DESeq2 calling DEGs despite detection in few replicates
1
0
Entering edit mode
lnblock2 • 0
@326247d3
Last seen 6 weeks ago

Hi, this is my first time doing differential expression analysis and I have a few questions about the data output. My data was collected from 4 different cell lines derived from 4 different animals (as biological replicates). We are getting inconsistent calling of DEGs and I'm not sure why. Attached are a few scatter plots of the genes in question.

For (B) it was called DEG even though it was only detected in one sample. For (A & C) these were NOT identified as a DEG with DESeq2 but were identified with edgeR's glmQLfit().

For DESeq2 I ran this with the default parameters. Any suggestions on which parameters I could change to account for variation between replicates? Are outliers handled differently when 3 out of 4 samples are highly expressed compared to when only 1 out for 4 samples are highly expressed?

I can add the code if that would help but it's more of a question about the algorithm itself. I can also provide more examples if that would be helpful. Thank you!

NOT identified as a DEG with DESeq2 but was identified with edgeR's glmQLfit(). NOT identified as a DEG with DESeq2 but was identified with edgeR's glmQLfit(). Was called DEG even though it was only detected in one sample.

DESeq2 • 83 views
ADD COMMENT
0
Entering edit mode
swbarnes2 ▴ 680
@swbarnes2-14086
Last seen 16 hours ago
San Diego

The software is correctly detecting a difference in averages between the two groups. It's really not the software's place to be deciding if those expression patterns are artifacts or not. If you think they are artifacts, you should remove them yourself.

ADD COMMENT

Login before adding your answer.

Traffic: 482 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6