ArticleBMC genomics2021
SCReadCounts: estimation of cell-level SNVs expression from scRNA-seq data.
Article in BMC genomics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed, 34 citations in OpenAlex.
- DAESC + : high-performance, integrated software for single-cell allele-specific expression data.BMC bioinformatics · 2026Article
- scSNViz: visualization and analysis of cell-specific expressed SNVs.Bioinformatics (Oxford, England) · 2026Article
- Clonal cell states link gastroesophageal junction tissues with metaplasia and cancer.Nature communications · 2025Article
- Conserved patterns of transcriptional dysregulation, heterogeneity, and cell states in clear cell kidney cancer.Cell reports · 2025Article
- scTML: a pan-cancer single-cell landscape of multiple mutation types.Nucleic acids research · 2025Article
- Computational methods for allele-specific expression in single cells.Trends in genetics : TIG · 2024Review
- CanCellVar: A database for single-cell variants map in human cancer.American journal of human genetics · 2024Article
- De novo detection of somatic mutations in high-throughput single-cell profiling data sets.Nature biotechnology · 2024Article
- Single-cell multiomics reveals the interplay of clonal evolution and cellular plasticity in hepatoblastoma.Nature communications · 2024Article
- STmut: a framework for visualizing somatic alterations in spatial transcriptomics data of cancer.Genome biology · 2023Article
- Preneoplastic liver colonization by 11p15.5 altered mosaic cells in young children with hepatoblastoma.Nature communications · 2023Article
- A targeted sequencing extension for transcript genotyping in single-cell transcriptomics.Life science alliance · 2023Article
- SCExecute: custom cell barcode-stratified analyses of scRNA-seq data.Bioinformatics (Oxford, England) · 2023Article
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- scReQTL: an approach to correlate SNVs to gene expression from individual scRNA-seq datasets.BMC genomics · 2021Article
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRecent studies have demonstrated the utility of scRNA-seq SNVs to distinguish tumor from normal cells, characterize intra-tumoral heterogeneity, and define mutation-associated expression signatures. In addition to cancer studies, SNVs from single cells have been useful in studies of transcriptional burst kinetics, allelic expression, chromosome X inactivation, ploidy estimations, and haplotype inference.
resultsTo aid these types of studies, we have developed a tool, SCReadCounts, for cell-level tabulation of the sequencing read counts bearing SNV reference and variant alleles from barcoded scRNA-seq alignments. Provided genomic loci and expected alleles, SCReadCounts generates cell-SNV matrices with the absolute variant- and reference-harboring read counts, as well as cell-SNV matrices of expressed Variant Allele Fraction (VAF
conclusionsSCReadCounts supplies a fast and efficient solution for estimation of cell-level SNV expression from scRNA-seq data. SCReadCounts enables distinguishing cells with monoallelic reference expression from those with no gene expression and is applicable to assess SNVs present in only a small proportion of the cells, such as somatic mutations in cancer.
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