ArticleBioinformatics (Oxford, England)2023
SCExecute: custom cell barcode-stratified analyses of scRNA-seq data.
Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- A High-Fidelity and Ancestrally Inclusive Patient-Derived Organoid Platform Resolves Cancer Cell Plasticity in Uterine Carcinosarcoma.bioRxiv : the preprint server for biology · 2026Article
- scSNViz: visualization and analysis of cell-specific expressed SNVs.Bioinformatics (Oxford, England) · 2026Article
- scSNViz: visualization and analysis of cell-specific expressed SNVs.Bioinformatics (Oxford, England) · 2026Article
- AI/ML-Driven Gene Analysis: New Perspectives on Variant Calling in Normal Human Tissue Using scRNA-seq Data.Methods in molecular biology (Clifton, N.J.) · 2026Article
- SURROGATE SELECTION OVERSAMPLES EXPANDED T CELL CLONOTYPES.The annals of applied statistics · 2025Article
- Computational methods for allele-specific expression in single cells.Trends in genetics : TIG · 2024Review
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Authors and funding
7 authors.
Funding
Abstract
motivationIn single-cell RNA-sequencing (scRNA-seq) data, stratification of sequencing reads by cellular barcode is necessary to study cell-specific features. However, apart from gene expression, the analyses of cell-specific features are not sufficiently supported by available tools designed for high-throughput sequencing data.
resultsWe introduce SCExecute, which executes a user-provided command on barcode-stratified, extracted on-the-fly, single-cell binary alignment map (scBAM) files. SCExecute extracts the alignments with each cell barcode from aligned, pooled single-cell sequencing data. Simple commands, monolithic programs, multi-command shell scripts or complex shell-based pipelines are then executed on each scBAM file. scBAM files can be restricted to specific barcodes and/or genomic regions of interest. We demonstrate SCExecute with two popular variant callers-GATK and Strelka2-executed in shell-scripts together with commands for BAM file manipulation and variant filtering, to detect single-cell-specific expressed single nucleotide variants from droplet scRNA-seq data (10X Genomics Chromium System).In conclusion, SCExecute facilitates custom cell-level analyses on barcoded scRNA-seq data using currently available tools and provides an effective solution for studying low (cellular) frequency transcriptome features. AVAILABILITY AND IMPLEMENTATION: SCExecute is implemented in Python3 using the Pysam package and distributed for Linux, MacOS and Python environments from https://horvathlab.github.io/NGS/SCExecute. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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