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

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

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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms
  • Computational Biology / methods
  • DNA Copy Number Variations*
  • DNA, Neoplasm / genetics
  • Humans
  • Neoplasms / genetics*
  • Sequence Analysis, DNA / methods*
  • Software*

Substances

  • DNA, Neoplasm