expression evidence)
#* Did '''''not''''' apply a filter for "Filter Documented Regulations by environmental condition".
#* Ranked genes by TF using: The % of genes in the list and in YEASTRACT regulated by each TF.
#* Clicked the ''Search'' button.
# Answered the following questions:
#* In the results window that appears, the p values colored green are considered "significant", the ones colored yellow are considered "borderline significant" and the ones colored pink are considered "not significant". '''''How many transcription factors are green or "significant"?'''''
#**43 are green or "significant".
#* '''''Copied the table of results from the web page and pasteed it into a new Excel workbook to preserve the results.'''''
#** '''''Uploaded the Excel file to OWW or Box and linked to it in my electronic lab notebook.'''''
#** '''''Is your transcription factor on the list? If so, what is their "% in user set", "% in YEASTRACT", and "p value".''''' (Note that this doesn't apply to the wt strain).
#***My transcription factor, Cin5 was on the list. Here is the data associated with it:
#****% in user set: 40.68%
#****% in YEASTRACT: 3.30%
#****p-value: 0.001495074628175
#*List of 20 significant transcription factors:
#*#Aft2p
#*#Mga2p
#*#Gis1p
#*#Hot1p
#*#Sut1p
#*#Zap1p
#*#Mig1p
#*#Hap2p
#*#Sut2p
#*#Bas1p
#*#Pho2p
#*#Opi1p
#*#Ert1p
#*#Oaf1p
#*#Sfp1p
#*#Mig3p
#*#Rlm1p
#*#Sum1p
#*#Ace2p
#*#Pho4p
#* Went back to the YEASTRACT database and followed the link to ''[http://www.yeastract.com/formgenerateregulationmatrix.php Generate Regulation Matrix]''.
#* Copied and pasted the list of transcription factors I identified (plus the transcription factor deleted in my strain: Cin5p) into both the "Transcription factors" field and the "Target ORF/Genes" field.
#* I used the "Regulations Filter" options of "Documented", "'''Only''' DNA binding evidence"
#** Clicked the "Generate" button.
#** In the results window that appeared, I clicked on the link to the "Regulation matrix (Semicolon Separated Values (CSV) file)" that appeared and saved it to my Desktop. I renamed this file with a meaningful name so that I could distinguish it from the other files I will generate.

=== Visualizing My Gene Regulatory Networks with GRNsight===

# Followed these steps for each of the three files I generated:
#* Opened the file in Excel. It did not open properly in Excel because a semicolon was used as the column delimiter instead of a comma. To fix this, I select the entire Column A. Then went to the "Data" tab and selected "Text to columns". In the Wizard that appeared, I selected "Delimited" and click "Next". In the next window, I selected "Semicolon", and clicked "Next". In the next window, I left the data format at "General", and clicked "Finish". This now looked like a table with the names of the transcription factors across the top and down the first column and all of the zeros and ones distributed throughout the rows and columns. This is called an "adjacency matrix." If there is a "1" in the cell, that means there is a connection between the transcription factor in that row with that column.
#* Saved this file in Microsoft Excel workbook format (.xlsx).
#* Checked to see that all of the transcription factors in the matrix were connected to at least one of the other transcription factors by making sure that there was at least one "1" in a row or column for that transcription factor. If a factor is not connected to any other factor, I deleted its row and column from the matrix. I made sure that I still had somewhere between 15 and 30 transcription factors in my network after this pruning.
#** I only deleted the transcription factor if there were all zeros in its column '''AND''' all zeros in its row. Visualizing the matrix in GRNsight (below) helped me find these easily.
#* For this adjacency matrix to be usable in GRNmap (the modeling software) and GRNsight (the visualization software), I needed to transpose the matrix. I Inserted a new worksheet into my Excel file and named it "network". Went back to the previous sheet and selected the entire matrix and copied it. Went to my new worksheet and clicked on the A1 cell in the upper left. Selected "Paste special" from the "Home" tab. In the window that appeared, I checked the box for "Transpose". This pasted my data with the columns transposed to rows and vice versa. This was necessary because I wanted the transcription factors that are the "regulatORS" across the top and the "regulatEES" along the side.
#* The labels for the genes in the columns and rows needed to match. Thus, I deleted the "p" from each of the gene names in the columns. I adjusted the case of the labels to make them all upper case.
#* In cell A1, I copied and pasted the text "rows genes affected/cols genes controlling".
#* Finally, for ease of working with the adjacency matrix in Excel, I wanted to alphabetize the gene labels both across the top and side.
#** I selected the area of the entire adjacency matrix.
#** I clicked the Data tab and clicked the custom sort button.
#** I sorted Column A alphabetically, being sure to exclude the header row.
#** Next I sorted row 1 from left to right, excluding cell A1. In the Custom Sort window, click on the options button and select sort left to right, excluding column 1.
#* Saved the workbook.
# Next I visualized what these gene regulatory networks look like with the GRNsight software.
#* I went to the [http://dondi.github.io/GRNsight/ GRNsight] home page.
#* I selected the menu item File > Open and select the regulation matrix .xlsx file that has the "network" worksheet in it that you formatted above. GRNsight created a graph of the network, I screenshot this and added it to my PowerPoint.

==Acknowledgements==
I worked with the rest of the [[Data Analysis]] guild: [[User:Aporras1|Antonio Porras]], [[User:dbashour|Dina Bashoura]], and [[User:Emmatyrnauer|Emma Tyrnauer]] on this assignment. We spoke in class and created a group chat so we could ask each other questions and help each other as we worked on the project. I also used the instructions from the [[Week 10]] assignment. I edited the instructions slightly so they would be specific to the profile I chose and the procedure I followed.

==References==

GRNsight. (2017). Home. Retrieved November 30, 2017 from http://dondi.github.io/GRNsight/

LMU BioDB 2017. (2017). Week 10 Retrieved November 28, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10

YEASTRACT. Generate Regulation Matrix. Retrieved November 30, 2017, from http://www.yeastract.com/formgenerateregulationmatrix.php

YEASTRACT. Rank by TF. Retrieved November 30, 2017, from http://www.yeastract.com/formrankbytf.php

Mbalducc Week 14

2017-12-01T01:50:33Z

Mbalducc: /* References */ added ref

==Files==
[[media:Mbalducc_Profile_22_yeastract_data.xlsx| Excel Sheet of Profile #22 TF from YEASTRACT]]

==Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes==
# Opened the gene list in Excel for the one of the significant profiles from my stem analysis. I chose a cluster with a clear cold shock/recovery up/down or down/up pattern.
#* Copied the list of gene IDs onto my clipboard.
# Launched a web browser and went to the [http://www.yeastract.com/ YEASTRACT database].
#* On the left panel of the window, clicked on the link to [http://www.yeastract.com/formrankbytf.php ''Rank by TF''].
#* Pasted my list of genes from my cluster into the box labeled ''ORFs/Genes''.
#* Checked the box for ''Check for all TFs''.
#* Accepted the defaults for the Regulations Filter (Documented, DNA binding plus expression evidence)
#* Did '''''not''''' apply a filter for "Filter Documented Regulations by environmental condition".
#* Ranked genes by TF using: The % of genes in the list and in YEASTRACT regulated by each TF.
#* Clicked the ''Search'' button.
# Answered the following questions:
#* In the results window that appears, the p values colored green are considered "significant", the ones colored yellow are considered "borderline significant" and the ones colored pink are considered "not significant". '''''How many transcription factors are green or "significant"?'''''
#**43 are green or "significant".
#* '''''Copied the table of results from the web page and pasteed it into a new Excel workbook to preserve the results.'''''
#** '''''Uploaded the Excel file to OWW or Box and linked to it in my electronic lab notebook.'''''
#** '''''Is your transcription factor on the list? If so, what is their "% in user set", "% in YEASTRACT", and "p value".''''' (Note that this doesn't apply to the wt strain).
#***My transcription factor, Cin5 was on the list. Here is the data associated with it:
#****% in user set: 40.68%
#****% in YEASTRACT: 3.30%
#****p-value: 0.001495074628175
#*List of 20 significant transcription factors:
#*#Aft2p
#*#Mga2p
#*#Gis1p
#*#Hot1p
#*#Sut1p
#*#Zap1p
#*#Mig1p
#*#Hap2p
#*#Sut2p
#*#Bas1p
#*#Pho2p
#*#Opi1p
#*#Ert1p
#*#Oaf1p
#*#Sfp1p
#*#Mig3p
#*#Rlm1p
#*#Sum1p
#*#Ace2p
#*#Pho4p
#* Went back to the YEASTRACT database and followed the link to ''[http://www.yeastract.com/formgenerateregulationmatrix.php Generate Regulation Matrix]''.
#* Copied and pasted the list of transcription factors I identified (plus the transcription factor deleted in my strain: Cin5p) into both the "Transcription factors" field and the "Target ORF/Genes" field.
#* I used the "Regulations Filter" options of "Documented", "'''Only''' DNA binding evidence"
#** Clicked the "Generate" button.
#** In the results window that appeared, I clicked on the link to the "Regulation matrix (Semicolon Separated Values (CSV) file)" that appeared and saved it to my Desktop. I renamed this file with a meaningful name so that I could distinguish it from the other files I will generate.

=== Visualizing Your Gene Regulatory Networks with GRNsight===

# Followed these steps for each of the three files I generated:
#* Opened the file in Excel. It did not open properly in Excel because a semicolon was used as the column delimiter instead of a comma. To fix this, I select the entire Column A. Then went to the "Data" tab and selected "Text to columns". In the Wizard that appeared, I selected "Delimited" and click "Next". In the next window, I selected "Semicolon", and clicked "Next". In the next window, I left the data format at "General", and clicked "Finish". This now looked like a table with the names of the transcription factors across the top and down the first column and all of the zeros and ones distributed throughout the rows and columns. This is called an "adjacency matrix." If there is a "1" in the cell, that means there is a connection between the transcription factor in that row with that column.
#* Saved this file in Microsoft Excel workbook format (.xlsx).
#* Checked to see that all of the transcription factors in the matrix were connected to at least one of the other transcription factors by making sure that there was at least one "1" in a row or column for that transcription factor. If a factor is not connected to any other factor, I deleted its row and column from the matrix. I made sure that I still had somewhere between 15 and 30 transcription factors in my network after this pruning.
#** I only deleted the transcription factor if there were all zeros in its column '''AND''' all zeros in its row. Visualizing the matrix in GRNsight (below) helped me find these easily.
#* For this adjacency matrix to be usable in GRNmap (the modeling software) and GRNsight (the visualization software), I needed to transpose the matrix. I Inserted a new worksheet into my Excel file and named it "network". Went back to the previous sheet and selected the entire matrix and copied it. Went to my new worksheet and clicked on the A1 cell in the upper left. Selected "Paste special" from the "Home" tab. In the window that appeared, I checked the box for "Transpose". This pasted my data with the columns transposed to rows and vice versa. This was necessary because I wanted the transcription factors that are the "regulatORS" across the top and the "regulatEES" along the side.
#* The labels for the genes in the columns and rows needed to match. Thus, I deleted the "p" from each of the gene names in the columns. I adjusted the case of the labels to make them all upper case.
#* In cell A1, I copied and pasted the text "rows genes affected/cols genes controlling".
#* Finally, for ease of working with the adjacency matrix in Excel, I wanted to alphabetize the gene labels both across the top and side.
#** I selected the area of the entire adjacency matrix.
#** I clicked the Data tab and clicked the custom sort button.
#** I sorted Column A alphabetically, being sure to exclude the header row.
#** Next I sorted row 1 from left to right, excluding cell A1. In the Custom Sort window, click on the options button and select sort left to right, excluding column 1.
#* Saved the workbook.
# Next I visualized what these gene regulatory networks look like with the GRNsight software.
#* I went to the [http://dondi.github.io/GRNsight/ GRNsight] home page.
#* I selected the menu item File > Open and select the regulation matrix .xlsx file that has the "network" worksheet in it that you formatted above. GRNsight created a graph of the network, I screenshot this and added it to my PowerPoint.

==Acknowledgements==
I worked with the rest of the [[Data Analysis]] guild: [[User:Aporras1|Antonio Porras]], [[User:dbashour|Dina Bashoura]], and [[User:Emmatyrnauer|Emma Tyrnauer]] on this assignment. We spoke in class and created a group chat so we could ask each other questions and help each other as we worked on the project. I also used the instructions from the [[Week 10]] assignment. I edited the instructions slightly so they would be specific to the profile I chose and the procedure I followed.

==References==

GRNsight. (2017). Home. Retrieved November 30, 2017 from http://dondi.github.io/GRNsight/

LMU BioDB 2017. (2017). Week 10 Retrieved November 28, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10

YEASTRACT. Generate Regulation Matrix. Retrieved November 30, 2017, from http://www.yeastract.com/formgenerateregulationmatrix.php

YEASTRACT. Rank by TF. Retrieved November 30, 2017, from http://www.yeastract.com/formrankbytf.php

Mbalducc Week 14

2017-12-01T01:47:19Z

Mbalducc: /* Acknowledgements */ added link to guild

==Files==
[[media:Mbalducc_Profile_22_yeastract_data.xlsx| Excel Sheet of Profile #22 TF from YEASTRACT]]

==Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes==
# Opened the gene list in Excel for the one of the significant profiles from my stem analysis. I chose a cluster with a clear cold shock/recovery up/down or down/up pattern.
#* Copied the list of gene IDs onto my clipboard.
# Launched a web browser and went to the [http://www.yeastract.com/ YEASTRACT database].
#* On the left panel of the window, clicked on the link to [http://www.yeastract.com/formrankbytf.php ''Rank by TF''].
#* Pasted my list of genes from my cluster into the box labeled ''ORFs/Genes''.
#* Checked the box for ''Check for all TFs''.
#* Accepted the defaults for the Regulations Filter (Documented, DNA binding plus expression evidence)
#* Did '''''not''''' apply a filter for "Filter Documented Regulations by environmental condition".
#* Ranked genes by TF using: The % of genes in the list and in YEASTRACT regulated by each TF.
#* Clicked the ''Search'' button.
# Answered the following questions:
#* In the results window that appears, the p values colored green are considered "significant", the ones colored yellow are considered "borderline significant" and the ones colored pink are considered "not significant". '''''How many transcription factors are green or "significant"?'''''
#**43 are green or "significant".
#* '''''Copied the table of results from the web page and pasteed it into a new Excel workbook to preserve the results.'''''
#** '''''Uploaded the Excel file to OWW or Box and linked to it in my electronic lab notebook.'''''
#** '''''Is your transcription factor on the list? If so, what is their "% in user set", "% in YEASTRACT", and "p value".''''' (Note that this doesn't apply to the wt strain).
#***My transcription factor, Cin5 was on the list. Here is the data associated with it:
#****% in user set: 40.68%
#****% in YEASTRACT: 3.30%
#****p-value: 0.001495074628175
#*List of 20 significant transcription factors:
#*#Aft2p
#*#Mga2p
#*#Gis1p
#*#Hot1p
#*#Sut1p
#*#Zap1p
#*#Mig1p
#*#Hap2p
#*#Sut2p
#*#Bas1p
#*#Pho2p
#*#Opi1p
#*#Ert1p
#*#Oaf1p
#*#Sfp1p
#*#Mig3p
#*#Rlm1p
#*#Sum1p
#*#Ace2p
#*#Pho4p
#* Went back to the YEASTRACT database and followed the link to ''[http://www.yeastract.com/formgenerateregulationmatrix.php Generate Regulation Matrix]''.
#* Copied and pasted the list of transcription factors I identified (plus the transcription factor deleted in my strain: Cin5p) into both the "Transcription factors" field and the "Target ORF/Genes" field.
#* I used the "Regulations Filter" options of "Documented", "'''Only''' DNA binding evidence"
#** Clicked the "Generate" button.
#** In the results window that appeared, I clicked on the link to the "Regulation matrix (Semicolon Separated Values (CSV) file)" that appeared and saved it to my Desktop. I renamed this file with a meaningful name so that I could distinguish it from the other files I will generate.

=== Visualizing Your Gene Regulatory Networks with GRNsight===

# Followed these steps for each of the three files I generated:
#* Opened the file in Excel. It did not open properly in Excel because a semicolon was used as the column delimiter instead of a comma. To fix this, I select the entire Column A. Then went to the "Data" tab and selected "Text to columns". In the Wizard that appeared, I selected "Delimited" and click "Next". In the next window, I selected "Semicolon", and clicked "Next". In the next window, I left the data format at "General", and clicked "Finish". This now looked like a table with the names of the transcription factors across the top and down the first column and all of the zeros and ones distributed throughout the rows and columns. This is called an "adjacency matrix." If there is a "1" in the cell, that means there is a connection between the transcription factor in that row with that column.
#* Saved this file in Microsoft Excel workbook format (.xlsx).
#* Checked to see that all of the transcription factors in the matrix were connected to at least one of the other transcription factors by making sure that there was at least one "1" in a row or column for that transcription factor. If a factor is not connected to any other factor, I deleted its row and column from the matrix. I made sure that I still had somewhere between 15 and 30 transcription factors in my network after this pruning.
#** I only deleted the transcription factor if there were all zeros in its column '''AND''' all zeros in its row. Visualizing the matrix in GRNsight (below) helped me find these easily.
#* For this adjacency matrix to be usable in GRNmap (the modeling software) and GRNsight (the visualization software), I needed to transpose the matrix. I Inserted a new worksheet into my Excel file and named it "network". Went back to the previous sheet and selected the entire matrix and copied it. Went to my new worksheet and clicked on the A1 cell in the upper left. Selected "Paste special" from the "Home" tab. In the window that appeared, I checked the box for "Transpose". This pasted my data with the columns transposed to rows and vice versa. This was necessary because I wanted the transcription factors that are the "regulatORS" across the top and the "regulatEES" along the side.
#* The labels for the genes in the columns and rows needed to match. Thus, I deleted the "p" from each of the gene names in the columns. I adjusted the case of the labels to make them all upper case.
#* In cell A1, I copied and pasted the text "rows genes affected/cols genes controlling".
#* Finally, for ease of working with the adjacency matrix in Excel, I wanted to alphabetize the gene labels both across the top and side.
#** I selected the area of the entire adjacency matrix.
#** I clicked the Data tab and clicked the custom sort button.
#** I sorted Column A alphabetically, being sure to exclude the header row.
#** Next I sorted row 1 from left to right, excluding cell A1. In the Custom Sort window, click on the options button and select sort left to right, excluding column 1.
#* Saved the workbook.
# Next I visualized what these gene regulatory networks look like with the GRNsight software.
#* I went to the [http://dondi.github.io/GRNsight/ GRNsight] home page.
#* I selected the menu item File > Open and select the regulation matrix .xlsx file that has the "network" worksheet in it that you formatted above. GRNsight created a graph of the network, I screenshot this and added it to my PowerPoint.

==Acknowledgements==
I worked with the rest of the [[Data Analysis]] guild: [[User:Aporras1|Antonio Porras]], [[User:dbashour|Dina Bashoura]], and [[User:Emmatyrnauer|Emma Tyrnauer]] on this assignment. We spoke in class and created a group chat so we could ask each other questions and help each other as we worked on the project. I also used the instructions from the [[Week 10]] assignment. I edited the instructions slightly so they would be specific to the profile I chose and the procedure I followed.

==References==

LMU BioDB 2017. (2017). Week 10 Retrieve November 28, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10

Mbalducc Week 14

2017-12-01T01:42:04Z

Mbalducc: /* Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes */ added notes

==Files==
[[media:Mbalducc_Profile_22_yeastract_data.xlsx| Excel Sheet of Profile #22 TF from YEASTRACT]]

==Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes==
# Opened the gene list in Excel for the one of the significant profiles from my stem analysis. I chose a cluster with a clear cold shock/recovery up/down or down/up pattern.
#* Copied the list of gene IDs onto my clipboard.
# Launched a web browser and went to the [http://www.yeastract.com/ YEASTRACT database].
#* On the left panel of the window, clicked on the link to [http://www.yeastract.com/formrankbytf.php ''Rank by TF''].
#* Pasted my list of genes from my cluster into the box labeled ''ORFs/Genes''.
#* Checked the box for ''Check for all TFs''.
#* Accepted the defaults for the Regulations Filter (Documented, DNA binding plus expression evidence)
#* Did '''''not''''' apply a filter for "Filter Documented Regulations by environmental condition".
#* Ranked genes by TF using: The % of genes in the list and in YEASTRACT regulated by each TF.
#* Clicked the ''Search'' button.
# Answered the following questions:
#* In the results window that appears, the p values colored green are considered "significant", the ones colored yellow are considered "borderline significant" and the ones colored pink are considered "not significant". '''''How many transcription factors are green or "significant"?'''''
#**43 are green or "significant".
#* '''''Copied the table of results from the web page and pasteed it into a new Excel workbook to preserve the results.'''''
#** '''''Uploaded the Excel file to OWW or Box and linked to it in my electronic lab notebook.'''''
#** '''''Is your transcription factor on the list? If so, what is their "% in user set", "% in YEASTRACT", and "p value".''''' (Note that this doesn't apply to the wt strain).
#***My transcription factor, Cin5 was on the list. Here is the data associated with it:
#****% in user set: 40.68%
#****% in YEASTRACT: 3.30%
#****p-value: 0.001495074628175
#*List of 20 significant transcription factors:
#*#Aft2p
#*#Mga2p
#*#Gis1p
#*#Hot1p
#*#Sut1p
#*#Zap1p
#*#Mig1p
#*#Hap2p
#*#Sut2p
#*#Bas1p
#*#Pho2p
#*#Opi1p
#*#Ert1p
#*#Oaf1p
#*#Sfp1p
#*#Mig3p
#*#Rlm1p
#*#Sum1p
#*#Ace2p
#*#Pho4p
#* Went back to the YEASTRACT database and followed the link to ''[http://www.yeastract.com/formgenerateregulationmatrix.php Generate Regulation Matrix]''.
#* Copied and pasted the list of transcription factors I identified (plus the transcription factor deleted in my strain: Cin5p) into both the "Transcription factors" field and the "Target ORF/Genes" field.
#* I used the "Regulations Filter" options of "Documented", "'''Only''' DNA binding evidence"
#** Clicked the "Generate" button.
#** In the results window that appeared, I clicked on the link to the "Regulation matrix (Semicolon Separated Values (CSV) file)" that appeared and saved it to my Desktop. I renamed this file with a meaningful name so that I could distinguish it from the other files I will generate.

=== Visualizing Your Gene Regulatory Networks with GRNsight===

# Followed these steps for each of the three files I generated:
#* Opened the file in Excel. It did not open properly in Excel because a semicolon was used as the column delimiter instead of a comma. To fix this, I select the entire Column A. Then went to the "Data" tab and selected "Text to columns". In the Wizard that appeared, I selected "Delimited" and click "Next". In the next window, I selected "Semicolon", and clicked "Next". In the next window, I left the data format at "General", and clicked "Finish". This now looked like a table with the names of the transcription factors across the top and down the first column and all of the zeros and ones distributed throughout the rows and columns. This is called an "adjacency matrix." If there is a "1" in the cell, that means there is a connection between the transcription factor in that row with that column.
#* Saved this file in Microsoft Excel workbook format (.xlsx).
#* Checked to see that all of the transcription factors in the matrix were connected to at least one of the other transcription factors by making sure that there was at least one "1" in a row or column for that transcription factor. If a factor is not connected to any other factor, I deleted its row and column from the matrix. I made sure that I still had somewhere between 15 and 30 transcription factors in my network after this pruning.
#** I only deleted the transcription factor if there were all zeros in its column '''AND''' all zeros in its row. Visualizing the matrix in GRNsight (below) helped me find these easily.
#* For this adjacency matrix to be usable in GRNmap (the modeling software) and GRNsight (the visualization software), I needed to transpose the matrix. I Inserted a new worksheet into my Excel file and named it "network". Went back to the previous sheet and selected the entire matrix and copied it. Went to my new worksheet and clicked on the A1 cell in the upper left. Selected "Paste special" from the "Home" tab. In the window that appeared, I checked the box for "Transpose". This pasted my data with the columns transposed to rows and vice versa. This was necessary because I wanted the transcription factors that are the "regulatORS" across the top and the "regulatEES" along the side.
#* The labels for the genes in the columns and rows needed to match. Thus, I deleted the "p" from each of the gene names in the columns. I adjusted the case of the labels to make them all upper case.
#* In cell A1, I copied and pasted the text "rows genes affected/cols genes controlling".
#* Finally, for ease of working with the adjacency matrix in Excel, I wanted to alphabetize the gene labels both across the top and side.
#** I selected the area of the entire adjacency matrix.
#** I clicked the Data tab and clicked the custom sort button.
#** I sorted Column A alphabetically, being sure to exclude the header row.
#** Next I sorted row 1 from left to right, excluding cell A1. In the Custom Sort window, click on the options button and select sort left to right, excluding column 1.
#* Saved the workbook.
# Next I visualized what these gene regulatory networks look like with the GRNsight software.
#* I went to the [http://dondi.github.io/GRNsight/ GRNsight] home page.
#* I selected the menu item File > Open and select the regulation matrix .xlsx file that has the "network" worksheet in it that you formatted above. GRNsight created a graph of the network, I screenshot this and added it to my PowerPoint.

==Acknowledgements==
I worked with the rest of the Data Analyst guild: [[User:Aporras1|Antonio Porras]], [[User:dbashour|Dina Bashoura]], and [[User:Emmatyrnauer|Emma Tyrnauer]] on this assignment. We spoke in class and created a group chat so we could ask each other questions and help each other as we worked on the project. I also used the instructions from the [[Week 10]] assignment. I edited the instructions slightly so they would be specific to the profile I chose and the procedure I followed.

==References==

LMU BioDB 2017. (2017). Week 10 Retrieve November 28, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10

Mbalducc Week 14

2017-12-01T01:30:48Z

Mbalducc: /* Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes */ changed instructions

==Files==
[[media:Mbalducc_Profile_22_yeastract_data.xlsx| Excel Sheet of Profile #22 TF from YEASTRACT]]

==Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes==
# Opened the gene list in Excel for the one of the significant profiles from my stem analysis. I chose a cluster with a clear cold shock/recovery up/down or down/up pattern.
#* Copied the list of gene IDs onto my clipboard.
# Launched a web browser and went to the [http://www.yeastract.com/ YEASTRACT database].
#* On the left panel of the window, clicked on the link to [http://www.yeastract.com/formrankbytf.php ''Rank by TF''].
#* Pasted my list of genes from my cluster into the box labeled ''ORFs/Genes''.
#* Checked the box for ''Check for all TFs''.
#* Accepted the defaults for the Regulations Filter (Documented, DNA binding plus expression evidence)
#* Did '''''not''''' apply a filter for "Filter Documented Regulations by environmental condition".
#* Ranked genes by TF using: The % of genes in the list and in YEASTRACT regulated by each TF.
#* Clicked the ''Search'' button.
# Answered the following questions:
#* In the results window that appears, the p values colored green are considered "significant", the ones colored yellow are considered "borderline significant" and the ones colored pink are considered "not significant". '''''How many transcription factors are green or "significant"?'''''
#**43 are green or "significant".
#* '''''Copied the table of results from the web page and pasteed it into a new Excel workbook to preserve the results.'''''
#** '''''Uploaded the Excel file to OWW or Box and linked to it in my electronic lab notebook.'''''
#** '''''Is your transcription factor on the list? If so, what is their "% in user set", "% in YEASTRACT", and "p value".''''' (Note that this doesn't apply to the wt strain).
#***My transcription factor, Cin5 was on the list. Here is the data associated with it:
#****% in user set: 40.68%
#****% in YEASTRACT: 3.30%
#****p-value: 0.001495074628175
#*List of 20 significant transcription factors:
#*#Aft2p
#*#Mga2p
#*#Gis1p
#*#Hot1p
#*#Sut1p
#*#Zap1p
#*#Mig1p
#*#Hap2p
#*#Sut2p
#*#Bas1p
#*#Pho2p
#*#Opi1p
#*#Ert1p
#*#Oaf1p
#*#Sfp1p
#*#Mig3p
#*#Rlm1p
#*#Sum1p
#*#Ace2p
#*#Pho4p
#* Went back to the YEASTRACT database and followed the link to ''[http://www.yeastract.com/formgenerateregulationmatrix.php Generate Regulation Matrix]''.
#* Copied and pasted the list of transcription factors I identified (plus the transcription factor deleted in my strain: Cin5p) into both the "Transcription factors" field and the "Target ORF/Genes" field.
#* I used the "Regulations Filter" options of "Documented", "'''Only''' DNA binding evidence"
#** Clicked the "Generate" button.
#** In the results window that appeared, I clicked on the link to the "Regulation matrix (Semicolon Separated Values (CSV) file)" that appeared and saved it to my Desktop. I renamed this file with a meaningful name so that I could distinguish it from the other files I will generate.

=== Visualizing Your Gene Regulatory Networks with GRNsight===

# Followed these steps for each of the three files I generated:
#* Opened the file in Excel. It did not open properly in Excel because a semicolon was used as the column delimiter instead of a comma. To fix this, I select the entire Column A. Then went to the "Data" tab and selected "Text to columns". In the Wizard that appeared, I selected "Delimited" and click "Next". In the next window, I selected "Semicolon", and clicked "Next". In the next window, I left the data format at "General", and clicked "Finish". This now looked like a table with the names of the transcription factors across the top and down the first column and all of the zeros and ones distributed throughout the rows and columns. This is called an "adjacency matrix." If there is a "1" in the cell, that means there is a connection between the transcription factor in that row with that column.
#* Saved this file in Microsoft Excel workbook format (.xlsx).
#* Checked to see that all of the transcription factors in the matrix were connected to at least one of the other transcription factors by making sure that there was at least one "1" in a row or column for that transcription factor. If a factor is not connected to any other factor, I deleted its row and column from the matrix. I made sure that I still had somewhere between 15 and 30 transcription factors in my network after this pruning.
#** I only deleted the transcription factor if there were all zeros in its column '''AND''' all zeros in its row. Visualizing the matrix in GRNsight (below) helped me find these easily.
#* For this adjacency matrix to be usable in GRNmap (the modeling software) and GRNsight (the visualization software), I needed to transpose the matrix. I Inserted a new worksheet into my Excel file and named it "network". Went back to the previous sheet and selected the entire matrix and copied it. Went to my new worksheet and clicked on the A1 cell in the upper left. Selected "Paste special" from the "Home" tab. In the window that appeared, I checked the box for "Transpose". This pasted my data with the columns transposed to rows and vice versa. This was necessary because I wanted the transcription factors that are the "regulatORS" across the top and the "regulatEES" along the side.
#* The labels for the genes in the columns and rows needed to match. Thus, I deleted the "p" from each of the gene names in the columns. I adjusted the case of the labels to make them all upper case.
#* In cell A1, I copied and pasted the text "rows genes affected/cols genes controlling".
#* Finally, for ease of working with the adjacency matrix in Excel, I wanted to alphabetize the gene labels both across the top and side.
#** I selected the area of the entire adjacency matrix.
#** I clicked the Data tab and clicked the custom sort button.
#** I sorted Column A alphabetically, being sure to exclude the header row.
#** Next I sorted row 1 from left to right, excluding cell A1. In the Custom Sort window, click on the options button and select sort left to right, excluding column 1.
#* Saved the workbook.
# Next I visualized what these gene regulatory networks look like with the GRNsight software.
#* I went to the [http://dondi.github.io/GRNsight/ GRNsight] home page.
#* I selected the menu item File > Open and select the regulation matrix .xlsx file that has the "network" worksheet in it that you formatted above. If the file has been formatted properly, GRNsight should automatically create a graph of your network. Move the nodes (genes) around until you get a layout that you like and take a screenshot of the results. Paste it into your PowerPoint presentation.

==== Summary of what you need to turn in for the individual Week 10 assignment ====

# Your individual journal page should have an '''''electronic lab notebook''''' recording your work. This includes the detailed methods specific to your analysis, your result files, the answers to any questions posed in the protocol above, a scientific conclusion, and the acknowledgments and references sections. Don't forget your paragraph which is a biological interpretation of your stem results.
# Upload your updated Excel spreadsheet to the wiki that has today's manipulations in it. Use the same filename as before so that the download link that you already (previous versions will still be available in the history).
# Append the screenshots of the stem results to the PowerPoint presentation that contains the p value table that you created for the [[Week 8]] assignments. Each slide in the presentation should have a meaningful title that describes the main message of the slide.
# Zip together all of the tab-delimited text files that you created for and from stem and upload them to the wiki.
#* the file that was saved from your original spreadsheet that you used to run stem
#* each of the genelist and GOlist files for each of your significant profiles.
# Write a paragraph-length conclusion for this week's exercise.

==Acknowledgements==
I worked with the rest of the Data Analyst guild: [[User:Aporras1|Antonio Porras]], [[User:dbashour|Dina Bashoura]], and [[User:Emmatyrnauer|Emma Tyrnauer]] on this assignment. We spoke in class and created a group chat so we could ask each other questions and help each other as we worked on the project. I also used the instructions from the [[Week 10]] assignment. I edited the instructions slightly so they would be specific to the profile I chose and the procedure I followed.

==References==

LMU BioDB 2017. (2017). Week 10 Retrieve November 28, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10

Mbalducc Week 14

2017-12-01T01:01:17Z

Mbalducc: /* Visualizing Your Gene Regulatory Networks with GRNsight */ added to instructions

==Files==
[[media:Mbalducc_Profile_22_yeastract_data.xlsx| Excel Sheet of Profile #22 TF from YEASTRACT]]

==Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes==
# Opened the gene list in Excel for the one of the significant profiles from my stem analysis. I chose a cluster with a clear cold shock/recovery up/down or down/up pattern.
#* Copied the list of gene IDs onto my clipboard.
# Launched a web browser and went to the [http://www.yeastract.com/ YEASTRACT database].
#* On the left panel of the window, clicked on the link to [http://www.yeastract.com/formrankbytf.php ''Rank by TF''].
#* Pasted my list of genes from my cluster into the box labeled ''ORFs/Genes''.
#* Checked the box for ''Check for all TFs''.
#* Accepted the defaults for the Regulations Filter (Documented, DNA binding plus expression evidence)
#* Did '''''not''''' apply a filter for "Filter Documented Regulations by environmental condition".
#* Ranked genes by TF using: The % of genes in the list and in YEASTRACT regulated by each TF.
#* Clicked the ''Search'' button.
# Answered the following questions:
#* In the results window that appears, the p values colored green are considered "significant", the ones colored yellow are considered "borderline significant" and the ones colored pink are considered "not significant". '''''How many transcription factors are green or "significant"?'''''
#**43 are green or "significant".
#* '''''Copied the table of results from the web page and pasteed it into a new Excel workbook to preserve the results.'''''
#** '''''Uploaded the Excel file to OWW or Box and linked to it in my electronic lab notebook.'''''
#** '''''Is your transcription factor on the list? If so, what is their "% in user set", "% in YEASTRACT", and "p value".''''' (Note that this doesn't apply to the wt strain).
#***My transcription factor, Cin5 was on the list. Here is the data associated with it:
#****% in user set: 40.68%
#****% in YEASTRACT: 3.30%
#****p-value: 0.001495074628175
#*List of 20 significant transcription factors:
#*#Aft2p
#*#Mga2p
#*#Gis1p
#*#Hot1p
#*#Sut1p
#*#Zap1p
#*#Mig1p
#*#Hap2p
#*#Sut2p
#*#Bas1p
#*#Pho2p
#*#Opi1p
#*#Ert1p
#*#Oaf1p
#*#Sfp1p
#*#Mig3p
#*#Rlm1p
#*#Sum1p
#*#Ace2p
#*#Pho4p
#* Went back to the YEASTRACT database and followed the link to ''[http://www.yeastract.com/formgenerateregulationmatrix.php Generate Regulation Matrix]''.
#* Copied and pasted the list of transcription factors I identified (plus the transcription factor deleted in my strain: Cin5p) into both the "Transcription factors" field and the "Target ORF/Genes" field.
#* I used the "Regulations Filter" options of "Documented", "'''Only''' DNA binding evidence"
#** Clicked the "Generate" button.
#** In the results window that appeared, I clicked on the link to the "Regulation matrix (Semicolon Separated Values (CSV) file)" that appeared and saved it to my Desktop. I renamed this file with a meaningful name so that I could distinguish it from the other files I will generate.

=== Visualizing Your Gene Regulatory Networks with GRNsight===

# Followed these steps for each of the three files I generated:
#* Opened the file in Excel. It did not open properly in Excel because a semicolon was used as the column delimiter instead of a comma. To fix this, I select the entire Column A. Then went to the "Data" tab and selected "Text to columns". In the Wizard that appeared, I selected "Delimited" and click "Next". In the next window, I selected "Semicolon", and clicked "Next". In the next window, I left the data format at "General", and clicked "Finish". This now looked like a table with the names of the transcription factors across the top and down the first column and all of the zeros and ones distributed throughout the rows and columns. This is called an "adjacency matrix." If there is a "1" in the cell, that means there is a connection between the transcription factor in that row with that column.
#* Saved this file in Microsoft Excel workbook format (.xlsx).
#* Checked to see that all of the transcription factors in the matrix were connected to at least one of the other transcription factors by making sure that there was at least one "1" in a row or column for that transcription factor. If a factor is not connected to any other factor, I deleted its row and column from the matrix. I made sure that I still had somewhere between 15 and 30 transcription factors in my network after this pruning.
#** I only deleted the transcription factor if there were all zeros in its column '''AND''' all zeros in its row. Visualizing the matrix in GRNsight (below) helped me find these easily.
#* For this adjacency matrix to be usable in GRNmap (the modeling software) and GRNsight (the visualization software), I needed to transpose the matrix. I Inserted a new worksheet into my Excel file and named it "network". Went back to the previous sheet and selected the entire matrix and copied it. Went to my new worksheet and clicked on the A1 cell in the upper left. Selected "Paste special" from the "Home" tab. In the window that appeared, I checked the box for "Transpose". This pasted my data with the columns transposed to rows and vice versa. This was necessary because I wanted the transcription factors that are the "regulatORS" across the top and the "regulatEES" along the side.
#* The labels for the genes in the columns and rows needed to match. Thus, I deleted the "p" from each of the gene names in the columns. I adjusted the case of the labels to make them all upper case.
#* In cell A1, I copied and pasted the text "rows genes affected/cols genes controlling".
#* Finally, for ease of working with the adjacency matrix in Excel, I wanted to alphabetize the gene labels both across the top and side.
#** I selected the area of the entire adjacency matrix.
#** I clicked the Data tab and clicked the custom sort button.
#** I sorted Column A alphabetically, being sure to exclude the header row.
#** Next I sorted row 1 from left to right, excluding cell A1. In the Custom Sort window, click on the options button and select sort left to right, excluding column 1.
#* Saved the workbook.

# Now we will visualize what these gene regulatory networks look like with the GRNsight software.
#* Go to the [http://dondi.github.io/GRNsight/ GRNsight] home page.
#* Select the menu item File > Open and select the regulation matrix .xlsx file that has the "network" worksheet in it that you formatted above. If the file has been formatted properly, GRNsight should automatically create a graph of your network. Move the nodes (genes) around until you get a layout that you like and take a screenshot of the results. Paste it into your PowerPoint presentation.

==== Summary of what you need to turn in for the individual Week 10 assignment ====

# Your individual journal page should have an '''''electronic lab notebook''''' recording your work. This includes the detailed methods specific to your analysis, your result files, the answers to any questions posed in the protocol above, a scientific conclusion, and the acknowledgments and references sections. Don't forget your paragraph which is a biological interpretation of your stem results.
# Upload your updated Excel spreadsheet to the wiki that has today's manipulations in it. Use the same filename as before so that the download link that you already (previous versions will still be available in the history).
# Append the screenshots of the stem results to the PowerPoint presentation that contains the p value table that you created for the [[Week 8]] assignments. Each slide in the presentation should have a meaningful title that describes the main message of the slide.
# Zip together all of the tab-delimited text files that you created for and from stem and upload them to the wiki.
#* the file that was saved from your original spreadsheet that you used to run stem
#* each of the genelist and GOlist files for each of your significant profiles.
# Write a paragraph-length conclusion for this week's exercise.

==Acknowledgements==
I worked with the rest of the Data Analyst guild: [[User:Aporras1|Antonio Porras]], [[User:dbashour|Dina Bashoura]], and [[User:Emmatyrnauer|Emma Tyrnauer]] on this assignment. We spoke in class and created a group chat so we could ask each other questions and help each other as we worked on the project. I also used the instructions from the [[Week 10]] assignment. I edited the instructions slightly so they would be specific to the profile I chose and the procedure I followed.

==References==

LMU BioDB 2017. (2017). Week 10 Retrieve November 28, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10

Mbalducc Week 14

2017-11-30T23:56:44Z

Mbalducc: /* Visualizing Your Gene Regulatory Networks with GRNsight */ new excel file

==Files==
[[media:Mbalducc_Profile_22_yeastract_data.xlsx| Excel Sheet of Profile #22 TF from YEASTRACT]]

==Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes==
# Opened the gene list in Excel for the one of the significant profiles from my stem analysis. I chose a cluster with a clear cold shock/recovery up/down or down/up pattern.
#* Copied the list of gene IDs onto my clipboard.
# Launched a web browser and went to the [http://www.yeastract.com/ YEASTRACT database].
#* On the left panel of the window, clicked on the link to [http://www.yeastract.com/formrankbytf.php ''Rank by TF''].
#* Pasted my list of genes from my cluster into the box labeled ''ORFs/Genes''.
#* Checked the box for ''Check for all TFs''.
#* Accepted the defaults for the Regulations Filter (Documented, DNA binding plus expression evidence)
#* Did '''''not''''' apply a filter for "Filter Documented Regulations by environmental condition".
#* Ranked genes by TF using: The % of genes in the list and in YEASTRACT regulated by each TF.
#* Clicked the ''Search'' button.
# Answered the following questions:
#* In the results window that appears, the p values colored green are considered "significant", the ones colored yellow are considered "borderline significant" and the ones colored pink are considered "not significant". '''''How many transcription factors are green or "significant"?'''''
#**43 are green or "significant".
#* '''''Copied the table of results from the web page and pasteed it into a new Excel workbook to preserve the results.'''''
#** '''''Uploaded the Excel file to OWW or Box and linked to it in my electronic lab notebook.'''''
#** '''''Is your transcription factor on the list? If so, what is their "% in user set", "% in YEASTRACT", and "p value".''''' (Note that this doesn't apply to the wt strain).
#***My transcription factor, Cin5 was on the list. Here is the data associated with it:
#****% in user set: 40.68%
#****% in YEASTRACT: 3.30%
#****p-value: 0.001495074628175
#*List of 20 significant transcription factors:
#*#Aft2p
#*#Mga2p
#*#Gis1p
#*#Hot1p
#*#Sut1p
#*#Zap1p
#*#Mig1p
#*#Hap2p
#*#Sut2p
#*#Bas1p
#*#Pho2p
#*#Opi1p
#*#Ert1p
#*#Oaf1p
#*#Sfp1p
#*#Mig3p
#*#Rlm1p
#*#Sum1p
#*#Ace2p
#*#Pho4p
#* Went back to the YEASTRACT database and followed the link to ''[http://www.yeastract.com/formgenerateregulationmatrix.php Generate Regulation Matrix]''.
#* Copied and pasted the list of transcription factors I identified (plus the transcription factor deleted in my strain: Cin5p) into both the "Transcription factors" field and the "Target ORF/Genes" field.
#* I used the "Regulations Filter" options of "Documented", "'''Only''' DNA binding evidence"
#** Clicked the "Generate" button.
#** In the results window that appeared, I clicked on the link to the "Regulation matrix (Semicolon Separated Values (CSV) file)" that appeared and saved it to my Desktop. I renamed this file with a meaningful name so that I could distinguish it from the other files I will generate.

=== Visualizing Your Gene Regulatory Networks with GRNsight===

# Followed these steps for each of the three files I generated:
#* Opened the file in Excel. It did not open properly in Excel because a semicolon was used as the column delimiter instead of a comma. To fix this, I select the entire Column A. Then went to the "Data" tab and selected "Text to columns". In the Wizard that appeared, I selected "Delimited" and click "Next". In the next window, I selected "Semicolon", and clicked "Next". In the next window, I left the data format at "General", and clicked "Finish". This now looked like a table with the names of the transcription factors across the top and down the first column and all of the zeros and ones distributed throughout the rows and columns. This is called an "adjacency matrix." If there is a "1" in the cell, that means there is a connection between the transcription factor in that row with that column.
#* Saved this file in Microsoft Excel workbook format (.xlsx).
#* Checked to see that all of the transcription factors in the matrix were connected to at least one of the other transcription factors by making sure that there was at least one "1" in a row or column for that transcription factor. If a factor is not connected to any other factor, I deleted its row and column from the matrix. I made sure that I still had somewhere between 15 and 30 transcription factors in my network after this pruning.
#** I only deleted the transcription factor if there were all zeros in its column '''AND''' all zeros in its row. Visualizing the matrix in GRNsight (below) helped me find these easily.
#* For this adjacency matrix to be usable in GRNmap (the modeling software) and GRNsight (the visualization software), I needed to transpose the matrix. I Inserted a new worksheet into my Excel file and named it "network". Went back to the previous sheet and selected the entire matrix and copied it. Went to my new worksheet and clicked on the A1 cell in the upper left. Selected "Paste special" from the "Home" tab. In the window that appeared, I checked the box for "Transpose". This pasted my data with the columns transposed to rows and vice versa. This was necessary because I wanted the transcription factors that are the "regulatORS" across the top and the "regulatEES" along the side.

#* The labels for the genes in the columns and rows needed to match. Thus, I deleted the "p" from each of the gene names in the columns. I adjusted the case of the labels to make them all upper case.
#* In cell A1, I copied and pasted the text "rows genes affected/cols genes controlling".
#* Finally, for ease of working with the adjacency matrix in Excel, we want to alphabatize the gene labels both across the top and side.
#** Select the area of the entire adjacency matrix.
#** Click the Data tab and click the custom sort button.
#** Sort Column A alphabetically, being sure to exclude the header row.
#** Now sort row 1 from left to right, excluding cell A1. In the Custom Sort window, click on the options button and select sort left to right, excluding column 1.
#* Name the worksheet containing your organized adjacency matrix "network" and Save.
# Now we will visualize what these gene regulatory networks look like with the GRNsight software.
#* Go to the [http://dondi.github.io/GRNsight/ GRNsight] home page.
#* Select the menu item File > Open and select the regulation matrix .xlsx file that has the "network" worksheet in it that you formatted above. If the file has been formatted properly, GRNsight should automatically create a graph of your network. Move the nodes (genes) around until you get a layout that you like and take a screenshot of the results. Paste it into your PowerPoint presentation.

==== Summary of what you need to turn in for the individual Week 10 assignment ====

# Your individual journal page should have an '''''electronic lab notebook''''' recording your work. This includes the detailed methods specific to your analysis, your result files, the answers to any questions posed in the protocol above, a scientific conclusion, and the acknowledgments and references sections. Don't forget your paragraph which is a biological interpretation of your stem results.
# Upload your updated Excel spreadsheet to the wiki that has today's manipulations in it. Use the same filename as before so that the download link that you already (previous versions will still be available in the history).
# Append the screenshots of the stem results to the PowerPoint presentation that contains the p value table that you created for the [[Week 8]] assignments. Each slide in the presentation should have a meaningful title that describes the main message of the slide.
# Zip together all of the tab-delimited text files that you created for and from stem and upload them to the wiki.
#* the file that was saved from your original spreadsheet that you used to run stem
#* each of the genelist and GOlist files for each of your significant profiles.
# Write a paragraph-length conclusion for this week's exercise.

==Acknowledgements==
I worked with the rest of the Data Analyst guild: [[User:Aporras1|Antonio Porras]], [[User:dbashour|Dina Bashoura]], and [[User:Emmatyrnauer|Emma Tyrnauer]] on this assignment. We spoke in class and created a group chat so we could ask each other questions and help each other as we worked on the project. I also used the instructions from the [[Week 10]] assignment. I edited the instructions slightly so they would be specific to the profile I chose and the procedure I followed.

==References==

LMU BioDB 2017. (2017). Week 10 Retrieve November 28, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10

Mbalducc Week 14

2017-11-30T23:41:53Z

Mbalducc: /* Visualizing Your Gene Regulatory Networks with GRNsight */ edited instructions

==Files==
[[media:Mbalducc_Profile_22_yeastract_data.xlsx| Excel Sheet of Profile #22 TF from YEASTRACT]]

==Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes==
# Opened the gene list in Excel for the one of the significant profiles from my stem analysis. I chose a cluster with a clear cold shock/recovery up/down or down/up pattern.
#* Copied the list of gene IDs onto my clipboard.
# Launched a web browser and went to the [http://www.yeastract.com/ YEASTRACT database].
#* On the left panel of the window, clicked on the link to [http://www.yeastract.com/formrankbytf.php ''Rank by TF''].
#* Pasted my list of genes from my cluster into the box labeled ''ORFs/Genes''.
#* Checked the box for ''Check for all TFs''.
#* Accepted the defaults for the Regulations Filter (Documented, DNA binding plus expression evidence)
#* Did '''''not''''' apply a filter for "Filter Documented Regulations by environmental condition".
#* Ranked genes by TF using: The % of genes in the list and in YEASTRACT regulated by each TF.
#* Clicked the ''Search'' button.
# Answered the following questions:
#* In the results window that appears, the p values colored green are considered "significant", the ones colored yellow are considered "borderline significant" and the ones colored pink are considered "not significant". '''''How many transcription factors are green or "significant"?'''''
#**43 are green or "significant".
#* '''''Copied the table of results from the web page and pasteed it into a new Excel workbook to preserve the results.'''''
#** '''''Uploaded the Excel file to OWW or Box and linked to it in my electronic lab notebook.'''''
#** '''''Is your transcription factor on the list? If so, what is their "% in user set", "% in YEASTRACT", and "p value".''''' (Note that this doesn't apply to the wt strain).
#***My transcription factor, Cin5 was on the list. Here is the data associated with it:
#****% in user set: 40.68%
#****% in YEASTRACT: 3.30%
#****p-value: 0.001495074628175
#*List of 20 significant transcription factors:
#*#Aft2p
#*#Mga2p
#*#Gis1p
#*#Hot1p
#*#Sut1p
#*#Zap1p
#*#Mig1p
#*#Hap2p
#*#Sut2p
#*#Bas1p
#*#Pho2p
#*#Opi1p
#*#Ert1p
#*#Oaf1p
#*#Sfp1p
#*#Mig3p
#*#Rlm1p
#*#Sum1p
#*#Ace2p
#*#Pho4p
#* Went back to the YEASTRACT database and followed the link to ''[http://www.yeastract.com/formgenerateregulationmatrix.php Generate Regulation Matrix]''.
#* Copied and pasted the list of transcription factors I identified (plus the transcription factor deleted in my strain: Cin5p) into both the "Transcription factors" field and the "Target ORF/Genes" field.
#* I used the "Regulations Filter" options of "Documented", "'''Only''' DNA binding evidence"
#** Clicked the "Generate" button.
#** In the results window that appeared, I clicked on the link to the "Regulation matrix (Semicolon Separated Values (CSV) file)" that appeared and saved it to my Desktop. I renamed this file with a meaningful name so that I could distinguish it from the other files I will generate.

=== Visualizing Your Gene Regulatory Networks with GRNsight===

# Followed these steps for each of the three files I generated:
#* Opened the file in Excel. It did not open properly in Excel because a semicolon was used as the column delimiter instead of a comma. To fix this, I select the entire Column A. Then went to the "Data" tab and selected "Text to columns". In the Wizard that appeared, I selected "Delimited" and click "Next". In the next window, I selected "Semicolon", and clicked "Next". In the next window, I left the data format at "General", and clicked "Finish". This now looked like a table with the names of the transcription factors across the top and down the first column and all of the zeros and ones distributed throughout the rows and columns. This is called an "adjacency matrix." If there is a "1" in the cell, that means there is a connection between the transcription factor in that row with that column.
#* Saved this file in Microsoft Excel workbook format (.xlsx).
#* Checked to see that all of the transcription factors in the matrix were connected to at least one of the other transcription factors by making sure that there was at least one "1" in a row or column for that transcription factor. If a factor is not connected to any other factor, I deleted its row and column from the matrix. I made sure that I still had somewhere between 15 and 30 transcription factors in my network after this pruning.

#** Only delete the transcription factor if there are all zeros in its column '''AND''' all zeros in its row. You may find visualizing the matrix in GRNsight (below) can help you find these easily.
#* For this adjacency matrix to be usable in GRNmap (the modeling software) and GRNsight (the visualization software), we need to transpose the matrix. Insert a new worksheet into your Excel file and name it "network". Go back to the previous sheet and select the entire matrix and copy it. Go to you new worksheet and click on the A1 cell in the upper left. Select "Paste special" from the "Home" tab. In the window that appears, check the box for "Transpose". This will paste your data with the columns transposed to rows and vice versa. This is necessary because we want the transcription factors that are the "regulatORS" across the top and the "regulatEES" along the side.
#* The labels for the genes in the columns and rows need to match. Thus, delete the "p" from each of the gene names in the columns. Adjust the case of the labels to make them all upper case.
#* In cell A1, copy and paste the text "rows genes affected/cols genes controlling".
#* Finally, for ease of working with the adjacency matrix in Excel, we want to alphabatize the gene labels both across the top and side.
#** Select the area of the entire adjacency matrix.
#** Click the Data tab and click the custom sort button.
#** Sort Column A alphabetically, being sure to exclude the header row.
#** Now sort row 1 from left to right, excluding cell A1. In the Custom Sort window, click on the options button and select sort left to right, excluding column 1.
#* Name the worksheet containing your organized adjacency matrix "network" and Save.
# Now we will visualize what these gene regulatory networks look like with the GRNsight software.
#* Go to the [http://dondi.github.io/GRNsight/ GRNsight] home page.
#* Select the menu item File > Open and select the regulation matrix .xlsx file that has the "network" worksheet in it that you formatted above. If the file has been formatted properly, GRNsight should automatically create a graph of your network. Move the nodes (genes) around until you get a layout that you like and take a screenshot of the results. Paste it into your PowerPoint presentation.

==== Summary of what you need to turn in for the individual Week 10 assignment ====

# Your individual journal page should have an '''''electronic lab notebook''''' recording your work. This includes the detailed methods specific to your analysis, your result files, the answers to any questions posed in the protocol above, a scientific conclusion, and the acknowledgments and references sections. Don't forget your paragraph which is a biological interpretation of your stem results.
# Upload your updated Excel spreadsheet to the wiki that has today's manipulations in it. Use the same filename as before so that the download link that you already (previous versions will still be available in the history).
# Append the screenshots of the stem results to the PowerPoint presentation that contains the p value table that you created for the [[Week 8]] assignments. Each slide in the presentation should have a meaningful title that describes the main message of the slide.
# Zip together all of the tab-delimited text files that you created for and from stem and upload them to the wiki.
#* the file that was saved from your original spreadsheet that you used to run stem
#* each of the genelist and GOlist files for each of your significant profiles.
# Write a paragraph-length conclusion for this week's exercise.

==Acknowledgements==
I worked with the rest of the Data Analyst guild: [[User:Aporras1|Antonio Porras]], [[User:dbashour|Dina Bashoura]], and [[User:Emmatyrnauer|Emma Tyrnauer]] on this assignment. We spoke in class and created a group chat so we could ask each other questions and help each other as we worked on the project. I also used the instructions from the [[Week 10]] assignment. I edited the instructions slightly so they would be specific to the profile I chose and the procedure I followed.

==References==

LMU BioDB 2017. (2017). Week 10 Retrieve November 28, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10

Mbalducc Week 14

2017-11-30T23:29:44Z

Mbalducc: typo

==Files==
[[media:Mbalducc_Profile_22_yeastract_data.xlsx| Excel Sheet of Profile #22 TF from YEASTRACT]]

==Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes==
# Opened the gene list in Excel for the one of the significant profiles from my stem analysis. I chose a cluster with a clear cold shock/recovery up/down or down/up pattern.
#* Copied the list of gene IDs onto my clipboard.
# Launched a web browser and went to the [http://www.yeastract.com/ YEASTRACT database].
#* On the left panel of the window, clicked on the link to [http://www.yeastract.com/formrankbytf.php ''Rank by TF''].
#* Pasted my list of genes from my cluster into the box labeled ''ORFs/Genes''.
#* Checked the box for ''Check for all TFs''.
#* Accepted the defaults for the Regulations Filter (Documented, DNA binding plus expression evidence)
#* Did '''''not''''' apply a filter for "Filter Documented Regulations by environmental condition".
#* Ranked genes by TF using: The % of genes in the list and in YEASTRACT regulated by each TF.
#* Clicked the ''Search'' button.
# Answered the following questions:
#* In the results window that appears, the p values colored green are considered "significant", the ones colored yellow are considered "borderline significant" and the ones colored pink are considered "not significant". '''''How many transcription factors are green or "significant"?'''''
#**43 are green or "significant".
#* '''''Copied the table of results from the web page and pasteed it into a new Excel workbook to preserve the results.'''''
#** '''''Uploaded the Excel file to OWW or Box and linked to it in my electronic lab notebook.'''''
#** '''''Is your transcription factor on the list? If so, what is their "% in user set", "% in YEASTRACT", and "p value".''''' (Note that this doesn't apply to the wt strain).
#***My transcription factor, Cin5 was on the list. Here is the data associated with it:
#****% in user set: 40.68%
#****% in YEASTRACT: 3.30%
#****p-value: 0.001495074628175
#*List of 20 significant transcription factors:
#*#Aft2p
#*#Mga2p
#*#Gis1p
#*#Hot1p
#*#Sut1p
#*#Zap1p
#*#Mig1p
#*#Hap2p
#*#Sut2p
#*#Bas1p
#*#Pho2p
#*#Opi1p
#*#Ert1p
#*#Oaf1p
#*#Sfp1p
#*#Mig3p
#*#Rlm1p
#*#Sum1p
#*#Ace2p
#*#Pho4p
#* Went back to the YEASTRACT database and followed the link to ''[http://www.yeastract.com/formgenerateregulationmatrix.php Generate Regulation Matrix]''.
#* Copied and pasted the list of transcription factors I identified (plus the transcription factor deleted in my strain: Cin5p) into both the "Transcription factors" field and the "Target ORF/Genes" field.
#* I used the "Regulations Filter" options of "Documented", "'''Only''' DNA binding evidence"
#** Clicked the "Generate" button.
#** In the results window that appeared, I clicked on the link to the "Regulation matrix (Semicolon Separated Values (CSV) file)" that appeared and saved it to my Desktop. I renamed this file with a meaningful name so that I could distinguish it from the other files I will generate.

=== Visualizing Your Gene Regulatory Networks with GRNsight===

# First we need to properly format the output files from YEASTRACT. You will repeat these steps for each of the three files you generated above.
#* Open the file in Excel. It will not open properly in Excel because a semicolon was used as the column delimiter instead of a comma. To fix this, Select the entire Column A. Then go to the "Data" tab and select "Text to columns". In the Wizard that appears, select "Delimited" and click "Next". In the next window, select "Semicolon", and click "Next". In the next window, leave the data format at "General", and click "Finish". This should now look like a table with the names of the transcription factors across the top and down the first column and all of the zeros and ones distributed throughout the rows and columns. This is called an "adjacency matrix." If there is a "1" in the cell, that means there is a connection between the trancription factor in that row with that column.
#* Save this file in Microsoft Excel workbook format (.xlsx).
#* Check to see that all of the transcription factors in the matrix are connected to at least one of the other transcription factors by making sure that there is at least one "1" in a row or column for that transcription factor. If a factor is not connected to any other factor, delete its row and column from the matrix. Make sure that you still have somewhere between 15 and 30 transcription factors in your network after this pruning.
#** Only delete the transcription factor if there are all zeros in its column '''AND''' all zeros in its row. You may find visualizing the matrix in GRNsight (below) can help you find these easily.
#* For this adjacency matrix to be usable in GRNmap (the modeling software) and GRNsight (the visualization software), we need to transpose the matrix. Insert a new worksheet into your Excel file and name it "network". Go back to the previous sheet and select the entire matrix and copy it. Go to you new worksheet and click on the A1 cell in the upper left. Select "Paste special" from the "Home" tab. In the window that appears, check the box for "Transpose". This will paste your data with the columns transposed to rows and vice versa. This is necessary because we want the transcription factors that are the "regulatORS" across the top and the "regulatEES" along the side.
#* The labels for the genes in the columns and rows need to match. Thus, delete the "p" from each of the gene names in the columns. Adjust the case of the labels to make them all upper case.
#* In cell A1, copy and paste the text "rows genes affected/cols genes controlling".
#* Finally, for ease of working with the adjacency matrix in Excel, we want to alphabatize the gene labels both across the top and side.
#** Select the area of the entire adjacency matrix.
#** Click the Data tab and click the custom sort button.
#** Sort Column A alphabetically, being sure to exclude the header row.
#** Now sort row 1 from left to right, excluding cell A1. In the Custom Sort window, click on the options button and select sort left to right, excluding column 1.
#* Name the worksheet containing your organized adjacency matrix "network" and Save.
# Now we will visualize what these gene regulatory networks look like with the GRNsight software.
#* Go to the [http://dondi.github.io/GRNsight/ GRNsight] home page.
#* Select the menu item File > Open and select the regulation matrix .xlsx file that has the "network" worksheet in it that you formatted above. If the file has been formatted properly, GRNsight should automatically create a graph of your network. Move the nodes (genes) around until you get a layout that you like and take a screenshot of the results. Paste it into your PowerPoint presentation.

==== Summary of what you need to turn in for the individual Week 10 assignment ====

# Your individual journal page should have an '''''electronic lab notebook''''' recording your work. This includes the detailed methods specific to your analysis, your result files, the answers to any questions posed in the protocol above, a scientific conclusion, and the acknowledgments and references sections. Don't forget your paragraph which is a biological interpretation of your stem results.
# Upload your updated Excel spreadsheet to the wiki that has today's manipulations in it. Use the same filename as before so that the download link that you already (previous versions will still be available in the history).
# Append the screenshots of the stem results to the PowerPoint presentation that contains the p value table that you created for the [[Week 8]] assignments. Each slide in the presentation should have a meaningful title that describes the main message of the slide.
# Zip together all of the tab-delimited text files that you created for and from stem and upload them to the wiki.
#* the file that was saved from your original spreadsheet that you used to run stem
#* each of the genelist and GOlist files for each of your significant profiles.
# Write a paragraph-length conclusion for this week's exercise.

==Acknowledgements==
I worked with the rest of the Data Analyst guild: [[User:Aporras1|Antonio Porras]], [[User:dbashour|Dina Bashoura]], and [[User:Emmatyrnauer|Emma Tyrnauer]] on this assignment. We spoke in class and created a group chat so we could ask each other questions and help each other as we worked on the project. I also used the instructions from the [[Week 10]] assignment. I edited the instructions slightly so they would be specific to the profile I chose and the procedure I followed.

==References==

LMU BioDB 2017. (2017). Week 10 Retrieve November 28, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10

Mbalducc Week 14

2017-11-30T23:21:03Z

Mbalducc: /* Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes */ yeastract generate instructions

Mbalducc Week 14

2017-11-30T23:15:24Z

Mbalducc: /* Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes */ added 20 TFs

Mbalducc Week 14

2017-11-30T23:10:18Z

Mbalducc: /* Files */ changed file

File:Mbalducc Profile 22 yeastract data.xlsx

2017-11-30T23:09:46Z

Mbalducc:

Mbalducc Week 14

2017-11-30T23:08:32Z

Mbalducc: /* Acknowledgements */ added acknowledgements

==Files==
[[media:Mbalducc_Profile_38_yeastract_data.xlsx| Excel Sheet of Profile #38 TF from YEASTRACT]]

==Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes==
# Opened the gene list in Excel for the one of the significant profiles from my stem analysis. I chose a cluster with a clear cold shock/recovery up/down or down/up pattern.
#* Copied the list of gene IDs onto my clipboard.
# Launched a web browser and went to the [http://www.yeastract.com/ YEASTRACT database].
#* On the left panel of the window, clicked on the link to [http://www.yeastract.com/formrankbytf.php ''Rank by TF''].
#* Pasted my list of genes from my cluster into the box labeled ''ORFs/Genes''.
#* Checked the box for ''Check for all TFs''.
#* Accepted the defaults for the Regulations Filter (Documented, DNA binding plus expression evidence)
#* Did '''''not''''' apply a filter for "Filter Documented Regulations by environmental condition".
#* Ranked genes by TF using: The % of genes in the list and in YEASTRACT regulated by each TF.
#* Clicked the ''Search'' button.
# Answered the following questions:
#* In the results window that appears, the p values colored green are considered "significant", the ones colored yellow are considered "borderline significant" and the ones colored pink are considered "not significant". '''''How many transcription factors are green or "significant"?'''''
#**43 are green.
#* '''''Copied the table of results from the web page and pasteed it into a new Excel workbook to preserve the results.'''''
#** '''''Uploaded the Excel file to OWW or Box and linked to it in my electronic lab notebook.'''''
#** '''''Is your transcription factor on the list? If so, what is their "% in user set", "% in YEASTRACT", and "p value".''''' (Note that this doesn't apply to the wt strain).
#***My transcription factor, Cin5 was on the list. Here is the data associated with it:
#****% in user set: 40.68%
#****% in YEASTRACT: 3.30%
#****p-value: 0.001495074628175
#*List of 20 significant transcription factors:

#* Go back to the YEASTRACT database and follow the link to ''[http://www.yeastract.com/formgenerateregulationmatrix.php Generate Regulation Matrix]''.
#* Copy and paste the list of transcription factors you identified (plus the transcription factor deleted in your strain) into both the "Transcription factors" field and the "Target ORF/Genes" field.
#* We are going to use the "Regulations Filter" options of "Documented", "'''Only''' DNA binding evidence"
#** Click the "Generate" button.
#** In the results window that appears, click on the link to the "Regulation matrix (Semicolon Separated Values (CSV) file)" that appears and save it to your Desktop. Rename this file with a meaningful name so that you can distinguish it from the other files you will generate.



==Acknowledgements==
I worked with the rest of the Data Analyst guild: [[User:Aporras1|Antonio Porras]], [[User:dbashour|Dina Bashoura]], and [[User:Emmatyrnauer|Emma Tyrnauer]] on this assignment. We spoke in class and created a group chat so we could ask each other questions and help each other as we worked on the project. I also used the instructions from the [[Week 10]] assignment. I edited the instructions slightly so they would be specific to the profile I chose and the procedure I followed.

==References==

LMU BioDB 2017. (2017). Week 10 Retrieve November 28, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10

Mbalducc Week 14

2017-11-30T23:06:36Z

Mbalducc: /* Acknowledgements */

==Files==
[[media:Mbalducc_Profile_38_yeastract_data.xlsx| Excel Sheet of Profile #38 TF from YEASTRACT]]

==Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes==
# Opened the gene list in Excel for the one of the significant profiles from my stem analysis. I chose a cluster with a clear cold shock/recovery up/down or down/up pattern.
#* Copied the list of gene IDs onto my clipboard.
# Launched a web browser and went to the [http://www.yeastract.com/ YEASTRACT database].
#* On the left panel of the window, clicked on the link to [http://www.yeastract.com/formrankbytf.php ''Rank by TF''].
#* Pasted my list of genes from my cluster into the box labeled ''ORFs/Genes''.
#* Checked the box for ''Check for all TFs''.
#* Accepted the defaults for the Regulations Filter (Documented, DNA binding plus expression evidence)
#* Did '''''not''''' apply a filter for "Filter Documented Regulations by environmental condition".
#* Ranked genes by TF using: The % of genes in the list and in YEASTRACT regulated by each TF.
#* Clicked the ''Search'' button.
# Answered the following questions:
#* In the results window that appears, the p values colored green are considered "significant", the ones colored yellow are considered "borderline significant" and the ones colored pink are considered "not significant". '''''How many transcription factors are green or "significant"?'''''
#**43 are green.
#* '''''Copied the table of results from the web page and pasteed it into a new Excel workbook to preserve the results.'''''
#** '''''Uploaded the Excel file to OWW or Box and linked to it in my electronic lab notebook.'''''
#** '''''Is your transcription factor on the list? If so, what is their "% in user set", "% in YEASTRACT", and "p value".''''' (Note that this doesn't apply to the wt strain).
#***My transcription factor, Cin5 was on the list. Here is the data associated with it:
#****% in user set: 40.68%
#****% in YEASTRACT: 3.30%
#****p-value: 0.001495074628175
#*List of 20 significant transcription factors:

#* Go back to the YEASTRACT database and follow the link to ''[http://www.yeastract.com/formgenerateregulationmatrix.php Generate Regulation Matrix]''.
#* Copy and paste the list of transcription factors you identified (plus the transcription factor deleted in your strain) into both the "Transcription factors" field and the "Target ORF/Genes" field.
#* We are going to use the "Regulations Filter" options of "Documented", "'''Only''' DNA binding evidence"
#** Click the "Generate" button.
#** In the results window that appears, click on the link to the "Regulation matrix (Semicolon Separated Values (CSV) file)" that appears and save it to your Desktop. Rename this file with a meaningful name so that you can distinguish it from the other files you will generate.



==Acknowledgements==
I worked with the rest of the Data Analyst guild: [[User:Aporras1|Antonio Porras]], [[User:dbashour|Dina Bashoura]], and [[User:Emmatyrnauer|Emma Tyrnauer]] on this assignment. I also used the instructions from the [[Week 10]] assignment. I edited the instructions slightly so they would be specific to the profile I chose and the procedure I followed.

==References==

LMU BioDB 2017. (2017). Week 10 Retrieve November 28, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10

Mbalducc Week 14

2017-11-30T23:06:11Z

Mbalducc: /* Acknowledgements */ added acknowledgements

==Files==
[[media:Mbalducc_Profile_38_yeastract_data.xlsx| Excel Sheet of Profile #38 TF from YEASTRACT]]

==Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes==
# Opened the gene list in Excel for the one of the significant profiles from my stem analysis. I chose a cluster with a clear cold shock/recovery up/down or down/up pattern.
#* Copied the list of gene IDs onto my clipboard.
# Launched a web browser and went to the [http://www.yeastract.com/ YEASTRACT database].
#* On the left panel of the window, clicked on the link to [http://www.yeastract.com/formrankbytf.php ''Rank by TF''].
#* Pasted my list of genes from my cluster into the box labeled ''ORFs/Genes''.
#* Checked the box for ''Check for all TFs''.
#* Accepted the defaults for the Regulations Filter (Documented, DNA binding plus expression evidence)
#* Did '''''not''''' apply a filter for "Filter Documented Regulations by environmental condition".
#* Ranked genes by TF using: The % of genes in the list and in YEASTRACT regulated by each TF.
#* Clicked the ''Search'' button.
# Answered the following questions:
#* In the results window that appears, the p values colored green are considered "significant", the ones colored yellow are considered "borderline significant" and the ones colored pink are considered "not significant". '''''How many transcription factors are green or "significant"?'''''
#**43 are green.
#* '''''Copied the table of results from the web page and pasteed it into a new Excel workbook to preserve the results.'''''
#** '''''Uploaded the Excel file to OWW or Box and linked to it in my electronic lab notebook.'''''
#** '''''Is your transcription factor on the list? If so, what is their "% in user set", "% in YEASTRACT", and "p value".''''' (Note that this doesn't apply to the wt strain).
#***My transcription factor, Cin5 was on the list. Here is the data associated with it:
#****% in user set: 40.68%
#****% in YEASTRACT: 3.30%
#****p-value: 0.001495074628175
#*List of 20 significant transcription factors:

#* Go back to the YEASTRACT database and follow the link to ''[http://www.yeastract.com/formgenerateregulationmatrix.php Generate Regulation Matrix]''.
#* Copy and paste the list of transcription factors you identified (plus the transcription factor deleted in your strain) into both the "Transcription factors" field and the "Target ORF/Genes" field.
#* We are going to use the "Regulations Filter" options of "Documented", "'''Only''' DNA binding evidence"
#** Click the "Generate" button.
#** In the results window that appears, click on the link to the "Regulation matrix (Semicolon Separated Values (CSV) file)" that appears and save it to your Desktop. Rename this file with a meaningful name so that you can distinguish it from the other files you will generate.



==Acknowledgements==
I worked with the rest of the Data Analyst guild: [User:Aporras1|Antonio Porras]], [[User:dbashour|Dina Bashoura]], and [[User:Emmatyrnauer|Emma Tyrnauer]] on this assignment. I also used the instructions from the [[Week 10]] assignment. I edited the instructions slightly so they would be specific to the profile I chose and the procedure I followed.

==References==

LMU BioDB 2017. (2017). Week 10 Retrieve November 28, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10

Mbalducc Week 14

2017-11-30T22:58:23Z

Mbalducc: /* Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes */ changed profile

==Files==
[[media:Mbalducc_Profile_38_yeastract_data.xlsx| Excel Sheet of Profile #38 TF from YEASTRACT]]

==Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes==
# Opened the gene list in Excel for the one of the significant profiles from my stem analysis. I chose a cluster with a clear cold shock/recovery up/down or down/up pattern.
#* Copied the list of gene IDs onto my clipboard.
# Launched a web browser and went to the [http://www.yeastract.com/ YEASTRACT database].
#* On the left panel of the window, clicked on the link to [http://www.yeastract.com/formrankbytf.php ''Rank by TF''].
#* Pasted my list of genes from my cluster into the box labeled ''ORFs/Genes''.
#* Checked the box for ''Check for all TFs''.
#* Accepted the defaults for the Regulations Filter (Documented, DNA binding plus expression evidence)
#* Did '''''not''''' apply a filter for "Filter Documented Regulations by environmental condition".
#* Ranked genes by TF using: The % of genes in the list and in YEASTRACT regulated by each TF.
#* Clicked the ''Search'' button.
# Answered the following questions:
#* In the results window that appears, the p values colored green are considered "significant", the ones colored yellow are considered "borderline significant" and the ones colored pink are considered "not significant". '''''How many transcription factors are green or "significant"?'''''
#**43 are green.
#* '''''Copied the table of results from the web page and pasteed it into a new Excel workbook to preserve the results.'''''
#** '''''Uploaded the Excel file to OWW or Box and linked to it in my electronic lab notebook.'''''
#** '''''Is your transcription factor on the list? If so, what is their "% in user set", "% in YEASTRACT", and "p value".''''' (Note that this doesn't apply to the wt strain).
#***My transcription factor, Cin5 was on the list. Here is the data associated with it:
#****% in user set: 40.68%
#****% in YEASTRACT: 3.30%
#****p-value: 0.001495074628175
#*List of 20 significant transcription factors:

#* Go back to the YEASTRACT database and follow the link to ''[http://www.yeastract.com/formgenerateregulationmatrix.php Generate Regulation Matrix]''.
#* Copy and paste the list of transcription factors you identified (plus the transcription factor deleted in your strain) into both the "Transcription factors" field and the "Target ORF/Genes" field.
#* We are going to use the "Regulations Filter" options of "Documented", "'''Only''' DNA binding evidence"
#** Click the "Generate" button.
#** In the results window that appears, click on the link to the "Regulation matrix (Semicolon Separated Values (CSV) file)" that appears and save it to your Desktop. Rename this file with a meaningful name so that you can distinguish it from the other files you will generate.



==Acknowledgements==
==References==

LMU BioDB 2017. (2017). Week 10 Retrieve November 28, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10

Mbalducc Week 14

2017-11-29T05:11:15Z

Mbalducc: /* Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes */

==Files==
[[media:Mbalducc_Profile_38_yeastract_data.xlsx| Excel Sheet of Profile #38 TF from YEASTRACT]]

==Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes==
# Opened the gene list in Excel for the one of the significant profiles from my stem analysis. I chose a cluster with a clear cold shock/recovery up/down or down/up pattern.
#* Copied the list of gene IDs onto my clipboard.
# Launched a web browser and went to the [http://www.yeastract.com/ YEASTRACT database].
#* On the left panel of the window, clicked on the link to [http://www.yeastract.com/formrankbytf.php ''Rank by TF''].
#* Pasted my list of genes from my cluster into the box labeled ''ORFs/Genes''.
#* Checked the box for ''Check for all TFs''.
#* Accepted the defaults for the Regulations Filter (Documented, DNA binding plus expression evidence)
#* Did '''''not''''' apply a filter for "Filter Documented Regulations by environmental condition".
#* Ranked genes by TF using: The % of genes in the list and in YEASTRACT regulated by each TF.
#* Clicked the ''Search'' button.
# Answered the following questions:
#* In the results window that appears, the p values colored green are considered "significant", the ones colored yellow are considered "borderline significant" and the ones colored pink are considered "not significant". '''''How many transcription factors are green or "significant"?'''''
#**0 p-values were colored green, 1 was colored yellow.
#* '''''Copied the table of results from the web page and pasteed it into a new Excel workbook to preserve the results.'''''
#** '''''Uploaded the Excel file to OWW or Box and linked to it in my electronic lab notebook.'''''
#** '''''Is your transcription factor on the list? If so, what is their "% in user set", "% in YEASTRACT", and "p value".''''' (Note that this doesn't apply to the wt strain).
#***My transcription factor, Cin5 was on the list. Here is the data associated with it:
#****% in user set: 30.30%
#****% in YEASTRACT: 0.92%
#****p-value: 0.459081369313114
#*List of 20 significant transcription factors:

#* Go back to the YEASTRACT database and follow the link to ''[http://www.yeastract.com/formgenerateregulationmatrix.php Generate Regulation Matrix]''.
#* Copy and paste the list of transcription factors you identified (plus the transcription factor deleted in your strain) into both the "Transcription factors" field and the "Target ORF/Genes" field.
#* We are going to use the "Regulations Filter" options of "Documented", "'''Only''' DNA binding evidence"
#** Click the "Generate" button.
#** In the results window that appears, click on the link to the "Regulation matrix (Semicolon Separated Values (CSV) file)" that appears and save it to your Desktop. Rename this file with a meaningful name so that you can distinguish it from the other files you will generate.



==Acknowledgements==
==References==

LMU BioDB 2017. (2017). Week 10 Retrieve November 28, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10

Mbalducc Week 14

2017-11-29T05:09:19Z

Mbalducc: /* Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes */

==Files==
[[media:Mbalducc_Profile_38_yeastract_data.xlsx| Excel Sheet of Profile #38 TF from YEASTRACT]]

==Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes==
# Opened the gene list in Excel for the one of the significant profiles from my stem analysis. I chose a cluster with a clear cold shock/recovery up/down or down/up pattern.
#* Copied the list of gene IDs onto my clipboard.
# Launched a web browser and went to the [http://www.yeastract.com/ YEASTRACT database].
#* On the left panel of the window, clicked on the link to [http://www.yeastract.com/formrankbytf.php ''Rank by TF''].
#* Pasted my list of genes from my cluster into the box labeled ''ORFs/Genes''.
#* Checked the box for ''Check for all TFs''.
#* Accepted the defaults for the Regulations Filter (Documented, DNA binding plus expression evidence)
#* Did '''''not''''' apply a filter for "Filter Documented Regulations by environmental condition".
#* Ranked genes by TF using: The % of genes in the list and in YEASTRACT regulated by each TF.
#* Clicked the ''Search'' button.
# Answered the following questions:
#* In the results window that appears, the p values colored green are considered "significant", the ones colored yellow are considered "borderline significant" and the ones colored pink are considered "not significant". '''''How many transcription factors are green or "significant"?'''''
#**0 p-values were colored green, 1 was colored yellow.
#* '''''Copied the table of results from the web page and pasteed it into a new Excel workbook to preserve the results.'''''
#** '''''Uploaded the Excel file to OWW or Box and linked to it in my electronic lab notebook.'''''
#** '''''Is your transcription factor on the list? If so, what is their "% in user set", "% in YEASTRACT", and "p value".''''' (Note that this doesn't apply to the wt strain).
#***My transcription factor, Cin5 was on the list. Here is the data associated with it:
#****% in user set: 30.30%
#****% in YEASTRACT: 0.92%
#****p-value: 0.459081369313114

# For the mathematical model and GRNsight, we need to define a ''gene regulatory network'' of transcription factors that regulate other transcription factors. We can use YEASTRACT to assist us with creating the network. We want to generate a network with approximately 15-30 transcription factors in it.
#* You need to select from this list of "significant" transcription factors, which ones you will use to run the model. You will use these transcription factors and add GLN3 and HAP4 if they are not in your list. Explain in your electronic notebook how you decided on which transcription factors to include. Record the list and your justification in your electronic lab notebook.
#* Go back to the YEASTRACT database and follow the link to ''[http://www.yeastract.com/formgenerateregulationmatrix.php Generate Regulation Matrix]''.
#* Copy and paste the list of transcription factors you identified (plus the transcription factor deleted in your strain) into both the "Transcription factors" field and the "Target ORF/Genes" field.
#* We are going to use the "Regulations Filter" options of "Documented", "'''Only''' DNA binding evidence"
#** Click the "Generate" button.
#** In the results window that appears, click on the link to the "Regulation matrix (Semicolon Separated Values (CSV) file)" that appears and save it to your Desktop. Rename this file with a meaningful name so that you can distinguish it from the other files you will generate.



==Acknowledgements==
==References==

LMU BioDB 2017. (2017). Week 10 Retrieve November 28, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10

Mbalducc Week 14

2017-11-29T05:05:59Z

Mbalducc: added file

==Files==
[[media:Mbalducc_Profile_38_yeastract_data.xlsx| Excel Sheet of Profile #38 TF from YEASTRACT]]

==Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes==
# Opened the gene list in Excel for the one of the significant profiles from my stem analysis. I chose a cluster with a clear cold shock/recovery up/down or down/up pattern.
#* Copied the list of gene IDs onto my clipboard.
# Launched a web browser and went to the [http://www.yeastract.com/ YEASTRACT database].
#* On the left panel of the window, clicked on the link to [http://www.yeastract.com/formrankbytf.php ''Rank by TF''].
#* Pasted my list of genes from my cluster into the box labeled ''ORFs/Genes''.
#* Checked the box for ''Check for all TFs''.
#* Accepted the defaults for the Regulations Filter (Documented, DNA binding plus expression evidence)
#* Did '''''not''''' apply a filter for "Filter Documented Regulations by environmental condition".
#* Ranked genes by TF using: The % of genes in the list and in YEASTRACT regulated by each TF.
#* Clicked the ''Search'' button.
# Answered the following questions:
#* In the results window that appears, the p values colored green are considered "significant", the ones colored yellow are considered "borderline significant" and the ones colored pink are considered "not significant". '''''How many transcription factors are green or "significant"?'''''
#**0 p-values were colored green, 1 was colored yellow.
#* '''''Copied the table of results from the web page and pasteed it into a new Excel workbook to preserve the results.'''''

#** '''''Uploaded the Excel file to OWW or Box and linked to it in my electronic lab notebook.'''''
#** '''''Is your transcription factor on the list? If so, what is their "% in user set", "% in YEASTRACT", and "p value".''''' (Note that this doesn't apply to the wt strain).
# For the mathematical model and GRNsight, we need to define a ''gene regulatory network'' of transcription factors that regulate other transcription factors. We can use YEASTRACT to assist us with creating the network. We want to generate a network with approximately 15-30 transcription factors in it.
#* You need to select from this list of "significant" transcription factors, which ones you will use to run the model. You will use these transcription factors and add GLN3 and HAP4 if they are not in your list. Explain in your electronic notebook how you decided on which transcription factors to include. Record the list and your justification in your electronic lab notebook.
#* Go back to the YEASTRACT database and follow the link to ''[http://www.yeastract.com/formgenerateregulationmatrix.php Generate Regulation Matrix]''.
#* Copy and paste the list of transcription factors you identified (plus the transcription factor deleted in your strain) into both the "Transcription factors" field and the "Target ORF/Genes" field.
#* We are going to use the "Regulations Filter" options of "Documented", "'''Only''' DNA binding evidence"
#** Click the "Generate" button.
#** In the results window that appears, click on the link to the "Regulation matrix (Semicolon Separated Values (CSV) file)" that appears and save it to your Desktop. Rename this file with a meaningful name so that you can distinguish it from the other files you will generate.



==Acknowledgements==
==References==

LMU BioDB 2017. (2017). Week 10 Retrieve November 28, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10

File:Mbalducc Profile 38 yeastract data.xlsx

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