annotate segmentation_tool.xml @ 5:25e1e84cfe1b draft

planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_segmentation commit a7be47698f53eb4f00961192327d93e8989276a7
author galaxyp
date Mon, 11 Jun 2018 17:32:53 -0400
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1 <tool id="mass_spectrometry_imaging_segmentations" name="MSI segmentation" version="1.10.0.1">
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2 <description>mass spectrometry imaging spatial clustering</description>
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3 <requirements>
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4 <requirement type="package" version="1.10.0">bioconductor-cardinal</requirement>
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5 <requirement type="package" version="2.2.1">r-gridextra</requirement>
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6 <requirement type="package" version="0.20-35">r-lattice</requirement>
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7 </requirements>
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8 <command detect_errors="exit_code">
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9 <![CDATA[
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11 #if $infile.ext == 'imzml'
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12 ln -s '${infile.extra_files_path}/imzml' infile.imzML &&
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13 ln -s '${infile.extra_files_path}/ibd' infile.ibd &&
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14 #elif $infile.ext == 'analyze75'
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15 ln -s '${infile.extra_files_path}/hdr' infile.hdr &&
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16 ln -s '${infile.extra_files_path}/img' infile.img &&
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17 ln -s '${infile.extra_files_path}/t2m' infile.t2m &&
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18 #else
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19 ln -s $infile infile.RData &&
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20 #end if
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21 cat '${MSI_segmentation}' &&
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22 echo ${MSI_segmentation} &&
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23 Rscript '${MSI_segmentation}'
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24
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25 ]]>
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26 </command>
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27 <configfiles>
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28 <configfile name="MSI_segmentation"><![CDATA[
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31 ################################# load libraries and read file #################
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32
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33 library(Cardinal)
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34 library(gridExtra)
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35 library(lattice)
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36
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37 ## Read MALDI Imaging dataset
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38
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39 #if $infile.ext == 'imzml'
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40 msidata = readImzML('infile')
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41 #elif $infile.ext == 'analyze75'
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42 msidata = readAnalyze('infile')
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43 #else
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44 load('infile.RData')
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45 #end if
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46
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47 ###################################### file properties in numbers ##############
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48
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49 ## Number of features (m/z)
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50 maxfeatures = length(features(msidata))
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51 ## Range m/z
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52 minmz = round(min(mz(msidata)), digits=2)
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53 maxmz = round(max(mz(msidata)), digits=2)
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54 ## Number of spectra (pixels)
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55 pixelcount = length(pixels(msidata))
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56 ## Range x coordinates
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57 minimumx = min(coord(msidata)[,1])
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58 maximumx = max(coord(msidata)[,1])
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59 ## Range y coordinates
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60 minimumy = min(coord(msidata)[,2])
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61 maximumy = max(coord(msidata)[,2])
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62 ## Range of intensities
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63 minint = round(min(spectra(msidata)[]), digits=2)
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64 maxint = round(max(spectra(msidata)[]), digits=2)
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65 medint = round(median(spectra(msidata)[]), digits=2)
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66 ## Number of intensities > 0
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67 npeaks= sum(spectra(msidata)[]>0)
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68 ## Spectra multiplied with m/z (potential number of peaks)
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69 numpeaks = ncol(spectra(msidata)[])*nrow(spectra(msidata)[])
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70 ## Percentage of intensities > 0
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71 percpeaks = round(npeaks/numpeaks*100, digits=2)
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72 ## Number of empty TICs
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73 TICs = colSums(spectra(msidata)[])
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74 NumemptyTIC = sum(TICs == 0)
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75
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76 ## Processing informations
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77 processinginfo = processingData(msidata)
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78 centroidedinfo = processinginfo@centroided # TRUE or FALSE
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79
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80 ## if TRUE write processinginfo if FALSE write FALSE
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81
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82 ## normalization
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83 if (length(processinginfo@normalization) == 0) {
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84 normalizationinfo='FALSE'
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85 } else {
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86 normalizationinfo=processinginfo@normalization
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87 }
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88 ## smoothing
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89 if (length(processinginfo@smoothing) == 0) {
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90 smoothinginfo='FALSE'
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91 } else {
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92 smoothinginfo=processinginfo@smoothing
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93 }
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94 ## baseline
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95 if (length(processinginfo@baselineReduction) == 0) {
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96 baselinereductioninfo='FALSE'
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97 } else {
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98 baselinereductioninfo=processinginfo@baselineReduction
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99 }
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100 ## peak picking
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101 if (length(processinginfo@peakPicking) == 0) {
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102 peakpickinginfo='FALSE'
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103 } else {
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104 peakpickinginfo=processinginfo@peakPicking
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105 }
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106
5
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107 properties = c("Number of m/z features",
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108 "Range of m/z values [Da]",
0
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109 "Number of pixels",
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110 "Range of x coordinates",
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111 "Range of y coordinates",
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112 "Range of intensities",
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113 "Median of intensities",
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114 "Intensities > 0",
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115 "Number of zero TICs",
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116 "Preprocessing",
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117 "Normalization",
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118 "Smoothing",
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119 "Baseline reduction",
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120 "Peak picking",
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121 "Centroided")
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122
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123 values = c(paste0(maxfeatures),
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124 paste0(minmz, " - ", maxmz),
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125 paste0(pixelcount),
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126 paste0(minimumx, " - ", maximumx),
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127 paste0(minimumy, " - ", maximumy),
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128 paste0(minint, " - ", maxint),
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129 paste0(medint),
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130 paste0(percpeaks, " %"),
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131 paste0(NumemptyTIC),
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132 paste0(" "),
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133 paste0(normalizationinfo),
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134 paste0(smoothinginfo),
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135 paste0(baselinereductioninfo),
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136 paste0(peakpickinginfo),
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137 paste0(centroidedinfo))
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138
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139 property_df = data.frame(properties, values)
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140
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141
4
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142 ######################################## PDF ###################################
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143 ################################################################################
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144 ################################################################################
0
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145
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146
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147 pdf("segmentationpdf.pdf", fonts = "Times", pointsize = 12)
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148 plot(0,type='n',axes=FALSE,ann=FALSE)
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149
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150 title(main=paste0("Spatial segmentation for file: \n\n", "$infile.display_name"))
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151
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152
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153 ############################# I) numbers ####################################
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154 #############################################################################
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155 grid.table(property_df, rows= NULL)
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156
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157 if (npeaks > 0)
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158 {
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159
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160
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161 ######################## II) segmentation tools #############################
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162 #############################################################################
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163 #set $color_string = ','.join(['"%s"' % $color.feature_color for $color in $colours])
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164 colourvector = c($color_string)
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165
5
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166 ### preparation for images and plots:
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167 #if str($image_cond.image_type) == "standard_image":
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168 print("standard image")
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169
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170 strip_input = TRUE
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171 lattice_input = FALSE
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172
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173 #elif str($image_cond.image_type) == "lattice_image":
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174 print("lattice image")
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175
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176 strip_input = strip.custom(bg="lightgrey", par.strip.text=list(col="black", cex=.9))
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177 lattice_input = TRUE
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178
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179 #end if
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180
0
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181
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182 #if str( $segm_cond.segmentationtool ) == 'pca':
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183 print('pca')
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184 ##pca
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185
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186 component_vector = character()
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187 for (numberofcomponents in 1:$segm_cond.pca_ncomp)
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188 {component_vector[numberofcomponents]= paste0("PC", numberofcomponents)}
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189 pca = PCA(msidata, ncomp=$segm_cond.pca_ncomp, column = component_vector, superpose = FALSE,
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190 method = "$segm_cond.pca_method", scale = $segm_cond.pca_scale, layout = c(ncomp, 1))
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191
5
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192 print(image(pca, main="PCA image", lattice=lattice_input, strip = strip_input, col=colourvector))
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193 print(plot(pca, main="PCA plot", lattice=lattice_input, col= colourvector, strip = strip_input))
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194
5
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195 pcaloadings = (pca@resultData\$ncomp\$loadings) ### loading for each m/z value
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196 pcascores = (pca@resultData\$ncomp\$scores) ### scores for each pixel
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197
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198 write.table(pcaloadings, file="$mzfeatures", quote = FALSE, row.names = TRUE, col.names=NA, sep = "\t")
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199 write.table(pcascores, file="$pixeloutput", quote = FALSE, row.names = TRUE, col.names=NA, sep = "\t")
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200
5
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201 ## optional output as .RData
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202 #if $output_rdata:
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203
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204 ## save as (.RData)
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205 save(pca, file="$segmentation_rdata")
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206
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207 #end if
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208
0
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209 #elif str( $segm_cond.segmentationtool ) == 'kmeans':
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210 print('kmeans')
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211 ##k-means
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212
2
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213 skm = spatialKMeans(msidata, r=c($segm_cond.kmeans_r), k=c($segm_cond.kmeans_k), method="$segm_cond.kmeans_method")
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214 print(image(skm, key=TRUE, main="K-means clustering", lattice=lattice_input, strip=strip_input, col= colourvector, layout=c(1,1)))
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215
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216 print(plot(skm, main="K-means plot", lattice=lattice_input, col= colourvector, strip=strip_input, layout=c($segm_cond.kmeans_layout)))
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217
2
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218 skm_clusters = data.frame(matrix(NA, nrow = pixelcount, ncol = 0))
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219 for (iteration in 1:length(skm@resultData)){
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220 skm_cluster = ((skm@resultData)[[iteration]]\$cluster)
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221 skm_clusters = cbind(skm_clusters, skm_cluster) }
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222 colnames(skm_clusters) = names((skm@resultData))
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223
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224 skm_toplabels = topLabels(skm, n=$segm_cond.kmeans_toplabels)
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225
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226 write.table(skm_toplabels, file="$mzfeatures", quote = FALSE, row.names = TRUE, col.names=NA, sep = "\t")
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227 write.table(skm_clusters, file="$pixeloutput", quote = FALSE, row.names = TRUE, col.names=NA, sep = "\t")
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228
5
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229 ## optional output as .RData
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230 #if $output_rdata:
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231
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232 ## save as (.RData)
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233 save(skm, file="$segmentation_rdata")
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234
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235 #end if
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236
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237 #elif str( $segm_cond.segmentationtool ) == 'centroids':
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238 print('centroids')
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239 ##centroids
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240
2
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241 ssc = spatialShrunkenCentroids(msidata, r=c($segm_cond.centroids_r), k=c($segm_cond.centroids_k), s=c($segm_cond.centroids_s), method="$segm_cond.centroids_method")
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242 print(image(ssc, key=TRUE, main="Spatial shrunken centroids", lattice=lattice_input, strip = strip_input, col= colourvector,layout=c(1,1)))
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243 print(plot(ssc, main="Spatial shrunken centroids plot", lattice=lattice_input, col= colourvector, strip = strip_input,layout=c($segm_cond.centroids_layout)))
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244
2
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245 ssc_classes = data.frame(matrix(NA, nrow = pixelcount, ncol = 0))
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246 for (iteration in 1:length(ssc@resultData)){
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247 ssc_class = ((ssc@resultData)[[iteration]]\$classes)
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248 ssc_classes = cbind(ssc_classes, ssc_class) }
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249 colnames(ssc_classes) = names((ssc@resultData))
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250
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251 ssc_toplabels = topLabels(ssc, n=$segm_cond.centroids_toplabels)
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252
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253 write.table(ssc_toplabels, file="$mzfeatures", quote = FALSE, row.names = TRUE, col.names=NA, sep = "\t")
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254 write.table(ssc_classes, file="$pixeloutput", quote = FALSE, row.names = TRUE, col.names=NA, sep = "\t")
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255
5
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256 ## optional output as .RData
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257 #if $output_rdata:
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258
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259 ## save as (.RData)
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260 save(ssc, file="$segmentation_rdata")
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261
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262 #end if
0
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263
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264 #end if
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265
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266 dev.off()
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267
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268 }else{
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269 print("Inputfile has no intensities > 0")
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270 dev.off()
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271 }
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272
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273 ]]></configfile>
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274 </configfiles>
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275 <inputs>
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276 <param name="infile" type="data" format="imzml, rdata, analyze75"
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277 label="Inputfile as imzML, Analyze7.5 or Cardinal MSImageSet saved as RData"
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278 help="Upload composite datatype imzml (ibd+imzML) or analyze75 (hdr+img+t2m) or regular upload .RData (Cardinal MSImageSet)"/>
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279 <conditional name="segm_cond">
4
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280 <param name="segmentationtool" type="select" label="Select the tool for spatial clustering">
0
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281 <option value="pca" selected="True">pca</option>
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282 <option value="kmeans">k-means</option>
4
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283 <option value="centroids">spatial shrunken centroids</option>
0
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284 </param>
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285 <when value="pca">
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286 <param name="pca_ncomp" type="integer" value="2"
4
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287 label="The number of principal components to calculate"/>
0
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288 <param name="pca_method" type="select"
4
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289 label="The function used to calculate the singular value decomposition">
0
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290 <option value="irlba" selected="True">irlba</option>
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291 <option value="svd">svd</option>
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292 </param>
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293 <param name="pca_scale" type="select" display="radio" optional="False"
4
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294 label="Scaling of data before analysis">
0
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295 <option value="TRUE">yes</option>
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296 <option value="FALSE" selected="True">no</option>
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297 </param>
4
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298 </when>
0
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299
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300 <when value="kmeans">
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301 <param name="kmeans_r" type="text" value="2"
4
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302 label="The spatial neighborhood radius of nearby pixels to consider (r)" help="Multiple values are allowed (e.g. 1,2,3 or 2:5)"/>
0
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303 <param name="kmeans_k" type="text" value="3"
4
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304 label="The number of clusters (k)" help="Multiple values are allowed (e.g. 1,2,3 or 2:5)"/>
0
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305 <param name="kmeans_method" type="select" display="radio"
4
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306 label="The method to use to calculate the spatial smoothing kernels for the embedding. The 'gaussian' method refers to spatially-aware (SA) clustering, and 'adaptive' refers to spatially-aware structurally-adaptive (SASA) clustering">
0
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307 <option value="gaussian">gaussian</option>
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308 <option value="adaptive" selected="True">adaptive</option>
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309 </param>
2
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310 <param name="kmeans_toplabels" type="integer" value="500"
5
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311 label="Number of toplabels (m/z) which should be written in tabular output"/>
2
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312 <param name="kmeans_layout" type="text" value="1,1"
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313 label="Number of rows and columns to plot pictures in pdf output" help="e.g. 1,1 means 1 plot per page; 2,3 means 2 rows with 3 plots each = 6 plots per page"/>
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314 </when>
0
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315
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316 <when value="centroids">
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317 <param name="centroids_r" type="text" value="2"
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318 label="The spatial neighborhood radius of nearby pixels to consider (r)" help="Multiple values are allowed (e.g. 1,2,3 or 2:5)"/>
0
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319 <param name="centroids_k" type="text" value="5"
4
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320 label="The initial number of clusters (k)" help="Multiple values are allowed (e.g. 1,2,3 or 2:5)"/>
2
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321 <param name="centroids_s" type="text" value="2"
4
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322 label="The sparsity thresholding parameter by which to shrink the t-statistics (s)"
5
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323 help="As s increases, fewer m/z features (m/z values) will be used in the spatial segmentation, and only the informative m/z features will be retained. Multiple values are allowed (e.g. 1,2,3 or 2:5)"/>
4
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324 <param name="centroids_method" type="select" display="radio" label = "The method to use to calculate the spatial smoothing kernels for the embedding. The 'gaussian' method refers to spatially-aware (SA) weights, and 'adaptive' refers to spatially-aware structurally-adaptive (SASA) weights">
0
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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325 <option value="gaussian" selected="True">gaussian</option>
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326 <option value="adaptive">adaptive</option>
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327 </param>
2
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328 <param name="centroids_toplabels" type="integer" value="500"
5
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329 label="Number of toplabels (m/z) which should be written in tabular output"/>
2
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330 <param name="centroids_layout" type="text" value="1,1"
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331 label="Number of rows and columns to plot pictures in pdf output" help="e.g. 1,1 means 1 plot per page; 2,3 means 2 rows with 3 plots each = 6 plots per page"/>
0
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332 </when>
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333 </conditional>
5
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334 <conditional name="image_cond">
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335 <param name="image_type" type="select" label="Select the image type">
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336 <option value="standard_image" selected="True">standard</option>
25e1e84cfe1b planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_segmentation commit a7be47698f53eb4f00961192327d93e8989276a7
galaxyp
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diff changeset
337 <option value="lattice_image">lattice</option>
25e1e84cfe1b planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_segmentation commit a7be47698f53eb4f00961192327d93e8989276a7
galaxyp
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338 </param>
25e1e84cfe1b planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_segmentation commit a7be47698f53eb4f00961192327d93e8989276a7
galaxyp
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diff changeset
339 <when value="standard_image"/>
25e1e84cfe1b planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_segmentation commit a7be47698f53eb4f00961192327d93e8989276a7
galaxyp
parents: 4
diff changeset
340 <when value="lattice_image"/>
25e1e84cfe1b planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_segmentation commit a7be47698f53eb4f00961192327d93e8989276a7
galaxyp
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341 </conditional>
0
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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342 <repeat name="colours" title="Colours for the plots" min="1" max="50">
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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343 <param name="feature_color" type="color" label="Colours" value="#ff00ff" help="Numbers of columns should be the same as number of components">
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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344 <sanitizer>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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345 <valid initial="string.letters,string.digits">
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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diff changeset
346 <add value="#" />
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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347 </valid>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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348 </sanitizer>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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349 </param>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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350 </repeat>
5
25e1e84cfe1b planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_segmentation commit a7be47698f53eb4f00961192327d93e8989276a7
galaxyp
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351 <param name="output_rdata" type="boolean" display="radio" label="Results as .RData output"/>
0
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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352 </inputs>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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353 <outputs>
5
25e1e84cfe1b planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_segmentation commit a7be47698f53eb4f00961192327d93e8989276a7
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354 <data format="pdf" name="segmentationimages" from_work_dir="segmentationpdf.pdf" label = "$infile.display_name segmentation"/>
25e1e84cfe1b planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_segmentation commit a7be47698f53eb4f00961192327d93e8989276a7
galaxyp
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355 <data format="tabular" name="mzfeatures" label="$infile.display_name m/z features"/>
25e1e84cfe1b planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_segmentation commit a7be47698f53eb4f00961192327d93e8989276a7
galaxyp
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356 <data format="tabular" name="pixeloutput" label="$infile.display_name pixels"/>
25e1e84cfe1b planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_segmentation commit a7be47698f53eb4f00961192327d93e8989276a7
galaxyp
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357 <data format="rdata" name="segmentation_rdata" label="$infile.display_name segmentation">
25e1e84cfe1b planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_segmentation commit a7be47698f53eb4f00961192327d93e8989276a7
galaxyp
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358 <filter>output_rdata</filter>
25e1e84cfe1b planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_segmentation commit a7be47698f53eb4f00961192327d93e8989276a7
galaxyp
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359 </data>
0
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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360 </outputs>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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361 <tests>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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362 <test>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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diff changeset
363 <param name="infile" value="" ftype="imzml">
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
parents:
diff changeset
364 <composite_data value="Example_Continuous.imzML"/>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
parents:
diff changeset
365 <composite_data value="Example_Continuous.ibd"/>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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366 </param>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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367 <param name="segmentationtool" value="pca"/>
5
25e1e84cfe1b planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_segmentation commit a7be47698f53eb4f00961192327d93e8989276a7
galaxyp
parents: 4
diff changeset
368 <param name="image_type" value="lattice_image"/>
0
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
parents:
diff changeset
369 <repeat name="colours">
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
parents:
diff changeset
370 <param name="feature_color" value="#ff00ff"/>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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diff changeset
371 </repeat>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
parents:
diff changeset
372 <repeat name="colours">
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
parents:
diff changeset
373 <param name="feature_color" value="#0000FF"/>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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diff changeset
374 </repeat>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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diff changeset
375 <output name="segmentationimages" file="pca_imzml.pdf" compare="sim_size" delta="20000"/>
1
942c11934f50 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit edbf2a6cb50fb04d0db56a7557a64e3bb7a0806a
galaxyp
parents: 0
diff changeset
376 <output name="mzfeatures" file="loadings_pca.tabular" compare="sim_size"/>
942c11934f50 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit edbf2a6cb50fb04d0db56a7557a64e3bb7a0806a
galaxyp
parents: 0
diff changeset
377 <output name="pixeloutput" file="scores_pca.tabular" compare="sim_size"/>
0
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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378 </test>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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diff changeset
379 <test>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
parents:
diff changeset
380 <param name="infile" value="" ftype="analyze75">
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
parents:
diff changeset
381 <composite_data value="Analyze75.hdr" />
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
parents:
diff changeset
382 <composite_data value="Analyze75.img" />
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
parents:
diff changeset
383 <composite_data value="Analyze75.t2m" />
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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diff changeset
384 </param>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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diff changeset
385 <param name="segmentationtool" value="kmeans"/>
2
76d0244b1bbc planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit ed7d3e6f1a09c78c8f71cc1bdc1a20249767f646
galaxyp
parents: 1
diff changeset
386 <param name="kmeans_r" value="1:3"/>
76d0244b1bbc planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit ed7d3e6f1a09c78c8f71cc1bdc1a20249767f646
galaxyp
parents: 1
diff changeset
387 <param name="kmeans_k" value="2,3"/>
4
38afc994e3cc planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_segmentation commit 1c808d60243bb1eeda0cd26cb4b0a17ab05de2c0
galaxyp
parents: 3
diff changeset
388 <param name="kmeans_toplabels" value="20"/>
0
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
parents:
diff changeset
389 <repeat name="colours">
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
parents:
diff changeset
390 <param name="feature_color" value="#ff00ff"/>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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diff changeset
391 </repeat>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
parents:
diff changeset
392 <repeat name="colours">
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
parents:
diff changeset
393 <param name="feature_color" value="#0000FF"/>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
parents:
diff changeset
394 </repeat>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
parents:
diff changeset
395 <repeat name="colours">
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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diff changeset
396 <param name="feature_color" value="#00C957"/>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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diff changeset
397 </repeat>
5
25e1e84cfe1b planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_segmentation commit a7be47698f53eb4f00961192327d93e8989276a7
galaxyp
parents: 4
diff changeset
398 <param name="output_rdata" value="True"/>
4
38afc994e3cc planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_segmentation commit 1c808d60243bb1eeda0cd26cb4b0a17ab05de2c0
galaxyp
parents: 3
diff changeset
399 <output name="segmentationimages" file="kmeans_analyze.pdf" compare="sim_size" delta="20000"/>
1
942c11934f50 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit edbf2a6cb50fb04d0db56a7557a64e3bb7a0806a
galaxyp
parents: 0
diff changeset
400 <output name="mzfeatures" file="toplabels_skm.tabular" compare="sim_size"/>
942c11934f50 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit edbf2a6cb50fb04d0db56a7557a64e3bb7a0806a
galaxyp
parents: 0
diff changeset
401 <output name="pixeloutput" file="cluster_skm.tabular" compare="sim_size"/>
5
25e1e84cfe1b planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_segmentation commit a7be47698f53eb4f00961192327d93e8989276a7
galaxyp
parents: 4
diff changeset
402 <output name="pixeloutput" file="cluster_skm.tabular" compare="sim_size"/>
25e1e84cfe1b planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_segmentation commit a7be47698f53eb4f00961192327d93e8989276a7
galaxyp
parents: 4
diff changeset
403 <output name="segmentation_rdata" file="cluster_skm.RData" compare="sim_size"/>
0
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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diff changeset
404 </test>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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diff changeset
405 <test>
4
38afc994e3cc planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_segmentation commit 1c808d60243bb1eeda0cd26cb4b0a17ab05de2c0
galaxyp
parents: 3
diff changeset
406 <param name="infile" value="preprocessed.RData" ftype="rdata"/>
0
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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diff changeset
407 <param name="segmentationtool" value="centroids"/>
4
38afc994e3cc planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_segmentation commit 1c808d60243bb1eeda0cd26cb4b0a17ab05de2c0
galaxyp
parents: 3
diff changeset
408 <param name="centroids_r" value="1,2"/>
38afc994e3cc planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_segmentation commit 1c808d60243bb1eeda0cd26cb4b0a17ab05de2c0
galaxyp
parents: 3
diff changeset
409 <param name="centroids_k" value="5"/>
38afc994e3cc planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_segmentation commit 1c808d60243bb1eeda0cd26cb4b0a17ab05de2c0
galaxyp
parents: 3
diff changeset
410 <param name="centroids_toplabels" value="50"/>
0
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
parents:
diff changeset
411 <repeat name="colours">
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
parents:
diff changeset
412 <param name="feature_color" value="#0000FF"/>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
parents:
diff changeset
413 </repeat>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
parents:
diff changeset
414 <repeat name="colours">
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
parents:
diff changeset
415 <param name="feature_color" value="#00C957"/>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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diff changeset
416 </repeat>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
parents:
diff changeset
417 <repeat name="colours">
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
parents:
diff changeset
418 <param name="feature_color" value="#B0171F"/>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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diff changeset
419 </repeat>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
galaxyp
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420 <repeat name="colours">
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421 <param name="feature_color" value="#FFD700"/>
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422 </repeat>
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423 <repeat name="colours">
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424 <param name="feature_color" value="#848484"/>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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425 </repeat>
4
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426 <output name="segmentationimages" file="centroids_rdata.pdf" compare="sim_size" delta="20000"/>
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427 <output name="mzfeatures" file="toplabels_ssc.tabular" compare="sim_size"/>
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428 <output name="pixeloutput" file="classes_ssc.tabular" compare="sim_size"/>
0
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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429 </test>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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430 </tests>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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431 <help>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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432 <![CDATA[
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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433
4
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434 Cardinal is an R package that implements statistical & computational tools for analyzing mass spectrometry imaging datasets. `More information on Cardinal <http://cardinalmsi.org//>`_
38afc994e3cc planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_segmentation commit 1c808d60243bb1eeda0cd26cb4b0a17ab05de2c0
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435
5
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436 This tool provides three different Cardinal functions for unsupervised clustering/spatial segmentation of mass spectrometry imaging data.
0
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437
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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438 Input data: 3 types of input data can be used:
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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439
4
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440 - imzml file (upload imzml and ibd file via the "composite" function) `Introduction to the imzml format <https://ms-imaging.org/wp/imzml/>`_
0
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441 - Analyze7.5 (upload hdr, img and t2m file via the "composite" function)
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442 - Cardinal "MSImageSet" data (with variable name "msidata", saved as .RData)
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443
4
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444 Options:
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445
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446 - PCA: principal component analysis
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447 - k-means: patially-aware k-means clustering
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448 - spatial shrunken centroids: Allows the number of segments to decrease according to the data. This allows automatic selection of the number of clusters
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449
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450 Output:
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451
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452 - Pdf with the heatmaps and plots for the segmentation
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453 - Tabular file with information on m/z and pixels: loadings/scores (PCA), toplabels/clusters (k-means), toplabels/classes (spatial shrunken centroids)
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454 - Optional .RData file which contains the segmentation results and can be used for further exploration in R
4
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455
0
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456 ]]>
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457 </help>
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458 <citations>
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459 <citation type="doi">10.1093/bioinformatics/btv146</citation>
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460 </citations>
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461 </tool>