I have a list of DEGs. With those genes I have P value and Padj value, so what is the differences and what value I have to keep in both ?
I have a list of DEGs. With those genes I have P value and Padj value, so what is the differences and what value I have to keep in both ?
Hi, the p-value in DESeq2 is calculated using the wald test. The null hypothesis of the wald test is that: for each gene, there is no differential expression across two sample groups (e.g., treated vs control). If the p-value is small (e.g., p<0.05), the null hypothesis is rejected, as there is only 5% of chance that the null hypothesis is true. However, when you have many genes being tested, by chance (5%), there is a number of genes that are not significantly expressed, but obtained significant p-values. Therefore, we need to correct this problem caused by multiple testing. DESeq2 adjust the p value from wald test using Benjamini and Hochberg method (BH-adjusted p values), which is presented in the column of padj in the results object.
You should use the adjusted p-value (padj), which is the transformation of the p-value after accounting for multiple testing.
As I understand, from your question, you need to read this , this article will help you understnad the logic behind it.
Why, When and How to Adjust Your P Values? All the best
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That's a quite fundamental question that tells me that you are not really familiar with statistics. Did you try to follow any tutorials? Who did give you these DEGs? Do you have any support from a bioinformatician or (bio)statistician?
I am not familiar with statistics, I got the DEGs from my advisor and my further work is annotation and validation.
You should understand the data you are working on, so do some reading before proceeding.
I recommend you to read this tutorial: https://bioc.ism.ac.jp/packages/2.14/bioc/vignettes/DESeq2/inst/doc/beginner.pdf