What is P-value Adjustment?
P value adjustment is an essential part of microarray analysis. Raw p values are calculated for each individual gene on a microarray using a t test, for example. But since there are about 40,000 different probes on a typical gene expression array, you are doing 40,000 independent statistical tests on the data. Even at a reasonable p value of 0.05 or 0.01 you should expect many many false positive results. P value adjustment using a method such as the Benjamini and Hochberg method will change the raw p values (individual genes) into a false discovery rate for the whole experiment. For example if you find 500 genes significant at an adjusted p value of 0.05, you know that approximately 25 of the 500 genes (5%) are false positives.
