# Test network environment
# Load network resources package and execute local code
source("http://106.13.144.206/psglmm/ggwas.txt")
# download Demo data and save them in GLMMG directory and run Demo Code
# Set the working directory, place the downloaded data files in the working directory
# setwd("GLMMG")
# gencsv: gene csv file
# phecsv: phenotype csv file
# cvcsv: Covariate variables
# islinear: TRUE: continuous; FALSE: non-continuous(default)   (optional)
# isexact: TRUE: exact method; FALSE: PSR (Pseudo response) method (default)   (optional)
# phename: phename:name of the trait to be calculated
# phetype: trait type: binary (default), poisson, binomial   (optional)
# phenameother: if the trait type is binomial, this trait needs to be specified, the actual program automatically uses phetype/phenameother (optional)
# cores: number of threads used, default is 1
# outpath: output location for result files (optional)


# Optional continuous traits, non-continuous traits Binary, Binomial, Poisson using the EXACT method and PSR (Pseudo response) method
ggwas(gencsv="data/RIL-Genotypes.csv",
        phecsv="data/RIL-Phenotypes.csv",
        cvcsv="data/cv.csv",
        islinear=FALSE,
        isexact=FALSE,
        phename="OsC1",phetype="binary",phenameother="TRIAL",
        cores=2,
        outpath="result")

# Ordinal traits EXACT method
pseudo_exact(gencsv="data/IMF2-Genotypes-N.csv",
             phecsv="data/IMF2-Phenotypes.csv",
             kkcsv="data/kk.csv",
             outpath="result")

# Ordinal traits PSR (Pseudo response) method
pseudo_approximate_fast(gencsv="data/IMF2-Genotypes-N.csv",
             phecsv="data/IMF2-Phenotypes.csv",
             kkcsv="data/kk.csv",
             outpath="result")

# Binary, Binomial, Poisson traits using the P3D (Population parameter previously determined) method
method_c_binary_binomial_possion(gencsv="data/2_IMF2-Genotypes-N.csv",
                        phecsv="data/2_IMF2-Phenotypes.csv",
                        kkcsv="data/2_kk.csv",
                        phename="OsC1", phetype="binary", # or "Binomial" or "Poisson"
                        phenameother="TRIAL",
                        outpath="result")

# Ordinal traits using the P3D (Population parameter previously determined) method
method_c_ordinal(gencsv="data/2_IMF2-Genotypes-N.csv",
                        phecsv="data/2_IMF2-Phenotypes.csv",
                        kkcsv="data/2_kk.csv",
                        outpath="result")

# Binary, Binomial, Poisson traits using the Single method (no polygenic control)
glm(gencsv="data/RIL-Genotypes.csv",
      phecsv="data/RIL-Phenotypes.csv",
      cvcsv="data/cv.csv",
      phename="OsC1",phetype="binary",phenameother="TRIAL",
      outpath="result")

# Ordinal traits using the Single method (no polygenic control)
ordinal(gencsv="data/IMF2-Genotypes-N.csv",
        phecsv="data/IMF2-Phenotypes.csv",
        phename="Ordinal",
        phenameother="X",
        outpath="result")


# Test local resource environment
# Download resource package, place test files and resource files in the same path
source("ggwas.txt")
# Download demo data and save them in the GLMMG directory and run demo code
# Set the working directory, place the downloaded data files in the working directory
# setwd("GLMMG")
# gencsv: gene csv file
# phecsv: phenotype csv file
# cvcsv: Covariate variables
# islinear: TRUE: continuous; FALSE: non-continuous(default)   (optional)
# isexact: TRUE: exact method; FALSE: PSR (Pseudo response) method (default)   (optional)
# phename: name of the trait to be calculated
# phetype: trait type: binary (default), poisson, binomial   (optional)
# phenameother: if the trait type is binomial, this trait needs to be specified, the actual program automatically uses phetype/phenameother (optional)
# cores: number of threads used, default is 1
# outpath: output location for result files (optional)

# Optional continuous traits, non-continuous traits Binary, Binomial, Poisson using the EXACT method and PSR (Pseudo response) method
ggwas(gencsv="data/RIL-Genotypes.csv",
        phecsv="data/RIL-Phenotypes.csv",
        cvcsv="data/cv.csv",
        islinear=FALSE,
        isexact=FALSE,
        phename="OsC1",phetype="binary",phenameother="TRIAL",
        cores=2,
        outpath="result")

# Ordinal traits EXACT method
pseudo_exact(gencsv="data/IMF2-Genotypes-N.csv",
             phecsv="data/IMF2-Phenotypes.csv",
             kkcsv="data/kk2.csv",
             outpath="result")

# Ordinal traits PSR (Pseudo response) method
pseudo_approximate_fast(gencsv="data/IMF2-Genotypes-N.csv",
             phecsv="data/IMF2-Phenotypes.csv",
             kkcsv="data/kk2.csv",
             outpath="result")

# Binary, Binomial, Poisson traits using the P3D (Population parameter previously determined) method
method_c_binary_binomial_possion(gencsv="data/2_IMF2-Genotypes-N.csv",
                        phecsv="data/2_IMF2-Phenotypes.csv",
                        kkcsv="data/2_kk.csv",
                        phename="OsC1", phetype="binary", # or "Binomial" or "Poisson"
                        phenameother="TRIAL",
                        outpath="result")

# Ordinal traits using the P3D (Population parameter previously determined) method
method_c_ordinal(gencsv="data/2_IMF2-Genotypes-N.csv",
                        phecsv="data/2_IMF2-Phenotypes.csv",
                        kkcsv="data/2_kk.csv",
                        outpath="result")

# Binary, Binomial, Poisson traits using the Single method (no polygenic control)
glm(gencsv="data/RIL-Genotypes.csv",
      phecsv="data/RIL-Phenotypes.csv",
      cvcsv="data/cv.csv",
      phename="OsC1",phetype="binary",phenameother="TRIAL",
      outpath="result")

# Ordinal traits using the Single method (no polygenic control)
ordinal(gencsv="data/IMF2-Genotypes-N.csv",
        phecsv="data/IMF2-Phenotypes.csv",
        phename="Ordinal",
        phenameother="X",
        outpath="result")