Difference between revisions of "Knguye66 Week 7"

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(Notes before starting: add notes)
(Acknowledgements: add acknowledgements)
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== Acknowledgements ==
 
== Acknowledgements ==
This section is in acknowledgement to partners...
+
This section is in acknowledgement to partner Christina Dominguez [[User:Cdomin12]], as well as, Marcus Avila [[User:Mavila9]] and Jonar Cowan [[User:Jcowan4]]
  
 
"Except for what is noted above, this individual journal entry was completed by me and not copied from another source."  
 
"Except for what is noted above, this individual journal entry was completed by me and not copied from another source."  

Revision as of 14:31, 15 October 2019

Notes before starting

  • T-test -> is this gene expression change significantly different than zero?
  • p<0.05: probability that you would have at least this big of a change by chance
    • ie. when we have 6189 genes, there are 6189 t-tests, are they significant? when we say there's a p<0.05, there's a 5% chance it's due to chance... meaning, if we have 6189 (5% of these are significant just by chance)
  • magnitude of difference
  • variation is sample measurements
  • number of samples/measurements

Microrray Data Analysis (wild type data)

Background

Part 1: Statistical Analysis Part 1

Bonferroni and p value Correction

Benjamini & Hochberg p value Correction

Sanity Check

- The number of genes that are significantly changed at p value cut-off of p < 0.05 -

  • How many genes have p < 0.05? and what is the percentage (out of 6189)?
    • -
  • How many genes have p < 0.01? and what is the percentage (out of 6189)?
    • -
  • How many genes have p < 0.001? and what is the percentage (out of 6189)?
    • -
  • How many genes have p < 0.0001? and what is the percentage (out of 6189)?
    • -

- Filter data to determine the following -

  • How many genes are p < 0.05 for the Bonferroni-corrected p value? and what is the percentage (out of 6189)?
    • -
  • How many genes are p < 0.05 for the Benjamini and Hochberg-corrected p value? and what is the percentage (out of 6189)?
    • -

- Compare your results with known data. Note that the average Log fold change is what we called "STRAIN)_AvgLogFC_(TIME)" in step 3 of the ANOVA analysis. Does NSR1 change expression due to cold shock in this experiment? -

  • Find NSR1 in your dataset. What is its unadjusted, Bonferroni-corrected, and B-H-corrected p values? What is its average Log fold change at each of the timepoints in the experiment?
    • -

- Find your favorite gene from Week 3. What is its unadjusted, Bonferroni-corrected, and B-H-corrected p values? What is its average Log fold change at each of the timepoints in the experiment? Does your favorite gene change expression due to cold shock in this experiment? -

    • -

Data and Files

Conclusion

Acknowledgements

This section is in acknowledgement to partner Christina Dominguez User:Cdomin12, as well as, Marcus Avila User:Mavila9 and Jonar Cowan User:Jcowan4

"Except for what is noted above, this individual journal entry was completed by me and not copied from another source."

User Page

User:knguye66

Template Page

Template:knguye66


Table of all assignments and journal entries for BIO-367-01

Week Individual Journal Entry Shared Journal
Week 1 - Class Journal Week 1
Week 2 knguye66 Week 2 Class Journal Week 2
Week 3 ILT1/YDR090C Week 3 Class Journal Week 3
Week 4 knguye66 Week 4 Class Journal Week 4
Week 5 DrugCentral Week 5 Class Journal Week 5
Week 6 knguye66 Week 6 Class Journal Week 6
Week 7 knguye66 Week 7 Class Journal Week 7
Week 8 knguye66 Week 8 Class Journal Week 8
Week 9 knguye66 Week 9 Class Journal Week 9
Week 10 knguye66 Week 10 Class Journal Week 10
Week 11 knguye66 Week 11 FunGals
Week 12/13 knguye66 Eyoung20 Week 12/13 FunGals
Week 15 knguye66 Eyoung20 Week 15 Class Journal Week 15

References