e-mail+thread+between+Phil+and+I+5-17-12

3 messages
 * selecting p value cutoff**


 * **Kurt Whittemore**  || Wed, May 16, 2012 at 4:29 PM ||
 * To: Phillip Stafford  ||
 * || Hi Phil, how do I select a p value cutoff. Kathy made the following statement which I don't think is quite correct.

"Why are you using a p value of 0.05 for the random array results? there are 10,000 tests, so p= 1/10k"

The main reason I don't think it is correct is because my t tests did not involve 10,000 samples. My tests involved comparing the intensity of 3 peptides in normal vs 3 peptides in condition X so there are 6 samples. So given the fact that I have 6 samples or 3 in each group, how do I choose an appropriate p value cutoff?

-Kurt ||  ||

[Quoted text hidden] ||  ||
 * **Kurt Whittemore**  || Wed, May 16, 2012 at 4:30 PM ||
 * To: Phillip Stafford  ||
 * || Ah so I guess my real question is how to choose alpha not p.


 * **Phillip Stafford**  || Wed, May 16, 2012 at 6:19 PM ||
 * To: Kurt Whittemore  ||
 * || Actually you did do 10,000 different tests - each binding event is a test. For each peptide, you have 6 samples, but every time you test a peptide for significance, it's a test. The 1/10000 is the p-value for which you expect 1 false positive. At p=0.05, you expect 5% false positives (500), so if you only have 10 peptides that are significant at p=0.05, then you have 490 false positives for your 10 hits.

Alpha is the significance level at which you do a significance test, p is the probability of making a false interpretation of your data. In this case it's the same thing.

Phil ||  ||