SCExecute: custom cell barcode-stratified analyses of scRNA-seq data

Authors

Nathan Edwards, Department of Biochemistry and Molecular & Cellular Biology, Georgetown University, Washington, DC, 20057, USA.
Christian Dillard, McCormick Genomics and Proteomics Center, School of Medicine and Health Sciences, The George Washington University, Washington, DC, 20037, USA.
Prashant N M, McCormick Genomics and Proteomics Center, School of Medicine and Health Sciences, The George Washington University, Washington, DC, 20037, USA.
Hongyu Liu, McCormick Genomics and Proteomics Center, School of Medicine and Health Sciences, The George Washington University, Washington, DC, 20037, USA.
Mia Yang, McCormick Genomics and Proteomics Center, School of Medicine and Health Sciences, The George Washington University, Washington, DC, 20037, USA.
Evgenia Ulianova, McCormick Genomics and Proteomics Center, School of Medicine and Health Sciences, The George Washington University, Washington, DC, 20037, USA.
Anelia Horvath, McCormick Genomics and Proteomics Center, School of Medicine and Health Sciences, The George Washington University, Washington, DC, 20037, USA.

Document Type

Journal Article

Publication Date

11-30-2022

Journal

Bioinformatics (Oxford, England)

DOI

10.1093/bioinformatics/btac768

Abstract

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.

APA Citation

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.
https://hsrc.himmelfarb.gwu.edu/gwhpubs/1880

Department

Biochemistry and Molecular Medicine