MOSS.GWAS               A function implementing the MOSS algorithm for
                        the analysis of GWAS data.
ex2plink                Convert example dataset to Plink format
genMOSSplus-package     Application of MOSS algorithm to dense SNP
                        array data
genos.clean             Removes badly predicted SNPs by MaCH
genos.clean.batch       Removes badly predicted SNPs by MaCH for all
                        files
get.data.dims           Obtains matrix dimensions
get.file.copy           Copies files from one directory to another
pre0.dir.create         Generate working subdirectory structure
pre1.plink2mach         Convert Plink to MaCH input format
pre1.plink2mach.batch   Convert Plink to MaCH input format for all
                        files
pre2.remove.genos       Remove genos with many empty values
pre2.remove.genos.batch
                        Remove genos with many empty values for all
                        files
pre3.call.mach          Call MaCH imputation with and without Hapmap
pre3.call.mach.batch    Call MaCH imputation with and without Hapmap
pre4.combine.case.control
                        Combine CASE and CONTROL files
pre4.combine.case.control.batch
                        Combine CASE and CONTROL files for all files
pre5.genos2numeric      Categorize genotype data into 3 levels
pre5.genos2numeric.batch
                        Categorize genotype data into 3 levels for each
                        file
pre6.merge.genos        Combine geno files across all chromosomes
pre7.add.conf.var       Append confounding variables
pre7.add.conf.var.unix
                        Append confounding variables using Linux
pre8.split.train.test   Split dataset into TRAIN and TEST files
pre8.split.train.test.batch
                        Split dataset into TRAIN and TEST files for all
                        files
run1.moss               Runs MOSS regression algorithm
tune1.subsets           Imputes dense map of SNPs on chromosome regions
                        with MaCH
