SCExecute: custom cell barcode-stratified analyses of scRNA-seq data.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 36448703.
- Also identified by DOI 10.1093/bioinformatics/btac768 and PMC identifier 9825775.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
In 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. We 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. 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 data are available at Bioinformatics online.
Medical subject headings
- Software
- Single-Cell Gene Expression Analysis