Question: Batch effect in RNAseq
gravatar for singh.vijender
11 months ago by
singh.vijender30 wrote:

PCA plot of triplicates

Figure A

enter image description here Figure B

The distribution of replicates from an RNA-seq study is plotted on the PCA plot as shown in the figures (plotted using top 500 highly variant genes).
(1) Figure A: Looking at the distribution what is your opinion on carrying out a DE analysis. What type of preprocessing of these samples (please suggest packages/tools) will help in carrying out DE? (2) Figure B: There is a strong batch effect as the variance between batch is higher than the variance between the conditions compared. I was thinking of comparing sample and treatment of the same batch independently using Gfold or NOIseq and then pull out genes which show similar fold changes between the 3 comparisons. Would like to have an opinion on that. Please comment.

rna-seq • 573 views
ADD COMMENTlink modified 11 months ago by Devon Ryan91k • written 11 months ago by singh.vijender30
gravatar for Devon Ryan
11 months ago by
Devon Ryan91k
Freiburg, Germany
Devon Ryan91k wrote:

The standard methods for dealing with a batch effect are:

  1. Add it to you model (e.g., in DESeq2, limma, or edgeR)
  2. Use something like Combat from the SVA package.

I personally prefer option 1 except in cases where the batch effect is expected to be fairly variable by sample.

ADD COMMENTlink written 11 months ago by Devon Ryan91k

Or removeBatchEffect from limma

ADD REPLYlink written 11 months ago by kristoffer.vittingseerup2.3k
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