Cargando…
Linkage Disequilibrium Estimation in Low Coverage High-Throughput Sequencing Data
High-throughput sequencing methods that multiplex a large number of individuals have provided a cost-effective approach for discovering genome-wide genetic variation in large populations. These sequencing methods are increasingly being utilized in population genetic studies across a diverse range of...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Genetics Society of America
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5972415/ https://www.ncbi.nlm.nih.gov/pubmed/29588288 http://dx.doi.org/10.1534/genetics.118.300831 |
_version_ | 1783326431763234816 |
---|---|
author | Bilton, Timothy P. McEwan, John C. Clarke, Shannon M. Brauning, Rudiger van Stijn, Tracey C. Rowe, Suzanne J. Dodds, Ken G. |
author_facet | Bilton, Timothy P. McEwan, John C. Clarke, Shannon M. Brauning, Rudiger van Stijn, Tracey C. Rowe, Suzanne J. Dodds, Ken G. |
author_sort | Bilton, Timothy P. |
collection | PubMed |
description | High-throughput sequencing methods that multiplex a large number of individuals have provided a cost-effective approach for discovering genome-wide genetic variation in large populations. These sequencing methods are increasingly being utilized in population genetic studies across a diverse range of species. Two side-effects of these methods, however, are (1) sequencing errors and (2) heterozygous genotypes called as homozygous due to only one allele at a particular locus being sequenced, which occurs when the sequencing depth is insufficient. Both of these errors have a profound effect on the estimation of linkage disequilibrium (LD) and, if not taken into account, lead to inaccurate estimates. We developed a new likelihood method, GUS-LD, to estimate pairwise linkage disequilibrium using low coverage sequencing data that accounts for undercalled heterozygous genotypes and sequencing errors. Our findings show that accurate estimates were obtained using GUS-LD, whereas underestimation of LD results if no adjustment is made for the errors. |
format | Online Article Text |
id | pubmed-5972415 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Genetics Society of America |
record_format | MEDLINE/PubMed |
spelling | pubmed-59724152018-05-30 Linkage Disequilibrium Estimation in Low Coverage High-Throughput Sequencing Data Bilton, Timothy P. McEwan, John C. Clarke, Shannon M. Brauning, Rudiger van Stijn, Tracey C. Rowe, Suzanne J. Dodds, Ken G. Genetics Investigations High-throughput sequencing methods that multiplex a large number of individuals have provided a cost-effective approach for discovering genome-wide genetic variation in large populations. These sequencing methods are increasingly being utilized in population genetic studies across a diverse range of species. Two side-effects of these methods, however, are (1) sequencing errors and (2) heterozygous genotypes called as homozygous due to only one allele at a particular locus being sequenced, which occurs when the sequencing depth is insufficient. Both of these errors have a profound effect on the estimation of linkage disequilibrium (LD) and, if not taken into account, lead to inaccurate estimates. We developed a new likelihood method, GUS-LD, to estimate pairwise linkage disequilibrium using low coverage sequencing data that accounts for undercalled heterozygous genotypes and sequencing errors. Our findings show that accurate estimates were obtained using GUS-LD, whereas underestimation of LD results if no adjustment is made for the errors. Genetics Society of America 2018-06 2018-03-26 /pmc/articles/PMC5972415/ /pubmed/29588288 http://dx.doi.org/10.1534/genetics.118.300831 Text en Copyright © 2018 Bilton et al. Available freely online through the author-supported open access option. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Investigations Bilton, Timothy P. McEwan, John C. Clarke, Shannon M. Brauning, Rudiger van Stijn, Tracey C. Rowe, Suzanne J. Dodds, Ken G. Linkage Disequilibrium Estimation in Low Coverage High-Throughput Sequencing Data |
title | Linkage Disequilibrium Estimation in Low Coverage High-Throughput Sequencing Data |
title_full | Linkage Disequilibrium Estimation in Low Coverage High-Throughput Sequencing Data |
title_fullStr | Linkage Disequilibrium Estimation in Low Coverage High-Throughput Sequencing Data |
title_full_unstemmed | Linkage Disequilibrium Estimation in Low Coverage High-Throughput Sequencing Data |
title_short | Linkage Disequilibrium Estimation in Low Coverage High-Throughput Sequencing Data |
title_sort | linkage disequilibrium estimation in low coverage high-throughput sequencing data |
topic | Investigations |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5972415/ https://www.ncbi.nlm.nih.gov/pubmed/29588288 http://dx.doi.org/10.1534/genetics.118.300831 |
work_keys_str_mv | AT biltontimothyp linkagedisequilibriumestimationinlowcoveragehighthroughputsequencingdata AT mcewanjohnc linkagedisequilibriumestimationinlowcoveragehighthroughputsequencingdata AT clarkeshannonm linkagedisequilibriumestimationinlowcoveragehighthroughputsequencingdata AT brauningrudiger linkagedisequilibriumestimationinlowcoveragehighthroughputsequencingdata AT vanstijntraceyc linkagedisequilibriumestimationinlowcoveragehighthroughputsequencingdata AT rowesuzannej linkagedisequilibriumestimationinlowcoveragehighthroughputsequencingdata AT doddskeng linkagedisequilibriumestimationinlowcoveragehighthroughputsequencingdata |