Week 9 - Revision history

Kdahlquist: replace zap1 with cin5

2019-10-29T22:47:28Z

replace zap1 with cin5

Kdahlquist: /* Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes (Tuesday, October 29) */ fix link

2019-10-29T22:37:52Z

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

Kdahlquist: /* Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes (Tuesday, October 29) */ remove reference to OWW

2019-10-24T22:58:51Z

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

Kdahlquist: /* Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes (Tuesday, Feb. 19) */ change date on header

2019-10-24T22:58:00Z

‎Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes (Tuesday, Feb. 19): change date on header

Kdahlquist: add interim deadline and comment out dealing with redundant GO terms

2019-10-24T22:57:29Z

add interim deadline and comment out dealing with redundant GO terms

Kdahlquist: /* Creating the GRNmap Input Workbook */ add TBD

2019-10-24T21:01:55Z

‎Creating the GRNmap Input Workbook: add TBD

Kdahlquist: /* Creating the GRNmap Input Workbook */ pasted in from biomath modeling, but kept commented out

2019-10-24T21:01:30Z

‎Creating the GRNmap Input Workbook: pasted in from biomath modeling, but kept commented out

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Kdahlquist: /* Visualizing Your Gene Regulatory Networks with GRNsight */ add new header for creating GRNmap input workbook

2019-10-24T21:00:37Z

‎Visualizing Your Gene Regulatory Networks with GRNsight: add new header for creating GRNmap input workbook

Kdahlquist: /* Shared Journal Assignment */ add shared reflections

2019-10-24T20:55:12Z

‎Shared Journal Assignment: add shared reflections

Kdahlquist: /* Data and Files */ add GRNsight file

2019-10-22T23:54:21Z

‎Data and Files: add GRNsight file

@@ Line 148: / Line 148: @@
 #** '''''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 ZAP1 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).
+#* 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 ZAP1) into both the "Transcription factors" field and the "Target ORF/Genes" field.
+#* 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.
@@ Line 237: / Line 237: @@
 ** Each sheet should be given a unique name that follows the convention "STRAIN_log2_expression", where the word "STRAIN" is replaced by the strain designation, which will appear in the optimization_diagnostics sheet.
 *** Everyone in the class will have at least one expression worksheet called "wt_log2_expression".
-*** You should have included the transcription factors GLN3, HAP4, and ZAP1 in your network.  Thus, we will use the expression data from the dGLN3, dHAP4, dZAP1 deletion strains in our workbooks as well, naming the worksheets "dgln3_log2_expression", "dhap4_log2_expression", and "dzap1_expression".
+*** You should have included the transcription factors GLN3, HAP4, and
 **** If, for some reason, you don't have all three of those genes in your network, only include expression data for the wild type and the genes out of those three that you have in your network.
 * The sheet should have the following columns in this order:
@@ Line 267: / Line 268: @@
 * The optimization_parameters sheet should have two columns (from left to right) entitled, "optimization_parameter" and "value".
-* You should copy this worksheet from the [https://github.com/kdahlquist/DahlquistLab/raw/master/data/Spring2019/15-genes_28-edges_sample_Sigmoid_estimation_2019.xlsx sample workbook] provided.  The only row that you need to modify is row 15, "Strain".  Include just the strain designations for which you have a corresponding STRAIN_log2_expression sheet.  If you don't have the dgln3, dhap4, or dzap1 expression sheets, then you will delete those from this row.  If you do so, make sure that you don't leave any gaps between cells.
+* You should copy this worksheet from the [https://github.com/kdahlquist/DahlquistLab/raw/master/data/Spring2019/15-genes_28-edges_sample_Sigmoid_estimation_2019.xlsx sample workbook] provided.  The only row that you need to modify is row 15, "Strain".  Include just the strain designations for which you have a corresponding STRAIN_log2_expression sheet.  If you don't have the dgln3, dhap4, or dcin5 expression sheets, then you will delete those from this row.  If you do so, make sure that you don't leave any gaps between cells.
 * What follows below is an explanation of what the optimization_parameters mean.
 ** alpha: Penalty term weighting (from the L-curve analysis)

@@ Line 149: / Line 149: @@
 # 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 ZAP1 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/formgenerateregulationmatrix.php Generate Regulation Matrix]''.
+#* 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 ZAP1) 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"

@@ Line 145: / Line 145: @@
 #* 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 OWW or Box and link to it in your electronic lab notebook.'''''
+#** '''''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.

@@ Line 128: / Line 128: @@
 '''''This is the stopping point for the interim deadline of 12:01am, Tuesday October 29.'''''
-==== Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes (Tuesday, Feb. 19)====
+==== 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.

@@ Line 1: / Line 1: @@
 '''This journal entry is due on Thursday, October 31, at 12:01am Pacific time.'''
-'''''Note that you have an interim deadline of Tuesday, October 29, at 12:01am Pacific time, the content of which will be determined in class on Thursday.'''''
+'''''Note that you have an interim deadline of Tuesday, October 29, at 12:01am Pacific time, the content of which will be determined in class on Thursday; see stopping point below.'''''
 == Objectives ==
@@ Line 119: / Line 117: @@
 ##* '''''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.
 ##* Open the GO list file you 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?'''''
-##* Select 6 Gene Ontology terms from your filtered list (either p < 0.05 or corrected p < 0.05).
+##* Select the top 6 Gene Ontology terms from your filtered list (either p < 0.05 or corrected p < 0.05).
-##** Each member of the group will be reporting on his or her own cluster in your research presentation.  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.
+<!--##** Each member of the group will be reporting on his or her own cluster in your research presentation.  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 your research 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 groups working with deletion strain data)?'''''
@@ Line 127: / Line 125: @@
 ##** 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].
 ==== Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes (Tuesday, Feb. 19)====

@@ Line 178: / Line 178: @@
 ==== Creating the GRNmap Input Workbook ====
 <!--
 Now that you have identified the gene regulatory network that you want to model, the next step is to generate the input Excel workbook that you will run in the GRNmap modeling software.

@@ Line 176: / Line 176: @@
 #* 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.  You can click the "Grid Layout" button to arrange the nodes in a grid, or you can click and drag 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.
 #** If you have nodes (genes) floating around in the display that are not connected to any other nodes, we need to delete them from the network for the modeling to work properly.  Go back to the Excel workbook and network sheet and delete both the row and column with the floating gene's name.  Then re-upload the edited file to GRNsight to visualize it.  Use this final version in your PowerPoint and subsequent modeling.
 ==== Data and Files ====

@@ Line 203: / Line 203: @@
 === Reflect ===
-TBA
+This week marks the end of Part 2 "Going Deeper" unit of the course.  At this point in the semester, you have worked with 7-8 other people in the class as partners on journal assignments.  Next week, you will be placed on teams of four that you will stay with throughout the rest of the semester.  Ultimately the teams will be assigned by Dr. Dahlquist based on balancing areas of expertise amongst the team members. However, I will also be gathering your input into the formation of the teams. In class on Thursday, October 31, you will confidentially fill out a card giving me the names of three other people in the class whom you want to be on your team (you are allowed choose people that haven't been your journal partner yet) and one person whom you prefer not to be on your team.
 [[Category:Assignment]]

@@ Line 182: / Line 182: @@
 * Your Excel workbook with all of your calculations (you may have had to make corrections since the last version).
 ** Note that you will be working with this workbook for the next week or two, adding computations to it.  Save the new versions to the wiki with the '''same filename'''.  The wiki will store each version of the file so you can always go back to a previous version, if need be.
-* Your PowerPoint slide with a summary table of p values, updated with the screenshots from the stem software.
+* Your PowerPoint slide with a summary table of p values, updated with the screenshots from the stem software and the GRNsight network.
 ** You will also be adding to the PowerPoint presentation during subsequent steps in the analysis.
 * The input .txt file that you used to run stem.
 * The zipped together genelist and GOlist files for each of your significant profiles.