BIOL368/F14:Week 15

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BIOL368: Bioinformatics Laboratory

Loyola Marymount University

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This journal entry is due on Wednesday, December 10 at midnight PST (Tuesday night/Wednesday morning). NOTE that the server records the time as Eastern Standard Time (EST). Therefore, midnight will register as 03:00.



Overview of DNA Microarray Analysis

This is a list of steps required to analyze DNA microarray data.

  1. Quantitate the fluorescence signal in each spot in the microarray image.
    • Typically performed by the scanner software, although third party software packages do exist.
    • The image of the microarray slide and this quantitation are considered the "raw-est" form of the data.
    • Ideally, this type of raw data would be made publicly available upon publication.
    • In practice, the image data is usually not made available because the raw image file of one slide could be up to 100 MB in size.
    • Also, some journals do not require data deposition as a requirement for publication, so often published data are not actually available anywhere for download.
    • Microarray data is not centrally located on the web. Some major sources are:
  2. Calculate the ratio of red/green fluorescence
  3. Log(base 2) transform the ratios
  4. Normalize the log ratios on each microarray slide
  5. Normalize the log ratios for a set of slides in an experiment
  6. Perform statistical analysis on the log ratios
  7. Compare individual genes with known data
  8. Look for patterns (expression profiles; clusters) in the data (many programs are available to do this)
  9. Perform Gene Ontology term enrichment analysis (we will use MAPPFinder for this)
  10. Map onto biological pathways (we will use GenMAPP for this)

Individual Journal Assignment

  • Store this journal entry as "username Week 15" (i.e., this is the text to place between the square brackets when you link to this page).
  • Create the following set of links. These links should all be in your personal template; then use the template on your journal entry.
    • Link to your journal entry from your user page.
    • Link back from your journal entry to your user page.
    • Link to this assignment from your journal entry.
    • Don't forget to add the "BIOL368/F14" category to the end of your wiki page.

Complete Microarray Data Analysis

  • Using the spreadsheet that you submitted for the Week 13 Assignment, you will now complete GenMAPP and MAPPFinder analysis of your dataset.
    • Dr. Dahlquist has added her calculations on your dataset to your spreadsheets and has uploaded them to the wiki.
      • Compare your results in your "forGenMAPP" sheet with the ones designated "_norm_KD" and "_notnorm_KD". I computed the statistics both with ("norm") and without ("notnorm") scaling and centering the data, so there should be two comparisons to make.
      • Re-do the sanity check at p < 0.05 as a quick measure of how similar the sheets are. We will decide in class which analysis to go with for the rest of the project.
      • Find one gene in your journal article for which the log2 fold change (or fold change) is reported. Look it up in your dataset to see if the numbers are similar. We will also use this to decide which set of calculations to use going forward.
      • You will need to re-do the complete sanity check to get the data to present in your final research presentation next week.
    • This page gives a sample protocol for the analysis of a Vibrio cholerae dataset.
  • You will keep a detailed electronic notebook page that details all of the data manipulations and calculations that you perform on your dataset.
  • You will upload the following list of files (note that it may be easier to zip all of these files together and then upload them as a single zipped file, rather than zipping and uploading individually, for filetypes not allowed by OpenWetWare).
    1. Your exceptions file when you imported your data into GenMAPP: .EX.txt
    2. Your Expression Dataset file: .gex
    3. Your GO results files: XXX-CriterionX-GO.txt
    4. Your GO results saved as Excel spreadsheets with filters applied: .xls or .xlsx
    5. The MAPP you looked at: .mapp
    6. The MAPPFinder GO mappings file: .gmf

Final Research Presentation

  • Your Final Research Presentation will be formatted similarly to your previous research presentations.
  • Your presentation will be 15-20 minutes long (approximately 15-20 slides, one per minute). Include:
    • Title slide
    • Outline slide
    • Background about your microarray dataset (from your journal club)
    • The experimental design of the microarray experiment
    • A table that lists the number of genes with significant changes in expression at the p value cut-offs of < 0.05, < 0.01, < 0.001, and Bonferroni-corrected p < 0.05.
    • A list of the top 10 "most significant" genes and their functions.
    • Tables that list the MAPPFinder results for increased and decreased gene expression.
    • Discussion and interpretation of your results, in comparison to the original journal club paper.
  • Upload your slides to the OpenWetWare wiki by the Week 15 journal assignment deadline. You may make changes to your slides in advance of your presentation, but you will be graded on what you upload by the journal deadline.

Note: The individual journal entry for this week is worth 10 points like all other journal entries. The research presentation is worth 80 points.

Shared Journal Assignment

  • Store your journal entry in the shared BIOL368/F14:Class Journal Week 15 page. If this page does not exist yet, go ahead and create it.
  • Link to the shared journal entry from your user page; this should be part of your template.
  • Link the shared journal page to this assignment page.
  • Sign your portion of the journal with the standard wiki signature shortcut (~~~~).
  • Add the "BIOL368/F14" category to the end of the wiki page (if someone has not already done so).


For your last reflection you will reflect on this entire semester:

  • What is the most important thing that you learned this semester in this class?
    • With your head (biological or bioinformatics principles)
    • With your heart (personal qualities and teamwork qualities that make things work or not work)?
    • With your hands (technical skills)?
  • What will you take away from this class that you will still use a year from now?