root/galaxy-central/tools/regVariation/t_test_two_samples.pl

# A program to implement the non-pooled t-test for two samples where the alternative hypothesis is two-sided or one-sided. 
# The first input file is a TABULAR format file representing the first sample and consisting of one column only.
# The second input file is a TABULAR format file representing the first sample nd consisting of one column only.
# The third input is the sidedness of the t-test: either two-sided or, one-sided with m1 less than m2 or, 
# one-sided with m1 greater than m2. 
# The fourth input is the equality status of the standard deviations of both populations
# The output file is a TXT file representing the result of the two sample t-test.

use strict;
use warnings;

#variable to handle the motif information
my $motif;
my $motifName = "";
my $motifNumber = 0;
my $totalMotifsNumber = 0;
my @motifNamesArray = ();

# check to make sure having correct files
my $usage = "usage: non_pooled_t_test_two_samples_galaxy.pl [TABULAR.in] [TABULAR.in] [testSidedness] [standardDeviationEquality] [TXT.out] \n";
die $usage unless @ARGV == 5;

#get the input arguments
my $firstSampleInputFile = $ARGV[0];
my $secondSampleInputFile = $ARGV[1];
my $testSidedness = $ARGV[2];
my $standardDeviationEquality = $ARGV[3]; 
my $outputFile = $ARGV[4];

#open the input files
open (INPUT1, "<", $firstSampleInputFile) || die("Could not open file $firstSampleInputFile \n"); 
open (INPUT2, "<", $secondSampleInputFile) || die("Could not open file $secondSampleInputFile \n"); 
open (OUTPUT, ">", $outputFile) || die("Could not open file $outputFile \n");


#variables to store the name of the R script file
my $r_script;
        
# R script to implement the two-sample test on the motif frequencies in upstream flanking region        
#construct an R script file and save it in the same directory where the perl file is located
$r_script = "non_pooled_t_test_two_samples.r";

open(Rcmd,">", $r_script) or die "Cannot open $r_script \n\n";
print Rcmd "
        sampleTable1 <- read.table(\"$firstSampleInputFile\", header=FALSE);
                sample1 <- sampleTable1[, 1];
                
                sampleTable2 <- read.table(\"$secondSampleInputFile\", header=FALSE);
                sample2 <- sampleTable2[, 1];
                
                testSideStatus <- \"$testSidedness\";
                STEqualityStatus <- \"$standardDeviationEquality\";
                
                #open the output a text file
                sink(file = \"$outputFile\");
                
                #check if the t-test is two-sided
                if (testSideStatus == \"two-sided\"){
                        
                        #check if the standard deviations are equal in both populations
                        if (STEqualityStatus == \"equal\"){
                                #two-sample t-test where standard deviations are assumed to be unequal, the test is two-sided
                                testResult <- t.test(sample1, sample2, var.equal = TRUE);       
                        } else{
                                #two-sample t-test where standard deviations are assumed to be unequal, the test is two-sided
                                testResult <- t.test(sample1, sample2, var.equal = FALSE);
                        }
                } else{  #the t-test is one sided       
                        
                        #check if the t-test is two-sided with m1 < m2
                        if (testSideStatus == \"one-sided:_m1_less_than_m2\"){
                                
                                #check if the standard deviations are equal in both populations
                                if (STEqualityStatus == \"equal\"){
                                        #two-sample t-test where standard deviations are assumed to be unequal, the test is one-sided: Halt: m1 < m2
                                        testResult <- t.test(sample1, sample2, var.equal = TRUE, alternative = \"less\");
                                } else{
                                        #two-sample t-test where standard deviations are assumed to be unequal, the test is one-sided: Halt: m1 < m2
                                        testResult <- t.test(sample1, sample2, var.equal = FALSE, alternative = \"less\");
                                }
                        } else{   #the t-test is one-sided with m1 > m2
                                #check if the standard deviations are equal in both populations
                                if (STEqualityStatus == \"equal\"){
                                        #two-sample t-test where standard deviations are assumed to be unequal, the test is one-sided: Halt: m1 < m2
                                        testResult <- t.test(sample1, sample2, var.equal = TRUE, alternative = \"greater\");
                                } else{
                                        #two-sample t-test where standard deviations are assumed to be unequal, the test is one-sided: Halt: m1 < m2
                                        testResult <- t.test(sample1, sample2, var.equal = FALSE, alternative = \"greater\");
                                }
                        }
                }
                
                #save the output of the t-test into the output text file
                testResult;
                
                #close the output text file
                sink();
                
                #eof" . "\n";
                
close Rcmd;     

system("R --no-restore --no-save --no-readline < $r_script > $r_script.out");

#close the input and output files
close(OUTPUT);
close(INPUT2);
close(INPUT1);