Difference between revisions of "Knguye66 Eyoung20 Week 15"

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#What is the p value for the enrichment of genes in this profile?
 
#What is the p value for the enrichment of genes in this profile?
 
#* Due to combining the profiles, we do not have p-values for the enrichment of genes in the 2 different groups.
 
#* Due to combining the profiles, we do not have p-values for the enrichment of genes in the 2 different groups.
 +
==== Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes (Tuesday, October 29)====
 +
 +
In the previous analysis using STEM, we found a number of gene expression profiles (aka clusters) which grouped genes based on similarity of gene expression changes over time.  The implication is that these genes share the same expression pattern because they are regulated by the same (or the same set) of transcription factors.  We will explore this using the YEASTRACT database.
 +
 +
# Open the gene list in Excel for the one of the significant profiles from your stem analysis.  Choose a cluster with a clear cold shock/recovery up/down or down/up pattern.  You should also choose one of the largest clusters.
 +
#* Copy the list of gene IDs onto your clipboard.
 +
# Launch a web browser and go to the [http://www.yeastract.com/ YEASTRACT database].
 +
#* On the left panel of the window, click on the link to [http://www.yeastract.com/formrankbytf.php ''Rank by TF''].
 +
#* Paste your list of genes from your cluster into the box labeled ''ORFs/Genes''.
 +
#* Check the box for ''Check for all TFs''.
 +
#* Accept the defaults for the Regulations Filter (Documented, DNA binding plus expression evidence)
 +
#* Do '''''not''''' apply a filter for "Filter Documented Regulations by environmental condition".
 +
#* Rank genes by TF using: The % of genes in the list and in YEASTRACT regulated by each TF.
 +
#* Click the ''Search'' button.
 +
# Answer 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"?'''''
 +
#* '''''Copy the table of results from the web page and paste it into a new Excel workbook to preserve the results.'''''
 +
#** '''''Upload the Excel file to the wiki and link to it in your electronic lab notebook.'''''
 +
#** '''''Are CIN5, GLN3, and/or HAP4 on the list?  If so, what is their "% in user set", "% in YEASTRACT", and "p value".'''''
 +
# For the mathematical model that we will build, 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 15-20 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, HAP4, and CIN5 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.  Each group member will select a different network (they can have some overlapping transcription factors, but some should also be different).
 +
#* Go back to the YEASTRACT database and follow the link to ''[http://www.yeastract.com/formregmatrix.php Generate Regulation Matrix]''.
 +
#* Copy and paste the list of transcription factors you identified (plus HAP4, GLN3, and CIN5) 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.
  
 
== Conclusion ==
 
== Conclusion ==

Revision as of 11:28, 2 December 2019

Combined Individual Journals for Kaitlyn Nguyen and Emma Young (Data Analysts).

Purpose

The purpose of this assignment is to record our progress towards the FunGals group deliverables as the Data Analysts for this week and the future weeks to come. The purpose of week 12 specifically was to download and adapt the data to the formatting we need for analysis. Then to begin the analysis with ANOVA and preparations for STEM.

Methods and Results: Progress

Progress 11/26/19

Running Stem Methods

- Analyzing and Interpreting STEM Results -

  1. Why did you select this profile? In other words, why was it interesting to you?
    • We collectively combined the 4 red profiles together because they had similar trends and to increase the number of genes for analysis (called "Red".) Similarly this was done to the 3 green profiles as well (upward trends), with the addition of the blue profile #29 added. We will call this group "Green".
  2. How many genes belong to this profile?
    • Red (composed of Profile #9,26,34,11): 289
    • Green (Profile #40,42,18,29): 214
  3. How many genes were expected to belong to this profile?
    • Red (composed of Profile #9,26,34,11): 51.5
    • Green (Profile #40,42,18,29): 48.5
  4. What is the p value for the enrichment of genes in this profile?
    • Due to combining the profiles, we do not have p-values for the enrichment of genes in the 2 different groups.

Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes (Tuesday, October 29)

In the previous analysis using STEM, we found a number of gene expression profiles (aka clusters) which grouped genes based on similarity of gene expression changes over time. The implication is that these genes share the same expression pattern because they are regulated by the same (or the same set) of transcription factors. We will explore this using the YEASTRACT database.

  1. Open the gene list in Excel for the one of the significant profiles from your stem analysis. Choose a cluster with a clear cold shock/recovery up/down or down/up pattern. You should also choose one of the largest clusters.
    • Copy the list of gene IDs onto your clipboard.
  2. Launch a web browser and go to the YEASTRACT database.
    • On the left panel of the window, click on the link to Rank by TF.
    • Paste your list of genes from your cluster into the box labeled ORFs/Genes.
    • Check the box for Check for all TFs.
    • Accept the defaults for the Regulations Filter (Documented, DNA binding plus expression evidence)
    • Do not apply a filter for "Filter Documented Regulations by environmental condition".
    • Rank genes by TF using: The % of genes in the list and in YEASTRACT regulated by each TF.
    • Click the Search button.
  3. Answer 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"?
    • Copy the table of results from the web page and paste it into a new Excel workbook to preserve the results.
      • Upload the Excel file to the wiki and link to it in your electronic lab notebook.
      • Are CIN5, GLN3, and/or HAP4 on the list? If so, what is their "% in user set", "% in YEASTRACT", and "p value".
  4. For the mathematical model that we will build, 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 15-20 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, HAP4, and CIN5 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. Each group member will select a different network (they can have some overlapping transcription factors, but some should also be different).
    • Go back to the YEASTRACT database and follow the link to Generate Regulation Matrix.
    • Copy and paste the list of transcription factors you identified (plus HAP4, GLN3, and CIN5) 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.

Conclusion

The first stage of our group's project was completed via referencing Week 8 and using Microsoft Excel to complete the tasks. The excel file will be located in the FunGals page for viewing and download. We were able to successfully complete the ANOVA analysis and correct found mistakes. We were able to complete a sanity check with results showing. For the sanity check the unadjusted p- values showed 37.2% of the genes had a p<0.05, 18.16% had a p<0.01, 5.04% have p<0.001, and 0.87% have p<0.0001. The sanity check for the Bonferroni-corrected p-value 0.11% of the genes have p<0.05. For the sanity check on the Benjamini and Hochberg-corrected p-value 16.36% go the genes had a p <0.05. Finally we were able to prepare the Data to run STEM in the next step of working on this project.

Data and files

excel workbook

Acknowledgements

This section is in acknowledgement to partner Kaitlyn Nguyen (User:knguye66), Michael Armas (User:Marmas), as well as, Iliana Crespin (User:Icrespin), and Emma Young (User:eyoung20). We would also like to acknowledge Dr. Dahlquist (User:KDahlquist) for introducing and teaching the topic and direction of this assignment. Also to acknowledge that this is a shared electronic notebook between Kaitlyn Nguyen and Emma Young.

"Except for what is noted above, this individual journal entry was completed by me and not copied from another source." Knguye66 (talk) 18:49, 20 November 2019 (PST)

"Except for what is noted above, this individual journal entry was completed by me and not copied from another source." Eyoung20 (talk) 16:40, 25 November 2019 (PST)

References

User Page

User:knguye66

Template Page

Template:knguye66


Table of all assignments and journal entries for BIO-367-01

Week Individual Journal Entry Shared Journal
Week 1 - Class Journal Week 1
Week 2 knguye66 Week 2 Class Journal Week 2
Week 3 ILT1/YDR090C Week 3 Class Journal Week 3
Week 4 knguye66 Week 4 Class Journal Week 4
Week 5 DrugCentral Week 5 Class Journal Week 5
Week 6 knguye66 Week 6 Class Journal Week 6
Week 7 knguye66 Week 7 Class Journal Week 7
Week 8 knguye66 Week 8 Class Journal Week 8
Week 9 knguye66 Week 9 Class Journal Week 9
Week 10 knguye66 Week 10 Class Journal Week 10
Week 11 knguye66 Week 11 FunGals
Week 12/13 knguye66 Eyoung20 Week 12/13 FunGals
Week 15 knguye66 Eyoung20 Week 15 Class Journal Week 15

Eyoung20 user page

Assignment pages Individual Journal Class Journal
week 1 Eyoung20 journal week 1 Class Journal Week 1
week 2 Eyoung20 journal week 2 Class Journal Week 2
week 3 ASP1/YDR321W Week 3 Class Journal Week 3
week 4 Eyoung20 journal week 4 Class Journal Week 4
week 5 Ancient mtDNA Week 5 Class Journal Week 5
week 6 Eyoung20 journal week 6 Class Journal Week 6
week 7 Eyoung20 journal week 7 Class Journal Week 7
week 8 Eyoung20 journal week 8 Class Journal Week 8
week 9 Eyoung20 journal week 9 Class Journal Week 9
week 10 Eyoung20 journal week 10 Class Journal Week 10
week 11 Eyoung20 journal week 11 FunGals
week 12/13 Knguye66 Eyoung20 Week 12/13 FunGals
week 15 Knguye66 Eyoung20 Week 15 FunGals
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