Difference between revisions of "Knguye66 Week 7"
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== Notes before starting == | == Notes before starting == | ||
| − | T-test -> is this gene expression change significantly different than zero? | + | * 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 | + | * 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 | |
| − | 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) | ||
== Microrray Data Analysis (wild type data) == | == Microrray Data Analysis (wild type data) == | ||
Revision as of 14:29, 15 October 2019
Contents
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)?
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- 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)?
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- 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 partners...
"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
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