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Introducing M-GCTA a Software Package to Estimate Maternal (or Paternal) Genetic Effects on Offspring Phenotypes.
Behavior Genetics ( IF 2.6 ) Pub Date : 2019-09-06 , DOI: 10.1007/s10519-019-09969-4
Zhen Qiao 1 , Jie Zheng 2, 3 , Øyvind Helgeland 4, 5 , Marc Vaudel 4 , Stefan Johansson 4, 6 , Pål R Njølstad 4, 7 , George Davey Smith 2, 3 , Nicole M Warrington 1, 8 , David M Evans 1, 2, 3
Affiliation  

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.

中文翻译:

引入 M-GCTA 一个软件包来估计母系(或父系)遗传对后代表型的影响。

遗传学界越来越关注估计亲本遗传效应对后代表型的相对贡献。在这里,我们描述了用户友好的 M-GCTA 软件包,用于估计母体(或父系)和后代基因型对后代表型解释的表型变异比例。该工具需要进行大型研究,其中可以在母亲(或父亲)后代对上获得全基因组基因型数据。该软件包括用于数据清理和质量控制的多个选项,包括检测和自动删除隐秘相关的个体对的能力。它还允许用户构建遗传关系矩阵,索引父母和后代之间基因组的遗传相似性,能够估计由母亲(或父亲)和后代遗传效应解释的方差。我们使用一系列数据模拟评估了软件的性能,并估计了计算时间和内存需求。我们展示了 M-GCTA 对先前分析的来自两个大型人口出生队列的出生体重数据的使用,即雅芳父母和儿童纵向研究 (ALSPAC) 和挪威母婴队列研究 (MoBa)。我们展示了出生体重的遗传变异如何主要由胎儿遗传而不是母体遗传变异来源来解释。我们展示了 M-GCTA 对先前分析的来自两个大型人口出生队列的出生体重数据的使用,即雅芳父母和儿童纵向研究 (ALSPAC) 和挪威母婴队列研究 (MoBa)。我们展示了出生体重的遗传变异如何主要由胎儿遗传而不是母体遗传变异来源来解释。我们展示了 M-GCTA 对先前分析的来自两个大型人口出生队列的出生体重数据的使用,即雅芳父母和儿童纵向研究 (ALSPAC) 和挪威母婴队列研究 (MoBa)。我们展示了出生体重的遗传变异如何主要由胎儿遗传而不是母体遗传变异来源来解释。
更新日期:2020-04-20
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