Integrative pipeline for profiling DNA copy number and inferring tumor phylogeny.

TitleIntegrative pipeline for profiling DNA copy number and inferring tumor phylogeny.
Publication TypeJournal Article
Year of Publication2018
AuthorsUrrutia, Eugene, Hao Chen, Zilu Zhou, Nancy R. Zhang, and Yuchao Jiang
Date Published2018 Jun 15
KeywordsAlgorithms, DNA Copy Number Variations, Genomics, High-Throughput Nucleotide Sequencing, Humans, Models, Genetic, Models, Statistical, Neoplasms, Polymorphism, Single Nucleotide, Sequence Analysis, DNA, Software

SUMMARY: Copy number variation is an important and abundant source of variation in the human genome, which has been associated with a number of diseases, especially cancer. Massively parallel next-generation sequencing allows copy number profiling with fine resolution. Such efforts, however, have met with mixed successes, with setbacks arising partly from the lack of reliable analytical methods to meet the diverse and unique challenges arising from the myriad experimental designs and study goals in genetic studies. In cancer genomics, detection of somatic copy number changes and profiling of allele-specific copy number (ASCN) are complicated by experimental biases and artifacts as well as normal cell contamination and cancer subclone admixture. Furthermore, careful statistical modeling is warranted to reconstruct tumor phylogeny by both somatic ASCN changes and single nucleotide variants. Here we describe a flexible computational pipeline, MARATHON, which integrates multiple related statistical software for copy number profiling and downstream analyses in disease genetic studies.AVAILABILITY AND IMPLEMENTATION: MARATHON is publicly available at INFORMATION: Supplementary data are available at Bioinformatics online.

Alternate JournalBioinformatics
Original PublicationIntegrative pipeline for profiling DNA copy number and inferring tumor phylogeny.
PubMed ID29415173
PubMed Central IDPMC6248831
Grant ListP01 CA142538 / CA / NCI NIH HHS / United States
R01 HG006137 / HG / NHGRI NIH HHS / United States
T32 ES007018 / ES / NIEHS NIH HHS / United States