A simple and efficient algorithm for genome‐wide homozygosity analysis in disease

Abstract Here we propose a simple statistical algorithm for rapidly scoring loci associated with disease or traits due to recessive mutations or deletions using genome‐wide single nucleotide polymorphism genotyping case–control data in unrelated individuals. This algorithm identifies loci by definin...

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Main Authors: Wei Liu, Jinhui Ding, Jesse Raphael Gibbs, Sue Jane Wang, John Hardy, Andrew Singleton
Format: Article
Language:English
Published: Springer Nature 2009-09-01
Series:Molecular Systems Biology
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Online Access:https://doi.org/10.1038/msb.2009.53
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author Wei Liu
Jinhui Ding
Jesse Raphael Gibbs
Sue Jane Wang
John Hardy
Andrew Singleton
author_facet Wei Liu
Jinhui Ding
Jesse Raphael Gibbs
Sue Jane Wang
John Hardy
Andrew Singleton
author_sort Wei Liu
collection DOAJ
description Abstract Here we propose a simple statistical algorithm for rapidly scoring loci associated with disease or traits due to recessive mutations or deletions using genome‐wide single nucleotide polymorphism genotyping case–control data in unrelated individuals. This algorithm identifies loci by defining homozygous segments of the genome present at significantly different frequencies between cases and controls. We found that false positive loci could be effectively removed from the output of this procedure by applying different physical size thresholds for the homozygous segments. This procedure is then conducted iteratively using random sub‐datasets until the number of selected loci converges. We demonstrate this method in a publicly available data set for Alzheimer's disease and identify 26 candidate risk loci in the 22 autosomes. In this data set, these loci can explain 75% of the genetic risk variability of the disease.
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spelling doaj-art-5db228bb56624e238b2e949d2526c93e2025-08-24T11:59:19ZengSpringer NatureMolecular Systems Biology1744-42922009-09-01511610.1038/msb.2009.53A simple and efficient algorithm for genome‐wide homozygosity analysis in diseaseWei Liu0Jinhui Ding1Jesse Raphael Gibbs2Sue Jane Wang3John Hardy4Andrew Singleton5Laboratory of Neurogenetics, NIA, Porter Neuroscience Building, NIH Main CampusLaboratory of Neurogenetics, NIA, Porter Neuroscience Building, NIH Main CampusLaboratory of Neurogenetics, NIA, Porter Neuroscience Building, NIH Main CampusOffice of Biostatistics, OTS, Center for Drug Evaluation and Research, US Food and Drug AdministrationDepartment of Molecular Neuroscience and Reta Lila Weston Laboratories, Institute of Neurology, University College LondonLaboratory of Neurogenetics, NIA, Porter Neuroscience Building, NIH Main CampusAbstract Here we propose a simple statistical algorithm for rapidly scoring loci associated with disease or traits due to recessive mutations or deletions using genome‐wide single nucleotide polymorphism genotyping case–control data in unrelated individuals. This algorithm identifies loci by defining homozygous segments of the genome present at significantly different frequencies between cases and controls. We found that false positive loci could be effectively removed from the output of this procedure by applying different physical size thresholds for the homozygous segments. This procedure is then conducted iteratively using random sub‐datasets until the number of selected loci converges. We demonstrate this method in a publicly available data set for Alzheimer's disease and identify 26 candidate risk loci in the 22 autosomes. In this data set, these loci can explain 75% of the genetic risk variability of the disease.https://doi.org/10.1038/msb.2009.53disease networkhomozygous segmentsrisk locistatistical algorithmwhole‐genome screening
spellingShingle Wei Liu
Jinhui Ding
Jesse Raphael Gibbs
Sue Jane Wang
John Hardy
Andrew Singleton
A simple and efficient algorithm for genome‐wide homozygosity analysis in disease
Molecular Systems Biology
disease network
homozygous segments
risk loci
statistical algorithm
whole‐genome screening
title A simple and efficient algorithm for genome‐wide homozygosity analysis in disease
title_full A simple and efficient algorithm for genome‐wide homozygosity analysis in disease
title_fullStr A simple and efficient algorithm for genome‐wide homozygosity analysis in disease
title_full_unstemmed A simple and efficient algorithm for genome‐wide homozygosity analysis in disease
title_short A simple and efficient algorithm for genome‐wide homozygosity analysis in disease
title_sort simple and efficient algorithm for genome wide homozygosity analysis in disease
topic disease network
homozygous segments
risk loci
statistical algorithm
whole‐genome screening
url https://doi.org/10.1038/msb.2009.53
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