RT Journal Article
SR Electronic
T1 scAllele: a versatile tool for the detection and analysis of variants in scRNA-seq
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2022.03.29.486330
DO 10.1101/2022.03.29.486330
A1 Giovanni Quinones Valdez
A1 Ting Fu
A1 Tracey Chan
A1 Xinshu (Grace) Xiao
YR 2022
UL http://biorxiv.org/content/early/2022/03/30/2022.03.29.486330.abstract
AB Single-cell RNA sequencing (scRNA-seq) data contain rich information at the gene, transcript, and nucleotide levels. Most analyses of scRNA-seq have focused on gene expression profiles, and it remains challenging to extract nucleotide variants and isoform-specific information. Here, we present scAllele, an integrative approach that detects single nucleotide variants, insertions, deletions, and their allelic linkage with splicing patterns in scRNA-seq. We demonstrate that scAllele achieves better performance in identifying nucleotide variants than other commonly used tools. In addition, the read-specific variant calls by scAllele enables allele-specific splicing analysis, a unique feature not afforded by other methods. Applied to a lung cancer scRNA-seq data set, scAllele identified variants with strong allelic linkage to alternative splicing, some of which being cancer-specific. scAllele represents a versatile tool to uncover multi-layer information and novel biological insights from scRNA-seq data.Competing Interest StatementThe authors have declared no competing interest.