edgeR for single-cell data with inferential replicates
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ATpoint • 470
Last seen 3 hours ago

I am wondering whether there are best-practices to use edgeR on single-cell (10X) data that were quantified with the Alevin module from Salmon, given that we want to use the inferential replicates that it produces via bootstrapping. I know there exists the catchSalmon function to calculate a per-transcript overdispersion value. Alevin first of all outputs gene level counts, and second I personally prefer to perform single-cell DE between clusters on the pseudobulk level (given one has biological replicates of course).

Therefore, are there best-practices to import the inferential replicates from Alevin into edgeR and can we "sum" this inferential replicate information per single cell to the pseudobulk level?

edgeR alevin • 157 views
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Last seen 41 minutes ago
WEHI, Melbourne, Australia

I don't know Alevin but, if it gives genewise counts, they should be able to go straight into edgeR. No need for catchSalmon.

I use edgeR's sumTechReps() function to make pseudo-bulk replicates from single cell counts.

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Thanks for the prompt reply. The reason I am asking is that 10X is a 3'-tagged rather than full-length protocol and according to the Swish paper taking into account mapping uncertainty might be beneficial for these kind of data, even on the gene level. So the main question would be whether one can robustly "sum" or "transfer" the inferential replicate information per single cell into the pseudobulk.


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