Question: Using SVA to correct for covariates in RNA-seq data
0
gravatar for sbrown669
6 months ago by
sbrown66920
sbrown66920 wrote:

I am working with RNA-seq data, and I need to correct for covariates. To do this, I want to use the Bioconductor package SVA. I want to produce a 'corrected dataset' and then use this for further analyses - to perform pairwise Pearson correlations and generate heat maps to visualise co-expression. However, as I understand it, the documentation explains how to feed the covariates into a model for differential expression analysis, not how to produce and export a corrected dataset based on the SVA calculations.

I'd appreciate any advice on doing this, or in fact being informed that I'm going about this in the wrong way.

ADD COMMENTlink modified 5 months ago • written 6 months ago by sbrown66920
3
gravatar for Kevin Blighe
6 months ago by
Kevin Blighe48k
Kevin Blighe48k wrote:

Hey,

Yes, from what I understand, SVA will just determine the batch covariates that [may] exist in your data. You can then use removeBatchEffects if you want to directly remove these batch effects from your data.

Be cautious of these batch detection methods, though - one does not want to remove genuine biological effects of interest that exist in the samples.

Kevin

ADD COMMENTlink modified 6 months ago • written 6 months ago by Kevin Blighe48k
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: 2323 users visited in the last hour