Work

Methods for copy number aberration detection from single-cell DNA-sequencing data

Year: 2020

Type: article

Abstract: Copy number aberrations (CNAs), which are pathogenic copy number variations (CNVs), play an important role in the initiation and progression of cancer. Single-cell DNA-sequencing (scDNAseq) technologies produce data that is ideal for inferring CNAs. In this review, we review eight methods that have been developed for detecting CNAs in scDNAseq data, and categorize them according to the steps of a seven-step pipeline that they employ. Furthermore, we review models and methods for evolutionary analyses of CNAs from scDNAseq data and highlight advances and future research directions for computational methods for CNA detection from scDNAseq data.

Source: Genome biology

DOI: 10.1186/s13059-020-02119-8

Authors: Xian F. Mallory, Mohammadamin Edrisi, Nicholas Navin, Luay Nakhleh

Institutions: Florida State University, Rice University, The University of Texas MD Anderson Cancer Center

Language: English

Topic: Genomic variations and chromosomal abnormalities

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $4,990