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Published on: October 18, 2013
Somatic variant detection in normal tissues from single-cell sequencing data
Biorxiv : the Preprint Server for Biology
|June 22, 2026
Summary
This study shows that single-cell sequencing can reliably detect rare somatic mutations in normal cells using computational tools like Monopogen. Single-nucleus ATAC-seq data proved particularly effective for variant calling and understanding cellular evolution.
Area of Science:
- Genomics
- Computational Biology
- Molecular Biology
Background:
- Single-cell sequencing (SCS) is vital for identifying somatic variants in individual cells, aiding phylogenetic analysis of cellular populations.
- Detecting somatic variants in normal tissues using SCS is challenging due to their rarity, unlike in tumor tissues.
- Evaluating the feasibility of somatic variant calling from single-nucleus RNA-seq (snRNA-seq) and single-nucleus ATAC-seq (snATAC-seq) is crucial.
Purpose of the Study:
- To assess the capability of snRNA-seq and snATAC-seq data for somatic variant calling.
- To compare the performance of computational tools Monopogen and SComatic for single-cell somatic variant detection.
- To establish the feasibility of reliable single-cell somatic mutation calling in normal tissues.
Main Methods:
- Profiling a cell-line mix of six HapMap samples using 10x Genomics 5' snRNA-seq and snATAC-seq.
- Utilizing PacBio long-read whole genome sequencing (WGS) data from individual cell lines as ground truth.
- Applying computational tools Monopogen and SComatic for somatic variant calling and evaluating other methods (DeepVariant, Cellsnp-lite, Mutect2).
Main Results:
- Monopogen achieved high SNV detection accuracies (93.30% in snRNA-seq, 99.64% in snATAC-seq), outperforming SComatic.
- Monopogen detected somatic SNVs at low cellular fractions (as low as 0.5%) and assigned variants to cells of origin with >80% accuracy.
- snATAC-seq demonstrated broader genomic coverage and detected more variants compared to snRNA-seq.
Conclusions:
- Single-cell somatic mutation calling is feasible and reliable using snRNA-seq and snATAC-seq data.
- Monopogen is a highly accurate tool for single-cell somatic variant calling, especially with snATAC-seq data.
- This approach facilitates studies on clonal evolution and cell-type-specific mutagenesis in normal tissues.
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