SVA: software for annotating and visualizing sequenced human genomes

被引：50

作者：

Ge, Dongliang ^{[1
,2
]}

Ruzzo, Elizabeth K. ^{[1
]}

Shianna, Kevin V. ^{[1
]}

He, Min ^{[1
]}

Pelak, Kimberly ^{[1
]}

Heinzen, Erin L. ^{[1
]}

Need, Anna C. ^{[1
]}

Cirulli, Elizabeth T. ^{[1
]}

Maia, Jessica M. ^{[1
]}

Dickson, Samuel P. ^{[1
]}

Zhu, Mingfu ^{[1
]}

Singh, Abanish ^{[1
]}

Allen, Andrew S. ^{[2
]}

Goldstein, David B. ^{[1
]}

机构：

[1] Duke Univ Sch Med, Ctr Human Genome Variat, Durham, NC 27708 USA

[2] Duke Univ Sch Med, Dept Biostat & Bioinformat, Durham, NC 27708 USA

来源：

BIOINFORMATICS | 2011年 / 27卷 / 14期

基金：

比尔及梅琳达.盖茨基金会;

关键词：

STRUCTURAL VARIATION; ASSOCIATION; ALIGNMENT; MAP;

D O I：

10.1093/bioinformatics/btr317

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Here we present Sequence Variant Analyzer (SVA), a software tool that assigns a predicted biological function to variants identified in next-generation sequencing studies and provides a browser to visualize the variants in their genomic contexts. SVA also provides for flexible interaction with software implementing variant association tests allowing users to consider both the bioinformatic annotation of identified variants and the strength of their associations with studied traits. We illustrate the annotation features of SVA using two simple examples of sequenced genomes that harbor Mendelian mutations.

引用

页码：1998 / 2000

页数：3

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