Question: Batch effect in RNAseq
gravatar for singh.vijender
5 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 • 301 views
ADD COMMENTlink modified 5 months ago by Devon Ryan88k • written 5 months ago by singh.vijender30
gravatar for Devon Ryan
5 months ago by
Devon Ryan88k
Freiburg, Germany
Devon Ryan88k 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 5 months ago by Devon Ryan88k

Or removeBatchEffect from limma

ADD REPLYlink written 5 months ago by kristoffer.vittingseerup1.6k
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