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

被引:26
|
作者
Walter, Vonn [1 ,2 ]
Nobel, Andrew B. [1 ,2 ,3 ]
Wright, Fred A. [1 ,2 ]
机构
[1] Univ N Carolina, Dept Biostat, Chapel Hill, NC 27599 USA
[2] Univ N Carolina, Lineberger Comprehens Canc Ctr, Chapel Hill, NC 27599 USA
[3] Univ N Carolina, Dept Stat & Operat Res, Chapel Hill, NC 27599 USA
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
NUCLEOTIDE POLYMORPHISM ARRAYS; CIRCULAR BINARY SEGMENTATION; ALLELIC-LOSS; HUMAN GENOME; WILMS-TUMOR; CGH DATA; CANCER; REGIONS; RESOLUTION; REVEALS;
D O I
10.1093/bioinformatics/btq717
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:678 / 685
页数:8
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