GENLIB: new function to simulate haplotype transmission in large complex genealogies

SUMMARY: Founder populations with deep genealogical data are well suited for investigating genetic variants contributing to diseases. Here, we present a major update of the genealogical analysis R package GENLIB, centered around a new function which can simulate the transmission of haplotypes from f...

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Detalles Bibliográficos
Autores principales: Rakesh, Mohan, Vézina, Hélène, Laprise, Catherine, Freeman, Ellen E, Burkett, Kelly M, Roy-Gagnon, Marie-Hélène
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Applications Note
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10049784/
https://www.ncbi.nlm.nih.gov/pubmed/36929931
http://dx.doi.org/10.1093/bioinformatics/btad136
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author Rakesh, Mohan
Vézina, Hélène
Laprise, Catherine
Freeman, Ellen E
Burkett, Kelly M
Roy-Gagnon, Marie-Hélène
author_facet Rakesh, Mohan
Vézina, Hélène
Laprise, Catherine
Freeman, Ellen E
Burkett, Kelly M
Roy-Gagnon, Marie-Hélène
author_sort Rakesh, Mohan
collection PubMed
description SUMMARY: Founder populations with deep genealogical data are well suited for investigating genetic variants contributing to diseases. Here, we present a major update of the genealogical analysis R package GENLIB, centered around a new function which can simulate the transmission of haplotypes from founders to probands along very large and complex user-specified genealogies. AVAILABILITY AND IMPLEMENTATION: The latest update of the GENLIB package (v1.1.9) contains the new gen.simuHaplo() function and is available on the CRAN repository and from https://github.com/R-GENLIB/GENLIB. Examples can be accessed at https://github.com/R-GENLIB/simuhaplo_functions.
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spelling pubmed-100497842023-03-29 GENLIB: new function to simulate haplotype transmission in large complex genealogies Rakesh, Mohan Vézina, Hélène Laprise, Catherine Freeman, Ellen E Burkett, Kelly M Roy-Gagnon, Marie-Hélène Bioinformatics Applications Note SUMMARY: Founder populations with deep genealogical data are well suited for investigating genetic variants contributing to diseases. Here, we present a major update of the genealogical analysis R package GENLIB, centered around a new function which can simulate the transmission of haplotypes from founders to probands along very large and complex user-specified genealogies. AVAILABILITY AND IMPLEMENTATION: The latest update of the GENLIB package (v1.1.9) contains the new gen.simuHaplo() function and is available on the CRAN repository and from https://github.com/R-GENLIB/GENLIB. Examples can be accessed at https://github.com/R-GENLIB/simuhaplo_functions. Oxford University Press 2023-03-17 /pmc/articles/PMC10049784/ /pubmed/36929931 http://dx.doi.org/10.1093/bioinformatics/btad136 Text en © The Author(s) 2023. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Note
Rakesh, Mohan
Vézina, Hélène
Laprise, Catherine
Freeman, Ellen E
Burkett, Kelly M
Roy-Gagnon, Marie-Hélène
GENLIB: new function to simulate haplotype transmission in large complex genealogies
title GENLIB: new function to simulate haplotype transmission in large complex genealogies
title_full GENLIB: new function to simulate haplotype transmission in large complex genealogies
title_fullStr GENLIB: new function to simulate haplotype transmission in large complex genealogies
title_full_unstemmed GENLIB: new function to simulate haplotype transmission in large complex genealogies
title_short GENLIB: new function to simulate haplotype transmission in large complex genealogies
title_sort genlib: new function to simulate haplotype transmission in large complex genealogies
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10049784/
https://www.ncbi.nlm.nih.gov/pubmed/36929931
http://dx.doi.org/10.1093/bioinformatics/btad136
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