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

Mohan Rakesh, Hélène Vézina, Catherine Laprise, Ellen E Freeman, Kelly M Burkett, Marie-Hélène Roy-Gagnon

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Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed

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1 · What the graph read from it

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1 citing paper in PubMed.

py_ped_sim: a flexible forward pedigree and genetic simulator for complex family pedigree analysis.BMC bioinformatics · 2025
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5 · Who and what money

Authors and funding

6 authors.

Mohan RakeshSchool of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada.

Hélène VézinaProjet BALSAC, Université du Québec à Chicoutimi, Chicoutimi, Québec, Canada.

Catherine LapriseCentre intersectoriel en santé durable, Université du Québec à Chicoutimi, Chicoutimi, Québec, Canada.

Ellen E FreemanSchool of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada.

Kelly M BurkettDepartment of Mathematics and Statistics, University of Ottawa, Ottawa, Ontario, Canada.

Marie-Hélène Roy-GagnonSchool of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada.ORCID 0000-0001-8747-0846

Funding

CIHR MOP 133560

6 · The paper itself

Abstract

summaryFounder 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.

Indexed as

Population GroupsSoftwareHaplotypesHumans

Identifiers

PMID36929931

DOI10.1093/bioinformatics/btad136

PMCPMC10049784

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