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Strategies for exome and genome sequence data analysis in disease‐gene discovery projects
Author(s) -
Robinson PN,
Krawitz P,
Mundlos S
Publication year - 2011
Publication title -
clinical genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.543
H-Index - 102
eISSN - 1399-0004
pISSN - 0009-9163
DOI - 10.1111/j.1399-0004.2011.01713.x
Subject(s) - exome , exome sequencing , biology , computational biology , genetics , dna sequencing , genome , gene , whole genome sequencing , genomics , disease gene identification , mutation
Robinson PN, Krawitz P, Mundlos S. Strategies for exome and genome sequence data analysis in disease‐gene discovery projects. 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.