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Detection of identity by descent using next-generation whole genome sequencing data
BACKGROUND: Identity by descent (IBD) has played a fundamental role in the discovery of genetic loci underlying human diseases. Both pedigree-based and population-based linkage analyses rely on estimating recent IBD, and evidence of ancient IBD can be used to detect population structure in genetic a...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3403908/ https://www.ncbi.nlm.nih.gov/pubmed/22672699 http://dx.doi.org/10.1186/1471-2105-13-121 |
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author | Su, Shu-Yi Kasberger, Jay Baranzini, Sergio Byerley, William Liao, Wilson Oksenberg, Jorge Sherr, Elliott Jorgenson, Eric |
author_facet | Su, Shu-Yi Kasberger, Jay Baranzini, Sergio Byerley, William Liao, Wilson Oksenberg, Jorge Sherr, Elliott Jorgenson, Eric |
author_sort | Su, Shu-Yi |
collection | PubMed |
description | BACKGROUND: Identity by descent (IBD) has played a fundamental role in the discovery of genetic loci underlying human diseases. Both pedigree-based and population-based linkage analyses rely on estimating recent IBD, and evidence of ancient IBD can be used to detect population structure in genetic association studies. Various methods for detecting IBD, including those implemented in the soft- ware programs fastIBD and GERMLINE, have been developed in the past several years using population genotype data from microarray platforms. Now, next-generation DNA sequencing data is becoming increasingly available, enabling the comprehensive analysis of genomes, in- cluding identifying rare variants. These sequencing data may provide an opportunity to detect IBD with higher resolution than previously possible, potentially enabling the detection of disease causing loci that were previously undetectable with sparser genetic data. RESULTS: Here, we investigate how different levels of variant coverage in sequencing and microarray genotype data influences the resolution at which IBD can be detected. This includes microarray genotype data from the WTCCC study, denser genotype data from the HapMap Project, low coverage sequencing data from the 1000 Genomes Project, and deep coverage complete genome data from our own projects. With high power (78%), we can detect segments of length 0.4 cM or larger using fastIBD and GERMLINE in sequencing data. This compares to similar power to detect segments of length 1.0 cM or higher with microarray genotype data. We find that GERMLINE has slightly higher power than fastIBD for detecting IBD segments using sequencing data, but also has a much higher false positive rate. CONCLUSION: We further quantify the effect of variant density, conditional on genetic map length, on the power to resolve IBD segments. These investigations into IBD resolution may help guide the design of future next generation sequencing studies that utilize IBD, including family-based association studies, association studies in admixed populations, and homozygosity mapping studies. |
format | Online Article Text |
id | pubmed-3403908 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-34039082012-07-25 Detection of identity by descent using next-generation whole genome sequencing data Su, Shu-Yi Kasberger, Jay Baranzini, Sergio Byerley, William Liao, Wilson Oksenberg, Jorge Sherr, Elliott Jorgenson, Eric BMC Bioinformatics Research Article BACKGROUND: Identity by descent (IBD) has played a fundamental role in the discovery of genetic loci underlying human diseases. Both pedigree-based and population-based linkage analyses rely on estimating recent IBD, and evidence of ancient IBD can be used to detect population structure in genetic association studies. Various methods for detecting IBD, including those implemented in the soft- ware programs fastIBD and GERMLINE, have been developed in the past several years using population genotype data from microarray platforms. Now, next-generation DNA sequencing data is becoming increasingly available, enabling the comprehensive analysis of genomes, in- cluding identifying rare variants. These sequencing data may provide an opportunity to detect IBD with higher resolution than previously possible, potentially enabling the detection of disease causing loci that were previously undetectable with sparser genetic data. RESULTS: Here, we investigate how different levels of variant coverage in sequencing and microarray genotype data influences the resolution at which IBD can be detected. This includes microarray genotype data from the WTCCC study, denser genotype data from the HapMap Project, low coverage sequencing data from the 1000 Genomes Project, and deep coverage complete genome data from our own projects. With high power (78%), we can detect segments of length 0.4 cM or larger using fastIBD and GERMLINE in sequencing data. This compares to similar power to detect segments of length 1.0 cM or higher with microarray genotype data. We find that GERMLINE has slightly higher power than fastIBD for detecting IBD segments using sequencing data, but also has a much higher false positive rate. CONCLUSION: We further quantify the effect of variant density, conditional on genetic map length, on the power to resolve IBD segments. These investigations into IBD resolution may help guide the design of future next generation sequencing studies that utilize IBD, including family-based association studies, association studies in admixed populations, and homozygosity mapping studies. BioMed Central 2012-06-06 /pmc/articles/PMC3403908/ /pubmed/22672699 http://dx.doi.org/10.1186/1471-2105-13-121 Text en Copyright ©2012 Su 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 Article Su, Shu-Yi Kasberger, Jay Baranzini, Sergio Byerley, William Liao, Wilson Oksenberg, Jorge Sherr, Elliott Jorgenson, Eric Detection of identity by descent using next-generation whole genome sequencing data |
title | Detection of identity by descent using next-generation whole genome sequencing data |
title_full | Detection of identity by descent using next-generation whole genome sequencing data |
title_fullStr | Detection of identity by descent using next-generation whole genome sequencing data |
title_full_unstemmed | Detection of identity by descent using next-generation whole genome sequencing data |
title_short | Detection of identity by descent using next-generation whole genome sequencing data |
title_sort | detection of identity by descent using next-generation whole genome sequencing data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3403908/ https://www.ncbi.nlm.nih.gov/pubmed/22672699 http://dx.doi.org/10.1186/1471-2105-13-121 |
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