Question: shall i select genes based on p-value alone if FDR is not significant?
gravatar for muthulaxmi.m
4.4 years ago by
muthulaxmi.m10 wrote:

In general, differential gene expression analysis from microarray profile uses p-value along with multiple corrections to get adjusted p-value. I have a doubt that, if none of the genes satisfy the criteria of FDR<0.05, shall i select significant genes based on p-value<0.05 criteria alone?

Since I could not find any literature supporting the filtering of genes based on p-value alone, can anyone guide me in selecting the significant genes. Is this case of FDR>0.05 is allowed in microarray data analysis?


ADD COMMENTlink modified 4.4 years ago by Devon Ryan95k • written 4.4 years ago by muthulaxmi.m10

It's preferable to use adjusted p-value to account for multiple testing. The threshold is arbitrary. In the case of FDR you can think of it as the fraction of false positives so if you pick genes at a FDR < 0.1 then 10% of the genes you've selected will be false positives. How you set the threshold depends on how costly the errors are going to be, e.g. is it worth doing follow up experiments on 100 genes knowing that 10 are false positives ? In general if you don't want to abide by the result of a statistical test then don't do it in the first place and if you don't care about statistical significance then just go ahead and pick genes based on whatever criteria suits you.

ADD REPLYlink written 4.4 years ago by Jean-Karim Heriche22k
gravatar for Devon Ryan
4.4 years ago by
Devon Ryan95k
Freiburg, Germany
Devon Ryan95k wrote:

If none of the genes are significant given your desired cut off then don't select anything. It is, after all, perfectly normal for experiments to show no change.

ADD COMMENTlink written 4.4 years ago by Devon Ryan95k
Please log in to add an answer.


Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 2.3.0
Traffic: 1958 users visited in the last hour