Author
Listed:
- Mathieu Quinodoz
(Institute of Molecular and Clinical Ophthalmology Basel (IOB)
University of Basel
University of Leicester)
- Virginie G. Peter
(Institute of Molecular and Clinical Ophthalmology Basel (IOB)
University of Basel
University of Leicester
Lausanne University Hospital (CHUV))
- Nicola Bedoni
(Lausanne University Hospital (CHUV))
- Béryl Royer Bertrand
(Lausanne University Hospital (CHUV))
- Katarina Cisarova
(Lausanne University Hospital (CHUV))
- Arash Salmaninejad
(Mashhad University of Medical Sciences)
- Neda Sepahi
(Fasa University of Sciences)
- Raquel Rodrigues
(Lisbon Academic Medical Center (CAML))
- Mehran Piran
(Fasa University of Sciences
Shiraz University of Medical Sciences)
- Majid Mojarrad
(Mashhad University of Medical Sciences)
- Alireza Pasdar
(Mashhad University of Medical Sciences
University of Aberdeen)
- Ali Ghanbari Asad
(Fasa University of Sciences)
- Ana Berta Sousa
(Lisbon Academic Medical Center (CAML)
Lisbon University)
- Luisa Coutinho Santos
(Instituto de Oftalmologia Dr Gama Pinto)
- Andrea Superti-Furga
(Lausanne University Hospital (CHUV))
- Carlo Rivolta
(Institute of Molecular and Clinical Ophthalmology Basel (IOB)
University of Basel
University of Leicester)
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.
Suggested Citation
Mathieu Quinodoz & Virginie G. Peter & Nicola Bedoni & Béryl Royer Bertrand & Katarina Cisarova & Arash Salmaninejad & Neda Sepahi & Raquel Rodrigues & Mehran Piran & Majid Mojarrad & Alireza Pasdar &, 2021.
"AutoMap is a high performance homozygosity mapping tool using next-generation sequencing data,"
Nature Communications, Nature, vol. 12(1), pages 1-7, December.
Handle:
RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-020-20584-4
DOI: 10.1038/s41467-020-20584-4
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