This function is an R wrapper for the JPSGCS program to estimate a graphical model for linkage disequilibrium (LD) from a sample of genotypes. The genetic markers are assumed to be on the same chromosome.
Name of a LINKAGE parameter file (also called a DATAFILE: see http://linkage.rockefeller.edu/soft/linkage/) that contains marker and genetic map information.
Name of a LINKAGE pedigree file “flipped” so that rows correspond to loci and columns correspond to individuals.
Name of the file in the current working directory to contain the fitted LD model.
The input pedigree file
is not the standard format where rows correspond to
individuals and columns to loci. Rather, it has been transposed so that
rows correspond to loci.
Transposed LINKAGE pedigree files may be written by the
with the option
Further information on the graphical model is available from the article listed in the References.
None. The result of the function call is the output file
This function can require large amounts of memory for large data sets (e.g. whole chromosomes of SNPs at the marker density of the HapMap project). The computation for fitting the LD model is done in java, using functions from Alun Thomas' suite of Java Programs for Statistical Genetics and Computational Statistics (JPSGCS). The JPSGCS java programs are accessed by R-wrappers provided by the rJPSGCS package, which initializes the java virtual machine (JVM) if not already done so by another package. To over-ride the default amount of memory java allocates for heap space, initialize the JVM before loading rJPSGCS as follows:
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Sigal Blay, Jinko Graham and Brad McNeney
Thomas A. Estimation of graphical models whose conditional independence graphs are interval graphs and its application to modeling linkage disequilibrium. Comput Stat Data Anal. 2009; 53:1818-1828.
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## Not run: data(exdat) sdat<-as(exdat$markers,"snp.matrix") #coerce to snp.matrix # Write a LINKAGE parameter file write.parfile(snp.data=sdat,map=exdat$map,file="test.par") # Write a "flipped" pedfile for the SNP data on unrelated subjects. write.pedfile(pedinf="unrelated",snp.data=sdat,file="ftest.ped",transpose=TRUE) FitGMLD(par="test.par",fped="ftest.ped",out.ld.par="test.ld.par") # Clean up unlink(c("test.par","ftest.ped","test.ld.par")) ## End(Not run)
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