Icrespin Journal Week 9

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Electronic Lab Notebook

Icrespin User Page

Assignment Page Individual Journal Entry Shared Journal Entry
Week 1 Icrespin Journal Week 1 Class Journal Week 1
Week 2 Icrespin Journal Week 2 Class Journal Week 2
Week 3 ILT1/YDR090C Week 3 Class Journal Week 3
Week 4 Icrespin Journal Week 4 Class Journal Week 4
Week 5 RNAct Week 5 Class Journal Week 5
Week 6 Icrespin Journal Week 6 Class Journal Week 6
Week 7 Icrespin Journal Week 7 Class Journal Week 7
Week 8 Icrespin Journal Week 8 Class Journal Week 8
Week 9 Icrespin Journal Week 9 Class Journal Week 9
Week 10 Icrespin Journal Week 10 Class Journal Week 10
Week 11 Icrespin Journal Week 11 FunGals
Week 12/13 Icrespin Journal Week 12/13 FunGals
Week 15 Icrespin Journal Week 15 FunGals

Purpose

The purpose of this week's assignment is to continue from week 8. Also, it is to better understand how STEM works, and how the user can analyze different profiles to comprehend cold shock.

Methods/Results

  1. Viewing and Saving STEM Results
    1. A new window will open 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.
      • Click 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:", click on the radio button that says "Based on real time". Then close the Interface Options window.
      • Take 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 your figures.
    2. Click 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.
      • Take a screenshot of each of the individual profile windows and save the images in your PowerPoint presentation.
      • At the bottom of each profile window, there are two yellow buttons "Profile Gene Table" and "Profile GO Table". For each of the profiles, click on the "Profile Gene Table" button to see the list of genes belonging to the profile. In the window that appears, click on the "Save Table" button and save the file to your desktop. Make your filename descriptive of the contents, e.g. "wt_profile#_genelist.txt", where you replace the number symbol with the actual profile number.
        • Upload these files to the wiki and link to them on your individual journal page. (Note that it will be easier to zip all the files together and upload them as one file).
      • For each of the significant profiles, click on the "Profile GO Table" to see the list of Gene Ontology terms belonging to the profile. In the window that appears, click on the "Save Table" button and save the file to your desktop. Make your filename descriptive of the contents, e.g. "wt_profile#_GOlist.txt", where you use "wt", "dGLN3", etc. to indicate the dataset and where you replace the number symbol with the actual profile number. At this point you have saved all of the primary data from the STEM software and it's time to interpret the results!
        • Upload these files to the wiki and link to them on your individual journal page. (Note that it will be easier to zip all the files together and upload them as one file).
  2. Analyzing and Interpreting STEM Results
    1. Select one of the profiles you saved in the previous step for further intepretation of the data. I suggest that you choose one that has a pattern of up- or down-regulated genes at the cold shock timepoints. Each member of your group should choose a different profile. Answer the following:
      • Why did you select this profile? In other words, why was it interesting to you?
        • Profile 1 (or in STEM it is profile 45) was selected because it was the first profile that comes up. It is interesting to see that it has an increase and then a sudden drop in its profile. It is cool to investigate because it isn't similar to the other profiles.
      • How many genes belong to this profile?
        • 406
      • How many genes were expected to belong to this profile?
        • 29.9
      • 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.
        • 0.00
      • 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?
        • 69/157
      • 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?
        • 9/157
      • Select the top 6 Gene Ontology terms from your filtered list (either p < 0.05 or corrected p < 0.05).
          • Note whether the same GO terms are showing up in multiple clusters.
            • GO:0005730
            • GO:0042254
            • GO:0006364
            • GO:0030687
            • GO:0005634
            • GO:0000447
        • Look up the definitions for each of the terms at 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)?
        • 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 on the left of the page.
        • 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.
          • GO:0005730
            • Name: Nucleolus
            • Definition: "A small, dense body one or more of which are present in the nucleus of eukaryotic cells. It is rich in RNA and protein, is not bounded by a limiting membrane, and is not seen during mitosis."
          • GO:0042254
            • Name: Ribosome biogenesis
            • Definition: "A cellular process that results in the biosynthesis of constituent macromolecules, assembly, and arrangement of constituent parts of ribosome subunits; includes transport to the sites of protein synthesis."
          • GO:0006364
            • Name:rRNA processing
            • Definition: "Any process involved in the conversion of a primary ribosomal RNA (rRNA) transcript into one or more mature rRNA molecules."
          • GO:0030687
            • Name: Preribosome, large subunit precursor
            • Definition: "A preribosomal complex consisting of 27SA, 27SB, and/or 7S pre-rRNA, 5S rRNA, ribosomal proteins including late-associating large subunit proteins, and associated proteins; a precursor of the eukaryotic cytoplasmic large ribosomal subunit."
          • GO:0005634
            • Name: Nucleus
            • Definition: "A membrane-bounded organelle of eukaryotic cells in which chromosomes are housed and replicated."
          • GO:0000447
            • Name: Endonucleolytic cleavage at A2
            • Definition: "Endonucleolytic cleavage between the SSU-rRNA and the 5.8S rRNA of an rRNA molecule originally produced as a tricistronic rRNA transcript that contained the Small SubUnit (SSU) rRNA, the 5.8S rRNA, and the Large SubUnit (LSU) rRNA, in that order, from 5' to 3' along the primary transcript."

Data and Files

Excel file of dGLN3 data

Powerpoint of STEM profiles

dGLN3 Genelists

dGLN3 GOlists

Acknowledgments

This week my partners are John Nimmers-Minor and Michael Armas. We discussed about the GOlists and decided on each person's profile to research.

Thank you Dr. Dahlquist for helping with any analysis questions that were asked.

I copied and pasted methods from Week 9. Also, names and definitions were copied and pasted from Gene Ontology Resource.


"Except for what is noted above, this individual page was completed by me and not copied from another source."Icrespin (talk) 18:13, 28 October 2019 (PDT)

References

Gene Ontology. (1999). Gene Ontology Resource. Retrieved October 28, 2019, from http://geneontology.org/

LMU BioDB 2019. (2019). Original Data. Retrieved October 25, 2019 from Media:BIOL367_F19_microarray-data_dGLN3.xlsx

LMU BioDB 2019. (2019). Week 9. Retrieved October 28, 2019, from https://xmlpipedb.cs.lmu.edu/biodb/fall2019/index.php/Week_9

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