Digit-a tool for detection and identification of genomic interchromosomal translocations

Richard Meier, Stefan Graw, Peter Beyerlein, Devin Koestler, Julian R. Molina, Jeremy Chien

Research output: Contribution to journalArticle

Abstract

Structural variations (SVs) in genomic DNA can have profound effects on the evolution of living organisms, on phenotypic variations and on disease processes. A critical step in discovering the full extent of structural variations is the development of tools to characterize these variations accurately in next generation sequencing data. Toward this goal, we developed a software pipeline named digit that implements a novel measure of mapping ambiguity to discover interchromosomal SVs from matepair and pair-end sequencing data. The workflow robustly handles the high numbers of artifacts present in mate-pair sequencing and reduces the false positive rate while maintaining sensitivity. In the simulated data set, our workflow recovered 96% of simulated SVs. It generates a self-updating library of common translocations and allows for the investigation of patient-or group-specific events, making it suitable for discovering and cataloging chromosomal translocations associated with specific groups, traits, diseases or population structures.

Original languageEnglish (US)
Pages (from-to)e72
JournalNucleic acids research
Volume45
Issue number9
DOIs
StatePublished - May 19 2017

ASJC Scopus subject areas

  • Genetics

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