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Characterizing linkage disequilibrium and evaluating imputation power of human genomic insertion-deletion polymorphisms

BACKGROUND: Indels are an important cause of human variation and central to the study of human disease. The 1000 Genomes Project Low-Coverage Pilot identified over 1.3 million indels shorter than 50 bp, of which over 890 were identified as potentially disruptive variants. Yet, despite their ubiquity...

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Autores principales: Lu, James T, Wang, Yi, Gibbs, Richard A, Yu, Fuli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3334570/
https://www.ncbi.nlm.nih.gov/pubmed/22377349
http://dx.doi.org/10.1186/gb-2012-13-2-r15
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author Lu, James T
Wang, Yi
Gibbs, Richard A
Yu, Fuli
author_facet Lu, James T
Wang, Yi
Gibbs, Richard A
Yu, Fuli
author_sort Lu, James T
collection PubMed
description BACKGROUND: Indels are an important cause of human variation and central to the study of human disease. The 1000 Genomes Project Low-Coverage Pilot identified over 1.3 million indels shorter than 50 bp, of which over 890 were identified as potentially disruptive variants. Yet, despite their ubiquity, the local genomic characteristics of indels remain unexplored. RESULTS: Herein we describe population- and minor allele frequency-based differences in linkage disequilibrium and imputation characteristics for indels included in the 1000 Genomes Project Low-Coverage Pilot for the CEU, YRI and CHB+JPT populations. Common indels were well tagged by nearby SNPs in all studied populations, and were also tagged at a similar rate to common SNPs. Both neutral and functionally deleterious common indels were imputed with greater than 95% concordance from HapMap Phase 3 and OMNI SNP sites. Further, 38 to 56% of low frequency indels were tagged by low frequency SNPs. We were able to impute heterozygous low frequency indels with over 50% concordance. Lastly, our analysis also revealed evidence of ascertainment bias. This bias prevents us from extending the applicability of our results to highly polymorphic indels that could not be identified in the Low-Coverage Pilot. CONCLUSIONS: Although further scope exists to improve the imputation of low frequency indels, our study demonstrates that there are already ample opportunities to retrospectively impute indels for prior genome-wide association studies and to incorporate indel imputation into future case/control studies.
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spelling pubmed-33345702012-04-25 Characterizing linkage disequilibrium and evaluating imputation power of human genomic insertion-deletion polymorphisms Lu, James T Wang, Yi Gibbs, Richard A Yu, Fuli Genome Biol Research BACKGROUND: Indels are an important cause of human variation and central to the study of human disease. The 1000 Genomes Project Low-Coverage Pilot identified over 1.3 million indels shorter than 50 bp, of which over 890 were identified as potentially disruptive variants. Yet, despite their ubiquity, the local genomic characteristics of indels remain unexplored. RESULTS: Herein we describe population- and minor allele frequency-based differences in linkage disequilibrium and imputation characteristics for indels included in the 1000 Genomes Project Low-Coverage Pilot for the CEU, YRI and CHB+JPT populations. Common indels were well tagged by nearby SNPs in all studied populations, and were also tagged at a similar rate to common SNPs. Both neutral and functionally deleterious common indels were imputed with greater than 95% concordance from HapMap Phase 3 and OMNI SNP sites. Further, 38 to 56% of low frequency indels were tagged by low frequency SNPs. We were able to impute heterozygous low frequency indels with over 50% concordance. Lastly, our analysis also revealed evidence of ascertainment bias. This bias prevents us from extending the applicability of our results to highly polymorphic indels that could not be identified in the Low-Coverage Pilot. CONCLUSIONS: Although further scope exists to improve the imputation of low frequency indels, our study demonstrates that there are already ample opportunities to retrospectively impute indels for prior genome-wide association studies and to incorporate indel imputation into future case/control studies. BioMed Central 2012 2012-02-29 /pmc/articles/PMC3334570/ /pubmed/22377349 http://dx.doi.org/10.1186/gb-2012-13-2-r15 Text en Copyright ©2012 Lu et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Lu, James T
Wang, Yi
Gibbs, Richard A
Yu, Fuli
Characterizing linkage disequilibrium and evaluating imputation power of human genomic insertion-deletion polymorphisms
title Characterizing linkage disequilibrium and evaluating imputation power of human genomic insertion-deletion polymorphisms
title_full Characterizing linkage disequilibrium and evaluating imputation power of human genomic insertion-deletion polymorphisms
title_fullStr Characterizing linkage disequilibrium and evaluating imputation power of human genomic insertion-deletion polymorphisms
title_full_unstemmed Characterizing linkage disequilibrium and evaluating imputation power of human genomic insertion-deletion polymorphisms
title_short Characterizing linkage disequilibrium and evaluating imputation power of human genomic insertion-deletion polymorphisms
title_sort characterizing linkage disequilibrium and evaluating imputation power of human genomic insertion-deletion polymorphisms
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3334570/
https://www.ncbi.nlm.nih.gov/pubmed/22377349
http://dx.doi.org/10.1186/gb-2012-13-2-r15
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