This article is free to access.
Identifying single nucleotide variants has become common practice for droplet-based single-cell RNA-seq experiments; however, presently, a pipeline does not exist to maximize variant calling accuracy. Furthermore, molecular duplicates generated in these experiments have not been utilized to optimally detect variant co-expression. Herein, we introduce scSNV designed from the ground up to “collapse” molecular duplicates and accurately identify variants and their co-expression. We demonstrate that scSNV is fast, with a reduced false-positive variant call rate, and enables the co-detection of genetic variants and A>G RNA edits across twenty-two samples.
Wilson, G. W., Derouet, M., Darling, G. E., & Yeung, J. C. (2021). scSNV: accurate dscRNA-seq SNV co-expression analysis using duplicate tag collapsing. Genome Biology, 22(1). https://doi.org/10.1186/s13059-021-02364-5