ArticleBMC bioinformatics2011
phenosim--A software to simulate phenotypes for testing in genome-wide association studies.
Article in BMC bioinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- H3AGWAS: a portable workflow for genome wide association studies.BMC bioinformatics · 2022Article
- Identifying Cancer genes by combining two-rounds RWR based on multiple biological data.BMC bioinformatics · 2019Article
- PhenotypeSimulator: A comprehensive framework for simulating multi-trait, multi-locus genotype to phenotype relationships.Bioinformatics (Oxford, England) · 2018Article
- Simulating variance heterogeneity in quantitative genome wide association studies.BMC bioinformatics · 2018Article
- cophesim: a comprehensive phenotype simulator for testing novel association methods.F1000Research · 2017Article
- Advantages of continuous genotype values over genotype classes for GWAS in higher polyploids: a comparative study in hexaploid chrysanthemum.BMC genomics · 2016Article
- Efficient Coalescent Simulation and Genealogical Analysis for Large Sample Sizes.PLoS computational biology · 2016Article
- SeqSIMLA: a sequence and phenotype simulation tool for complex disease studies.BMC bioinformatics · 2013Article
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Authors and funding
3 authors.
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Abstract
backgroundThere 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.
resultsHere, 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.
conclusionsBy 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.
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