Computer Science – Computational Engineering – Finance – and Science
Scientific paper
2011-11-20
Computer Science
Computational Engineering, Finance, and Science
PDF file including supplementary material. 9 pages. Preprint
Scientific paper
10.1093/bib/bbs005
A variety of genome-wide profiling techniques are available to probe complementary aspects of genome structure and function. Integrative analysis of heterogeneous data sources can reveal higher-level interactions that cannot be detected based on individual observations. A standard integration task in cancer studies is to identify altered genomic regions that induce changes in the expression of the associated genes based on joint analysis of genome-wide gene expression and copy number profiling measurements. In this review, we provide a comparison among various modeling procedures for integrating genome-wide profiling data of gene copy number and transcriptional alterations and highlight common approaches to genomic data integration. A transparent benchmarking procedure is introduced to quantitatively compare the cancer gene prioritization performance of the alternative methods. The benchmarking algorithms and data sets are available at http://intcomp.r-forge.r-project.org
Bicciato Silvio
Dugas Martin
Klein Hans-Ulrich
Lahti Leo
Schäfer Martin
No associations
LandOfFree
Cancer gene prioritization by integrative analysis of mRNA expression and DNA copy number data: a comparative review does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Cancer gene prioritization by integrative analysis of mRNA expression and DNA copy number data: a comparative review, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Cancer gene prioritization by integrative analysis of mRNA expression and DNA copy number data: a comparative review will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-130220