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Introducing M-GCTA a Software Package to Estimate Maternal (or Paternal) Genetic Effects on Offspring Phenotypes.
Qiao, Zhen; Zheng, Jie; Helgeland, Øyvind; Vaudel, Marc; Johansson, Stefan; Njølstad, Pål R; Smith, George Davey; Warrington, Nicole M; Evans, David M.
Afiliação
  • Qiao Z; University of Queensland Diamantina Institute, University of Queensland, Brisbane, QLD, Australia.
  • Zheng J; Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK.
  • Helgeland Ø; Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK.
  • Vaudel M; KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway.
  • Johansson S; Department of Genetics and Bioinformatics, Health Data and Digitalization, Norwegian Institute of Public Health, Oslo, Norway.
  • Njølstad PR; KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway.
  • Smith GD; KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway.
  • Warrington NM; Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway.
  • Evans DM; KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway.
Behav Genet ; 50(1): 51-66, 2020 01.
Article em En | MEDLINE | ID: mdl-31493278
ABSTRACT
There is increasing interest within the genetics community in estimating the relative contribution of parental genetic effects on offspring phenotypes. Here we describe the user-friendly M-GCTA software package used to estimate the proportion of phenotypic variance explained by maternal (or alternatively paternal) and offspring genotypes on offspring phenotypes. The tool requires large studies where genome-wide genotype data are available on mother- (or alternatively father-) offspring pairs. The software includes several options for data cleaning and quality control, including the ability to detect and automatically remove cryptically related pairs of individuals. It also allows users to construct genetic relationship matrices indexing genetic similarity across the genome between parents and offspring, enabling the estimation of variance explained by maternal (or alternatively paternal) and offspring genetic effects. We evaluated the performance of the software using a range of data simulations and estimated the computing time and memory requirements. We demonstrate the use of M-GCTA on previously analyzed birth weight data from two large population based birth cohorts, the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Norwegian Mother and Child Cohort Study (MoBa). We show how genetic variation in birth weight is predominantly explained by fetal genetic rather than maternal genetic sources of variation.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Peso ao Nascer / Previsões Tipo de estudo: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Child / Female / Humans / Male Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Peso ao Nascer / Previsões Tipo de estudo: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Child / Female / Humans / Male Idioma: En Ano de publicação: 2020 Tipo de documento: Article