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

Robinson, P. N., Krawitz, P., & Mundlos, S. (2011). Strategies for exome and genome sequence data analysis in disease-gene discovery projects. Clin Genet, 80(2), 127-32. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/21615730 http://onlinelibrary.wiley.com/doi/10.1111/j.1399-0004.2011.01713.x/abstract.

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 Creators:
Robinson, P. N.1, Author              
Krawitz, P., Author
Mundlos, S.1, Author              
Affiliations:
1Research Group Development & Disease (Head: Stefan Mundlos), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433557              

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Free keywords: Animals; Base Sequence; Chromosome Mapping/methods; Disease/*genetics; Exons/*genetics; Genetic Association Studies/*methods; Genetic Predisposition to Disease; *Genome; Homozygote; Humans; Mutation; Sequence Analysis, DNA/*methods
 Abstract: 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.

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 Dates: 2011
 Publication Status: Published in print
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Title: Clin Genet
Source Genre: Journal
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Pages: - Volume / Issue: 80 (2) Sequence Number: - Start / End Page: 127 - 32 Identifier: ISSN: 1399-0004 (Electronic) 0009-9163 (Linking)