# Matthew E. Jurek Week 9

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###t90= .5704 | ###t90= .5704 | ||

###t120= .5507 | ###t120= .5507 | ||

+ | #Which gene has the smallest p value in your dataset (at any timepoint)? You can find this by sorting your data based on p value (but be careful that you don't cause a mismatch in the rows of your data!) Look up the function of this gene at the Saccharomyces Genome Database and record it in your notebook. Why do you think the cell is changing this gene's expression upon cold shock? | ||

+ | ##YGR172C= 0.0000124867704668826 |

## Revision as of 21:31, 2 April 2013

## Sanity Check

- How many genes have p value < 0.05?
- t15= 385
- t30= 544
- t60= 434
- t90= 231
- t120= 190

- What about p < 0.01?
- t15= 81
- t30= 108
- t60= 87
- t90= 28
- t120= 34

- What about p < 0.001?
- t15= 8
- t30= 10
- t60= 6
- t90= 5
- t120= 4

- What about p < 0.0001?
- t15= 0
- t30= 1
- t60= 1
- t90= 1
- t120= 0

- Perform this correction and determine whether and how many of the genes are still significantly changed at p < 0.05 after the Bonferroni correction.
- t15= 0
- t30= 0
- t60= 0
- t90= 0
- t120= 0

- For the timepoint that had the greatest number of genes significantly changed at p < 0.05, answer the following: Following the correction, there were no p values <.05. Thus, the following are calculations for each time point.
- Keeping the "Pval" filter at p < 0.05, filter the "AvgLogFC" column to show all genes with an average log fold change greater than zero. How many meet these two criteria?
- t15= 203
- t30= 332
- t60= 168
- t90= 118
- t120= 104

- Keeping the "Pval" filter at p < 0.05, filter the "AvgLogFC" column to show all genes with an average log fold change less than zero. How many meet these two criteria?
- t15= 182
- t30= 212
- t60= 266
- t90= 86
- t120= 86

- Keeping the "Pval" filter at p < 0.05, How many have an average log fold change of > 0.25 and p < 0.05?
- t15= 0
- t30= 0
- t60= 0
- t90= 0
- t120= 0

- How many have an average log fold change of < -0.25 and p < 0.05? (These are more realistic values for the fold change cut-offs because it represents about a 20% fold change which is about the level of detection of this technology.)
- t15= 150
- t30= 198
- t60= 247
- t90= 63
- t120= 74

- Find NSR1 in your dataset. Is it's expression significantly changed at any timepoint? Record the average fold change and p value for NSR1 for each timepoint in your dataset.
- Fold Change
- t15= .91
- t30= 1.19
- t60= 1.26
- t90= -.74
- t120= -.25

- P Value
- t15= .0385
- t30= .0722
- t60= .1618
- t90= .5704
- t120= .5507

- Fold Change
- Which gene has the smallest p value in your dataset (at any timepoint)? You can find this by sorting your data based on p value (but be careful that you don't cause a mismatch in the rows of your data!) Look up the function of this gene at the Saccharomyces Genome Database and record it in your notebook. Why do you think the cell is changing this gene's expression upon cold shock?
- YGR172C= 0.0000124867704668826