Difference between revisions of "Aporras1 Week 10"

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==Electronic Notebook==
 
==Electronic Notebook==
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This is a list of steps required to analyze DNA microarray data.
 
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#Quantitate the fluorescence signal in each spot
 
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#Calculate the ratio of red/green fluorescence
 
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#Log<sub>2</sub> transform the ratios
 
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#* Steps 1-3 have been performed for you by the GenePix Pro software (which runs the microarray scanner).
 
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#Normalize the ratios on each microarray slide
 
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#Normalize the ratios for a set of slides in an experiment
 
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#* Steps 4-5 was performed for you using a script in R, a statistics package (see: [https://openwetware.org/wiki/Dahlquist:Microarray_Data_Analysis_Workflow#Steps_4-5:_Within-_and_Between-chip_Normalization Microarray Data Analysis Workflow])
 
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#* You will perform the following steps:
 
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#Perform statistical analysis on the ratios
 
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#Compare individual genes with known data
 
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#* Steps 6-7 are performed in Microsoft Excel
 
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#Pattern finding algorithms (clustering)
 
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#Map onto biological pathways
 
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#* We will use software called STEM for the clustering and mapping
 
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# Identifying regulatory transcription factors responsible for observed changes in gene expression
 
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# Dynamical systems modeling of the gene regulatory network ([http://kdahlquist.github.io/GRNmap/ GRNmap])
 
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# Viewing modeling results in [http://dondi.github.io/GRNsight/ GRNsight]
 
  
 
==== Clustering and GO Term Enrichment with stem ====
 
==== Clustering and GO Term Enrichment with stem ====
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#* This created a folder called <code>stem</code>.  Inside the folder, double-clicked on the <code>stem.jar</code> and launched the STEM program.
 
#* This created a folder called <code>stem</code>.  Inside the folder, double-clicked on the <code>stem.jar</code> and launched the STEM program.
 
# '''Running STEM'''
 
# '''Running STEM'''
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## In section 1 (Expression Data Info) of the the main STEM interface window, click on the ''Browse...'' button to navigate to and select your file.
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## In section 1 (Expression Data Info) of the the main STEM interface window, clicked on the ''Browse...'' button to navigate to the file.
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##* Click on the radio button ''No normalization/add 0''.
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##* Clicked on the radio button ''No normalization/add 0''.
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##* Check the box next to ''Spot IDs included in the data file''.
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##* Checked the box next to ''Spot IDs included in the data file''.
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## In section 2 (Gene Info) of the main STEM interface window, select ''Saccharomyces cerevisiae (SGD)'', from the drop-down menu for Gene Annotation Source.  Select ''No cross references'', from the Cross Reference Source drop-down menu.  Select ''No Gene Locations'' from the Gene Location Source drop-down menu.
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## 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.
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## In section 3 (Options) of the main STEM interface window, make sure that the Clustering Method says "STEM Clustering Method" and do not change the defaults for Maximum Number of Model Profiles or Maximum Unit Change in Model Profiles between Time Points.
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## In section 3 (Options) of the main STEM interface window, made sure that the Clustering Method says "STEM Clustering Method" and didn't change the defaults for Maximum Number of Model Profiles or Maximum Unit Change in Model Profiles between Time Points.
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## In section 4 (Execute) click on the yellow Execute button to run STEM.
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## In section 4 (Execute) clicked on the yellow Execute button to run STEM.
 
# '''Viewing and Saving STEM Results'''
 
# '''Viewing and Saving STEM Results'''
 
## 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.
 
## 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.

Revision as of 01:05, 7 November 2017

User page: Antonio Porras

Assignment page: Week 10 Assignment

Electronic Notebook

Clustering and GO Term Enrichment with stem

  1. Prepare your microarray data file for loading into STEM.
    • Downloaded Excel workbook AP_dZAP1 from the Week 8 assignment.
    • Inserted a new worksheet into the Excel workbook, and named it "dZAP1_stem".
    • Selected all of the data from "dZAP1_ANOVA" worksheet and used Paste special > pasted values into "dZAP1_stem" worksheet.
      • Changed leftmost column header "Master_Index" to "SPOT". Changed column B "ID" 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).
        • Selected all of the rows (except for the header row) and deleted the rows by right-clicking and choosing "Delete Row" from the context menu. Undid the filter. This ensured that I would cluster only the genes with a "significant" change in expression and not the noise. Record the number of genes left in your electronic notebook. 1775 genes were 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 the spreadsheet as Text (Tab-delimited) (*.txt). Clicked OK to the warnings and closed my file.
        • Turned on the 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 the Desktop.
    • Unzipped the file.
    • This created a folder called stem. Inside the folder, double-clicked on the stem.jar and launched 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 the 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 didn't 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 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).
  5. 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?
      • How many genes belong to this profile?
      • How many 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.
      • 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).
        • Each member of the group will be reporting on his or her own cluster in your 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 your 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.

Essential Files

  1. Media:AP dZAP1 STEM Profiles and Powerpoint.zip

Acknowledgements

  1. Worked in class with Katie Wright to discuss any questions we had throughout the process of completing the Week 10 assignment.
  2. Recieved help from both Dondi and Dr. Dahlquist during the allotted class period.

While I worked with the people noted above, this individual journal entry was completed by me and not copied from another source.

Aporras1 (talk) 14:53, 31 October 2017 (PDT)

References

  1. 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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