|DiNAMIC: a method to identify recurrent DNA copy number aberrations in tumors.
|Year of Publication
|Walter, Vonn, Andrew B. Nobel, and Fred A. Wright
|2011 Mar 01
|Algorithms, 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.
|DiNAMIC: A method to identify recurrent DNA copy number aberrations in tumors.
|PubMed Central ID
|P30 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
DiNAMIC: a method to identify recurrent DNA copy number aberrations in tumors.