Hi, I am working extensively on SMARTseq2 single-cell data generated using the Takara iCell8 platform. However, I prefer to work in Seurat instead of their own shiny-based analysis package called CogentDS.

Today I was wondering about which normalization to use. After a long stretch of fruitless googling I couldn't find any useful resource on this.

So far I've been importing raw count data to Seurat. However, SMARTseq2 does not include UMIs. It being full length additionally brings the factor of gene length. From what I've read, most people advise against using TPM data in Seurat as some of its functions are optimized for raw count data. But does this make sense? Am I not introducing heavy sequencing depth (multiple chips with different amounts of cells on each) and gene length (detecting an awful lot of genes with extremely varying length) bias into the analysis? Should I not be working with TPMs instead? Is there a way to generate TPM from counts directly in Seurat if I have gene information available or would I have to do the conversion manually?

Thanks a lot, Niko