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Journal Article

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

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Rodelsperger,  C.
Research Group Development & Disease (Head: Stefan Mundlos), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Hecht,  J.
Research Group Development & Disease (Head: Stefan Mundlos), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Schweiger,  M. R.
Cancer Genomics (Michal-Ruth Schweiger), Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Robinson,  P. N.
Research Group Development & Disease (Head: Stefan Mundlos), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Citation

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.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0010-78B4-B
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.