Write GRM binary files.

Description

Function to write a binary GRM format recently introduced by GCTA. It takes a correlation matrix as used by other Kriging functions, and writes three files: binary file for storing the diagonal + lower triangular elements, a text file for sample IDs, and a binary file storing the number of SNPs used in the correlation matrix calculation.

Usage

write_GRMBin(X, n.snps = 0, prefix, size = 4)

Arguments

Value

None. Though side effects are writing three files as described above.

References

http://www.complextraitgenomics.com/software/gcta/estimate_grm.html

Examples

  
  ## create a random genotype matrix
  nSamples <- 10
  mMarkers <- 100
  X <- matrix(rbinom(n=100, size=2, prob=0.5), nrow=nSamples)
  ## compute the Genetric Relatedness Matrix
  grm <- cor(X)
  ## write a Genetic Relatedness Matrix (GRM)
  ## NOTE: to following is not run here -- not writing any files in examples
  #write_GRMBin(grm, n.snps=mMarkers, prefix="grm.out")

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(OmicKriging)
Loading required package: doParallel
Loading required package: foreach
Loading required package: iterators
Loading required package: parallel
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/OmicKriging/write_GRMBin.Rd_%03d_medium.png", width=480, height=480)
> ### Name: write_GRMBin
> ### Title: Write GRM binary files.
> ### Aliases: write_GRMBin
> 
> ### ** Examples
> 
>   
>   ## create a random genotype matrix
>   nSamples <- 10
>   mMarkers <- 100
>   X <- matrix(rbinom(n=100, size=2, prob=0.5), nrow=nSamples)
>   ## compute the Genetric Relatedness Matrix
>   grm <- cor(X)
>   ## write a Genetic Relatedness Matrix (GRM)
>   ## NOTE: to following is not run here -- not writing any files in examples
>   #write_GRMBin(grm, n.snps=mMarkers, prefix="grm.out")
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>