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Brief Bioinform. 2012 May;13(3):305-16. doi: 10.1093/bib/bbr056. Epub 2011 Sep 23.

Lessons from a decade of integrating cancer copy number alterations with gene expression profiles.

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  • 1Department of Biostatistics and Computational Biology, CLS-11075, Dana-Farber Cancer Institute, Harvard School of Public Health, CLS-11075 3 Blackfan Circle, Boston, MA 02115, USA.


Over the last decade, multiple functional genomic datasets studying chromosomal aberrations and their downstream effects on gene expression have accumulated for several cancer types. A vast majority of them are in the form of paired gene expression profiles and somatic copy number alterations (CNA) information on the same patients identified using microarray platforms. In response, many algorithms and software packages are available for integrating these paired data. Surprisingly, there has been no serious attempt to review the currently available methodologies or the novel insights brought using them. In this work, we discuss the quantitative relationships observed between CNA and gene expression in multiple cancer types and biological milestones achieved using the available methodologies. We discuss the conceptual evolution of both, the step-wise and the joint data integration methodologies over the last decade. We conclude by providing suggestions for building efficient data integration methodologies and asking further biological questions.

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