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Wham: Identifying Structural Variants of Biological Consequence.


ABSTRACT: Existing methods for identifying structural variants (SVs) from short read datasets are inaccurate. This complicates disease-gene identification and efforts to understand the consequences of genetic variation. In response, we have created Wham (Whole-genome Alignment Metrics) to provide a single, integrated framework for both structural variant calling and association testing, thereby bypassing many of the difficulties that currently frustrate attempts to employ SVs in association testing. Here we describe Wham, benchmark it against three other widely used SV identification tools-Lumpy, Delly and SoftSearch-and demonstrate Wham's ability to identify and associate SVs with phenotypes using data from humans, domestic pigeons, and vaccinia virus. Wham and all associated software are covered under the MIT License and can be freely downloaded from github (https://github.com/zeeev/wham), with documentation on a wiki (http://zeeev.github.io/wham/). For community support please post questions to https://www.biostars.org/.

SUBMITTER: Kronenberg ZN 

PROVIDER: S-EPMC4666669 | biostudies-other | 2015 Dec

REPOSITORIES: biostudies-other

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Wham: Identifying Structural Variants of Biological Consequence.

Kronenberg Zev N ZN   Osborne Edward J EJ   Cone Kelsey R KR   Kennedy Brett J BJ   Domyan Eric T ET   Shapiro Michael D MD   Elde Nels C NC   Yandell Mark M  

PLoS computational biology 20151201 12


Existing methods for identifying structural variants (SVs) from short read datasets are inaccurate. This complicates disease-gene identification and efforts to understand the consequences of genetic variation. In response, we have created Wham (Whole-genome Alignment Metrics) to provide a single, integrated framework for both structural variant calling and association testing, thereby bypassing many of the difficulties that currently frustrate attempts to employ SVs in association testing. Here  ...[more]

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