Question: Select top differentially expressed genes based on both p-value and fold-change
0
gravatar for RT
3.6 years ago by
RT350
European Union
RT350 wrote:

I always selected top differentially expressed genes based on p-values (DESeq2 for differential-expr analysis). Just recently, someone suggested me to use both p-value and fold change to select top genes. I am little confused as p-values already take fold-change into consideration. Can someone shed some more light on what I am missing here?

ADD COMMENTlink modified 3.6 years ago by Santosh Anand5.2k • written 3.6 years ago by RT350

Hi, have you solved your problem? I am also confused about rankproduct. The reviewer asked me to consider both p-values and foldchange and use rankproduct to select top genes. According to reference, rankproduct is another method to find DEG. Could you please help me? Thanks.

ADD REPLYlink written 22 months ago by fuyanhu20150

You do not need to comment twice in the same thread. I'd suggest you ask a new question, since you sem to be more interested in rankproduct than the P-values or fold change specifically.

ADD REPLYlink written 22 months ago by Joe18k
6
gravatar for Santosh Anand
3.6 years ago by
Santosh Anand5.2k
Santosh Anand5.2k wrote:

Fold change is a measure of the ratio of means of two populations (say control and treatment).

p value measures how much confidence you have in that ratio. The p value usually will take into account the difference in means and variances (or standard deviation) of the populations being compared, but not directly the fold-change. Of course, if the fold change is high => difference in mean is high => the gene has more chance to becomes significant. However, even if the difference in mean is small, and the variances in two groups are also small => you are confident that this difference is real and not coming just by chance => the gene could become significant. That is to say, p-value is not directly determined by fold change

ADD COMMENTlink modified 3.6 years ago • written 3.6 years ago by Santosh Anand5.2k

so what is the best way to select top genes? As I said, I was suggested to consider both p-values and fold-change and use rankproduct for this. Rankproduct is used for identification of DEGs. I am not sure how to apply it to foldchange and pvalue.

Any other ideas of combining pval and fc for seelcting top genes are welcome.

ADD REPLYlink written 3.6 years ago by RT350
2

One typical approach would be to decide on a cut-off P-value you consider reasonable given your data and what you're asking. For instance, is P < 0.05 enough? Too many false positives? Go to P < 0.01 perhaps to reduce the size of your dataset?

Once you've defined a significance cutoff, then sort your DEGs that survive filtering by fold change, and take all of those above a fold change cutoff.Many people decide on log2 fold change cutoffs arbitrarily.

ADD REPLYlink modified 3.6 years ago • written 3.6 years ago by Joe18k

which, where, what rankproduct (Reference?)

ADD REPLYlink written 3.6 years ago by Santosh Anand5.2k
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