SCExecute: custom cell barcode-stratified analyses of scRNA-seq data
Bioinformatics (Oxford, England)
MOTIVATION: 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. RESULTS: 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 (sceSNVs) from droplet scRNA-seq data (10X Genomics Chromium System). 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: 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.
Edwards, Nathan; Dillard, Christian; N M, Prashant; Liu, Hongyu; Yang, Mia; Ulianova, Evgenia; and Horvath, Anelia, "SCExecute: custom cell barcode-stratified analyses of scRNA-seq data" (2022). GW Authored Works. Paper 1880.
Biochemistry and Molecular Medicine