Institute of Plant Breeding, Seed Science and Population Genetics, University of Hohenheim, Stuttgart, Germany.
BMC Bioinformatics. 2011 Jun 29;12:265. doi: 10.1186/1471-2105-12-265.
There is a great interest in understanding the genetic architecture of complex traits in natural populations. Genome-wide association studies (GWAS) are becoming routine in human, animal and plant genetics to understand the connection between naturally occurring genotypic and phenotypic variation. Coalescent simulations are commonly used in population genetics to simulate genotypes under different parameters and demographic models.
Here, we present phenosim, a software to add a phenotype to genotypes generated in time-efficient coalescent simulations. Both qualitative and quantitative phenotypes can be generated and it is possible to partition phenotypic variation between additive effects and epistatic interactions between causal variants. The output formats of phenosim are directly usable as input for different GWAS tools. The applicability of phenosim is shown by simulating a genome-wide association study in Arabidopsis thaliana.
By using the coalescent approach to generate genotypes and phenosim to add phenotypes, the data sets can be used to assess the influence of various factors such as demography, genetic architecture or selection on the statistical power of association methods to detect causal genetic variants under a wide variety of population genetic scenarios. phenosim is freely available from the authors' website http://evoplant.uni-hohenheim.de.
人们对于理解自然种群中复杂特征的遗传结构非常感兴趣。全基因组关联研究（GWAS）在人类、动物和植物遗传学中已成为常规手段，用于理解自然发生的基因型和表型变异之间的联系。在种群遗传学中，合并模拟通常用于根据不同的参数和人口模型模拟基因型。
在这里，我们介绍了 phenosim，这是一种在时间高效的合并模拟中为基因型添加表型的软件。可以生成定性和定量的表型，并且可以在加性效应和因果变异之间的上位性相互作用之间划分表型变异。phenosim 的输出格式可直接用作不同 GWAS 工具的输入。通过在拟南芥中模拟全基因组关联研究，展示了 phenosim 的适用性。
通过使用合并方法生成基因型和 phenosim 添加表型，可以使用这些数据集来评估各种因素（如人口统计学、遗传结构或选择）对关联方法检测因果遗传变异的统计能力的影响，在广泛的种群遗传情景下。phenosim 可从作者的网站 http://evoplant.uni-hohenheim.de 免费获得。
