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annotate pathifier.R @ 1:0960bd1161fa draft default tip

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planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/main/tools/pathifier commit f7363f7c391bd501fc4d1c10aaf372ec2bd82732
author artbio
date Mon, 12 Feb 2024 23:57:01 +0000
parents fec313f5c889
children
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fec313f5c889 "planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/pathifier commit b94cfc7bf8df30aa8e9249b75ea31332ee2bada1"
artbio
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1 ##################################################################################################
fec313f5c889 "planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/pathifier commit b94cfc7bf8df30aa8e9249b75ea31332ee2bada1"
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2 # Running PATHIFIER (Drier et al., 2013)
fec313f5c889 "planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/pathifier commit b94cfc7bf8df30aa8e9249b75ea31332ee2bada1"
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3 # Based on the work of Author: Miguel Angel Garcia-Campos - Github: https://github.com/AngelCampos
fec313f5c889 "planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/pathifier commit b94cfc7bf8df30aa8e9249b75ea31332ee2bada1"
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4 ##################################################################################################
fec313f5c889 "planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/pathifier commit b94cfc7bf8df30aa8e9249b75ea31332ee2bada1"
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5
fec313f5c889 "planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/pathifier commit b94cfc7bf8df30aa8e9249b75ea31332ee2bada1"
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6
1
0960bd1161fa planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/main/tools/pathifier commit f7363f7c391bd501fc4d1c10aaf372ec2bd82732
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7 options(show.error.messages = FALSE, error = function() {
0960bd1161fa planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/main/tools/pathifier commit f7363f7c391bd501fc4d1c10aaf372ec2bd82732
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8 cat(geterrmessage(), file = stderr())
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9 q("no", 1, FALSE)
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10 })
0
fec313f5c889 "planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/pathifier commit b94cfc7bf8df30aa8e9249b75ea31332ee2bada1"
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11 # we need that to not crash galaxy with an UTF8 error on German LC settings.
fec313f5c889 "planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/pathifier commit b94cfc7bf8df30aa8e9249b75ea31332ee2bada1"
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12 loc <- Sys.setlocale("LC_MESSAGES", "en_US.UTF-8")
fec313f5c889 "planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/pathifier commit b94cfc7bf8df30aa8e9249b75ea31332ee2bada1"
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13
fec313f5c889 "planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/pathifier commit b94cfc7bf8df30aa8e9249b75ea31332ee2bada1"
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14 library(pathifier)
fec313f5c889 "planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/pathifier commit b94cfc7bf8df30aa8e9249b75ea31332ee2bada1"
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15 library(optparse)
fec313f5c889 "planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/pathifier commit b94cfc7bf8df30aa8e9249b75ea31332ee2bada1"
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16 library(pheatmap)
fec313f5c889 "planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/pathifier commit b94cfc7bf8df30aa8e9249b75ea31332ee2bada1"
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17 library(scatterplot3d)
fec313f5c889 "planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/pathifier commit b94cfc7bf8df30aa8e9249b75ea31332ee2bada1"
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18 library(circlize)
fec313f5c889 "planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/pathifier commit b94cfc7bf8df30aa8e9249b75ea31332ee2bada1"
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19
fec313f5c889 "planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/pathifier commit b94cfc7bf8df30aa8e9249b75ea31332ee2bada1"
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20 option_list <- list(
1
0960bd1161fa planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/main/tools/pathifier commit f7363f7c391bd501fc4d1c10aaf372ec2bd82732
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21 make_option(
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22 "--exp",
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23 type = "character",
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24 help = "Expression matrix"
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25 ),
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26 make_option(
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27 "--sep",
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28 type = "character",
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29 default = "\t",
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30 help = "File separator [default : '%default']"
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31 ),
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32 make_option(
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33 "--genes",
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34 type = "character",
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35 help = "Gene sets Pathways : gmt format (one pathway per line : Name, description, genes (one by column), tab separated)"
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36 ),
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37 make_option(
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38 "--is_normal",
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39 default = FALSE,
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40 type = "logical",
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41 help = "Define normals cells in your data"
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42 ),
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43 make_option(
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44 "--normals",
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45 type = "character",
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46 help = "A vector of sample status : 1 = Healthy, 0 = Tumor. Must be in the same order as in expression data"
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47 ),
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48 make_option(
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49 "--logfile",
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50 type = "character",
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51 default = "log.txt",
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52 help = "Log file name [default : '%default']"
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53 ),
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54 make_option(
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55 "--max_stability",
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56 type = "logical",
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57 default = TRUE,
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58 help = "If true, throw away components leading to low stability of sampling noise [default : '%default']"
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59 ),
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60 make_option(
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61 "--attempts",
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62 type = "integer",
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63 default = 10,
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64 help = "Number of runs to determine stability. [default : '%default']"
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65 ),
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66 make_option(
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67 "--min_std",
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68 type = "character",
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69 default = "0.4",
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70 help = "Minimum of standard deviation to filter out low variable genes.
0
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71 Use --min.std data, to use the minimum std of your data [default : '%default']"
1
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72 ),
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73 make_option(
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74 "--min_exp",
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75 type = "character",
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76 default = "4",
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77 help = "Minimum of gene expression to filter out low expressed genes.
0
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78 Use --min.exp data, to use the minimum expression of your data [default : '%default']"
1
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79 ),
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80 make_option(
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81 "--pds",
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82 type = "character",
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83 default = "PDS.tsv",
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84 help = "Output PDS (Pathway deregulation score) of Pathifier in tabular file [default : '%default']"
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85 ),
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86 make_option(
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87 "--heatmap_cluster_cells",
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88 type = "logical",
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89 default = TRUE,
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90 help = "Cluster columns (cells) in the heatmap [default : '%default']"
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91 ),
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92 make_option(
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93 "--heatmap_cluster_pathways",
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94 type = "logical",
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95 default = TRUE,
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96 help = "Cluster rows (pathways) in the heatmap [default : '%default']"
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97 ),
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98 make_option(
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99 "--heatmap_show_cell_labels",
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100 type = "logical",
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101 default = FALSE,
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102 help = "Print column names (cells) on the heatmap [default : '%default']"
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103 ),
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104 make_option(
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105 "--heatmap_show_pathway_labels",
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106 type = "logical",
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107 default = FALSE,
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108 help = "Print row names (pathways) on the heatmap [default : '%default']"
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109 ),
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110 make_option(
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111 "--plot",
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112 type = "character",
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113 default = "./plot.pdf",
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114 help = "Pathifier visualization [default : '%default']"
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115 ),
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116 make_option(
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117 "--rdata",
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118 type = "character",
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119 default = "./results.rdata",
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120 help = "Pathifier object (S4) [default : '%default']"
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121 )
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122 )
0
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123 parser <- OptionParser(usage = "%prog [options] file", option_list = option_list)
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124 args <- parse_args(parser)
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125 if (args$sep == "tab") {
1
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126 args$sep <- "\t"
0
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127 }
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128
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129
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130 # set seed for reproducibility
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131 set.seed(123)
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132
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133 # Load expression data for PATHIFIER
1
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134 exp_matrix <- as.matrix(read.delim(
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135 file = args$exp,
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136 as.is = TRUE,
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137 row.names = 1,
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138 sep = args$sep,
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139 check.names = FALSE
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140 ))
0
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141
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142 # Load Genesets annotation
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143 gene_sets_file <- file(args$genes, open = "r")
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144 gene_sets <- readLines(gene_sets_file)
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145 close(gene_sets_file)
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146
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147 # Generate a list that contains genes in genesets
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148 gs <- strsplit(gene_sets, "\t")
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149 names(gs) <- lapply(gs, function(x) x[1])
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150 gs <- lapply(gs, function(x) x[-c(1:2)])
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151
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152 # Generate a list that contains the names of the genesets used
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153 pathwaynames <- names(gs)
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154
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155 # Prepare data and parameters ##################################################
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156 # Extract information from binary phenotypes. 1 = Normal, 0 = Tumor
1
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157 if (args$is_normal == TRUE) {
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158 normals <- read.delim(file = args$normals, h = FALSE)
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159 normals <- as.logical(normals[, 2])
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160 n_exp_matrix <- exp_matrix[, normals]
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161 } else {
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162 n_exp_matrix <- exp_matrix
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163 }
0
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164
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165 # Calculate MIN_STD
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166 rsd <- apply(n_exp_matrix, 1, sd)
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167 min_std <- quantile(rsd, 0.25)
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168
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169 # Calculate MIN_EXP
1
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170 min_exp <- quantile(
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171 as.vector(as.matrix(exp_matrix)),
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172 0.1
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173 ) # Percentile 10 of data
0
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174
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175 # Filter low value genes. At least 10% of samples with values over min_exp
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176 # Set expression levels < MIN_EXP to MIN_EXP
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177 over <- apply(exp_matrix, 1, function(x) x > min_exp)
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178 g_over <- apply(over, 2, mean)
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179 g_over <- names(g_over)[g_over > 0.1]
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180 exp_matrix_filtered <- exp_matrix[g_over, ]
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181 exp_matrix_filtered[exp_matrix_filtered < min_exp] <- min_exp
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182
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183 # Set maximum 5000 genes with more variance
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184 variable_genes <- names(sort(apply(exp_matrix_filtered, 1, var), decreasing = TRUE))[1:5000]
0
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185 variable_genes <- variable_genes[!is.na(variable_genes)]
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186 exp_matrix_filtered <- exp_matrix_filtered[variable_genes, ]
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187 allgenes <- as.vector(rownames(exp_matrix_filtered))
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188
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189
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190 if (args$min_std == "data") {
1
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191 args$min_std <- min_std
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192 } else {
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193 args$min_std <- as.numeric(args$min_std)
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194 }
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195
fec313f5c889 "planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/pathifier commit b94cfc7bf8df30aa8e9249b75ea31332ee2bada1"
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196 if (args$min_exp == "data") {
1
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197 args$min_exp <- min_exp
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198 } else {
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199 args$min_exp <- as.numeric(args$min_exp)
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200 }
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201
fec313f5c889 "planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/pathifier commit b94cfc7bf8df30aa8e9249b75ea31332ee2bada1"
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202
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203 # Open pdf
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204 pdf(args$plot)
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205
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206 # Construct continuous color scale
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207 col_score_fun <- colorRamp2(c(0, 0.5, 1), c("#4575B4", "#FFFFBF", "#D73027"))
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208
fec313f5c889 "planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/pathifier commit b94cfc7bf8df30aa8e9249b75ea31332ee2bada1"
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209 # Run Pathifier
1
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210 if (args$is_normal == TRUE) {
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211 pds <- quantify_pathways_deregulation(exp_matrix_filtered,
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212 allgenes,
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213 gs,
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214 pathwaynames,
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215 normals,
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216 maximize_stability = args$max_stability,
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217 attempts = args$attempts,
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218 logfile = args$logfile,
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219 min_std = args$min_std,
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220 min_exp = args$min_exp
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221 )
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222 for (i in pathwaynames) {
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223 df <- data.frame(pds$curves[[i]][, 1:3],
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224 normal = normals,
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225 PDS = as.numeric(pds$scores[[i]]),
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226 curve_order = as.vector(pds$curves_order[[i]])
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227 )
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228 ordered <- df[df$curve_order, ]
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229
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230
1
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231 layout(cbind(1:2, 1:2), heights = c(7, 1))
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232 sc3 <- scatterplot3d(ordered[, 1:3],
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233 main = paste("Principal curve of", i),
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234 box = FALSE, pch = 19, type = "l"
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235 )
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236 sc3$points3d(ordered[, 1:3],
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237 box = FALSE, pch = 19,
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238 col = col_score_fun(ordered$PDS)
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239 )
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240
1
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241 # Plot color scale legend
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242 par(mar = c(5, 3, 0, 3))
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243 plot(seq(min(ordered$PDS), max(ordered$PDS), length = 100), rep(0, 100),
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244 pch = 15,
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245 axes = TRUE, yaxt = "n", xlab = "Color scale of PDS", ylab = "", bty = "n",
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246 col = col_score_fun(seq(min(ordered$PDS), max(ordered$PDS), length = 100))
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247 )
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248
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249
1
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250 cols_status <- ifelse(ordered$normal, "blue", "red")
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251 sc3 <- scatterplot3d(ordered[, 1:3],
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252 main = paste("Principal curve of", i),
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253 box = FALSE, pch = "", type = "l"
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254 )
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255 sc3$points3d(ordered[, 1:3],
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256 box = FALSE,
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257 pch = ifelse(ordered$normal, 19, 8),
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258 col = ifelse(ordered$normal, "blue", "red")
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259 )
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260 legend("topright",
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261 pch = c(19, 8), yjust = 0,
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262 legend = c("normal", "cancer"),
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263 col = c("blue", "red"), cex = 1.1
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264 )
0
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265
1
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266 ## annotation for heatmap
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267 sample_status <- data.frame(Status = factor(ifelse(df$normal, "normal", "tumor")))
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268 rownames(sample_status) <- colnames(exp_matrix_filtered)
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269 color_status_heatmap <- list(Status = c(normal = "blue", tumor = "red"))
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270 }
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271 } else {
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272 pds <- quantify_pathways_deregulation(exp_matrix_filtered,
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273 allgenes,
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274 gs,
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275 pathwaynames,
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276 maximize_stability = args$max_stability,
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277 attempts = args$attempts,
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278 logfile = args$logfile,
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279 min_std = args$min_std,
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280 min_exp = args$min_exp
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281 )
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282 for (i in pathwaynames) {
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283 df <- data.frame(pds$curves[[i]][, 1:3],
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284 PDS = as.numeric(pds$scores[[i]]),
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285 curve_order = as.vector(pds$curves_order[[i]])
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286 )
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287 ordered <- df[df$curve_order, ]
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288
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289 layout(cbind(1:2, 1:2), heights = c(7, 1))
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290 sc3 <- scatterplot3d(ordered[, 1:3],
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291 main = paste("Principal curve of", i),
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292 box = FALSE, pch = 19, type = "l"
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293 )
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294 sc3$points3d(ordered[, 1:3],
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295 box = FALSE, pch = 19,
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296 col = col_score_fun(ordered$PDS)
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297 )
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298
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299 # Plot color scale legend
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300 par(mar = c(5, 3, 0, 3))
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301 plot(seq(min(ordered$PDS), max(ordered$PDS), length = 100), rep(0, 100),
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302 pch = 15,
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303 axes = TRUE, yaxt = "n", xlab = "Color scale of PDS", ylab = "", bty = "n",
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304 col = col_score_fun(seq(min(ordered$PDS), max(ordered$PDS), length = 100))
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305 )
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306
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307
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308 ## annotation for heatmap (for the moment none for this situation)
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309 sample_status <- NA
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310 color_status_heatmap <- NA
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311 }
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312 }
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313
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314 ## Create dataframe from Pathifier list and round score to 4 digits
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315 pds_scores <- mapply(FUN = function(x) cbind(round(x, 4)), pds$scores)
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316 dimnames(pds_scores) <- list(colnames(exp_matrix_filtered), names(pds$scores))
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317
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318 ## plot heatmap
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319 if (ncol(pds_scores) > 1) {
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320 pheatmap(t(pds_scores),
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321 main = "Heatmap of Pathway Deregulation Score", # heat map title
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322 cluster_rows = args$heatmap_cluster_pathways, # apply clustering method
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323 cluster_cols = args$heatmap_cluster_cells, # apply clustering method
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324
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325 # Additional Options
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326 ## Color labeled columns
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327 annotation_col = sample_status,
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328 annotation_colors = color_status_heatmap,
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329 show_rownames = args$heatmap_show_pathway_labels,
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330 show_colnames = args$heatmap_show_cell_labels,
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331 border_color = NA,
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332 legend = TRUE
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333 )
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334 }
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335 dev.off()
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336
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337
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338 ## write table
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339 write.table(pds_scores,
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340 args$pds,
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341 row.names = TRUE,
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342 col.names = TRUE,
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343 quote = FALSE,
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344 sep = "\t"
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345 )
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346
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347 ## write S4 pathifier object
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348 save(pds, file = args$rdata)