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Updated: May 7, 2026

Detection of Copy Number Alterations Using Single Cell Sequencing

Detection of Copy Number Alterations Using Single Cell Sequencing

Published on: February 17, 2017

SNACS: a tool for demultiplexing single-cell DNA sequencing data.

Vanessa E Kennedy¹, Ritu Roy², Cheryl A C Peretz^2,3

¹Division of Blood and Marrow Transplantation and Cellular Therapy, Department of Medicine, Stanford University, Stanford, CA, 94304, United States.

Bioinformatics (Oxford, England)

|June 5, 2025

Summary

This summary is machine-generated.

SNACS accurately demultiplexes single-cell DNA sequencing data by combining cell-surface identifiers and genetic variations. This method significantly improves accuracy compared to existing techniques for analyzing cancer heterogeneity.

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Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

Area of Science:

Genomics
Cancer Research
Bioinformatics

Background:

Single-cell DNA sequencing (scDNA-seq) and scDAb-seq offer insights into cancer heterogeneity.
Scaling these technologies for large patient cohorts is challenging due to cost and time.
Multiplexing is a potential solution, but accurate demultiplexing for scDNA-seq is needed.

Purpose of the Study:

To develop a novel method for accurate demultiplexing of single-cell DNA sequencing data.
To enable cost-effective and time-efficient analysis of large patient cohorts using multiplexing.

Main Methods:

Introduction of SNACS (single-nucleotide polymorphism and antibody-based cell sorting).
SNACS utilizes patient-level cell-surface identifiers and natural genetic polymorphism variations.
Validation on multi-sample leukemia patient datasets with known ground truth.

Main Results:

SNACS achieved high demultiplexing accuracy, ranging from 0.948 to 0.991.
This significantly outperforms existing single-cell literature demultiplexing methods (0.552 to 0.934).

Conclusions:

SNACS provides an accurate and effective solution for demultiplexing scDNA-seq data.
The method facilitates scalable and cost-effective analysis of cancer heterogeneity through multiplexing.