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BACOM: in silico detection of genomic deletion types and correction of normal cell contamination in copy number data
Author(s) -
Guoqiang Yu,
Bai Zhang,
G. Steven Bova,
Jianfeng Xu,
IeMing Shih,
Yue Wang
Publication year - 2011
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btr183
Subject(s) - in silico , computer science , copy number variation , computational biology , pipeline (software) , genome , copy number analysis , biology , genetics , gene , programming language
Identification of somatic DNA copy number alterations (CNAs) and significant consensus events (SCEs) in cancer genomes is a main task in discovering potential cancer-driving genes such as oncogenes and tumor suppressors. The recent development of SNP array technology has facilitated studies on copy number changes at a genome-wide scale with high resolution. However, existing copy number analysis methods are oblivious to normal cell contamination and cannot distinguish between contributions of cancerous and normal cells to the measured copy number signals. This contamination could significantly confound downstream analysis of CNAs and affect the power to detect SCEs in clinical samples.

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