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Obelisc: an identical-by-descent mapping tool based on SNP streak

MOTIVATION: Genetic linkage analysis has made a huge contribution to the genetic mapping of Mendelian diseases. However, most previously available linkage analysis methods have limited applicability. Since parametric linkage analysis requires predefined model of inheritance with a fixed set of param...

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Autores principales: Sonehara, Kyuto, Okada, Yukinori
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8023673/
https://www.ncbi.nlm.nih.gov/pubmed/33135050
http://dx.doi.org/10.1093/bioinformatics/btaa940
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author Sonehara, Kyuto
Okada, Yukinori
author_facet Sonehara, Kyuto
Okada, Yukinori
author_sort Sonehara, Kyuto
collection PubMed
description MOTIVATION: Genetic linkage analysis has made a huge contribution to the genetic mapping of Mendelian diseases. However, most previously available linkage analysis methods have limited applicability. Since parametric linkage analysis requires predefined model of inheritance with a fixed set of parameters, it is inapplicable without fully structured pedigree information. Furthermore, the analytical results are dependent on the specification of model parameters. While non-parametric linkage analysis can avoid these problems, the runs of homozygosity (ROH) mapping, a widely used non-parametric linkage analysis method, can only deal with recessive inheritance. The implementation of non-parametric linkage analyses capable of dealing with both dominant and recessive inheritance has been required. RESULTS: We have developed the Obelisc (Observational linkage scan), a flexibly applicable user-friendly non-parametric linkage analysis tool, which also provides an intuitive visualization of the analytical results. Obelisc is based on the SNP streak approach, which does not require any predefined inheritance model with parameters. In contrast to the ROH mapping, the SNP streak approach is applicable to both dominant and recessive traits. To illustrate the performance of Obelisc, we generated a pseudo-pedigree from the publicly available BioBank Japan Project genome-wide genotype dataset (n > 180 000). By applying Obelisc to this pseudo-pedigree, we successfully identified the regions with inherited identical-by-descent haplotypes shared among the members of the pseudo-pedigree, which was validated by the population-based haplotype phasing approach. AVAILABILITY AND IMPLEMENTATION: Obelisc is feely available at https://github.com/qsonehara/Obelisc as a python package with example datasets. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-80236732021-04-13 Obelisc: an identical-by-descent mapping tool based on SNP streak Sonehara, Kyuto Okada, Yukinori Bioinformatics Discovery Note MOTIVATION: Genetic linkage analysis has made a huge contribution to the genetic mapping of Mendelian diseases. However, most previously available linkage analysis methods have limited applicability. Since parametric linkage analysis requires predefined model of inheritance with a fixed set of parameters, it is inapplicable without fully structured pedigree information. Furthermore, the analytical results are dependent on the specification of model parameters. While non-parametric linkage analysis can avoid these problems, the runs of homozygosity (ROH) mapping, a widely used non-parametric linkage analysis method, can only deal with recessive inheritance. The implementation of non-parametric linkage analyses capable of dealing with both dominant and recessive inheritance has been required. RESULTS: We have developed the Obelisc (Observational linkage scan), a flexibly applicable user-friendly non-parametric linkage analysis tool, which also provides an intuitive visualization of the analytical results. Obelisc is based on the SNP streak approach, which does not require any predefined inheritance model with parameters. In contrast to the ROH mapping, the SNP streak approach is applicable to both dominant and recessive traits. To illustrate the performance of Obelisc, we generated a pseudo-pedigree from the publicly available BioBank Japan Project genome-wide genotype dataset (n > 180 000). By applying Obelisc to this pseudo-pedigree, we successfully identified the regions with inherited identical-by-descent haplotypes shared among the members of the pseudo-pedigree, which was validated by the population-based haplotype phasing approach. AVAILABILITY AND IMPLEMENTATION: Obelisc is feely available at https://github.com/qsonehara/Obelisc as a python package with example datasets. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2020-11-02 /pmc/articles/PMC8023673/ /pubmed/33135050 http://dx.doi.org/10.1093/bioinformatics/btaa940 Text en © The Author(s) 2020. Published by Oxford University Press. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Discovery Note
Sonehara, Kyuto
Okada, Yukinori
Obelisc: an identical-by-descent mapping tool based on SNP streak
title Obelisc: an identical-by-descent mapping tool based on SNP streak
title_full Obelisc: an identical-by-descent mapping tool based on SNP streak
title_fullStr Obelisc: an identical-by-descent mapping tool based on SNP streak
title_full_unstemmed Obelisc: an identical-by-descent mapping tool based on SNP streak
title_short Obelisc: an identical-by-descent mapping tool based on SNP streak
title_sort obelisc: an identical-by-descent mapping tool based on snp streak
topic Discovery Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8023673/
https://www.ncbi.nlm.nih.gov/pubmed/33135050
http://dx.doi.org/10.1093/bioinformatics/btaa940
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