NEXT-scASV: A Nextflow Pipeline for Allele-Specific Variants Calling from single cell RNA-seq data

Andrey Shevtsov; Andrey Buyan; Vladimir Nozdrin; Pavel Akhtyamov; Alexei Stupnikov; Georgy Meshcheryakov; Ivan V Kulakovskiy; Yulia A Medvedeva

doi:10.1093/gigascience/giag042

NEXT-scASV: A Nextflow Pipeline for Allele-Specific Variants Calling from single cell RNA-seq data

Gigascience. 2026 Apr 6:giag042. doi: 10.1093/gigascience/giag042. Online ahead of print.

Authors

Andrey Shevtsov^{1

2}, Andrey Buyan³, Vladimir Nozdrin⁴, Pavel Akhtyamov^{5

6}, Alexei Stupnikov^{1

7}, Georgy Meshcheryakov³, Ivan V Kulakovskiy^{3

7

8}, Yulia A Medvedeva^{1

9}

Affiliations

¹ Research Institute of Biotechnology, Russian Academy of Sciences.
² Bioinformatics Group, AIRI, Moscow 121170, Russia.
³ Institute of Protein Research, Russian Academy of Sciences, Pushchino, Russia.
⁴ Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, Moscow, Russia.
⁵ Moscow Center for Advanced Studies, Department of Biomedical Physics, Moscow 123592, Russia.
⁶ National Research University Higher School of Economics, 11 Pokrovksy Bulvar, Moscow 109028, Russia.
⁷ Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia.
⁸ Institute of Biochemistry and Genetics, Ufa Federal Research Centre of the Russian Academy of Sciences, Ufa, Russia.
⁹ Mohamed Bin Zayed University of Artificial Intelligence, Abu Dhabi, UAE.

PMID: 41947412
DOI: 10.1093/gigascience/giag042

Abstract

The rapid accumulation of single-cell sequencing data presents major computational challenges in reproducibility, scaling, and handling data characteristics like sparsity and technical variations, which complicate even basic analyses. The next level of complexity is the allele-specific analysis, focused on identifying differential gene expression or regulation between homologous chromosomes by estimating the allelic imbalance of read counts at individual single-nucleotide variants. Here we present NEXT-scASV, a scalable Nextflow pipeline for calling allele-specific variants (ASVs) from 5' single-cell RNA sequencing data. NEXT-scASV automates the entire process-from read alignment and quality control to variant calling and statistical evaluation of the allelic imbalance-within a containerized environment, ensuring reproducibility and ease of deployment across platforms. NEXT-scASV is able to perform de novo ASV detection from single-cell sequencing data without prior genotyping. Its modular design allows for massive parallelization, efficiently handling the scale of modern atlas-level studies. We validate NEXT-scASV on a dataset of 135,000 peripheral blood mononuclear cells (PBMCs) from 57 donors, demonstrating that it processes large-scale data efficiently, completing analysis in a week on a cluster with one node and 100 threads. Crucially, the pipeline reliably identifies ASVs even in rare cell populations (e.g., gdT GZMBhi and memory B IGHMhi cells), which remains elusive for bulk analyses. We also successfully detect allele-specific regulation of long non-coding RNAs and other lowly expressed, cell type-specific genes. Genes linked to detected ASVs show a high concordance (80%) with previously reported eQTLs. This strong validation confirms that NEXT-scASV produces biologically relevant results, making it a powerful tool for uncovering allele-specific regulation in large-scale, complex single-cell studies.

Keywords: Nextflow; allele-specific variants; computational pipeline; regulatory variants; single-cell RNA-seq.