annotate get_expression_profiles.R @ 10:48b767deb90b draft

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author proteore
date Wed, 13 Mar 2019 09:23:41 -0400
parents 2c0bab71a436
children 56c93d1fc8fd
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8
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1 # Read file and return file content as data.frame
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2 read_file <- function(path,header){
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3 file <- try(read.csv(path,header=header, sep="\t",stringsAsFactors = FALSE, quote="\"", check.names = F),silent=TRUE)
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4 if (inherits(file,"try-error")){
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5 stop("File not found !")
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6 }else{
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7 return(file)
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8 }
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9 }
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10
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11 str2bool <- function(x){
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12 if (any(is.element(c("t","true"),tolower(x)))){
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13 return (TRUE)
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14 }else if (any(is.element(c("f","false"),tolower(x)))){
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15 return (FALSE)
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16 }else{
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17 return(NULL)
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18 }
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19 }
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20
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21 # input has to be a list of IDs in ENSG format
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22 # tissue is one of unique(HPA.normal.tissue$Tissue)
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23 # level is one, or several, or 0 (=ALL) of "Not detected", "Medium", "High", "Low"
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24 # reliability is one, or several, or 0 (=ALL) of "Approved", "Supported", "Uncertain"
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25 annot.HPAnorm<-function(input, HPA_normal_tissue, tissue, level, reliability, not_mapped_option) {
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26 dat <- subset(HPA_normal_tissue, Gene %in% input)
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27 res.Tissue<-subset(dat, Tissue %in% tissue)
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28 res.Level<-subset(res.Tissue, Level %in% level)
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29 res.Rel<-subset(res.Level, Reliability %in% reliability)
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30
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31 if (not_mapped_option) {
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32 if (length(setdiff(intersect(input, unique(dat$Gene)), unique(res.Rel$Gene)))>0) {
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33 not_match_IDs <- matrix(setdiff(intersect(input, unique(dat$Gene)), unique(res.Rel$Gene)), ncol = 1, nrow = length(setdiff(intersect(input, unique(dat$Gene)), unique(res.Rel$Gene))))
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34 not.match <- matrix("no match", ncol = ncol(HPA_normal_tissue) - 1, nrow = length(not_match_IDs))
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35 not.match <- cbind(not_match_IDs, unname(not.match))
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36 colnames(not.match) <- colnames(HPA_normal_tissue)
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37 res <- rbind(res.Rel, not.match)
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38 } else {
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39 res <- res.Rel
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40 }
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41
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42 if (length(setdiff(input, unique(dat$Gene)))>0) {
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43 not.mapped <- matrix(ncol = ncol(HPA_normal_tissue) - 1, nrow = length(setdiff(input, unique(dat$Gene))))
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44 not.mapped <- cbind(matrix(setdiff(input, unique(dat$Gene)), ncol = 1, nrow = length(setdiff(input, unique(dat$Gene)))), unname(not.mapped))
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45 colnames(not.mapped) <- colnames(HPA_normal_tissue)
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46 res <- rbind(res, not.mapped)
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47 }
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48
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49 } else {
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50 res <- res.Rel
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51 }
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52
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53 return(res)
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54
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55 }
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56
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57 annot.HPAcancer<-function(input, HPA_cancer_tissue, cancer, not_mapped_option) {
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58 dat <- subset(HPA_cancer_tissue, Gene %in% input)
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59 res.Cancer<-subset(dat, Cancer %in% cancer)
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60
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61 if (not_mapped_option) {
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62 not.mapped <- matrix(ncol=ncol(HPA_cancer_tissue)-1, nrow=length(setdiff(input, unique(dat$Gene))))
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63 not.mapped <- cbind(matrix(setdiff(input, unique(dat$Gene)), ncol = 1, nrow = length(setdiff(input, unique(dat$Gene)))), unname(not.mapped))
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64 colnames(not.mapped) <- colnames(HPA_cancer_tissue)
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65 res <- rbind(res.Cancer, not.mapped)
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66 } else {
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67 res <- res.Cancer
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68 }
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69 return(res)
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70 }
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71
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72
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73 main <- function() {
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74 args <- commandArgs(TRUE)
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75 if(length(args)<1) {
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76 args <- c("--help")
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77 }
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78
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79 # Help section
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80 if("--help" %in% args) {
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81 cat("Selection and Annotation HPA
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82 Arguments:
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83 --ref_file: HPA normal/cancer tissue file path
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84 --input_type: type of input (list of id or filename)
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85 --input: list of IDs in ENSG format
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86 --column_number: the column number which you would like to apply...
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87 --header: true/false if your file contains a header
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88 --atlas: normal/cancer
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89 if normal:
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90 --tissue: list of tissues
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91 --level: Not detected, Low, Medium, High
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92 --reliability: Supportive, Uncertain
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93 if cancer:
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94 --cancer: Cancer tissues
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95 --not_mapped: true/false if your output file should contain not-mapped and not-match IDs
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96 --output: output filename \n")
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97 q(save="no")
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98 }
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99
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100 # Parse arguments
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101 parseArgs <- function(x) strsplit(sub("^--", "", x), "=")
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102 argsDF <- as.data.frame(do.call("rbind", parseArgs(args)))
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103 args <- as.list(as.character(argsDF$V2))
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104 names(args) <- argsDF$V1
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105
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106 #save(args,file = "/home/dchristiany/proteore_project/ProteoRE/tools/Get_expression_profiles/args.rda")
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107 #load("/home/dchristiany/proteore_project/ProteoRE/tools/Get_expression_profiles/args.rda")
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108
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109 # Extract input
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110 input_type = args$input_type
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111 if (input_type == "list") {
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112 list_id = strsplit(args$input, "[ \t\n]+")[[1]]
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113 } else if (input_type == "file") {
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114 filename = args$input
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115 column_number = as.numeric(gsub("c", "" ,args$column_number))
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116 header = str2bool(args$header)
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117 file = read_file(filename, header)
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118 list_id = sapply(strsplit(file[,column_number], ";"), "[", 1)
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119 }
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120 input = list_id
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121
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122 # Read reference file
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123 reference_file = read_file(args$ref_file, TRUE)
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124
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125 # Extract other options
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126 atlas = args$atlas
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127 not_mapped_option = str2bool(args$not_mapped)
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128 if (atlas=="normal") {
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129 tissue = strsplit(args$tissue, ",")[[1]]
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130 level = strsplit(args$level, ",")[[1]]
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131 reliability = strsplit(args$reliability, ",")[[1]]
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132 # Calculation
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133 res = annot.HPAnorm(input, reference_file, tissue, level, reliability, not_mapped_option)
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134 } else if (atlas=="cancer") {
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135 cancer = strsplit(args$cancer, ",")[[1]]
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136 # Calculation
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137 res = annot.HPAcancer(input, reference_file, cancer, not_mapped_option)
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138 }
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139
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140 # Write output
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141 output = args$output
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142 res <- apply(res, c(1,2), function(x) gsub("^$|^ $", NA, x))
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143 write.table(res, output, sep = "\t", quote = FALSE, row.names = FALSE)
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144 }
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145
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146 main()