Patterns, Profiles, and Parsimony: Dissecting Transcriptional Signatures From Minimal Single-Cell RNA-Seq Output With SALSA.

ABSTRACT: Single-cell RNA sequencing (scRNA-seq) technologies have precipitated the development of bioinformatic tools to reconstruct cell lineage specification and differentiation processes with single-cell precision. However, current start-up costs and recommended data volumes for statistical analysis remain prohibitively expensive, preventing scRNA-seq technologies from becoming mainstream. Here, we introduce single-cell amalgamation by latent semantic analysis (SALSA), a versatile workflow that combines measurement reliability metrics with latent variable extraction to infer robust expression profiles from ultra-sparse sc-RNAseq data. SALSA uses a matrix focusing approach that starts by identifying facultative genes with expression levels greater than experimental measurement precision and ends

SUBMITTER: Lozoya OA 

PROVIDER: S-EPMC7586319 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature