Work

Global copy number profiling of cancer genomes

Year: 2015

Type: article

Abstract: UNLABELLED: In this article, we introduce a robust and efficient strategy for deriving global and allele-specific copy number alternations (CNA) from cancer whole exome sequencing data based on Log R ratios and B-allele frequencies. Applying the approach to the analysis of over 200 skin cancer samples, we demonstrate its utility for discovering distinct CNA events and for deriving ancillary information such as tumor purity. AVAILABILITY AND IMPLEMENTATION: https://github.com/xfwang/CLOSE CONTACT: [email protected] or [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Source: Bioinformatics

DOI: 10.1093/bioinformatics/btv676

Authors: Xuefeng Wang, Mengjie Chen, Xiaoqing Yu, Natapol Pornputtapong, Hao Chen, Nancy R. Zhang, R. Scott Powers, Michael Krauthammer

Institutions: Yale University, Stony Brook University, University of North Carolina at Chapel Hill, University of California, Davis, University of Pennsylvania

Language: English

Topic: Cancer Genomics and Diagnostics

Subfield: Cancer Research

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: green

Funders: Yale University, Academic Swiss Caucasus Net, National Institutes of Health, National Cancer Institute, National Institute of General Medical Sciences, U.S. National Library of Medicine

Awards: G1755495520, G2084079019, G2868962275, G3276807266, G4462060839, Statistical Methods for Cancer Clinical Trials, 1/2: Partnership to study racial/ethnic differences in GI cancer biology, COMPUTATIONAL AND FUNCTIONAL APPROACHES TO VALIDATING CANCER GENOME TARGETS, G633930570, G666505512, G736634319, G9000070285, Biomedical Informatics and Data Science Training at Yale, G9000145222, G9000207646, Yale SPORE in Skin Cancer, CSHL Cancer Center Support Grant

OpenAlex ID: W2286981607

FWCI: 0.331

Cites: 8

Cited by: 4

Related to: 10