This article is part of a special issue on exome sequencing.
Reducing the exome search space for Mendelian diseases using genetic linkage analysis of exome genotypes
1 Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria 3052, Australia
2 Department of Otolaryngology-Head and Neck Surgery, University of Iowa, Iowa City, Iowa 52242, USA
3 Department of Molecular Physiology and Biophysics, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA
4 Murdoch Childrens Research Institute, Royal Children's Hospital, Parkville, Victoria 3052, Australia
5 Bruce Lefroy Centre for Genetic Health Research, Murdoch Childrens Research Institute, Royal Children's Hospital, Parkville, Victoria 3052, Australia
6 Genetics Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran 19834, Iran
7 Department of Paediatrics, University of Melbourne, Royal Children's Hospital, Parkville, Victoria 3052, Australia
8 Children's Neuroscience Centre, Royal Children's Hospital, Parkville, Victoria 3052, Australia
9 Interdepartmental PhD Program in Genetics, University of Iowa, Iowa City, Iowa 52242, USA
10 Department of Mathematics and Statistics, The University of Melbourne, Parkville, Victoria 3010, Australia
Genome Biology 2011, 12:R85 doi:10.1186/gb-2011-12-9-r85Published: 14 September 2011
Many exome sequencing studies of Mendelian disorders fail to optimally exploit family information. Classical genetic linkage analysis is an effective method for eliminating a large fraction of the candidate causal variants discovered, even in small families that lack a unique linkage peak. We demonstrate that accurate genetic linkage mapping can be performed using SNP genotypes extracted from exome data, removing the need for separate array-based genotyping. We provide software to facilitate such analyses.