Journal Article

Integrative pipeline for profiling DNA copy number and inferring tumor phylogeny

Eugene Urrutia, Hao Chen, Zilu Zhou, Nancy R Zhang and Yuchao Jiang

Edited by Bonnie Berger

in Bioinformatics

Volume 34, issue 12, pages 2126-2128
Published in print June 2018 | ISSN: 1367-4803
Published online February 2018 | e-ISSN: 1460-2059 | DOI:
Integrative pipeline for profiling DNA copy number and inferring tumor phylogeny

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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

Supplementary information

Supplementary data are available at Bioinformatics online.

Journal Article.  1589 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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