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HannahVMeyer / PhenotypeSimulator

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"genvar" parameter #14

Closed fmoradi1365 closed 5 years ago

fmoradi1365 commented 5 years ago

Hello,

I am using your PhenotypeSimulator package in my research and have a few questions:

On the second page of the paper you published in Bioinformatics, it is saying that "... a proportion $\theta$ is selected to be causal across all traits ...". However, I have difficulties understanding the role of $\theta$ in your simulation setting. Is it "genvar" parameter in your R codes? If so, should it be set to (number of causal SNPs) / (total number of SNPs)?

Many thanks for your time.

HannahVMeyer commented 5 years ago

Hi - thanks for your interest in the package.

From the documentation of the main simulation function:

?PhenotypeSimulator::runSimulation
[...]
genVar    Proportion [double] of total genetic variance.
theta     Proportion [double] of variance of shared genetic variant effects
h2s       Proportion [double] of genetic variance of genetic variant effects.
h2bg      Proportion [double] of genetic variance of infinitesimal genetic effects; either h2s or h2bg 
          have to be specified and h2s + h2bg = 1.

genVar specifies how much of the total phenotypic variance is explained by genetics. So for instance, if you want 30% of your overall phenotypic variance to be genetic, set genVar=0.3. The genetic variance includes direct genetic variant effects (h2s) and infinitesimal genetic effects (h2bg, often described as background, relatedness and kinship structure). Both genVar and either h2s or h2bg have to be specified. Just as genVar, h2s and h2bg are proportions, this time of the variance explained by genetics. If for instance you want 20% of your genVar to be attributed to direct SNP effects, set h2s=0.2. This means the total SNP variance of the phenotypes will be 0.3*0.2=0.06.

PhenotypeSimulator also offers to specify how the SNPs affect the traits you are simulating: they can either have the same effect across all traits, or different effects. theta specifies the variance of the shared effects, for instance theta=0.3 means the SNP genetic variance explained is 30%, and total phenotypic variance explained is 0.30.20.3=0.018.

The concept of the shared and independent effects is depicted in Figure 1 of the paper.

fmoradi1365 commented 5 years ago

Hi Hannah,

Thank you very much for the explanation. So, I should call runSimulation function to be able to specify both genVar and theta parameters.

HannahVMeyer commented 5 years ago

Yes, correct. These are both parameters accepted by runSimulation(). Good luck with your simulations!