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Abstract
Homozygosity mapping is a powerful method for identifying mutations in patients with recessive conditions, especially in consanguineous families or isolated populations. Historically, it has been used in conjunction with genotypes from highly polymorphic markers, such as DNA microsatellites or common SNPs. Traditional software performs rather poorly with data from Whole Exome Sequencing (WES) and Whole Genome Sequencing (WGS), which are now extensively used in medical genetics. We develop AutoMap, a tool that is both web-based or downloadable, to allow performing homozygosity mapping directly on VCF (Variant Call Format) calls from WES or WGS projects. Following a training step on WES data from 26 consanguineous families and a validation procedure on a matched cohort, our method shows higher overall performances when compared with eight existing tools. Most importantly, when tested on real cases with negative molecular diagnosis from an internal set, AutoMap detects three gene-disease and multiple variant-disease associations that were previously unrecognized, projecting clear benefits for both molecular diagnosis and research activities in medical genetics.
Homozygosity mapping is a useful tool for identifying candidate mutations in recessive conditions, however application to next generation sequencing data has been sub-optimal. Here, the authors present AutoMap, which efficiently identifies runs of homozygosity in whole exome/genome sequencing data.
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1 Institute of Molecular and Clinical Ophthalmology Basel (IOB), Basel, Switzerland (GRID:grid.508836.0); University of Basel, Department of Ophthalmology, Basel, Switzerland (GRID:grid.6612.3) (ISNI:0000 0004 1937 0642); University of Leicester, Department of Genetics and Genome Biology, Leicester, UK (GRID:grid.9918.9) (ISNI:0000 0004 1936 8411)
2 Institute of Molecular and Clinical Ophthalmology Basel (IOB), Basel, Switzerland (GRID:grid.508836.0); University of Basel, Department of Ophthalmology, Basel, Switzerland (GRID:grid.6612.3) (ISNI:0000 0004 1937 0642); University of Leicester, Department of Genetics and Genome Biology, Leicester, UK (GRID:grid.9918.9) (ISNI:0000 0004 1936 8411); Lausanne University Hospital (CHUV), Institute of Experimental Pathology, Lausanne, Switzerland (GRID:grid.8515.9) (ISNI:0000 0001 0423 4662)
3 Lausanne University Hospital (CHUV), Service of Medical Genetics, Lausanne, Switzerland (GRID:grid.8515.9) (ISNI:0000 0001 0423 4662)
4 Mashhad University of Medical Sciences, Department of Medical Genetics, Faculty of Medicine, Mashhad, Iran (GRID:grid.411583.a) (ISNI:0000 0001 2198 6209)
5 Fasa University of Sciences, Noncommunicable Diseases Research Center, Fasa, Iran (GRID:grid.411135.3) (ISNI:0000 0004 0415 3047)
6 Lisbon Academic Medical Center (CAML), Department of Medical Genetics, Hospital Santa Maria, Centro Hospitalar Universitário Lisboa Norte (CHULN), Lisbon, Portugal (GRID:grid.411265.5) (ISNI:0000 0001 2295 9747)
7 Fasa University of Sciences, Noncommunicable Diseases Research Center, Fasa, Iran (GRID:grid.411135.3) (ISNI:0000 0004 0415 3047); Shiraz University of Medical Sciences, Bioinformatics and Computational Biology Research Center, Shiraz, Iran (GRID:grid.412571.4) (ISNI:0000 0000 8819 4698)
8 Mashhad University of Medical Sciences, Department of Medical Genetics, Faculty of Medicine, Mashhad, Iran (GRID:grid.411583.a) (ISNI:0000 0001 2198 6209); University of Aberdeen, Division of Applied Medicine, Medical School, Aberdeen, UK (GRID:grid.7107.1) (ISNI:0000 0004 1936 7291)
9 Lisbon Academic Medical Center (CAML), Department of Medical Genetics, Hospital Santa Maria, Centro Hospitalar Universitário Lisboa Norte (CHULN), Lisbon, Portugal (GRID:grid.411265.5) (ISNI:0000 0001 2295 9747); Lisbon University, Medical Faculty, Lisbon, Portugal (GRID:grid.9983.b) (ISNI:0000 0001 2181 4263)
10 Instituto de Oftalmologia Dr Gama Pinto, Lisbon, Portugal (GRID:grid.9983.b)