PLoS GeneticsGeneticsPeer-reviewed journal article
Estimating indirect parental genetic effects on offspring phenotypes using virtual parental genotypes derived from sibling and half sibling pairs
Liang‐Dar HwangiD, Justin D. TubbsiD, Justin LuongiD, Mischa LundbergiD, Gunn-Helen MoeniD, Geng WangiD, Nicole M. WarringtoniD, Pak Chung ShamiD, Gabriel Cuéllar-PartidaiD, David M. EvansiD
Abstract
Indirect parental genetic effects may be defined as the influence of parental genotypes on offspring phenotypes over and above that which results from the transmission of genes from parents to children. However, given the relative paucity of large-scale family-based cohorts around the world, it is difficult to demonstrate parental genetic effects on human traits, particularly at individual loci. In this manuscript, we illustrate how parental genetic effects on offspring phenotypes, including late onset diseases, can be estimated at individual loci in principle using large-scale genome-wide association study (GWAS) data, even in the absence of parental genotypes. Our strategy involves creating "virtual" mothers and fathers by estimating the genotypic dosages of parental genotypes using physically genotyped data from relative pairs. We then utilize the expected dosages of the parents, and the actual genotypes of the offspring relative pairs, to perform conditional genetic association analyses to obtain asymptotically unbiased estimates of maternal, paternal and offspring genetic effects. We develop a freely available web application that quantifies the power of our approach using closed form asymptotic solutions. We implement our methods in a user-friendly software package IMPISH (IMputing Parental genotypes In Siblings and Half-Siblings) which allows users to quickly and efficiently impute parental genotypes across the genome in large genome-wide datasets, and then use these estimated dosages in downstream linear mixed model association analyses. We conclude that imputing parental genotypes from relative pairs may provide a useful adjunct to existing large-scale genetic studies of parents and their offspring.
- organism: human
- assay: GWAS summary statistics
- research focus: variant effect prediction
- research focus: gene regulatory network inference
- research focus: benchmarking
- research focus: software / tool
- approach: statistical model
- approach: matrix factorization
- Citations
- 30
- FWCI
- 3.07
- Field percentile
- top 7%
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