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Bioinformatics. 2011 Mar 1;27(5):678-85. doi: 10.1093/bioinformatics/btq717. Epub 2010 Dec 23.

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

Author information

1
Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA. vwalter@email.unc.edu

Abstract

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.

PMID:
21183584
PMCID:
PMC3042182
DOI:
10.1093/bioinformatics/btq717
[Indexed for MEDLINE]
Free PMC Article

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