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  Identity-by-descent filtering of exome sequence data for disease-gene identification in autosomal recessive disorders

Rodelsperger, C., Krawitz, P., Bauer, S., Hecht, J., Bigham, A. W., Bamshad, M., et al. (2011). Identity-by-descent filtering of exome sequence data for disease-gene identification in autosomal recessive disorders. Bioinformatics, 27(6), 829-36. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/21278187 http://bioinformatics.oxfordjournals.org/content/27/6/829.full.pdf.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-781E-E Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-781F-C
Genre: Journal Article

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Rodelsperger, C.1, Author              
Krawitz, P., Author
Bauer, S., Author
Hecht, J.1, Author              
Bigham, A. W., Author
Bamshad, M., Author
de Condor, B. J., Author
Schweiger, M. R.2, Author              
Robinson, P. N.1, Author              
Affiliations:
1Research Group Development & Disease (Head: Stefan Mundlos), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433557              
2Cancer Genomics (Michal-Ruth Schweiger), Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1479649              

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Free keywords: Algorithms; Computational Biology/methods; Consanguinity; Exons; *Genes, Recessive; Genetic Diseases, Inborn/*genetics; *Genome, Human; Genome-Wide Association Study/*methods; Genotype; Haplotypes; Humans; Inheritance Patterns; Markov Chains; Models, Genetic; Mutation
 Abstract: MOTIVATION: Next-generation sequencing and exome-capture technologies are currently revolutionizing the way geneticists screen for disease-causing mutations in rare Mendelian disorders. However, the identification of causal mutations is challenging due to the sheer number of variants that are identified in individual exomes. Although databases such as dbSNP or HapMap can be used to reduce the plethora of candidate genes by filtering out common variants, the remaining set of genes still remains on the order of dozens. RESULTS: Our algorithm uses a non-homogeneous hidden Markov model that employs local recombination rates to identify chromosomal regions that are identical by descent (IBD = 2) in children of consanguineous or non-consanguineous parents solely based on genotype data of siblings derived from high-throughput sequencing platforms. Using simulated and real exome sequence data, we show that our algorithm is able to reduce the search space for the causative disease gene to a fifth or a tenth of the entire exome. AVAILABILITY: An R script and an accompanying tutorial are available at http://compbio.charite.de/index.php/ibd2.html.

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 Dates: 2011
 Publication Status: Published in print
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Title: Bioinformatics
Source Genre: Journal
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Pages: - Volume / Issue: 27 (6) Sequence Number: - Start / End Page: 829 - 36 Identifier: ISSN: 1367-4811 (Electronic) 1367-4803 (Linking)