Accurate identification of significant aberrations in contaminated cancer genome

Xuchu Hou, Guoqiang Yu, Xiguo Yuan, Bai Zhang, Ie Ming Shih, Zhen Zhang, Robert Clarke, Subha Madhavan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Somatic Copy Number Alterations (CNAs) are quite common in human cancers. Identifying CNAs and Significant Copy number Aberrations (SCAs) in cancer genomes is a critical task in searching for cancer-associated genes. The advanced genomic technologies, such as SNP array technology, facilitate copy number study at a genome-wide scale with high resolution. However, in reality, due to normal tissue contamination, the observed intensity signals are actually the mixture of copy number signals contributed from both tumor cells and normal cells. This genetic heterogeneity could significantly affect the subsequent copy number analysis and SCAs detection. In order to accurately identify significant aberrations in contaminated cancer genome, we devise an approach including two major steps. We first use a statistical method, Bayesian Analysis of Copy number Mixtures (BACOM) to estimate the normal tissue contamination fraction and recover the "true" copy number profile. Then, based on the recovered profiles, we detect SCAs using Genome-wide Identification of Significant Aberrations in Cancer Genome (SAIC). We comprehensively evaluate the performance of the proposed algorithm on a large number of simulation data. The results show that the algorithm has higher detection power than peer methods including the most popular GISTIC. We then apply the method to the real copy number data of Glioblastoma Multiforme and successfully identified majority of SCAs reported by GISTIC, and some novel SCAs that contain some cancer-associated genes.

Original languageEnglish (US)
Title of host publicationProceedings 2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012
Pages74-77
Number of pages4
DOIs
StatePublished - Dec 1 2012
Event2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012 - Washington, DC, United States
Duration: Dec 2 2012Dec 4 2012

Publication series

NameProceedings - IEEE International Workshop on Genomic Signal Processing and Statistics
ISSN (Print)2150-3001
ISSN (Electronic)2150-301X

Other

Other2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012
CountryUnited States
CityWashington, DC
Period12/2/1212/4/12

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Keywords

  • copy number alterations
  • normal tissue contamination
  • significant copy number aberrations

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology (miscellaneous)
  • Computational Theory and Mathematics
  • Signal Processing
  • Biomedical Engineering

Cite this

Hou, X., Yu, G., Yuan, X., Zhang, B., Shih, I. M., Zhang, Z., Clarke, R., & Madhavan, S. (2012). Accurate identification of significant aberrations in contaminated cancer genome. In Proceedings 2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012 (pp. 74-77). [6507730] (Proceedings - IEEE International Workshop on Genomic Signal Processing and Statistics). https://doi.org/10.1109/GENSIPS.2012.6507730