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train_metabolites.R
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train_metabolites.R
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#!/usr/bin/env Rscript
##################
# Load libraries #
##################
library(melonnpan)
library(optparse)
###########################
# Command line parameters #
###########################
option_list = list(
make_option(
c("-i", "--metab"), # i stands for input metabolites
type = "character"),
make_option(
c("-g", "--metag"), # g stands for input genes or genomic features
type = "character"),
make_option(
c("-o", "--output"), # o stands for output
type = "character"),
make_option(
c("-a", "--alpha"),
default = seq(0.05, 0.95, 0.05),
type = "numeric"), # a stands for alpha
make_option(
c("-l", "--lambda.choice"), default="lambda.1se", # l stands for lambda
type = "character"),
make_option(
c("-n", "--nfolds"), default = 10, # n stands for n-fold
type = "integer"),
make_option(
c("-m", "--correction"), default = "fdr", # m stands for multiplicity correction
type = "character"),
make_option(
c("-c", "--method"), default = "spearman", # c stands for correlation method
type = "character"),
make_option(
c("-p", "--cores"), default = 4, # p stands for number of parallel cores
type = "integer"),
make_option(
c("-r", "--seed"), default = 1234, # r stands for random seed
type = "numeric"),
make_option(
c("-t", "--cutoff"), default = 0.3, # t stands for threshold for Cohen correlation cutoff
type = "numeric"),
make_option(
c("-v", "--verbose"), default = FALSE, # v stands for verbose
action = "store_true"),
make_option(
c("-b", "--no.transform.metab"), default = FALSE,
action = "store_true"),
make_option(
c("-d", "--no.transform.metag"), default = FALSE,
action = "store_true"),
make_option(
c("-q", "--discard.poor.predictions"), default = FALSE,
action = "store_true"),
make_option(
c("-f", "--plot"), default=FALSE, # f stands for figures
action = "store_true"),
make_option(
c("-s", "--outputString"),
default = c("MelonnPan_Training_Summary",
"MelonnPan_Trained_Weights",
"MelonnPan_Trained_Metabolites"),
type = "character") # s stands for string
)
##########################
# Print progress message #
##########################
cat("Running MelonnPan-Train using the following parameters:", "\n");
opt <- parse_args(OptionParser(option_list=option_list), positional_arguments = TRUE)
print(opt)
#########################
# Extract CLI arguments #
#########################
metab<- opt$options$metab
metag<- opt$options$metag
output<- opt$options$output
alpha<- opt$options$alpha
lambda.choice<- opt$options$lambda.choice
nfolds<- opt$options$nfolds
correction<- opt$options$correction
method<- opt$options$method
cores<- opt$options$cores
seed<- opt$options$seed
cutoff<- opt$options$cutoff
verbose<- opt$options$verbose
no.transform.metab<- opt$options$no.transform.metab
no.transform.metag<- opt$options$no.transform.metag
discard.poor.predictions<- opt$options$discard.poor.predictions
plot<- opt$options$plot
outputString<- opt$options$outputString
#####################
# Train metabolites #
#####################
DD<-melonnpan::melonnpan.train(metab = metab,
metag = metag,
output = output,
alpha = alpha,
lambda.choice = lambda.choice,
nfolds = nfolds,
correction = correction,
method = method,
cores = cores,
seed = seed,
cutoff = cutoff,
verbose = verbose,
no.transform.metab = no.transform.metab,
no.transform.metag = no.transform.metag,
discard.poor.predictions = discard.poor.predictions,
plot = plot,
outputString = outputString)