predict_RF.R

#!/usr/bin/env Rscript

# This R script makes predictions on a dataset using a trained classifier

# param1: The path to a TSV containing the data for which to make predictions.
#         Columns must be named the same as the training data. We recommend using the Snakefile-prepare pipeline to obtain this data.
# param2: An RDA file containing the trained classifier. This is output by train_RF.R
# param3: The path to a TSV in which to write the predictions. It will be created if it doesn't exist.


args <- commandArgs(trailingOnly = TRUE)
test.data<- args[1]
model <- args[2]
output<- args[3]

# load libraries
library(data.table)
library(plyr)
library(dplyr)
suppressMessages(library(mlr))

# load model
print("loading appropriate model")
load(model)

# load test
print("loading and formatting test data")
test<- read.table(test.data, header=TRUE, sep="\t", na.strings=c("NA",".","na","N/A"), skipNul=FALSE, row.names=NULL)

# making predictions
print("making predictions and outputting results")
pred= predict(fit, newdata= test, type="prob")
write.table(pred$data, sep='\t', quote=FALSE, row.names=FALSE, na=".", output)