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planemo upload commit 13e72e84c523bda22bda792bbebf4720d28542d5-dirty
author labis-app
date Fri, 10 Aug 2018 15:45:44 -0400
parents ba070efb6f78
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ba070efb6f78 planemo upload commit 13e72e84c523bda22bda792bbebf4720d28542d5-dirty
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1 # auxiliar script to help with the read of all R scripts
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2 read_function <- function(options) {
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4 # reads the table from input
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5 table <- read.delim(options$inputfile_name, header=TRUE, fill=TRUE);
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7 # get the defined regex from the requested type
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8 if (options$type == "lfqlog2") {
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9 regexpr <- "LFQ[.]intensity[.]([^[:digit:]]+)[[:digit:]]+";
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10 code <- "LFQ";
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11 } else if (options$type == "intensity") {
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12 regexpr <- "Intensity[.]([^[:digit:]]+)[[:digit:]]+";
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13 code <- "INT";
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14 } else {
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15 regexpr <- "MS[.]MS[.]Count[.]([^[:digit:]]+)[[:digit:]]+";
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16 code <- "MS";
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17 }
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18 if (!(TRUE %in% grepl(regexpr, colnames(table)))) {
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19 print (sprintf("Error: No columns of type %s in input table", code));
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20 q(1,save="no");
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21 }
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23 # define the columns that will be taken in account for the t-test
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24 columns_names <- grep(regexpr, colnames(table), value=TRUE);
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26 # here I extract the different experiment names in an array for easier
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27 # manipulation, ordering them
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28 experiment_names <- mixedsort(gsub(".*[.]([^[:digit:]]+[[:digit:]]+).*", "\\1",
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29 columns_names));
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30
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31 # extract from the experiment names all the different categories in the table
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32 different_categories <- unique(gsub("([^[:digit:]]+).*", "\\1",
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33 experiment_names));
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34
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35 read_list <- list(table=table, regex=regexpr, code=code, col_names=columns_names, ex_names=experiment_names, diff_cat=different_categories);
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36
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37 return(read_list);
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38 }