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Related Experiment Video

Updated: Oct 16, 2025

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Improved SNV Discovery in Barcode-Stratified scRNA-seq Alignments.

Prashant N M¹, Hongyu Liu^1,2, Christian Dillard³

¹McCormick Genomics and Proteomics Center, School of Medicine and Health Sciences, The George Washington University, Washington, DC 20037, USA.

|October 23, 2021

Summary

Detecting single nucleotide variants (SNVs) in individual cells using single-cell RNA sequencing (scRNA-seq) reveals twice as many SNVs compared to pooled data. This cell-level approach uncovers novel variants and substitutions, enhancing our understanding of cellular heterogeneity.

Keywords:

SNP SNV SNV expression expressed SNVs mutation scRNA-seq somatic mutation

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Last Updated: Oct 16, 2025

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

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Published on: January 10, 2019

Detection of Rare Mutations in CtDNA Using Next Generation Sequencing

Detection of Rare Mutations in CtDNA Using Next Generation Sequencing

Published on: August 24, 2017

Area of Science:

Genomics
Molecular Biology
Bioinformatics

Background:

Single nucleotide variant (SNV) detection from single-cell RNA sequencing (scRNA-seq) typically uses pooled sequencing reads.
This approach may limit the comprehensive identification of SNVs present in individual cells.

Purpose of the Study:

To evaluate the information gained by performing SNV detection on individual cell scRNA-seq data.
To compare cell-level SNV detection with traditional pooled data analysis.

Main Methods:

Alignments were split by cellular barcode before variant calling for individual cell analysis.
Utilized three variant callers (GATK, Strelka2, Mutect2) and SCReadCounts for cell-level tabulation.
Reanalyzed publicly available MCF7 cell line data during anticancer treatment.

Main Results:

Variant calls on individual cell alignments identified at least a two-fold higher number of SNVs compared to pooled scRNA-seq.
These SNVs were enriched in novel variants, stop-codon, and missense substitutions.
Demonstrated the potential of cell-level variant detection.

Conclusions:

SNV detection from individual cell scRNA-seq data significantly increases variant discovery.
Highlights the need for cell-level variant detection tools to understand cellular heterogeneity and somatic mutation evolution.