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bioRxiv · 10.1101/2022.03.29.486330

scAllele: a versatile tool for the detection and analysis of variants in scRNA-seq

Quinones-Valdez, G.·Fu, T.·Chan, T. W.·Xiao, X.
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Abstract

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.

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Quinones-Valdez, G., Fu, T., Chan, T. W., Xiao, X.. 2022-03-30. scAllele: a versatile tool for the detection and analysis of variants in scRNA-seq. https://doi.org/10.1101/2022.03.29.486330

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