gravatar for Devon Ryan

12 minutes ago by

Freiburg, Germany

TMM, RLE, and quantile normalization aren't appropriate on data for which there are expected unidirectional global shifts. In such cases you either need a spike-in or prior knowledge about genes that aren't changing (these are then used with TMM/RLE/etc. to compute scaling factors).

scRNA-seq isn't any different in this regard, except if you're primarily doing it for finding cell-types you can hope there's more going on than simply transcriptional amplification and just ignore spike-ins. Spike-ins are probably more accurate in scRNA-seq, since it's more likely that you actually know how many cells you have.

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