No abstract

9Inferring the activity of transcription factors in single cells is a key task to improve our 2 0 4 1 relationships function at the single-cell level and therefore their implications can only be truly 4 2 understood at single-cell resolution 3-8 . 4 3 Recent single-cell RNA-sequencing (scRNA-Seq) studies have significantly advanced our 4 4 understanding of cellular development and disease 4, 7, 9-29 , yet how best to infer regulatory 4 5 activity at the single-cell level is still unclear. While a number of methods for inferring 4 6 regulatory activity have appeared 30-32 , all attempt to do so by first inferring the regulatory 4 7interactions from the noisy scRNA-Seq data itself, an approach recently assessed by others to 4 8 be highly suboptimal 33 , mainly because of the relatively high dropout rate of such data 5, 34 . 4 9 7 1 Motivation and rationale for the SCIRA algorithm 7 2