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

Area of Science:

• Genomics
• Cancer Research
• Bioinformatics

Background:

• DNA copy number aberrations (gains and losses) are frequent in tumors and implicated in cancer development.
• Existing high-resolution array-based methods struggle to differentiate recurrent from sporadic copy number aberrations.

Purpose of the Study:

• To introduce a novel computational method, Discovering Copy Number Aberrations Manifested In Cancer (DiNAMIC), for statistically assessing recurrent copy number aberrations.
• To provide a robust tool for analyzing genomic data in cancer research.

Main Methods:

• DiNAMIC employs a novel cyclic permutation scheme for its statistical testing procedure.
• The method is designed to be carefully motivated and rigorously tested.

Main Results:

• Extensive simulations demonstrate DiNAMIC's ability to control false positive discoveries across various realistic scenarios.
• Application of DiNAMIC to two public tumor datasets identified multiple loci with significant biological relevance.

Conclusions:

• DiNAMIC offers a statistically sound and effective approach for identifying recurrent copy number aberrations in cancer.
• The method aids in discovering biologically significant genomic alterations from tumor data.