Difference between revisions of "Hivanson Week 10"

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(→‎Clustering and GO Term Enrichment with stem: answer profile 22 questions)
(fixed all procedure)
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# '''Analyzing and Interpreting STEM Results'''
 
# '''Analyzing and Interpreting STEM Results'''
 
## I selected profile 22 for further intepretation of the data.  
 
## 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?'''
−
'''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?'''
−
I selected profile 22 because the overall trend of a spike only at 90 minutes is different from the rest of the profiles' trends.
+
##**46 genes
−
 
+
##*'''How many genes were expected to belong to this profile?'''
−
'''How many genes belong to this profile?'''
+
##**23.6 genes
−
 
+
##*'''What is the p value for the enrichment of genes in this profile?'''
−
46 genes
+
##**2.3E-5
−
 
+
##* 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 genes were expected to belong to this profile?'''
+
##* '''How many GO terms are associated with this profile at p < 0.05?'''
−
 
+
##** 25
−
23.6 genes
+
##* 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?'''
−
'''What is the p value for the enrichment of genes in this profile?'''
+
##** 7
−
 
+
##* I select 6 Gene Ontology terms from your filtered list
−
2.3E-5
+
##** 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 http://geneontology.org].'''''
−
##* 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?'''''
+
##**'''Why does the cell react to cold shock by changing the expression of genes associated with these GO terms?'''
−
##* Select 6 Gene Ontology terms from your filtered list (either p < 0.05 or corrected p < 0.05). 
+
##***The genes that are associated with these GO terms include stress responses, like <code>cellular response to oxidative stress</code>, 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 <code>cytoplasm</code>, <code>cytoskeleton</code>, and <code>fungal-type vacuole</code> which all may need to have regulated rigidity or some other physical characteristics at lower temperatures.
−
##** 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.
+
##**'''Also, what does this have to do with the transcription factor being deleted (for the groups working with deletion strain data)'''
−
##*** Note whether the same GO terms are showing up in multiple clusters.
+
##***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.
−
##**'''''Look up the definitions for each of the terms at [http://geneontology.org http://geneontology.org]. In your journal entry, 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 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 [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].
 
−
 
 
−
 
 
−
[[Image:HivansonstemresultsdCIN5.png|Execution results|500px]]
 
−
 
 
−
 
 
−
 
 
−
 
 
−
'''How many GO terms are associated with this profile at p < 0.05?'''
 
−
25
 
−
 
 
−
'''How many GO terms are associated with this profile with a corrected p value < 0.05?'''
 
−
7
 
  
 
{| class="wikitable"
 
{| class="wikitable"
−
|+ GO ID Definitions
+
|+ GO ID Terms
 
|-
 
|-
−
! GO ID !! Definition
+
! GO ID !! Term
 
|-
 
|-
 
| GO:0034599 || cellular response to oxidative stress
 
| GO:0034599 || cellular response to oxidative stress
Line 91: Line 74:
 
|}
 
|}
  
−
'''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 <code>cellular response to oxidative stress</code>, 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 <code>cytoplasm</code>, <code>cytoskeleton</code>, and <code>fungal-type vacuole</code> which all may need to have regulated rigidity or some other physical characteristics at lower temperatures.
+
[[Image:HivansonstemresultsdCIN5.png|Execution results|500px]]
  
−
'''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.
 
  
 
===Data & Files===
 
===Data & Files===

Revision as of 21:21, 25 March 2024

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 myPowerPoint 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?
        • 46 genes
      • How many genes were expected to belong to this profile?
        • 23.6 genes
      • What is the p value for the enrichment of genes in this profile?
        • 2.3E-5
      • 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


Execution results


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

Slides

Conclusion

Acknowledgments

References

Template:Hivanson

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