Mercurial > repos > galaxyp > mass_spectrometry_imaging_segmentations

annotate segmentation_tool.xml @ 3:ff5a4a795db6 draft

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planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_segmentation commit 06c2b45d8644b1d7fc01622a5c59dcbf8886d0f1
author galaxyp
date Mon, 23 Apr 2018 17:17:52 -0400
parents 76d0244b1bbc
children 38afc994e3cc
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ff5a4a795db6 planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_segmentation commit 06c2b45d8644b1d7fc01622a5c59dcbf8886d0f1
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1 <tool id="mass_spectrometry_imaging_segmentations" name="MSI segmentation" version="1.7.0.3">
0
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2 <description>tool for spatial clustering</description>
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3 <requirements>
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4 <requirement type="package" version="1.7.0">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="2.23-15">r-kernsmooth</requirement>
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7 <requirement type="package" version="0.20-35">r-lattice</requirement>
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8 </requirements>
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9 <command detect_errors="exit_code">
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10 <![CDATA[
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11
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12 #if $infile.ext == 'imzml'
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13 cp '${infile.extra_files_path}/imzml' infile.imzML &&
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14 cp '${infile.extra_files_path}/ibd' infile.ibd &&
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15 #elif $infile.ext == 'analyze75'
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16 cp '${infile.extra_files_path}/hdr' infile.hdr &&
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17 cp '${infile.extra_files_path}/img' infile.img &&
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18 cp '${infile.extra_files_path}/t2m' infile.t2m &&
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19 #else
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20 ln -s $infile infile.RData &&
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21 #end if
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22 cat '${MSI_segmentation}' &&
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23 echo ${MSI_segmentation} &&
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24 Rscript '${MSI_segmentation}'
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25
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26 ]]>
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27 </command>
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28 <configfiles>
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29 <configfile name="MSI_segmentation"><![CDATA[
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32 ################################# load libraries and read file #########################
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34
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35 library(Cardinal)
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36 library(gridExtra)
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37 library(KernSmooth)
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38 library(lattice)
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39
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40 ## Read MALDI Imaging dataset
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41
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42 #if $infile.ext == 'imzml'
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43 msidata = readMSIData('infile.imzML')
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44 #elif $infile.ext == 'analyze75'
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45 msidata = readMSIData('infile.hdr')
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46 #else
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47 load('infile.RData')
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48 #end if
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49
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50 ###################################### file properties in numbers ######################
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51
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52 ## Number of features (mz)
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53 maxfeatures = length(features(msidata))
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54 ## Range mz
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55 minmz = round(min(mz(msidata)), digits=2)
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56 maxmz = round(max(mz(msidata)), digits=2)
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57 ## Number of spectra (pixels)
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58 pixelcount = length(pixels(msidata))
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59 ## Range x coordinates
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60 minimumx = min(coord(msidata)[,1])
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61 maximumx = max(coord(msidata)[,1])
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62 ## Range y coordinates
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63 minimumy = min(coord(msidata)[,2])
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64 maximumy = max(coord(msidata)[,2])
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65 ## Range of intensities
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66 minint = round(min(spectra(msidata)[]), digits=2)
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67 maxint = round(max(spectra(msidata)[]), digits=2)
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68 medint = round(median(spectra(msidata)[]), digits=2)
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69 ## Number of intensities > 0
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70 npeaks= sum(spectra(msidata)[]>0)
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71 ## Spectra multiplied with mz (potential number of peaks)
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72 numpeaks = ncol(spectra(msidata)[])*nrow(spectra(msidata)[])
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73 ## Percentage of intensities > 0
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74 percpeaks = round(npeaks/numpeaks*100, digits=2)
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75 ## Number of empty TICs
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76 TICs = colSums(spectra(msidata)[])
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77 NumemptyTIC = sum(TICs == 0)
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78
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79
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80 ## Processing informations
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81 processinginfo = processingData(msidata)
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82 centroidedinfo = processinginfo@centroided # TRUE or FALSE
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83
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84 ## if TRUE write processinginfo if no write FALSE
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85
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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86 ## normalization
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87 if (length(processinginfo@normalization) == 0) {
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88 normalizationinfo='FALSE'
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89 } else {
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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90 normalizationinfo=processinginfo@normalization
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91 }
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92 ## smoothing
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93 if (length(processinginfo@smoothing) == 0) {
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94 smoothinginfo='FALSE'
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95 } else {
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96 smoothinginfo=processinginfo@smoothing
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97 }
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98 ## baseline
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99 if (length(processinginfo@baselineReduction) == 0) {
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100 baselinereductioninfo='FALSE'
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101 } else {
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102 baselinereductioninfo=processinginfo@baselineReduction
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103 }
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104 ## peak picking
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105 if (length(processinginfo@peakPicking) == 0) {
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106 peakpickinginfo='FALSE'
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107 } else {
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108 peakpickinginfo=processinginfo@peakPicking
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109 }
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110
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111 #############################################################################
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112
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113 properties = c("Number of mz features",
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114 "Range of mz values [Da]",
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115 "Number of pixels",
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116 "Range of x coordinates",
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117 "Range of y coordinates",
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118 "Range of intensities",
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119 "Median of intensities",
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120 "Intensities > 0",
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121 "Number of zero TICs",
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122 "Preprocessing",
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123 "Normalization",
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124 "Smoothing",
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125 "Baseline reduction",
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126 "Peak picking",
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127 "Centroided")
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128
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129 values = c(paste0(maxfeatures),
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130 paste0(minmz, " - ", maxmz),
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131 paste0(pixelcount),
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132 paste0(minimumx, " - ", maximumx),
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133 paste0(minimumy, " - ", maximumy),
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134 paste0(minint, " - ", maxint),
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135 paste0(medint),
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136 paste0(percpeaks, " %"),
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137 paste0(NumemptyTIC),
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138 paste0(" "),
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139 paste0(normalizationinfo),
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140 paste0(smoothinginfo),
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141 paste0(baselinereductioninfo),
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142 paste0(peakpickinginfo),
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143 paste0(centroidedinfo))
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144
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145 property_df = data.frame(properties, values)
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146
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147
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148 ######################################## PDF #############################################
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149 ##########################################################################################
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150 ##########################################################################################
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151
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152
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153 pdf("segmentationpdf.pdf", fonts = "Times", pointsize = 12)
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154 plot(0,type='n',axes=FALSE,ann=FALSE)
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155
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156 title(main=paste0("Spatial segmentation for file: \n\n", "$infile.display_name"))
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157
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158
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159 ############################# I) numbers ####################################
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160 #############################################################################
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161 grid.table(property_df, rows= NULL)
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162
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163 if (npeaks > 0)
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164 {
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165
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166
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167 ######################## II) segmentation tools #############################
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168 #############################################################################
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169 #set $color_string = ','.join(['"%s"' % $color.feature_color for $color in $colours])
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170 colourvector = c($color_string)
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171
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172
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173 #if str( $segm_cond.segmentationtool ) == 'pca':
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174 print('pca')
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175 ##pca
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176
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177 component_vector = character()
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178 for (numberofcomponents in 1:$segm_cond.pca_ncomp)
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179 {component_vector[numberofcomponents]= paste0("PC", numberofcomponents)}
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180 pca = PCA(msidata, ncomp=$segm_cond.pca_ncomp, column = component_vector, superpose = FALSE,
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181 method = "$segm_cond.pca_method", scale = $segm_cond.pca_scale, layout = c(ncomp, 1))
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182
2
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183 print(image(pca, main="PCA image", lattice=TRUE, strip = strip.custom(bg="lightgrey", par.strip.text=list(col="black", cex=.9)), col=colourvector, ylim=c(maximumy+2, 0)))
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184 print(plot(pca, main="PCA plot", lattice=TRUE, col= colourvector, strip = strip.custom(bg="lightgrey", par.strip.text=list(col="black", cex=.9))))
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185
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186
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187 pcaloadings = (pca@resultData\$ncomp\$loadings) ### loading for each mz value
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188 pcascores = (pca@resultData\$ncomp\$scores) ### scores for each pixel
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189
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190 write.table(pcaloadings, file="$mzfeatures", quote = FALSE, row.names = TRUE, col.names=NA, sep = "\t")
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191 write.table(pcascores, file="$pixeloutput", quote = FALSE, row.names = TRUE, col.names=NA, sep = "\t")
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192
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193 #elif str( $segm_cond.segmentationtool ) == 'kmeans':
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194 print('kmeans')
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195 ##k-means
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196
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197 skm = spatialKMeans(msidata, r=c($segm_cond.kmeans_r), k=c($segm_cond.kmeans_k), method="$segm_cond.kmeans_method")
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198 print(image(skm, key=TRUE, main="K-means clustering", lattice=TRUE, strip = strip.custom(bg="lightgrey", par.strip.text=list(col="black", cex=.9)), col= colourvector, ylim=c(maximumy+2, 0), layout=c(1,1)))
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199
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200 print(plot(skm, main="K-means plot", lattice=TRUE, col= colourvector, strip = strip.custom(bg="lightgrey", par.strip.text=list(col="black", cex=.9)), layout=c($segm_cond.kmeans_layout)))
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201
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202
2
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203 skm_clusters = data.frame(matrix(NA, nrow = pixelcount, ncol = 0))
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204 for (iteration in 1:length(skm@resultData)){
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205 skm_cluster = ((skm@resultData)[[iteration]]\$cluster)
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206 skm_clusters = cbind(skm_clusters, skm_cluster) }
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207 colnames(skm_clusters) = names((skm@resultData))
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208
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209 skm_toplabels = topLabels(skm, n=$segm_cond.kmeans_toplabels)
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210
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211 write.table(skm_toplabels, file="$mzfeatures", quote = FALSE, row.names = TRUE, col.names=NA, sep = "\t")
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212 write.table(skm_clusters, file="$pixeloutput", quote = FALSE, row.names = TRUE, col.names=NA, sep = "\t")
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213
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214
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215 #elif str( $segm_cond.segmentationtool ) == 'centroids':
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216 print('centroids')
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217 ##centroids
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218
2
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219 ssc = spatialShrunkenCentroids(msidata, r=c($segm_cond.centroids_r), k=c($segm_cond.centroids_k), s=c($segm_cond.centroids_s), method="$segm_cond.centroids_method")
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220 print(image(ssc, key=TRUE, main="Spatial shrunken centroids", lattice=TRUE, strip = strip.custom(bg="lightgrey", par.strip.text=list(col="black", cex=.9)), col= colourvector, ylim=c(maximumy+2, 0),layout=c(1,1)))
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221 print(plot(ssc, main="Spatial shrunken centroids plot", lattice=TRUE, col= colourvector, strip = strip.custom(bg="lightgrey", par.strip.text=list(col="black", cex=.9)),layout=c($segm_cond.centroids_layout)))
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222
2
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223 ssc_classes = data.frame(matrix(NA, nrow = pixelcount, ncol = 0))
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224 for (iteration in 1:length(ssc@resultData)){
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225 ssc_class = ((ssc@resultData)[[iteration]]\$classes)
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226 ssc_classes = cbind(ssc_classes, ssc_class) }
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227 colnames(ssc_classes) = names((ssc@resultData))
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228
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229 ssc_toplabels = topLabels(ssc, n=$segm_cond.centroids_toplabels)
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230
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231 write.table(ssc_toplabels, file="$mzfeatures", quote = FALSE, row.names = TRUE, col.names=NA, sep = "\t")
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232 write.table(ssc_classes, file="$pixeloutput", quote = FALSE, row.names = TRUE, col.names=NA, sep = "\t")
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233
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234
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235 #end if
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236
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237 dev.off()
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238
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239 }else{
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240 print("Inputfile has no intensities > 0")
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241 dev.off()
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242 }
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243
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244 ]]></configfile>
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245 </configfiles>
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246 <inputs>
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247 <param name="infile" type="data" format="imzml, rdata, analyze75"
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248 label="Inputfile as imzML, Analyze7.5 or Cardinal MSImageSet saved as RData"
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249 help="Upload composite datatype imzml (ibd+imzML) or analyze75 (hdr+img+t2m) or regular upload .RData (Cardinal MSImageSet)"/>
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250 <conditional name="segm_cond">
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251 <param name="segmentationtool" type="select" label="Select the tool for spatial clustering.">
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252 <option value="pca" selected="True">pca</option>
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253 <option value="kmeans">k-means</option>
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254 <option value="centroids">shrunken centroids</option>
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255 </param>
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256 <when value="pca">
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257 <param name="pca_ncomp" type="integer" value="2"
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258 label="The number of principal components to calculate."/>
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259 <param name="pca_method" type="select"
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260 label="The function used to calculate the singular value decomposition.">
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261 <option value="irlba" selected="True">irlba</option>
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262 <option value="svd">svd</option>
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263 </param>
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264 <param name="pca_scale" type="select" display="radio" optional="False"
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265 label="Shoud the data be scaled first?">
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266 <option value="TRUE">yes</option>
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267 <option value="FALSE" selected="True">no</option>
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268 </param>
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269 </when>
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270
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271 <when value="kmeans">
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272 <param name="kmeans_r" type="text" value="2"
2
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273 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
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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274 <param name="kmeans_k" type="text" value="3"
2
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275 label="The number of clusters (k)." help="Multiple values are allowed (e.g. 1,2,3 or 2:5)"/>
0
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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276 <param name="kmeans_method" type="select" display="radio"
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277 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.">
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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278 <option value="gaussian">gaussian</option>
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279 <option value="adaptive" selected="True">adaptive</option>
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280 </param>
2
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281 <param name="kmeans_toplabels" type="integer" value="500"
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282 label="Number of toplabels (masses) which should be written in tabular output"/>
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283 <param name="kmeans_layout" type="text" value="1,1"
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284 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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285 </when>
0
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286
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287 <when value="centroids">
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288 <param name="centroids_r" type="text" value="2"
2
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289 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
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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290 <param name="centroids_k" type="text" value="5"
2
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291 label="The initial number of clusters (k)." help="Multiple values are allowed (e.g. 1,2,3 or 2:5)"/>
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292 <param name="centroids_s" type="text" value="2"
0
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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293 label="The sparsity thresholding parameter by which to shrink the t-statistics (s)."
2
76d0244b1bbc planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit ed7d3e6f1a09c78c8f71cc1bdc1a20249767f646
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294 help="As s increases, fewer mass features (m/z values) will be used in the spatial segmentation, and only the informative mass features will be retained. Multiple values are allowed (e.g. 1,2,3 or 2:5)."/>
0
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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295 <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.">
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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296 <option value="gaussian" selected="True">gaussian</option>
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297 <option value="adaptive">adaptive</option>
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298 </param>
2
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299 <param name="centroids_toplabels" type="integer" value="500"
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300 label="Number of toplabels (masses) which should be written in tabular output"/>
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301 <param name="centroids_layout" type="text" value="1,1"
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302 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
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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303 </when>
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304 </conditional>
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305 <repeat name="colours" title="Colours for the plots" min="1" max="50">
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306 <param name="feature_color" type="color" label="Colours" value="#ff00ff" help="Numbers of columns should be the same as number of components">
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307 <sanitizer>
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308 <valid initial="string.letters,string.digits">
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309 <add value="#" />
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310 </valid>
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311 </sanitizer>
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312 </param>
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313 </repeat>
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314 </inputs>
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315 <outputs>
3
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316 <data format="pdf" name="segmentationimages" from_work_dir="segmentationpdf.pdf" label = "${tool.name} ${on_string}"/>
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317 <data format="tabular" name="mzfeatures" label="Mz features ${on_string}"/>
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318 <data format="tabular" name="pixeloutput" label="Pixels ${on_string}"/>
0
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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319 </outputs>
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320 <tests>
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321 <test>
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322 <param name="infile" value="" ftype="imzml">
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323 <composite_data value="Example_Continuous.imzML"/>
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324 <composite_data value="Example_Continuous.ibd"/>
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325 </param>
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326 <param name="segmentationtool" value="pca"/>
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327 <repeat name="colours">
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328 <param name="feature_color" value="#ff00ff"/>
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329 </repeat>
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330 <repeat name="colours">
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331 <param name="feature_color" value="#0000FF"/>
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332 </repeat>
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333 <output name="segmentationimages" file="pca_imzml.pdf" compare="sim_size" delta="20000"/>
1
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334 <output name="mzfeatures" file="loadings_pca.tabular" compare="sim_size"/>
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335 <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
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336 </test>
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337 <test>
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338 <param name="infile" value="" ftype="analyze75">
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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339 <composite_data value="Analyze75.hdr" />
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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340 <composite_data value="Analyze75.img" />
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341 <composite_data value="Analyze75.t2m" />
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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342 </param>
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343 <param name="segmentationtool" value="kmeans"/>
2
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344 <param name="kmeans_r" value="1:3"/>
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345 <param name="kmeans_k" value="2,3"/>
0
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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346 <repeat name="colours">
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347 <param name="feature_color" value="#ff00ff"/>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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348 </repeat>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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349 <repeat name="colours">
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350 <param name="feature_color" value="#0000FF"/>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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351 </repeat>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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352 <repeat name="colours">
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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353 <param name="feature_color" value="#00C957"/>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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354 </repeat>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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355 <output name="segmentationimages" file="kmeans_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
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356 <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
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357 <output name="pixeloutput" file="cluster_skm.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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358 </test>
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359 <test>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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360 <param name="infile" value="preprocessing_results1.RData" ftype="rdata"/>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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361 <param name="segmentationtool" value="centroids"/>
2
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362 <param name="centroids_r" ftype="text" value="1,2"/>
76d0244b1bbc planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit ed7d3e6f1a09c78c8f71cc1bdc1a20249767f646
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363 <param name="centroids_k" ftype="text" value="5"/>
76d0244b1bbc planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit ed7d3e6f1a09c78c8f71cc1bdc1a20249767f646
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364 <param name="centroids_toplabels" ftype="integer" value="100"/>
0
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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365 <repeat name="colours">
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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366 <param name="feature_color" value="#0000FF"/>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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367 </repeat>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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368 <repeat name="colours">
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369 <param name="feature_color" value="#00C957"/>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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370 </repeat>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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371 <repeat name="colours">
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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372 <param name="feature_color" value="#B0171F"/>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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373 </repeat>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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374 <repeat name="colours">
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375 <param name="feature_color" value="#FFD700"/>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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376 </repeat>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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377 <repeat name="colours">
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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378 <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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379 </repeat>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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380 <output name="segmentationimages" file="centroids_imzml.pdf" compare="sim_size" delta="20000"/>
1
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381 <output name="mzfeatures" file="toplabels_ssc.tabular" compare="sim_size"/>
942c11934f50 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit edbf2a6cb50fb04d0db56a7557a64e3bb7a0806a
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382 <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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383 </test>
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384 </tests>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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385 <help>
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386 <![CDATA[
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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387
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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388 Spatially aware segmentation of mass-spectrometry imaging data by unsupervised clustering algorithms. Underlying structures can be identified with the following tools: pca, k-means clustering and spatial shrunken centroids. The spatialShrunkenCentroids method allows the number of segments to decrease according to the data. This allows automatic selection of the number
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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389 of clusters.
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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390
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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391 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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392
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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393 - imzml file (upload imzml and ibd file via the "composite" function) `Introduction to the imzml format <http://ms-imaging.org/wp/introduction/>`_
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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394 - Analyze7.5 (upload hdr, img and t2m file via the "composite" function)
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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395 - Cardinal "MSImageSet" data (with variable name "msidata", saved as .RData)
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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396
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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397 The output of this tool contains a pdf with plots from the segmentation tools.
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398 ]]>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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399 </help>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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400 <citations>
71eaa6d9d057 planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_segmentation commit da5a0723327f7cce689b230ccd69f3edecb1bc6b
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401 <citation type="doi">10.1093/bioinformatics/btv146</citation>
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402 </citations>
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403 </tool>