Watson, CM, Crinnion, LA, Gurgel-Gianetti, J et al. (8 more authors) (2015) Rapid Detection of Rare Deleterious Variants by Next Generation Sequencing with Optional Microarray SNP Genotype Data. Human Mutation, 36 (9). pp. 823-830. ISSN 1059-7794
Abstract
Autozygosity mapping is a powerful technique for the identification of rare, autosomal recessive, disease-causing genes. The ease with which this category of disease gene can be identified has greatly increased through the availability of genome-wide SNP genotyping microarrays and subsequently of exome sequencing. Although these methods have simplified the generation of experimental data, its analysis, particularly when disparate data types must be integrated, remains time-consuming. Moreover, the huge volume of sequence variant data generated from next generation sequencing experiments opens up the possibility of using these data instead of microarray genotype data to identify disease loci. To allow these two types of data to be used in an integrated fashion, we have developed AgileVCFMapper, a program that performs both the mapping of disease loci by SNP genotyping and the analysis of potentially deleterious variants using exome sequence variant data, in a single step. This method does not require microarray SNP genotype data, although analysis with a combination of microarray and exome genotype data enables more precise delineation of disease loci, due to superior marker density and distribution. This article is protected by copyright. All rights reserved.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2015 The Authors. Human Mutation published by Wiley Periodicals, Inc. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Autozygosity Mapping; Exome; Next Generation Sequencing; Software |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Inst of Biomed & Clin Sciences (LIBACS) (Leeds) > Genetics (LIBACS) (Leeds) The University of Leeds > Faculty of Medicine and Health (Leeds) > Institute of Molecular Medicine (LIMM) (Leeds) > Section of Translational Medicine (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 30 Jul 2015 09:53 |
Last Modified: | 25 Feb 2016 12:19 |
Published Version: | http://dx.doi.org/10.1002/humu.22818 |
Status: | Published |
Publisher: | Wiley |
Identification Number: | 10.1002/humu.22818 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:88521 |