correcting the batch effects in Limma and SVA
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Bogdan ▴ 620
@bogdan-2367
Last seen 2 days ago
Palo Alto, CA, USA

Dear all,

about correcting the batch effects in LIMMA and SVA, 'd appreciate having your comments :

assuming that we have a set of RNA-seq data (no treatment, + treatment) in many distinct BATCHES, would the linear model in LIMMA :

design <- model.matrix(~0 + BATCH + Treatment, data=RNA)

suffice to correct for batch effects, or shall we additionally use COMBAT (as it is described in the SVA package : https://bioconductor.org/packages/release/bioc/vignettes/sva/inst/doc/sva.pdf ) in order to obtain the corrected counts ?

thanks a lot,

-- bogdan

limma combat sva • 1.5k views
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@gordon-smyth
Last seen 8 minutes ago
WEHI, Melbourne, Australia

I would myself just put BATCH in the limma linear model and omit Combat, and that is also recommended by Vegard Nygaard's group:

https://support.bioconductor.org/p/72926/

The Combat author (Dr Johnson) has agreed with this advice unless there are large difference in batch variances, in which case he has recommended using Combat but also including BATCH in the limma linear model:

https://support.bioconductor.org/p/72815/

I'm not sure how that would be done for RNA-seq though. I guess Combat would be run on logCPM values, in which case you would have to follow it up with limma-trend rather than limma-voom.

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Thanks a lot, Gordon. Very precious advise !

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Dear Gordon, if I may add and ask please (on a related topic):

would COMBAT and LIMMA be suited for assessing the differential expression between clusters of single cells (that were generated by using 10X Genomics protocols/kits) ?

've noted a tutorial from UC Davis that propose SVA/COMBAT and LIMMA for batch correction and differential expression :

https://ucdavis-bioinformatics-training.github.io/2019-single-cell-RNA-sequencing-Workshop-UCDUCSF/scrnaseqanalysis/scRNA_Workshop-PART6.html

thanks,

bogdan

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Entering edit mode

Dear Gordon, if I may add and ask please (on a related topic regarding single cell RNA-seq):

would COMBAT and LIMMA be suited for assessing the differential expression between clusters of single cells (that were generated by using 10X Genomics protocols/kits) ?

've noted a tutorial from UC Davis that propose SVA/COMBAT and LIMMA for batch correction and differential expression :

https://ucdavis-bioinformatics-training.github.io/2019-single-cell-RNA-sequencing-Workshop-UCDUCSF/scrnaseqanalysis/scRNA_Workshop-PART6.html

thanks,

bogdan

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