Mbalducc Week 10

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Files

dCIN5 Profile Gene Lists

dCIN5 Profile GO Lists

Clustering and GO Term Enrichment with STEM

  1. Prepared microarray data file for loading into STEM
    • Downloaded: 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.
  2. Downloaded and extracted the STEM software. Click here to go to the STEM web site.
    • Clicked on the download link, registered, and downloaded the stem.zip file to my Desktop.
    • Unzipped the file.
    • This created a folder called stem. Inside the folder, double-clicked on the stem.jar to launch the STEM program.
  3. Running STEM
    1. 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.
    2. 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.
    3. 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.
    4. In section 4 (Execute) 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)". 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 Alt and PrintScreen buttons to save the view in the active window to the clipboard) and paste it into a PowerPoint presentation to save my figures.
    2. 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.
      1. 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.
  5. Analyzing and Interpreting STEM Results
    1. 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 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. 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.
        • 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 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. 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, 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

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