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annotate t-test.R @ 0:ba070efb6f78 draft

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author labis-app
date Tue, 03 Jul 2018 17:34:13 -0400
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1 #!/usr/bin/env Rscript
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2
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3 # t-test.R
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4 # AUTHOR: Daniel Travieso
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5 # E-mail: danielgtravieso@gmail.com
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6 # LAST REVISED: April 2015
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7 #
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8 # Required packages to work: (getopt", "gtools")
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9 # Laboratory of Mass Spectrometry at Brazilian Biosciences National Laboratory
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10 # http://lnbio.cnpem.br/
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11 # Copyright CC BY-NC-SA (c) 2014 Brazilian Center for Research in Energy and Materials
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12 # All rights reserved.
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13 require('gtools', quietly=TRUE);
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14 require('getopt', quietly=TRUE);
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15 #include and execute the read util script
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16 library('read_util.R');
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17 library('write_util.R');
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18
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19 #define de options input that the read_util$code will have
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20 opt = matrix(c(
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21 'inputfile_name', 'i', 1, 'character',
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22 'type', 't', 1, 'character',
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23 'outputfile_name', 'o', 1, 'character'
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24 ),byrow=TRUE, ncol=4);
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25
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26 # parse de input
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27 options = getopt(opt);
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28
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29 read_util <- read_function(options);
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30
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31 i<-1;
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32 columns <- list();
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33 aux <- c();
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34 for (cat in read_util$diff_cat) {
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35 col <- read_util$col_names[gsub(read_util$regex, "\\1", read_util$col_names) == cat]
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36 aux <- c(aux, col);
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37 columns[[i]] <- col;
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38 i<-i+1;
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39 }
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40 # this is a filtered read_util$table to help with calculations
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41 table_only_columns <- read_util$table[-1, aux]
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42
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43 # this loop computes the ttest result for each row
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44 # and adds it to a vector
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45 i <- 2;
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46 ttestresult <- c("");
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47 ttestsignificant <- c("");
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48 if (length(read_util$diff_cat) < 2) {
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49 print(sprintf("Can't calculate t-test. There is only one category for %s collumns", read_util$code));
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50 q(1,save="no");
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51 }
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52
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53 for (i in seq(2, nrow(table_only_columns)+1)) {
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54 # the t-test arguments are the control values vector, the treatment values vector
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55 # and some extra arguments. var.equal says it's a student t-test with stardard
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56 # deviations assumed equal. mu=0 sets the hipothesis to be null.
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57 ttestresult[i] <- t.test(table_only_columns[i-1, columns[[1]]],
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58 table_only_columns[i-1, columns[[2]]], var.equal=TRUE, mu=0)$p.value;
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59 if (is.na(ttestresult[i]))
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60 ttestresult[i] = 1.0
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61 }
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62
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63 # this defines if the p-value returned for each row is significant
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64 ttestsignificant[ttestresult <= 0.05] <- "+"
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65 ttestsignificant[ttestresult > 0.05] <- ""
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66
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67
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68 # create two extra rows on the read_util$table, one for p-values and other
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69 # for siginificance
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70 #TODO: ou colocar perto da intensidade que se refere ou na 3ยช coluna
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71 read_util$table[paste0("T.test.result.", read_util$code)] <- NA;
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72 read_util$table[paste0("T.test.result.", read_util$code)] <- ttestresult;
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73 read_util$table[paste0("T.test.significant.", read_util$code)] <- NA;
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74 read_util$table[paste0("T.test.significant.", read_util$code)] <- ttestsignificant;
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75
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78
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79 # write out the read_util$table
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80 writeout(options$outputfile_name, read_util$table);