DiNAMIC: a method to identify recurrent DNA copy number aberrations in tumors.

TitleDiNAMIC: a method to identify recurrent DNA copy number aberrations in tumors.
Publication TypeJournal Article
Year of Publication2011
AuthorsWalter, Vonn, Andrew B. Nobel, and Fred A. Wright
Date Published2011 Mar 01
KeywordsAlgorithms, Computational Biology, DNA Copy Number Variations, DNA, Neoplasm, Humans, Neoplasms, Sequence Analysis, DNA, Software

MOTIVATION: DNA copy number gains and losses are commonly found in tumor tissue, and some of these aberrations play a role in tumor genesis and development. Although high resolution DNA copy number data can be obtained using array-based techniques, no single method is widely used to distinguish between recurrent and sporadic copy number aberrations.RESULTS: Here we introduce Discovering Copy Number Aberrations Manifested In Cancer (DiNAMIC), a novel method for assessing the statistical significance of recurrent copy number aberrations. In contrast to competing procedures, the testing procedure underlying DiNAMIC is carefully motivated, and employs a novel cyclic permutation scheme. Extensive simulation studies show that DiNAMIC controls false positive discoveries in a variety of realistic scenarios. We use DiNAMIC to analyze two publicly available tumor datasets, and our results show that DiNAMIC detects multiple loci that have biological relevance.AVAILABILITY: Source code implemented in R, as well as text files containing examples and sample datasets are available at http://www.bios.unc.edu/research/genomic_software/DiNAMIC.

Alternate JournalBioinformatics
Original PublicationDiNAMIC: A method to identify recurrent DNA copy number aberrations in tumors.
PubMed ID21183584
PubMed Central IDPMC3042182
Grant ListP30 ES010126 / ES / NIEHS NIH HHS / United States
T32 CA106209 / CA / NCI NIH HHS / United States
P01 CA142538 / CA / NCI NIH HHS / United States
P01C142538 / / PHS HHS / United States
R01 MH090936 / MH / NIMH NIH HHS / United States