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Phenotype Simulator
brakitsch edited this page Dec 8, 2015
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Our software package also includes the eQTL simulator we have used for the power simulations in our paper. In a nutshell, each gene is simulated as a linear function of all causal genes, the cis SNP, noise and hidden confounding factors. For more information, we refer to the supplement of our paper.
The simulator has a command line interface that is easily accessible:
./GNetLMM_simPheno --bfile bfile --pfile pfile
where
- bfile is the basename of of the binary bed file (bfile.bed,bfile.bim,bfile.fam are required).
- pfile is the basename of the phenotype file that is generated.The file pfile.matrix contains the gene expression values: each gene is saved in a row and each sample in a column. The file pfile.rows contains meta-information over the genes, pfile.cols meta-information over the samples. The file pfile.conf saves the hidden confounding factors, pfile.Aconf the mapping between the confounding factors and the genes, and pfile.Agene the gene-gene network, where A[i,j]=1 if gene j causes gene i.
By changing the following parameters different genetic architectures can be simulated and, in particular, the power experiments of our paper can be reproduced.
Option | Default | Datatype | Explanation |
---|---|---|---|
--seed | 0 | int | seed for random number generator |
--networkDesign | sparse | string | can either be star or sparse |
--T | 100 | int | number of simulated genes |
--varSnp | 0.1 | float | variance explained by the causal cis marker |
--varNetwork | 0.8 | int | variance explained by the gene-gene and gene-confounder network |
--alpha | 1.0 | float | ratio between variance explained by the gene-gene network and the gene-confounder network |
--nConfounder | 3 | int | number of confounders |
--confPerGene | 1 | float | expected number of confounders per gene |
--expN | 5 | float | expected number of in- and out-going edges |