Sincast: a computational framework to predict cell identities in single-cell transcriptomes using bulk atlases as references.

ABSTRACT: Characterizing the molecular identity of a cell is an essential step in single-cell RNA sequencing (scRNA-seq) data analysis. Numerous tools exist for predicting cell identity using single-cell reference atlases. However, many challenges remain, including correcting for inherent batch effects between reference and query data andinsufficient phenotype data from the reference. One solution is to project single-cell data onto established bulk reference atlases to leverage their rich phenotype information. Sincast is a computational framework to query scRNA-seq data by projection onto bulk reference atlases. Prior to projection, single-cell data are transformed to be directly comparable to bulk data, either with pseudo-bulk aggregation or graph-based imputation to address sparse single-cell ex

SUBMITTER: Deng Y 

PROVIDER: S-EPMC9155616 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature