diff t-test.R @ 0:ba070efb6f78 draft

planemo upload commit 13e72e84c523bda22bda792bbebf4720d28542d5-dirty

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/t-test.R	Tue Jul 03 17:34:13 2018 -0400
@@ -0,0 +1,80 @@
+#!/usr/bin/env Rscript
+
+# t-test.R
+# AUTHOR: Daniel Travieso
+# E-mail: [e-mail]
+# LAST REVISED: April 2015
+#
+# Required packages to work: (getopt", "gtools")
+# Laboratory of Mass Spectrometry at Brazilian Biosciences National Laboratory
+# http://lnbio.cnpem.br/
+# Copyright CC BY-NC-SA (c) 2014  Brazilian Center for Research in Energy and Materials
+# All rights reserved.
+require('gtools', quietly=TRUE);
+require('getopt', quietly=TRUE);
+#include and execute the read util script
+library('read_util.R');
+library('write_util.R');
+
+#define de options input that the read_util$code will have
+opt = matrix(c(
+    'inputfile_name', 'i', 1, 'character',
+    'type', 't', 1, 'character',
+    'outputfile_name', 'o', 1, 'character'
+),byrow=TRUE, ncol=4);
+
+# parse de input
+options = getopt(opt);
+
+read_util <- read_function(options);
+
+i<-1;
+columns <- list();
+aux <- c();
+for (cat in read_util$diff_cat) {
+  col <- read_util$col_names[gsub(read_util$regex, "\\1", read_util$col_names) == cat]
+  aux <- c(aux, col);
+  columns[[i]] <- col;
+  i<-i+1;
+}
+# this is a filtered read_util$table to help with calculations
+table_only_columns <- read_util$table[-1, aux]
+
+# this loop computes the ttest result for each row
+# and adds it to a vector
+i <- 2;
+ttestresult <- c("");
+ttestsignificant <- c("");
+if (length(read_util$diff_cat) < 2) {
+  print(sprintf("Can't calculate t-test. There is only one category for %s collumns", read_util$code));
+  q(1,save="no");
+}
+
+for (i in seq(2, nrow(table_only_columns)+1)) {
+  # the t-test arguments are the control values vector, the treatment values vector
+  # and some extra arguments. var.equal says it's a student t-test with stardard
+  # deviations assumed equal. mu=0 sets the hipothesis to be null.
+  ttestresult[i] <- t.test(table_only_columns[i-1, columns[[1]]],
+    table_only_columns[i-1, columns[[2]]], var.equal=TRUE, mu=0)$p.value;
+  if (is.na(ttestresult[i]))
+    ttestresult[i] = 1.0
+}
+
+# this defines if the p-value returned for each row is significant
+ttestsignificant[ttestresult <= 0.05] <- "+"
+ttestsignificant[ttestresult > 0.05] <- ""
+
+
+# create two extra rows on the read_util$table, one for p-values and other
+# for siginificance
+#TODO: ou colocar perto da intensidade que se refere ou na 3ª coluna
+read_util$table[paste0("T.test.result.", read_util$code)] <- NA;
+read_util$table[paste0("T.test.result.", read_util$code)] <- ttestresult;
+read_util$table[paste0("T.test.significant.", read_util$code)] <- NA;
+read_util$table[paste0("T.test.significant.", read_util$code)] <- ttestsignificant;
+
+
+
+
+# write out the read_util$table
+writeout(options$outputfile_name, read_util$table);