Systematic comparative analysis of single-nucleotide variant detection methods from single-cell RNA sequencing data.

ABSTRACT:

Background

Systematic interrogation of single-nucleotide variants (SNVs) is one of the most promising approaches to delineate the cellular heterogeneity and phylogenetic relationships at the single-cell level. While SNV detection from abundant single-cell RNA sequencing (scRNA-seq) data is applicable and cost-effective in identifying expressed variants, inferring sub-clones, and deciphering genotype-phenotype linkages, there is a lack of computational methods specifically developed for SNV calling in scRNA-seq. Although variant callers for bulk RNA-seq have been sporadically used in scRNA-seq, the performances of different tools have not been assessed.

Results

Here, we perform a systematic comparison of seven tools including SAMtools, the GATK pipeline, CTAT, FreeBayes, MuTe

SUBMITTER: Liu F 

PROVIDER: S-EPMC6862814 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature