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

TITLE=SCCNV: A Software Tool for Identifying Copy Number Variation From Single-Cell Whole-Genome Sequencing

JOURNAL=Frontiers in Genetics

VOLUME=11

YEAR=2020

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2020.505441

DOI=10.3389/fgene.2020.505441

ISSN=1664-8021

ABSTRACT=<p>Identification of <italic>de novo</italic> copy number variations (CNVs) across the genome in single cells requires single-cell whole-genome amplification (WGA) and sequencing. Although many experimental protocols of amplification methods have been developed, all suffer from uneven distribution of read depth across the genome after sequencing of DNA amplicons, which constrains the usage of conventional CNV calling methodologies. Here, we present SCCNV, a software tool for detecting CNVs from whole genome-amplified single cells. SCCNV is a read-depth based approach with adjustment for the WGA bias. We demonstrate its performance by analyzing data obtained with most of the single-cell amplification methods that have been employed for CNV analysis, including DOP-PCR, MDA, MALBAC, and LIANTI. SCCNV is freely available at <ext-link ext-link-type="uri" xlink:href="https://github.com/biosinodx/SCCNV" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/biosinodx/SCCNV</ext-link>.</p>