I have plate-based single cell data from 7 vaccinees from two different dosing regimens (SmartSeq v4, Nextera Libraries). These were run through a pipeline leading to FeatureCounts prior to DESeq2 described here: DEseq2 error with different numbers of rows - #12 by carolyn_nielsen
I have just discussed this data with a colleague though and he wondered whether DESeq2 properly controlled for or pseudo-pooled cells from within the same vaccinee sample, or whether they were (incorrectly) treated as independent samples and inflating the number of significant differences between the two groups.
I had assumed that DESeq2 controlled for cells coming from the same vaccinee sample given there is a single FeatureCounts collection input per vaccinee. Is this correct? Is DESeq2 an appropriate tool for single cell analyses?
Each collection selected below for input to DESeq contains a FeatureCount tabular file per cell from that vaccinee (i.e 37-88 FeatureCount files per collection depending on number of cells obtained from each vaccinee):