Strategies for exome and genome sequence data analysis in disease-gene discovery projects

被引：63

作者：

Robinson, P. N. ^{[1
,2
,3
]}

Krawitz, P. ^{[1
,2
,3
]}

Mundlos, S. ^{[1
,2
,3
]}

机构：

[1] Charite, Inst Med Genet & Humangenet, D-13353 Berlin, Germany

[2] Charite, Berlin Brandenburg Ctr Regenerat Therapies BCRT, D-13353 Berlin, Germany

[3] Max Planck Inst Mol Genet, Berlin, Germany

来源：

CLINICAL GENETICS | 2011年 / 80卷 / 02期

关键词：

bioinformatics; disease gene; exome; genome; next-generation sequencing; HUMAN PHENOTYPE ONTOLOGY; DE-NOVO MUTATIONS; MENTAL-RETARDATION; HEARING-LOSS; SPECTRUM; MAP;

D O I：

10.1111/j.1399-0004.2011.01713.x

中图分类号：

Q3 [遗传学];

学科分类号：

071007 ; 090102 ;

摘要：

In whole-exome sequencing (WES), target capture methods are used to enrich the sequences of the coding regions of genes from fragmented total genomic DNA, followed by massively parallel, 'next-generation' sequencing of the captured fragments. Since its introduction in 2009, WES has been successfully used in several disease-gene discovery projects, but the analysis of whole-exome sequence data can be challenging. In this overview, we present a summary of the main computational strategies that have been applied to identify novel disease genes in whole-exome data, including intersect filters, the search for de novo mutations, and the application of linkage mapping or inference of identity-by-descent (IBD) in family studies.

引用

页码：127 / 132

页数：6

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