Cell type matching in single-cell RNA-sequencing data using FR-Match.

ABSTRACT: Reference cell atlases powered by single cell and spatial transcriptomics technologies are becoming available to study healthy and diseased tissue at single cell resolution. One important use of these data resources is to compare cell types from new dataset with cell types in the reference atlases to evaluate their phenotypic similarities and differences, for example, for identifying novel cell types under disease conditions. For this purpose, rigorously-validated computational algorithms are needed to perform these cell type matching tasks that can compare datasets from different experiment platforms and sample types. Here, we present significant enhancements to FR-Match (v2.0)-a multivariate nonparametric statistical testing approach for matching cell types in query datasets to reference

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC9200772 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature