Downstream analysis of bam files from scRNA-Seq Data

Question

[rajeev.vikram]

Hi,

I am new to single cell RNA-Seq, and am trying to find a workflow related question. I have aligned about 1500 cells from two different experiments (but using same experimental procedure). I am wondering how do I go ahead with differential expression analysis. Should I merge all the bam files and then generate a count table? or should I use string tie on each cell (use the hisat-stringtie pipeline). I am a bit confused because the data set is too large. I understand that ultimately I should have an expression matrix (Genes/Expression level/cell). What should be the next step after alignment (i,e creation of individual bam files) ? Please advice.

Thanks

Answer 1

[Devon Ryan]

Normally one would use featureCounts or something to get the per-gene/per-cell counts. In single-cell studies this tends to involve using UMIs for deduplication, so be sure to account for that if possible. If you happen to know what groups the various cells belong to then you can go ahead with differential expression then. Otherwise you'll need to come up with your own groups (via tSNE or what not) and then do the DE between those groups.

[rajeev.vikram]

Thanks Ryan, This makes things a lot more clear.