title: Cancer gene prioritization by integrative analysis of mRNA expression and DNA copy number data: a comparative review.
abstract: A variety of genome-wide profiling techniques are available to investigate 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 highlight common approaches to genomic data integration and provide a transparent benchmarking procedure to quantitatively compare method performances in cancer gene prioritization. Algorithms, data sets and benchmarking results are available at http://intcomp.r-forge.r-project.org.
authors.affiliation: Wageningen University, Laboratory of Microbiology, 6703HB Wageningen, Netherlands. leo.lahti@iki.fi
authors.forename: Leo
authors.initials: L
authors.lastname: Lahti
authors.forename: Martin
authors.initials: M
authors.lastname: Schäfer
authors.forename: Hans-Ulrich
authors.initials: HU
authors.lastname: Klein
authors.forename: Silvio
authors.initials: S
authors.lastname: Bicciato
authors.forename: Martin
authors.initials: M
authors.lastname: Dugas
mesh_terms: D000465:Algorithms; D019295:Computational Biology; D056915:DNA Copy Number Variations / Q000235:genetics*; D004273:DNA, Neoplasm / Q000235:genetics*; D005260:Female; D015972:Gene Expression Regulation, Neoplastic; D023281:Genomics / Q000379:methods; D006801:Humans; D009369:Neoplasms / Q000235:genetics*; D009857:Oncogenes; D012333:RNA, Messenger / Q000096:biosynthesis*; D012334:RNA, Neoplasm / Q000096:biosynthesis*
chemical_list: D004273:DNA, Neoplasm; D012333:RNA, Messenger; D012334:RNA, Neoplasm