Mercurial > repos > proteore > proteore_heatmap_visualization

annotate heatmap_viz.R @ 3:07748b0136bb draft default tip

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planemo upload commit fb27a6b5de5cd7b269a41be3c85c593b77aa1b18-dirty
author proteore
date Thu, 27 Jun 2019 04:18:07 -0400
parents 99207b432ebc
children
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1 #!/usr/bin/Rscript
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2 options(warn=-1) #TURN OFF WARNINGS !!!!!!
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3
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4 suppressMessages(library('plotly',quietly = T))
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5 suppressMessages(library('heatmaply',quietly = T))
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7 #packageVersion('plotly')
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8
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9 get_args <- function(){
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10
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11 ## Collect arguments
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12 args <- commandArgs(TRUE)
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13
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14 ## Default setting when no arguments passed
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15 if(length(args) < 1) {
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16 args <- c("--help")
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17 }
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18
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19 ## Help section
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20 if("--help" %in% args) {
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21 cat("Pathview R script
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22 Arguments:
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23 --help Print this test
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24 --input path of the input file (must contains a colum of uniprot and/or geneID accession number)
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25 --output Output file
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26 --type type of output file, could be html, pdf, jpg or png
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27 --cols Columns to use for heatmap, exemple : '3:8' to use columns from the third to the 8th
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28 --row_names Column which contains row names
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29 --header True or False
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30 --col_text_angle Angle of columns label ; from -90 to 90 degres
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31 --dist_fun function used to compute the distance
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32
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33 Example:
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34 ./heatmap_viz.R --input='dat.nucl.norm.imputed.tsv' --output='heatmap.html' --cols='3:8' --row_names='2' --header=TRUE --col_text_angle=0 \n\n")
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35
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36 q(save="no")
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37 }
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38
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39 parseArgs <- function(x) strsplit(sub("^--", "", x), "=")
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40 argsDF <- as.data.frame(do.call("rbind", parseArgs(args)))
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41 args <- as.list(as.character(argsDF$V2))
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42 names(args) <- argsDF$V1
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43
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44 return(args)
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45 }
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46
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47 read_file <- function(path,header){
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48 file <- try(read.csv(path,header=header, sep="\t",stringsAsFactors = FALSE, quote="",fill=TRUE,check.names = F),silent=TRUE)
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49 if (inherits(file,"try-error")){
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50 stop("File not found !")
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51 }else{
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52 return(file)
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53 }
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54 }
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55
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56 #convert a string to boolean
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57 str2bool <- function(x){
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58 if (any(is.element(c("t","true"),tolower(x)))){
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59 return (TRUE)
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60 }else if (any(is.element(c("f","false"),tolower(x)))){
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61 return (FALSE)
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62 }else{
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63 return(NULL)
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64 }
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65 }
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66
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67 #remove remaining quote
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68 #only keep usefull columns
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69 #remove lines with at least one empty cell in a matrix between two defined columns
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70 clean_df <- function(mat,cols,rownames_col){
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71 uto = mat[,cols]
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72 uto <- as.data.frame(apply(uto,c(1,2),function(x) gsub(",",".",x)))
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73 uto <- as.data.frame(apply(uto,c(1,2),function(x) {ifelse(is.character(x),as.numeric(x),x)}))
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74 rownames(uto) <- mat[,rownames_col]
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75 #bad_lines <- which(apply(uto, 1, function(x) any(is.na(x))))
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76 #if (length(bad_lines) > 0) {
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77 # uto <- uto[- bad_lines,]
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78 # print(paste("lines",bad_lines, "has been removed: at least one non numeric content"))
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79 #}
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80 return(uto)
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81 }
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82
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83 get_cols <-function(input_cols) {
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84 input_cols <- gsub("c","",gsub("C","",gsub(" ","",input_cols)))
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85 if (grepl(":",input_cols)) {
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86 first_col=unlist(strsplit(input_cols,":"))[1]
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87 last_col=unlist(strsplit(input_cols,":"))[2]
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88 cols=first_col:last_col
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89 } else {
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90 cols = as.integer(unlist(strsplit(input_cols,",")))
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91 }
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92 return(cols)
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93 }
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94
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95 #get args
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96 args <- get_args()
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97
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98 #save(args,file="/home/dchristiany/proteore_project/ProteoRE/tools/heatmap_viz/args.rda")
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99 #load("/home/dchristiany/proteore_project/ProteoRE/tools/heatmap_viz/args.rda")
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100
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101 header=str2bool(args$header)
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102 output <- rapply(strsplit(args$output,"\\."),c) #remove extension
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103 output <- paste(output[1:length(output)-1],collapse=".")
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104 output <- paste(output,args$type,sep=".")
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105 cols = get_cols(args$cols)
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106 rownames_col = as.integer(gsub("c","",gsub("C","",gsub(" ","",args$row_names))))
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107 if (length(cols) <=1 ){
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108 stop("You need several colums to build a heatmap")
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109 }
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110 dist=args$dist
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111 clust=args$clust
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112 dendrogram=args$dendrogram
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113
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114 #cleaning data
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115 uto <- read_file(args$input,header)
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116 uto <- clean_df(uto,cols,rownames_col)
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117 uto <- uto[rowSums(is.na(uto)) != ncol(uto), ] #remove emptylines
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118
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119 if (header) {
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120 col_names = names(uto)
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121 } else {
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122 col_names = cols
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123 }
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124
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125 #building heatmap
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126 if (dist %in% c("pearson","spearman","kendall")){
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127 heatmaply(uto, file=output, margins=c(100,50,NA,0), plot_method="plotly", labRow = rownames(uto), labCol = col_names, distfun=dist,
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128 hclust_method = clust, dendrogram = dendrogram, grid_gap = 0,cexCol = 1, column_text_angle = as.numeric(args$col_text_angle),
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129 width = 1000, height=1000, colors = c('blue','green','yellow','red'))
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130 } else {
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131 heatmaply(uto, file=output, margins=c(100,50,NA,0), plot_method="plotly", labRow = rownames(uto), labCol = col_names, dist_method = dist,
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132 hclust_method = clust, dendrogram = dendrogram, grid_gap = 0,cexCol = 1, column_text_angle = as.numeric(args$col_text_angle),
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133 width = 1000, height=1000, colors = c('blue','green','yellow','red'))
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134 }
0
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135
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136 ####heatmaply
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137
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138 simulateExprData <- function(n, n0, p, rho0, rho1){ row
0
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139 # n: total number of subjects
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140 # n0: number of subjects with exposure 0
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141 # n1: number of subjects with exposure 1
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142 # p: number of genes
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143 # rho0: rho between Z_i and Z_j for subjects with exposure 0
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144 # rho1: rho between Z_i and Z_j for subjects with exposure 1
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145
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146 # Simulate gene expression values according to exposure 0 or 1,
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147 # according to a centered multivariate normal distribution with
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148 # covariance between Z_i and Z_j being rho^|i-j|
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149 n1 <- n - n0
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150 times <- 1:p
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151 H <- abs(outer(times, times, "-"))
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152 V0 <- rho0^H
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153 V1 <- rho1^H
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154
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155 # rows are people, columns are genes
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156 genes0 <- MASS::mvrnorm(n = n0, mu = rep(0,p), Sigma = V0)
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157 genes1 <- MASS::mvrnorm(n = n1, mu = rep(0,p), Sigma = V1)
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158 genes <- rbind(genes0,genes1)
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159 return(genes)
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160 }
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161
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162 #genes <- simulateExprData(n = 50, n0 = 25, p = 100, rho0 = 0.01, rho1 = 0.95)
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163
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164 #heatmaply(genes, k_row = 2, k_col = 2)
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165
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166 #heatmaply(cor(genes), k_row = 2, k_col = 2)
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167
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168
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169
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170
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171
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173