epistatic.correlation: Calculate the epistatic interaction effect between SNP pairs...
In AQS-Group/WISH: WISH

Description Usage Arguments Value References Examples

A WISH network can be built based on epistatic interaction effects between SNP pairs. Those interaction effects are calculated using linear models.

1	epistatic.correlation(phenotype,genotype,threads=1,test=T,simple=T,glm=F)

`phenotype`	Dataframe with the rows correspinding to the individuals in the analysis,and columns for the different measured phenotypes and fixed/random factors. Only give one phenotype column at a time. Phenotypes should be non-categorical continous or discrete/semi-discrete variables. Make sure that the dataframe contains the same individuals as in the genotype-file, and that those are in the same order.
`genotype`	Dataframe with the genotype information, resulting from the function generate.genotype(). Make sure that the dataframe contains the same individuals as in the phenotype-file, and that those are in the same order.
`threads`	Number of threads to use for parallel execution in the function registerDoParallel()
`test`	True or False value indicating if a test run is being perform. If True will calculate the expected time it will take for the full analysis based on calculating 100.000 models with the setting chosen
`simple`	True or false value indicating if only a major/major and minor/minor directed interaction model are tested (simple=T) or if if interactions on the major/minor minor axis are tested as well, with the best one of the two being selected (simple=F).
`glm`	If T will use a generelized linear model with a binomial link function instead of a regular linear model. This should be used if your phenotype is binary.

A list of two matrices. The first matrix gives the epistatic interaction effects between all the SNP-pairs which were in the input genotype data) and selected with the pvalue from the GWAS results. The second matrix are the corresponding pvalues of the parameter estimates of the epistatic interactions.

Lisette J.A. Kogelman and Haja N.Kadarmideen (2014). Weighted Interaction SNP Hub (WISH) network method for building genetic networks for complex diseases and traits using whole genome genotype data. BMC Systems Biology 8(Suppl 2):S5. http://www.biomedcentral.com/1752-0509/8/S2/S5.