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tstrait: a quantitative trait simulator for ancestral recombination graphs.
Tagami, Daiki; Bisschop, Gertjan; Kelleher, Jerome.
Afiliação
  • Tagami D; Department of Statistics, University of Oxford, Oxford OX1 3LB, United Kingdom.
  • Bisschop G; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom.
  • Kelleher J; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom.
Bioinformatics ; 40(6)2024 Jun 03.
Article em En | MEDLINE | ID: mdl-38796683
ABSTRACT

SUMMARY:

Ancestral recombination graphs (ARGs) encode the ensemble of correlated genealogical trees arising from recombination in a compact and efficient structure and are of fundamental importance in population and statistical genetics. Recent breakthroughs have made it possible to simulate and infer ARGs at biobank scale, and there is now intense interest in using ARG-based methods across a broad range of applications, particularly in genome-wide association studies (GWAS). Sophisticated methods exist to simulate ARGs using population genetics models, but there is currently no software to simulate quantitative traits directly from these ARGs. To apply existing quantitative trait simulators users must export genotype data, losing important information about ancestral processes and producing prohibitively large files when applied to the biobank-scale datasets currently of interest in GWAS. We present tstrait, an open-source Python library to simulate quantitative traits on ARGs, and show how this user-friendly software can quickly simulate phenotypes for biobank-scale datasets on a laptop computer. AVAILABILITY AND IMPLEMENTATION tstrait is available for download on the Python Package Index. Full documentation with examples and workflow templates is available on https//tskit.dev/tstrait/docs/, and the development version is maintained on GitHub (https//github.com/tskit-dev/tstrait).
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Recombinação Genética / Software / Estudo de Associação Genômica Ampla Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Recombinação Genética / Software / Estudo de Associação Genômica Ampla Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article