Hivanson Week 10

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Revision as of 14:56, 26 March 2024 by Hivanson (talk | contribs) (Clustering and GO Term Enrichment with stem: new list 4)
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Purpose

Methods/Results

Clustering and GO Term Enrichment with stem

  1. Preparing microarray data file for loading into STEM.
    • I inserted a new worksheet into my Excel workbook, and named it "dCIN5_stem".
    • I selected all of the data from the "ANOVA_dCIN5" worksheet and special pasted values into the "dCIN5_stem" worksheet.
      • I renamed Column A to "SPOT" and Column B to "Gene Symbol." I deleted the column named "Standard_Name."
      • I filtered the data in "dCIN5_B-H_p-value" > 0.05.
        • Once the data has been filtered, I selected and deleted all of the rows (except for your header row). I undid the filter.
      • I deleted all of the data columns except for the Average Log Fold change columns for timepoints 15m, 30m, 60m, 90m, and 120m.
      • I renamed the data columns from "dCIN5_AvgLogFC_t
      • I removed #DIV/0! errors using find and replace with nothing in the replace field.
      • I saved the dCIN5_stem sheet as Text (Tab-delimited) (*.txt).
  2. I downloaded and extracted the STEM software. Click here to go to the STEM web site.
      • I downloaded the Gene Ontology and yeast GO annotations from the 10 Wiki page.
    • I launched the STEM program.
  3. Running STEM
    1. In section 1 (Expression Data Info) of the the main STEM interface window, I clicked on the Browse... button to navigate to and select the .txt file.
      • I clicked on the radio button No normalization/add 0.
      • I checked the box next to Spot IDs included in the data file.
    2. In section 2 (Gene Info) of the main STEM interface window, I left the default selection for the three drop-down menu selections for Gene Annotation Source, Cross Reference Source, and Gene Location Source as "User provided".
    3. I clicked the "Browse..." button to the right of the "Gene Annotation File" item. I selected the file "gene_association.sgd.gz" and click Open.
    4. In section 3 (Options) of the main STEM interface window, I ensured 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.
    5. In section 4 (Execute) I clicked on the yellow Execute button to run STEM.
  4. Viewing and Saving STEM Results
    1. A new window opened called "All STEM Profiles (1)".
      • I 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:", I clicked on the radio button that says "Based on real time". I then closed the Interface Options window.
      • I screenshotted this window and pasted it into my PowerPoint presentation.
    2. I clicked on each of the significant/colored profiles to open a window showing a more detailed plot containing all of the genes in that profile.
      • I screenshoted each of the individual profile windows and saved the images in my PowerPoint presentation.
      • For each of the profiles, I clicked on the "Profile Gene Table" button, then clicked on the "Save Table" button to save the file for each profile. This can be found in the Data and Files section below.
      • For each of the significant profiles, I clicked on the "Profile GO Table" to see the list of Gene Ontology terms belonging to the profile, then clicked on the "Save Table" button for each profile. This can be found in the Data and Files section below.
  5. Analyzing and Interpreting STEM Results
    1. I selected profile 22 for further intepretation of the data.
      • Why did you select this profile? In other words, why was it interesting to you?
        • I selected profile 22 because the overall trend of a spike only at 90 minutes is different from the rest of the profiles' trends.
      • How many genes belong to this profile?
        • 179 genes
      • How many genes were expected to belong to this profile?
        • 22.9 genes
      • What is the p value for the enrichment of genes in this profile?
        • 3.4E-98
      • I opened the GO list file that I saved for profile 22 in Excel. I selected the third row and then filtered 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?
        • 25
      • I filtered 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?
        • 7
      • I select 6 Gene Ontology terms from your filtered list
        • These were selected by choosing the six most significant terms that were not redundant with each other.
        • I looked up the definitions for each of the terms at http://geneontology.org.
        • Why does the cell react to cold shock by changing the expression of genes associated with these GO terms?
          • The genes that are associated with these GO terms include stress responses, like cellular response to oxidative stress, and its related terms that I excluded from the above table due to similarity. This makes sense as cold shock is considered a stressor. Additionally, various cellular structure components are associated with these GO terms, such as cytoplasm, cytoskeleton, and fungal-type vacuole which all may need to have regulated rigidity or some other physical characteristics at lower temperatures.
        • Also, what does this have to do with the transcription factor being deleted (for the groups working with deletion strain data)
          • I want to compare our results to that of the wildtype. I don't understand completely what effects the CIN5 deletion should have, or what this does to the yeast. I tried reading the SGD description of CIN5. Will clarify with Dr. Dahlquist.
GO ID Terms
GO ID Term
GO:0034599 cellular response to oxidative stress
GO:0005737 cytoplasm
GO:0006897 endocytosis
GO:0030479 actin cortical patch
GO:0005856 cytoskeleton
GO:0000324 fungal-type vacuole

How many transcription factors are green or "significant"? 57 Are CIN5 or GLN3 on the list? If so, what is their "% in user set", "% in YEASTRACT", and "p value"? CIN5 and GLN3 are not present on the list.

Note: Yeastract stated: Unknown gene/ORF name(s), 'YCRX17W', 'YCRX18C'.

Initially, transcription factors selection was determined by selecting the 15 most significant transcription factors by p value. The transcription factors are as follows:   Pdr3   Rpn4   Yap1   Gcn4   Rph1   Pdr1   Gis1   Aft2   Yrr1   Mga2   YGR067C   Sut1   Msn4   Stp1   Mig1

Boxes with no nodes attached were removed and replaced with the next-most significant transcriptions factor, starting with Gis1, Sut1, and Mga2, which were replaced with Cbf1, Bas1, and Hap2.   Pdr3   Rpn4   Yap1   Gcn4   Rph1   Pdr1   Cbf1   Aft2   Yrr1   Hap2   YGR067C   Bas1   Msn4   Stp1   Mig1

Mig1, Hap2, Msn4, and Rph1 were removed and replaced with Aft1, Msn2, Rme1, and Sut2   Pdr3   Rpn4   Yap1   Gcn4   Sut2   Pdr1   Cbf1   Aft2   Yrr1   Msn2   YGR067C   Bas1   Rme1   Stp1   Aft1

Rme1 and Msn2 were replaced with Pho2 and Ash1.

. Pdr3   Rpn4   Yap1   Gcn4   Sut2   Pdr1   Cbf1   Aft2   Yrr1   Ash1   YGR067C   Bas1   Pho2   Stp1   Aft1

Ash1 was replaced with Snf1p

. Pdr3   Rpn4   Yap1   Gcn4   Sut2   Pdr1   Cbf1   Aft2   Yrr1   Snf1p   YGR067C   Bas1   Pho2   Stp1   Aft1

Data & Files

Excel file with microarray data for dCIN5

Tab text file with dCIN5 stem data

Stem dCIN5 significant profiles genelist folder

Stem dCIN5 significant profiles GOlist folder

dCIN5 Profile 22 genelist in yeastract results

Slides

Conclusion

Acknowledgments

References

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