Title | Global copy number profiling of cancer genomes. |
Publication Type | Journal Article |
Year of Publication | 2016 |
Authors | Wang, Xuefeng, Mengjie Chen, Xiaoqing Yu, Natapol Pornputtapong, Hao Chen, Nancy R. Zhang, Scott R Powers, and Michael Krauthammer |
Journal | Bioinformatics |
Volume | 32 |
Issue | 6 |
Pagination | 926-8 |
Date Published | 2016 Mar 15 |
ISSN | 1367-4811 |
Keywords | Algorithms, DNA Copy Number Variations, Gene Frequency, Genome, Human, Humans, Neoplasms, Sequence Analysis, DNA |
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: xuefeng.wang@stonybrook.edu or michael.krauthammer@yale.eduSUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
DOI | 10.1093/bioinformatics/btv676 |
Alternate Journal | Bioinformatics |
Original Publication | Global copy number profiling of cancer genomes. |
PubMed ID | 26576652 |
PubMed Central ID | PMC4907391 |
Grant List | R01 CA082659 / CA / NCI NIH HHS / United States R01 GM105785 / GM / NIGMS NIH HHS / United States T15 LM007056 / LM / NLM NIH HHS / United States P50 CA121974 / CA / NCI NIH HHS / United States P30 CA045508 / CA / NCI NIH HHS / United States U01 CA168409 / CA / NCI NIH HHS / United States P01 CA142538 / CA / NCI NIH HHS / United States P30 CA016359 / CA / NCI NIH HHS / United States |
Project:
Software Weblinks: