Estimating and Correcting for Off-Target Cellular Contamination in Brain Cell Type Specific RNA-Seq Data.

ABSTRACT: Transcriptionally profiling minor cellular populations remains an ongoing challenge in molecular genomics. Single-cell RNA sequencing has provided valuable insights into a number of hypotheses, but practical and analytical challenges have limited its widespread adoption. A similar approach, which we term single-cell type RNA sequencing (sctRNA-seq), involves the enrichment and sequencing of a pool of cells, yielding cell type-level resolution transcriptomes. While this approach offers benefits in terms of mRNA sampling from targeted cell types, it is potentially affected by off-target contamination from surrounding cell types. Here, we leveraged single-cell sequencing datasets to apply a computational approach for estimating and controlling the amount of off-target cell type contamination

SUBMITTER: Sicherman J 

PROVIDER: S-EPMC7966716 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature