Question: Does tools for removing batch effect from microarray data work for RNA-seq data as well ?
1
gravatar for jack
5.3 years ago by
jack790
Germany
jack790 wrote:

Hi all,

 

I want to estimate and remove batch effect from RNA-seq data.  RNA-seq data is count data and has skewed distribution, becuase of this fact, I want to know that, whether  tools for removing batch effect from microarray data are also aplicable to RNA-seq data ?

rna-seq next-gen R • 2.3k views
ADD COMMENTlink modified 5.3 years ago by Charles Warden7.3k • written 5.3 years ago by jack790
2
gravatar for Devon Ryan
5.3 years ago by
Devon Ryan92k
Freiburg, Germany
Devon Ryan92k wrote:

Have a look at svaseq.

ADD COMMENTlink written 5.3 years ago by Devon Ryan92k
2
gravatar for James
5.3 years ago by
James20
San Francisco, CA
James20 wrote:

Check out RUVSeq, a new package in Bioconductor based on a recent Nature Biotech paper.

ADD COMMENTlink written 5.3 years ago by James20
1
gravatar for Charles Warden
5.3 years ago by
Charles Warden7.3k
Duarte, CA
Charles Warden7.3k wrote:

If you work with something like log2(RPKM + 0.1) values and you know about the underlying causes of the batch effects, then I would use something like a normal ANOVA model to take the confounding variables into consideration.

If you don't know the confounding variables, you can try using tools like SVA.  However, that may also remove true variability, so I think the effectiveness will vary between datasets.

ADD COMMENTlink written 5.3 years ago by Charles Warden7.3k

Part of the appeal of an RUV-like approach compared to something like (vanilla) SVA is the use of control genes or replicate samples to provide better estimates of technical vs. biological variability. A comparison between the 'ssva' method in the preprint using control genes with SVA and the RUV approach would be really interesting.

ADD REPLYlink written 5.3 years ago by James20
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