What is the difference between the P-value and the P-adj columns in the DESeq2 data table? Which of these columns is more important for assessing significant differences in gene expression?

Hi @Hunter,

as probably you know, the p-value is a measure of how likely you are to get a specific gene if no real difference exists. A p-value threshold of 0.05 states that there is a 5% chance that the result is a false positive (considered differentially expressed when is not).

While 5% is acceptable for one test, if we do a lot of tests on the data, then this 5% can result in a large number of false positives (e.g. a differential expression analysis of 8.000 expressed genes would include 8.000 * 0.05 = 400 false positives!) An adjusted p-value aims to overcome the problems due to multiple testing by reducing the p-value threshold from the common 0.05 to a more reasonable value.

Then, depending on how strict you want the analysis to be, you should choose one or the other value.

Regards