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comparison msi_filtering.xml @ 1:98c101b19f3c draft

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planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_filtering commit 06c2b45d8644b1d7fc01622a5c59dcbf8886d0f1
author galaxyp
date Mon, 23 Apr 2018 17:18:35 -0400
parents f17d3f1a065f
children 22db5eb94e50
comparison
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0:f17d3f1a065f 1:98c101b19f3c
1 <tool id="mass_spectrometry_imaging_filtering" name="MSI filtering" version="1.7.0"> 1 <tool id="mass_spectrometry_imaging_filtering" name="MSI filtering" version="1.7.0.1">
2 <description>tool for filtering mass spectrometry imaging data</description> 2 <description>tool for filtering mass spectrometry imaging data</description>
3 <requirements> 3 <requirements>
4 <requirement type="package" version="1.7.0">bioconductor-cardinal</requirement> 4 <requirement type="package" version="1.7.0">bioconductor-cardinal</requirement>
5 <requirement type="package" version="2.2.1">r-gridextra</requirement> 5 <requirement type="package" version="2.2.1">r-gridextra</requirement>
6 </requirements> 6 </requirements>
43 load('infile.RData') 43 load('infile.RData')
44 #end if 44 #end if
45 45
46 ###################################### inputfile properties in numbers ###################### 46 ###################################### inputfile properties in numbers ######################
47 47
48 #if $outputs.outputs_select == "quality_control" 48 #if $outputs.outputs_select == "quality_control":
49 ## Number of features (mz) 49 ## Number of features (mz)
50 maxfeatures = length(features(msidata)) 50 maxfeatures = length(features(msidata))
51 ## Range mz 51 ## Range mz
52 minmz = round(min(mz(msidata)), digits=2) 52 minmz = round(min(mz(msidata)), digits=2)
53 maxmz = round(max(mz(msidata)), digits=2) 53 maxmz = round(max(mz(msidata)), digits=2)
74 featuresinfile = mz(msidata) 74 featuresinfile = mz(msidata)
75 #end if 75 #end if
76 76
77 77
78 ###################################### filtering of pixels ###################### 78 ###################################### filtering of pixels ######################
79 #if $inputpixels: 79
80 input_list = read.delim("$inputpixels", header = FALSE, 80 #if str($pixels_cond.pixel_filtering) == "single_column":
81 na.strings=c("","NA", "#NUM!", "#ZAHL!"), stringsAsFactors = FALSE) 81 print("single column")
82 validpixels = input_list[,$pixel_column] %in% names(pixels(msidata)) 82
83 83 #if $pixels_cond.single_pixels:
84 if (validpixels != 0) 84 input_list = read.delim("$pixels_cond.single_pixels", header = FALSE, stringsAsFactors = FALSE)
85 numberpixels = length(input_list[,$pixels_cond.pixel_column])
86 valid_entries = input_list[,$pixels_cond.pixel_column] %in% names(pixels(msidata))
87 validpixels = sum(valid_entries)
88
89 if (validpixels != 0)
90 {
91 pixelsofinterest = pixels(msidata)[names(pixels(msidata)) %in% input_list[valid_entries,$pixels_cond.pixel_column]]
92 msidata = msidata[,pixelsofinterest]
93 }else{
94 validpixels=0
95 }
96
97 #else
98 validpixels=0
99 numberpixels = 0
100 #end if
101
102 #elif str($pixels_cond.pixel_filtering) == "two_columns":
103 print("two columns")
104
105 #if $pixels_cond.two_columns_pixel:
106
107 input_list = read.delim("$pixels_cond.two_columns_pixel", header = FALSE,
108 stringsAsFactors = FALSE)
109 numberpixels = length(input_list[,$pixels_cond.pixel_column_x])
110
111 inputpixel_x = input_list[,$pixels_cond.pixel_column_x]
112 inputpixel_y = input_list[,$pixels_cond.pixel_column_y]
113
114 inputpixels = cbind(inputpixel_x, inputpixel_y)
115 colnames(inputpixels) = c("x", "y")
116 valid_rows = merge(inputpixels, coord(msidata)[,1:2])
117 validpixels = nrow(valid_rows)
118
119 if (validpixels != 0)
85 { 120 {
86 pixelsofinterest = pixels(msidata)[names(pixels(msidata)) %in% input_list[validpixels,$pixel_column]] 121
122 pixelvector = character()
123
124 for (pixel in 1:nrow(valid_rows))
125 {
126 pixelvector[pixel] = paste0("x = ", valid_rows[pixel,1],", ", "y = ", valid_rows[pixel,2])
127 }
128
129 pixelsofinterest= pixels(msidata)[names(pixels(msidata)) %in% pixelvector]
87 msidata = msidata[,pixelsofinterest] 130 msidata = msidata[,pixelsofinterest]
88 numberpixels = length(input_list[,$pixel_column]) 131 }else{
89 }else { 132 validpixels=0
90 numberpixels = 0
91 } 133 }
92 134
93 135
94 #else 136 #else
95 input_list = data.frame(0, 0) 137 validpixels=0
96 validpixels=0 138 numberpixels = 0
139 #end if
140
141 #elif str($pixels_cond.pixel_filtering) == "pixel_range":
142 print("pixel range")
143
144 numberpixels = "range"
145 validpixels = "range"
146
147 if (sum(coord(msidata)\$x <= $pixels_cond.max_x_range & coord(msidata)\$x >= $pixels_cond.min_x_range) > 0)
148 {
149 msidata = msidata[, coord(msidata)\$x <= $pixels_cond.max_x_range & coord(msidata)\$x >= $pixels_cond.min_x_range]
150 }
151
152 if (sum(coord(msidata)\$y <= $pixels_cond.max_y_range & coord(msidata)\$y >= $pixels_cond.min_y_range) > 0)
153 {
154 msidata = msidata[, coord(msidata)\$y <= $pixels_cond.max_y_range & coord(msidata)\$y >= $pixels_cond.min_y_range]
155 }
156
157
158
159 #elif str($pixels_cond.pixel_filtering) == "none":
160 print("no pixel filtering")
97 numberpixels = 0 161 numberpixels = 0
162 validpixels = 0
163
98 #end if 164 #end if
99 165
100 166
101 167
102 ###################################### filtering of features ###################### 168 ###################################### filtering of features ######################
103 169
104 #if $inputfeatures: 170 #if str($features_cond.features_filtering) == "features_list":
105 input_features = read.delim("$inputfeatures", header = FALSE, 171
106 na.strings=c("","NA", "#NUM!", "#ZAHL!"), stringsAsFactors = FALSE) 172 print("feature list")
107 validfeatures = input_features[,$feature_column] %in% names(features(msidata)) 173
108 174 input_features = read.delim("$inputfeatures", header = FALSE, stringsAsFactors = FALSE)
109 if (validfeatures != 0) 175
176 startingrow = $features_cond.feature_header+1
177 extracted_features = input_features[startingrow:nrow(input_features),$features_cond.feature_column]
178 numberfeatures = length(extracted_features)
179
180
181 if (grepl("m/z = ", input_features[startingrow,$features_cond.feature_column])==FALSE)
182
183 { print("no m/z = in data")
184
185 if (class(extracted_features) == "numeric")
110 { 186 {
111 featuresofinterest = features(msidata)[names(features(msidata)) %in% input_features[validfeatures,$feature_column]] 187 charactervector = rep("m/z = ", numberfeatures)
112 msidata = msidata[featuresofinterest,] 188 mz_added = paste0(charactervector, round(extracted_features,digits=2))
113 numberfeatures = length(input_features[,$feature_column]) 189 validfeatures = mz_added %in% names(features(msidata))
114 } else { 190 featuresofinterest = features(msidata)[names(features(msidata)) %in% mz_added[validfeatures]]
115 numberfeatures = 0 191 }else{
192 validfeatures = 0
193 featuresofinterest = features(msidata)
116 } 194 }
117 195 }else{
118 196 validfeatures = extracted_features %in% names(features(msidata))
119 #else 197 featuresofinterest = features(msidata)[names(features(msidata)) %in% extracted_features[validfeatures]]
120 input_features = data.frame(0, 0) 198 }
199
200 msidata = msidata[featuresofinterest,]
201
202
203
204 #elif str($features_cond.features_filtering) == "features_range":
205
206 print("feature range")
207
208 numberfeatures = "range"
209 validfeatures = NA
210
211 if (sum(mz(msidata) >= $features_cond.min_mz & mz(msidata) <= $features_cond.max_mz)> 0)
212 {
213 msidata = msidata[mz(msidata) >= $features_cond.min_mz & mz(msidata) <= $features_cond.max_mz,]
214 }
215
216
217 #elif str($features_cond.features_filtering) == "none":
218
219 print("no feature filtering")
121 validfeatures = 0 220 validfeatures = 0
122 numberfeatures = 0 221 numberfeatures = 0
123 #end if 222 #end if
124 223
125 224
126 225
127
128
129
130 # save msidata as Rfile 226 # save msidata as Rfile
131 save(msidata, file="$msidata_filtered") 227 save(msidata, file="$msidata_filtered")
132 228
133 ###################################### outputfile properties in numbers ###################### 229 ###################################### outputfile properties in numbers ######################
134 230
135 #if $outputs.outputs_select == "quality_control" 231 #if $outputs.outputs_select == "quality_control":
136 232
137 ## Number of features (mz) 233 ## Number of features (mz)
138 maxfeatures2 = length(features(msidata)) 234 maxfeatures2 = length(features(msidata))
139 ## Range mz 235 ## Range mz
140 minmz2 = round(min(mz(msidata)), digits=2) 236 minmz2 = round(min(mz(msidata)), digits=2)
166 "Range of x coordinates", 262 "Range of x coordinates",
167 "Range of y coordinates", 263 "Range of y coordinates",
168 "Intensities > 0", 264 "Intensities > 0",
169 "Median TIC per pixel", 265 "Median TIC per pixel",
170 "Number of zero TICs", 266 "Number of zero TICs",
171 paste0("# pixels in ", "$inputpixels.display_name"), 267 "pixel overview",
172 paste0("# mz in ", "$inputfeatures.display_name")) 268 "feature overview")
173 269
174 before = c(paste0(maxfeatures), 270 before = c(paste0(maxfeatures),
175 paste0(minmz, " - ", maxmz), 271 paste0(minmz, " - ", maxmz),
176 paste0(pixelcount), 272 paste0(pixelcount),
177 paste0(minimumx, " - ", maximumx), 273 paste0(minimumx, " - ", maximumx),
188 paste0(minimumx2, " - ", maximumx2), 284 paste0(minimumx2, " - ", maximumx2),
189 paste0(minimumy2, " - ", maximumy2), 285 paste0(minimumy2, " - ", maximumy2),
190 paste0(percpeaks2, " %"), 286 paste0(percpeaks2, " %"),
191 paste0(medint2), 287 paste0(medint2),
192 paste0(NumemptyTIC2), 288 paste0(NumemptyTIC2),
193 paste0("valid pixels: ", sum(validpixels)), 289 paste0("valid pixels: ", validpixels),
194 paste0("valid mz: ", sum(validfeatures))) 290 paste0("valid mz: ", sum(validfeatures)))
195 291
196 292
197 property_df = data.frame(properties, before, filtered) 293 property_df = data.frame(properties, before, filtered)
198 294
199 295
200 296
201 ######################################## PDF QC ############################################# 297 ######################################## PDF QC #############################################
202
203 298
204 pdf("filtertool_QC.pdf", fonts = "Times", pointsize = 12) 299 pdf("filtertool_QC.pdf", fonts = "Times", pointsize = 12)
205 plot(0,type='n',axes=FALSE,ann=FALSE) 300 plot(0,type='n',axes=FALSE,ann=FALSE)
206 301
207 title(main=paste0("Qualitycontrol of filtering tool for file: \n\n", "$infile.display_name")) 302 title(main=paste0("Qualitycontrol of filtering tool for file: \n\n", "$infile.display_name"))
208 303
209 304
305
210 grid.table(property_df, rows= NULL) 306 grid.table(property_df, rows= NULL)
211 307
212
213 ### heatmap image as visual pixel control 308 ### heatmap image as visual pixel control
309
310 if (length(features(msidata))> 0 & length(pixels(msidata)) > 0)
311 {
214 312
215 313
216 image(msidata, mz=$outputs.inputmz, plusminus = $outputs.plusminus_dalton, contrast.enhance = "none", 314 image(msidata, mz=$outputs.inputmz, plusminus = $outputs.plusminus_dalton, contrast.enhance = "none",
217 main= paste0($outputs.inputmz," ± ", $outputs.plusminus_dalton, " Da"), ylim = c(maximumy2+0.2*maximumy2,minimumy2-0.2*minimumy2)) 315 main= paste0($outputs.inputmz," ± ", $outputs.plusminus_dalton, " Da"), ylim = c(maximumy2+0.2*maximumy2,minimumy2-0.2*minimumy2))
218 316
219 ### control features which are left 317 ### control features which are left
220 318
221 par(mfrow = c(2,1)) 319 plot(featuresinfile, rep(1,length(featuresinfile)), yaxt="n", ylab=NA, xlab="m/z values", col="red", ylim=c(0.8, 1.1), main="Distribution of m/z values")
222 plot(featuresinfile, ylab = "m/z in Dalton", xlab = "feature index") 320 lines(mz(msidata),rep(0.9, length(mz(msidata))), col="green", type="p")
223 plot(mz(msidata), ylab = "m/z in Dalton", xlab = "feature index") 321 legend("top", horiz=TRUE,
224 322 legend = c("before", "filtered"),
323 fill = c("red", "green"))
324
325
326
327
328 }else{
329 print("file has no features or pixels left")
330 }
225 331
226 dev.off() 332 dev.off()
227 333
228 #end if 334 #end if
229 335
249 ]]></configfile> 355 ]]></configfile>
250 </configfiles> 356 </configfiles>
251 <inputs> 357 <inputs>
252 <param name="infile" type="data" format="imzml, rdata, analyze75" 358 <param name="infile" type="data" format="imzml, rdata, analyze75"
253 label="Inputfile as imzML, Analyze7.5 or Cardinal MSImageSet saved as RData" 359 label="Inputfile as imzML, Analyze7.5 or Cardinal MSImageSet saved as RData"
254 help="Upload composite datatype imzml (ibd+imzML) or analyze75 (hdr+img+t2m) or regular upload .RData (Cardinal MSImageSet)"/> 360 help="Upload composite datatype imzML (ibd+imzML) or analyze75 (hdr+img+t2m) or regular upload .RData (Cardinal MSImageSet)"/>
255 <param name="inputpixels" type="data" optional="true" format="tabular" label="pixels for filtering of MSI data" 361
256 help="tabular file with pixels of interest in the form x = 1, y = 1"/> 362 <conditional name="pixels_cond">
257 <param name="pixel_column" data_ref="inputpixels" optional="true" label="Column with pixels" type="data_column" /> 363 <param name="pixel_filtering" type="select" label="Select pixel filtering option">
258 <param name="inputfeatures" type="data" optional="true" format="tabular" label="features for filtering of MSI data" 364 <option value="none" selected="True">none</option>
259 help="tabular file with masses of interest in the form mz = 800.05"/> 365 <option value="single_column">tabular file with single column (x = 1, y = 1)</option>
260 <param name="feature_column" data_ref="inputfeatures" optional="true" label="Column with features" type="data_column" /> 366 <option value="two_columns">tabular file with separate columns for x and y values</option>
367 <option value="pixel_range">ranges for x and y</option>
368 </param>
369 <when value="none"/>
370 <when value="single_column">
371 <param name="single_pixels" type="data" format="tabular" label="Pixels in single column for filtering of MSI data"
372 help="tabular file with pixels of interest in the form x = 1, y = 1"/>
373 <param name="pixel_column" data_ref="single_pixels" label="Column with pixels" type="data_column"/>
374 </when>
375 <when value="two_columns">
376 <param name="two_columns_pixel" type="data" format="tabular" label="Pixels in two columns for filtering of MSI data"
377 help="tabular file with pixels of interest in two separate columns"/>
378 <param name="pixel_column_x" data_ref="two_columns_pixel" label="Column with x values" type="data_column"/>
379 <param name="pixel_column_y" data_ref="two_columns_pixel" label="Column with y values" type="data_column"/>
380 </when>
381 <when value="pixel_range">
382 <param name="min_x_range" type="integer" value="0" label="Minimum value for x"/>
383 <param name="max_x_range" type="integer" value="100" label="Maximum value for x"/>
384 <param name="min_y_range" type="integer" value="0" label="Minimum value for y"/>
385 <param name="max_y_range" type="integer" value="100" label="Maximum value for y"/>
386 </when>
387 </conditional>
388
389 <conditional name="features_cond">
390 <param name="features_filtering" type="select" label="Select feature filtering option">
391 <option value="none" selected="True">none</option>
392 <option value="features_list">tabular file with features (data type: 800.12 or m/z = 800.12)</option>
393 <option value="features_range">range of features</option>
394 </param>
395
396 <when value="none"/>
397 <when value="features_list">
398 <param name="inputfeatures" type="data" format="tabular" label="Features for filtering of MSI data" help="tabular file with masses of interest either as numbers (800.05) or in the form m/z = 800.05"/>
399 <param name="feature_column" data_ref="inputfeatures" label="Column with features" type="data_column"/>
400 <param name="feature_header" label="Number of header lines to skip" value="0" type="integer"/>
401 </when>
402 <when value="features_range">
403 <param name="min_mz" type="integer" value="1" label="Minimum value for mz (in Dalton)"/>
404 <param name="max_mz" type="integer" value="100" label="Maximum value for mz (in Dalton)"/>
405 </when>
406 </conditional>
261 407
262 <conditional name="outputs"> 408 <conditional name="outputs">
263 <param name="outputs_select" type="select" label="Quality control output"> 409 <param name="outputs_select" type="select" label="Quality control output">
264 <option value="quality_control" selected="True">yes</option> 410 <option value="quality_control" selected="True">yes</option>
265 <option value="no_quality_control" >no</option> 411 <option value="no_quality_control">no</option>
266 </param> 412 </param>
267 <when value="quality_control"> 413 <when value="quality_control">
268 <param name="inputmz" type="float" value="1296.7" label="Mass for which a heatmap image will be drawn" help="Use a mass which is still present in all pixels to control if the pixel filtering went well"/> 414 <param name="inputmz" type="float" value="1296.7" label="Mass for which a heatmap image will be drawn" help="Use a mass which is still present in all pixels to control if the pixel filtering went well"/>
269 <param name="plusminus_dalton" value="0.25" type="float" label="mass range for mz value" help="plusminus mass window in Dalton"/> 415 <param name="plusminus_dalton" value="0.25" type="float" label="mass range for mz value" help="plusminus mass window in Dalton"/>
270 </when> 416 </when>
417 <when value="no_quality_control"/>
271 </conditional> 418 </conditional>
272 <param name="output_matrix" type="boolean" display="radio" label="Intensity matrix output"/> 419 <param name="output_matrix" type="boolean" display="radio" label="Intensity matrix output"/>
273 </inputs> 420 </inputs>
274 <outputs> 421 <outputs>
275 <data format="rdata" name="msidata_filtered" label="${tool.name} on $infile.display_name"/> 422 <data format="rdata" name="msidata_filtered" label="${tool.name} ${on_string}"/>
276 <data format="pdf" name="filtering_qc" from_work_dir="filtertool_QC.pdf" label = "QC ${tool.name} on $infile.display_name"> 423 <data format="pdf" name="filtering_qc" from_work_dir="filtertool_QC.pdf" label = "QC ${tool.name} ${on_string}">
277 <filter>outputs["outputs_select"] == "quality_control"</filter> 424 <filter>outputs["outputs_select"] == "quality_control"</filter>
278 </data> 425 </data>
279 <data format="tabular" name="matrixasoutput" label="matrix ${tool.name} on $infile.display_name"> 426 <data format="tabular" name="matrixasoutput" label="Matrix ${tool.name} on ${on_string}">
280 <filter>output_matrix</filter> 427 <filter>output_matrix</filter>
281 </data> 428 </data>
282 </outputs> 429 </outputs>
283 430
284 <tests> 431 <tests>
285 <test expect_num_outputs="2"> 432 <test expect_num_outputs="2">
286 <param name="infile" value="" ftype="imzml"> 433 <param name="infile" value="" ftype="imzml">
287 <composite_data value="Example_Continuous.imzML"/> 434 <composite_data value="Example_Continuous.imzML"/>
288 <composite_data value="Example_Continuous.ibd"/> 435 <composite_data value="Example_Continuous.ibd"/>
289 </param> 436 </param>
290 <param name="inputpixels" ftype="tabular" value = "inputpixels.tabular"/> 437 <param name="pixel_filtering" value="single_column"/>
438 <param name="single_pixels" ftype="tabular" value = "inputpixels.tabular"/>
291 <param name="pixel_column" value="1"/> 439 <param name="pixel_column" value="1"/>
440 <param name="features_filtering" value="features_list"/>
292 <param name="inputfeatures" ftype="tabular" value = "inputfeatures.tabular"/> 441 <param name="inputfeatures" ftype="tabular" value = "inputfeatures.tabular"/>
293 <param name="feature_column" value="2"/> 442 <param name="feature_column" value="2"/>
294 443 <param name="feature_header" value="1"/>
295 <conditional name="outputs"> 444 <param name="outputs_select" value="quality_control"/>
296 <param name="outputs_select" value="quality_control"/> 445 <param name="inputmz" value="328.9"/>
297 <param name="inputmz" value="328.9"/> 446 <param name="plusminus_dalton" value="0.25"/>
298 <param name="plusminus_dalton" value="0.25"/>
299 </conditional>
300 <output name="filtering_qc" file="imzml_filtered.pdf" compare="sim_size" delta="20000"/> 447 <output name="filtering_qc" file="imzml_filtered.pdf" compare="sim_size" delta="20000"/>
301 <output name="msidata_filtered" file="imzml_filtered.RData" compare="sim_size" /> 448 <output name="msidata_filtered" file="imzml_filtered.RData" compare="sim_size" />
449 </test>
450 <test expect_num_outputs="2">
451 <param name="infile" value="" ftype="imzml">
452 <composite_data value="Example_Continuous.imzML"/>
453 <composite_data value="Example_Continuous.ibd"/>
454 </param>
455 <param name="pixel_filtering" value="pixel_range"/>
456 <param name="min_x_range" value="0"/>
457 <param name="max_x_range" value="10"/>
458 <param name="min_y_range" value="2"/>
459 <param name="max_y_range" value="2"/>
460 <param name="outputs_select" value="quality_control"/>
461 <param name="inputmz" value="328.9"/>
462 <param name="plusminus_dalton" value="0.25"/>
463 <output name="filtering_qc" file="imzml_filtered2.pdf" compare="sim_size" delta="20000"/>
464 <output name="msidata_filtered" file="imzml_filtered2.RData" compare="sim_size" />
465 </test>
466 <test expect_num_outputs="3">
467 <param name="infile" value="" ftype="imzml">
468 <composite_data value="Example_Continuous.imzML"/>
469 <composite_data value="Example_Continuous.ibd"/>
470 </param>
471 <param name="pixel_filtering" value="pixel_range"/>
472 <param name="min_x_range" value="0"/>
473 <param name="max_x_range" value="10"/>
474 <param name="min_y_range" value="2"/>
475 <param name="max_y_range" value="2"/>
476 <param name="features_filtering" value="features_range"/>
477 <param name="min_mz" value="200" />
478 <param name="max_mz" value="500"/>
479 <param name="outputs_select" value="quality_control"/>
480 <param name="inputmz" value="328.9"/>
481 <param name="plusminus_dalton" value="0.25"/>
482 <param name="output_matrix" value="True"/>
483 <output name="filtering_qc" file="imzml_filtered3.pdf" compare="sim_size" delta="20000"/>
484 <output name="msidata_filtered" file="imzml_filtered3.RData" compare="sim_size" />
485 <output name="matrixasoutput" file="imzml_matrix3.tabular"/>
486 </test>
487 <test expect_num_outputs="2">
488 <param name="infile" value="" ftype="imzml">
489 <composite_data value="Example_Continuous.imzML"/>
490 <composite_data value="Example_Continuous.ibd"/>
491 </param>
492 <param name="pixel_filtering" value="two_columns"/>
493 <param name="two_columns_pixel" ftype="tabular" value = "inputpixels_2column.tabular"/>
494 <param name="pixel_column_x" value="1"/>
495 <param name="pixel_column_y" value="3"/>
496 <param name="features_filtering" value="features_list"/>
497 <param name="inputfeatures" ftype="tabular" value = "inputcalibrantfile2.txt"/>
498 <param name="feature_column" value="1"/>
499 <param name="feature_header" value="0"/>
500 <param name="outputs_select" value="quality_control"/>
501 <param name="inputmz" value="328.9"/>
502 <param name="plusminus_dalton" value="0.25"/>
503 <output name="filtering_qc" file="imzml_filtered4.pdf" compare="sim_size" delta="20000"/>
504 <output name="msidata_filtered" file="imzml_filtered4.RData" compare="sim_size" />
505 </test>
506 <test expect_num_outputs="2">
507 <param name="infile" value="" ftype="imzml">
508 <composite_data value="Example_Continuous.imzML"/>
509 <composite_data value="Example_Continuous.ibd"/>
510 </param>
511 <param name="pixel_filtering" value="pixel_range"/>
512 <param name="min_x_range" value="0"/>
513 <param name="max_x_range" value="10"/>
514 <param name="min_y_range" value="2"/>
515 <param name="max_y_range" value="20"/>
516 <param name="features_filtering" value="features_range"/>
517 <param name="min_mz" value="1" />
518 <param name="max_mz" value="150"/>
519 <param name="outputs_select" value="quality_control"/>
520 <param name="inputmz" value="328.9"/>
521 <param name="plusminus_dalton" value="0.25"/>
522 <output name="filtering_qc" file="imzml_filtered5.pdf" compare="sim_size" delta="20000"/>
523 <output name="msidata_filtered" file="imzml_filtered5.RData" compare="sim_size" />
302 </test> 524 </test>
303 <test expect_num_outputs="3"> 525 <test expect_num_outputs="3">
304 <param name="infile" value="" ftype="analyze75"> 526 <param name="infile" value="" ftype="analyze75">
305 <composite_data value="Analyze75.hdr"/> 527 <composite_data value="Analyze75.hdr"/>
306 <composite_data value="Analyze75.img"/> 528 <composite_data value="Analyze75.img"/>
307 <composite_data value="Analyze75.t2m"/> 529 <composite_data value="Analyze75.t2m"/>
308 </param> 530 </param>
309 <param name="inputpixels" ftype="tabular" value = "inputpixels2.tabular"/> 531 <param name="pixel_filtering" value="single_column"/>
532 <param name="single_pixels" ftype="tabular" value = "inputpixels2.tabular"/>
310 <param name="pixel_column" value="1"/> 533 <param name="pixel_column" value="1"/>
534 <param name="features_filtering" value="features_list"/>
311 <param name="inputfeatures" ftype="tabular" value = "featuresofinterest2.tabular"/> 535 <param name="inputfeatures" ftype="tabular" value = "featuresofinterest2.tabular"/>
312 <param name="feature_column" value="1"/> 536 <param name="feature_column" value="1"/>
313 <conditional name="outputs"> 537 <conditional name="outputs">
314 <param name="outputs_select" value="quality_control"/> 538 <param name="outputs_select" value="quality_control"/>
315 <param name="inputmz" value="702"/> 539 <param name="inputmz" value="702"/>
318 <param name="output_matrix" value="True"/> 542 <param name="output_matrix" value="True"/>
319 <output name="filtering_qc" file="analyze_filtered.pdf" compare="sim_size" delta="20000"/> 543 <output name="filtering_qc" file="analyze_filtered.pdf" compare="sim_size" delta="20000"/>
320 <output name="msidata_filtered" file="analyze_filtered.RData" compare="sim_size" /> 544 <output name="msidata_filtered" file="analyze_filtered.RData" compare="sim_size" />
321 <output name="matrixasoutput" file="analyze_matrix.tabular"/> 545 <output name="matrixasoutput" file="analyze_matrix.tabular"/>
322 </test> 546 </test>
323 <test expect_num_outputs="1"> 547 <test expect_num_outputs="2">
324 <param name="infile" value="" ftype="analyze75"> 548 <param name="infile" value="" ftype="analyze75">
325 <composite_data value="Analyze75.hdr"/> 549 <composite_data value="Analyze75.hdr"/>
326 <composite_data value="Analyze75.img"/> 550 <composite_data value="Analyze75.img"/>
327 <composite_data value="Analyze75.t2m"/> 551 <composite_data value="Analyze75.t2m"/>
328 </param> 552 </param>
329 <conditional name="outputs"> 553 <conditional name="outputs">
330 <param name="outputs_select" value="no_quality_control"/> 554 <param name="outputs_select" value="quality_control"/>
555 <param name="inputmz" value="702"/>
556 <param name="plusminus_dalton" value="0.25"/>
331 </conditional> 557 </conditional>
332 <output name="msidata_filtered" file="analyze_originaloutput.RData" compare="sim_size" /> 558 <output name="filtering_qc" file="analyze75_filtered2.pdf" compare="sim_size" delta="20000"/>
559 <output name="msidata_filtered" file="analyze_originaloutput2.RData" compare="sim_size" />
333 </test> 560 </test>
334 <test expect_num_outputs="2"> 561 <test expect_num_outputs="2">
335 <param name="infile" value="preprocessing_results1.RData" ftype="rdata"/> 562 <param name="infile" value="preprocessing_results1.RData" ftype="rdata"/>
336 <conditional name="outputs"> 563 <conditional name="outputs">
337 <param name="outputs_select" value="no_quality_control"/> 564 <param name="outputs_select" value="no_quality_control"/>
338 </conditional> 565 </conditional>
339 <param name="output_matrix" value="True"/> 566 <param name="output_matrix" value="True"/>
340 <output name="matrixasoutput" file="rdata_matrix.tabular"/> 567 <output name="matrixasoutput" file="rdata_matrix.tabular"/>
568 <output name="msidata_filtered" file="rdata_notfiltered.RData" compare="sim_size" />
341 </test> 569 </test>
342 </tests> 570 </tests>
343 <help> 571 <help>
344 <![CDATA[ 572 <![CDATA[
345 573
346 This tool can filter three types of mass-spectrometry imaging files (see below) for pixels and features of interest. This can be used to keep only pixels in a regions of interest. 574 This tool can filter three types of mass-spectrometry imaging files (see below) for pixels and features of interest. This can be used to keep only pixels in a regions of interest.
347 For filtering at least one valid pixel/feature is needed otherwise no filtering will be performed. 575 For filtering at least one valid pixel/feature is needed otherwise no filtering will be performed. It is recommended to use the filtering tool only for feature masses which have been extracted from the same dataset. If you have feature masses from dataset A and you want to use them to filter dataset B, first find the corresponding (closest) features in dataset B by using the tool "Join two files on column allowing a small difference". Afterwards use the corresponding feature masses from dataset B to filter dataset B.
348 576
349 Input data: 3 types of input data can be used: 577 Input data: 3 types of input data can be used:
350 578
351 - imzml file (upload imzml and ibd file via the "composite" function) `Introduction to the imzml format <http://ms-imaging.org/wp/introduction/>`_ 579 - imzml file (upload imzml and ibd file via the "composite" function) `Introduction to the imzml format <http://ms-imaging.org/wp/introduction/>`_
352 - Analyze7.5 (upload hdr, img and t2m file via the "composite" function) 580 - Analyze7.5 (upload hdr, img and t2m file via the "composite" function)