SCCNV: a software tool for identifying copy number variation from single-cell whole-genome sequencing

Author:

Dong Xiao,Zhang Lei,Hao Xiaoxiao,Wang Tao,Vijg Jan

Abstract

AbstractBackgroundIdentification of de novo mutations from cell populations requires single-cell whole-genome sequencing (SCWGS). Although many experimental protocols of SCWGS have been developed, few computational tools are available for downstream analysis of different types of somatic mutations, including copy number variation (CNV).ResultsWe developed SCCNV, a software tool for detecting CNVs from whole genome-amplified single cells. SCCNV is a read-depth based approach with adjustment for the whole-genome amplification bias.ConclusionsWe demonstrate its performance by analyzing data collected from most of the single-cell amplification methods, including DOP-PCR, MDA, MALBAC and LIANTI. SCCNV is freely available at https://github.com/biosinodx/SCCNV.

Publisher

Cold Spring Harbor Laboratory

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Copy number variation detection using single cell sequencing data;Proceedings of the 12th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics;2021-08

2. SCCNV: A Software Tool for Identifying Copy Number Variation From Single-Cell Whole-Genome Sequencing;Frontiers in Genetics;2020-11-16

3. Characterizing allele- and haplotype-specific copy numbers in single cells with CHISEL;Nature Biotechnology;2020-09-02

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