期刊
THEORETICAL POPULATION BIOLOGY
卷 107, 期 -, 页码 26-30出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.tpb.2015.08.005
关键词
Relationship; Genetic variance; Heritability; Base population; Mixed models
资金
- INRA metaprogram SelGen in project X-Gen
- INRA metaprogram SelGen in project SelDir
Use of relationships between individuals to estimate genetic variances and heritabilities via mixed models is standard practice in human, plant and livestock genetics. Different models or information for relationships may give different estimates of genetic variances. However, comparing these estimates across different relationship models is not straightforward as the implied base populations differ between relationship models. In this work, I present a method to compare estimates of variance components across different relationship models. I suggest referring genetic variances obtained using different relationship models to the same reference population, usually a set of individuals in the population. Expected genetic variance of this population is the estimated variance component from the mixed model times a statistic, D-k, which is the average self-relationship minus the average (self- and across-) relationship. For most typical models of relationships, D-k is close to 1. However, this is not true for very deep pedigrees, for identity-by-state relationships, or for non-parametric kernels, which tend to overestimate the genetic variance and the heritability. Using mice data, I show that heritabilities from identity-by-state and kernel-based relationships are overestimated. Weighting these estimates by D-k scales them to a base comparable to genomic or pedigree relationships, avoiding wrong comparisons, for instance, missing heritabilities. (C) 2015 Elsevier Inc. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据