PT  - JOURNAL ARTICLE
AU  - Giovanni Quinones Valdez
AU  - Ting Fu
AU  - Tracey Chan
AU  - Xinshu (Grace) Xiao
TI  - scAllele: a versatile tool for the detection and analysis of variants in scRNA-seq
AID  - 10.1101/2022.03.29.486330
DP  - 2022 Jan 01
TA  - bioRxiv
PG  - 2022.03.29.486330
4099  - http://biorxiv.org/content/early/2022/03/30/2022.03.29.486330.short
4100  - http://biorxiv.org/content/early/2022/03/30/2022.03.29.486330.full
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.