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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
Published on: June 23, 2012
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NEXT-scASV: a Nextflow pipeline for allele-specific variant calling from single-cell RNA-seq data.
Andrey Shevtsov1,2, Andrey Buyan3, Vladimir Nozdrin4
1Research Institute of Biotechnology, Russian Academy of Sciences, Moscow117312 Vavilova Street 7 Russia.
Gigascience
|April 8, 2026
Summary
NEXT-scASV is a new pipeline for allele-specific variant (ASV) calling in single-cell RNA sequencing data. It efficiently handles large datasets and identifies allele-specific gene regulation, even in rare cell types.
Area of Science:
- Genomics
- Computational Biology
- Molecular Biology
Background:
- Single-cell RNA sequencing (scRNA-seq) generates vast datasets with computational challenges like scalability and reproducibility.
- Allele-specific analysis in scRNA-seq aims to detect differential gene expression between homologous chromosomes by assessing allelic imbalance at single-nucleotide variants.
Purpose of the Study:
- To introduce NEXT-scASV, a scalable Nextflow pipeline for automated allele-specific variant (ASV) calling from 5' scRNA-seq data.
- To enable de novo ASV detection without prior genotyping, facilitating large-scale allele-specific expression studies.
Main Methods:
- Developed a containerized Nextflow pipeline (NEXT-scASV) for end-to-end processing: read alignment, quality control, ASV calling, and allelic imbalance statistical evaluation.
- Implemented a modular design for massive parallelization to handle atlas-level scRNA-seq datasets.
- Validated the pipeline on 135,000 peripheral blood mononuclear cells (PBMCs) from 57 donors.
Main Results:
- NEXT-scASV processed large-scale data efficiently, completing analysis in one week on a single cluster node with 100 threads.
- Successfully identified ASVs in rare cell populations (gdT GZMBhi, memory B IGHMhi cells) and detected allele-specific regulation in long non-coding RNAs and other low-expression genes.
- Detected ASVs showed 80% concordance with previously reported expression quantitative trait loci (eQTLs), confirming biological relevance.
Conclusions:
- NEXT-scASV provides a reproducible, scalable, and automated solution for allele-specific variant calling in scRNA-seq data.
- The pipeline reliably uncovers allele-specific gene regulation, including in challenging rare cell types and lowly expressed genes.
- NEXT-scASV is a powerful tool for advancing large-scale, complex single-cell studies by revealing biologically relevant allele-specific insights.
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