RNAseq outlier is a critical sample
3
0
Entering edit mode
grastalt27 • 0
@grastalt27-10859
Last seen 5.3 years ago

Hi Everyone,

 

I'm trying to analyze some RNAseq results, but one of my samples is a pretty bad outlier by PCA and by clustering over the entire transcriptome.

I have 4 groups with 3 biological replicates.  These samples were run in 2 batches.

When I try to summarize my reads using RSubread's featureCounts, the outlier has a very low assignment %, with a high % of multiple assignments

 

My question is how should I proceed with my analysis?  I don't have enough replicates to kick the outlier out.  Are there methods to fix outliers?  Is it valid to consider this outlier as a separate batch (Removing the variation with removeBatchEffect)? 

Thank you!

rnaseq outlier statistics batch effect • 859 views
ADD COMMENT
1
Entering edit mode
@steve-lianoglou-2771
Last seen 4 days ago
Denali

voomWithQualityWeights to the rescue!

... in the limma package (in case you weren't aware).

ADD COMMENT
1
Entering edit mode
@gordon-smyth
Last seen 1 minute ago
WEHI, Melbourne, Australia

No, it isn't valid to consider an outlier as a separate batch.

There are only two possibilities: down-weight the outlier using the appropriate functions in limma (as suggested by Steve) or throw the sample out (as suggested by Dario).

ADD COMMENT
0
Entering edit mode
Dario Strbenac ★ 1.5k
@dario-strbenac-5916
Last seen 7 days ago
Australia

Since you have three replicates in each group, you should just exclude the unusual sample from the analysis. You don't need balanced sample sizes in every experimental group.

ADD COMMENT

Login before adding your answer.

Traffic: 367 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