DESeq2 after Seurat analysis on integrated datasets
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bio.boi • 0
@c94db738
Last seen 14 months ago
United States

Hi everyone,

I'm still a novice when it comes to R, but I've been trying to teach myself using some of my lab's data sets. I'm currently working on comparing 2 single cell RNA-seq data sets (control vs treatment) and I've gone through all of the initial analysis (clustering, identifying cell types and integrating the two sets together), and now I have been trying to look at differential gene expression between the two conditions. I tried using the FindMarkers() function with the DESeq2 and MAST parameters, but am not having much luck. Upon further research, it seems the best way to go about it may be to actually use DESeq2 after all of my Seurat analyses. I think the problem I'm having is adding a psuedocount to the data (getting a "data contains at least one zero" error). My though was to add a column specifying the control vs treatment groups so that I can use those as idents in DESeq2, but I was hoping to get some insight to see if this was the best way to do this.

Any and all recommendations are greatly appreciated!

Thanks

DESeq2 SingleCell GeneExpression Seurat • 2.3k views
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ATpoint ★ 4.0k
@atpoint-13662
Last seen 5 hours ago
Germany

The Bioconductor single-cell book OSCA covers differential expression in great detail, please go through it http://bioconductor.org/books/release/OSCA/

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