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comparison spectra_plots.xml @ 2:3642ed221eb2 draft

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planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/cardinal commit f127be2141cf22e269c85282d226eb16fe14a9c1
author galaxyp
date Fri, 15 Feb 2019 10:23:28 -0500
parents 1d9931768896
children 58c4aef16eb0
comparison
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1:1d9931768896 2:3642ed221eb2
1 <tool id="cardinal_spectra_plots" name="MSI plot spectra" version="@VERSION@.1"> 1 <tool id="cardinal_spectra_plots" name="MSI plot spectra" version="@VERSION@.2">
2 <description> 2 <description>
3 mass spectrometry imaging mass spectra plots 3 mass spectrometry imaging mass spectra plots
4 </description> 4 </description>
5 <macros> 5 <macros>
6 <import>macros.xml</import> 6 <import>macros.xml</import>
25 library(Cardinal) 25 library(Cardinal)
26 library(gridExtra) 26 library(gridExtra)
27 library(ggplot2) 27 library(ggplot2)
28 library(scales) 28 library(scales)
29 29
30
30 @READING_MSIDATA@ 31 @READING_MSIDATA@
31 32
32 @DATA_PROPERTIES@ 33 @DATA_PROPERTIES@
33 34
34 35
50 51
51 grid.table(property_df, rows= NULL) 52 grid.table(property_df, rows= NULL)
52 53
53 ## set NA to 0 otherwise plot function will not work 54 ## set NA to 0 otherwise plot function will not work
54 55
55 ##spectra(msidata)[is.na(spectra(msidata)[])] = 0 ## in case of NA values they will be set to zero 56 #if str($processed_cond.processed_file) == "processed":
56 57 ##processed file needs to be converted into matrix to be able to replace NAs
57 spectra_df = spectra(msidata)[] 58 iData(msidata) <- iData(msidata)[]
58 spectra_df[is.na(spectra_df)] = 0 59 spectra(msidata)[][is.na(spectra(msidata)[])] = 0
59 print(paste0("Number of NA which were converted into 0:",sum(is.na(spectra_df)))) 60 #else
60 spectra(msidata) = spectra_df 61 spectra(msidata)[is.na(spectra(msidata))] = 0
61 62 #end if
62 63
63 if (npeaks > 0){ 64 ## run only if mz and pixels are > 0
65
66 if (ncol(msidata)>0 & nrow(msidata) >0){
64 67
65 pixeldf = data.frame(matrix(ncol = 2, nrow=0)) 68 pixeldf = data.frame(matrix(ncol = 2, nrow=0))
66 69
67 ############################# single pixel ################################ 70 ############################# single pixel ################################
68 ########################################################################### 71 ###########################################################################
71 print("single_pixel") 74 print("single_pixel")
72 75
73 #for $chosenpixel in $pixel_conditional.repeatpixel: 76 #for $chosenpixel in $pixel_conditional.repeatpixel:
74 77
75 pixelname = paste0("x = ", $chosenpixel.inputx,", ", "y = ", $chosenpixel.inputy) 78 pixelname = paste0("x = ", $chosenpixel.inputx,", ", "y = ", $chosenpixel.inputy)
76 pixelisvalid = as.character(pixelname %in% names(pixels(msidata))) 79
80
81
82 input_pixels = paste($chosenpixel.inputx, $chosenpixel.inputy, sep="_")
83 dataset_pixels = paste(coord(msidata)\$x, coord(msidata)\$y, sep="_")
84
85 pixelisvalid = as.character(input_pixels %in% dataset_pixels)
86
87
88
77 pixeldf = rbind(pixeldf, cbind(pixelname, pixelisvalid)) 89 pixeldf = rbind(pixeldf, cbind(pixelname, pixelisvalid))
78 90
79 ############################# II) control image #################### 91 ############################# II) control image ####################
80 92
81 if (pixelisvalid == "TRUE"){ 93 if (pixelisvalid == "TRUE"){
82 print(pixelisvalid)
83 94
84 image(msidata, mz=$chosenpixel.inputmz, ylim = c(maximumy+(0.2*maximumy),minimumy-1), 95 image(msidata, mz=$chosenpixel.inputmz, ylim = c(maximumy+(0.2*maximumy),minimumy-1),
85 colorkey=FALSE, plusminus = $chosenpixel.plusminusinDalton, 96 colorkey=FALSE, plusminus = $chosenpixel.plusminusinDalton,
86 main= paste0("x= ",$chosenpixel.inputx, ", y= ", $chosenpixel.inputy)) 97 main= paste0("x= ",$chosenpixel.inputx, ", y= ", $chosenpixel.inputy))
87 98
186 ## print legend only for less than 10 samples 197 ## print legend only for less than 10 samples
187 if (length(levels(msidata\$annotation)) < 10){ 198 if (length(levels(msidata\$annotation)) < 10){
188 key_legend = TRUE 199 key_legend = TRUE
189 }else{key_legend = FALSE} 200 }else{key_legend = FALSE}
190 201
191 spectra(msidata)[is.na(spectra(msidata)[])] = 0 ## in case of NA values they will be set to zero
192 plot(msidata, pixel=1:ncol(msidata), pixel.groups=msidata\$annotation, key=key_legend, col=hue_pal()(length(levels(msidata\$annotation))),superpose=TRUE) 202 plot(msidata, pixel=1:ncol(msidata), pixel.groups=msidata\$annotation, key=key_legend, col=hue_pal()(length(levels(msidata\$annotation))),superpose=TRUE)
193 }else{ 203 }else{
194 spectra(msidata)[is.na(spectra(msidata)[])] = 0 ## in case of NA values they will be set to zero
195 plot(msidata, pixel=1:ncol(msidata), key=TRUE)} 204 plot(msidata, pixel=1:ncol(msidata), key=TRUE)}
196 205
197 ##################### II) Sample: plot zoom-in mass spectrum ########## 206 ##################### II) Sample: plot zoom-in mass spectrum ##########
198 207
199 #if $pixel_conditional.zoomed_sample: 208 #if $pixel_conditional.zoomed_sample:
200 iData(msidata) <- iData(msidata)[] ## getting back data on disk
201 #for $token in $pixel_conditional.zoomed_sample: 209 #for $token in $pixel_conditional.zoomed_sample:
202 print("zoomed sample pixels") 210 print("zoomed sample pixels")
203 211
204 minmasspixel = features(msidata, mz=$token.xlimmin) 212 minmasspixel = features(msidata, mz=$token.xlimmin)
205 maxmasspixel = features(msidata, mz=$token.xlimmax) 213 maxmasspixel = features(msidata, mz=$token.xlimmax)
315 </repeat> 323 </repeat>
316 </when> 324 </when>
317 </conditional> 325 </conditional>
318 </inputs> 326 </inputs>
319 <outputs> 327 <outputs>
320 <data format="pdf" name="plots" from_work_dir="mzplots.pdf" label="${tool.name} on ${on_string}"/> 328 <data format="pdf" name="plots" from_work_dir="mzplots.pdf" label="${tool.name} on ${on_string}:results"/>
321 </outputs> 329 </outputs>
322 <tests> 330 <tests>
323 <test> 331 <test>
324 <expand macro="infile_imzml"/> 332 <expand macro="infile_imzml"/>
325 <conditional name="pixel_conditional"> 333 <conditional name="pixel_conditional">