I am trying to build the preprocessing pipeline presented in The Tabula Muris Consortium et al. (pp).
It is a pipeline to preprocess single-cell sequencing data. There is one step that is not clear:
Counts were log-normalized (log(1 + counts per N)), then scaled by linear regression against the number of reads (or UMIs), the percent of reads mapping to Rn45s, and the percent of reads to ribosomal genes.
I understand the first part (I assume that log in this context is log2), but I need help on understanding how to scale by linear regression against the number of reads, the percent of reads mapping to Rn45s, and the percent of reads to ribosomal genes.