Question: EdgeR (TMM): Samples with outlier but still show extremely low p-value and FDR
0
gravatar for Joe
18 days ago by
Joe30
USA
Joe30 wrote:

please see my data here:

https://user-images.githubusercontent.com/20710640/34529987-ba9f1414-f07b-11e7-913a-3ea787771a6e.JPG

https://github.com/Jinggg2016/NGS/issues/4

These are not raw data but normalized after edgeR. I list the first few genes with highest fold change, and found one sample is definitely a outlier (highlight in yellow), which cause high fold change (If I remove this outlier, the fold change is only 2 fold-ish.) I am so surprised that the p value and FDR are both extremely small even with an outlier.

Is it common issue when use edgeR for differential expression?

If it is a real issue, how could I find out outlier if I have a large set samples (eg, >100 samples) for data analysis?

We usually use DEseq2 for DE, DEseq2 can identify outlier and report NA for p value.

Thanks,

ADD COMMENTlink written 18 days ago by Joe30
Please log in to add an answer.

Help
Access

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 2.3.0
Traffic: 616 users visited in the last hour