Mercurial > repos > galaxyp > cardinal_spectra_plots

comparison spectra_plots.xml @ 14:1693b2126f30 draft

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"planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/cardinal commit 180894cfabbee2d308be140a0f0b4dba119e88d4-dirty"
author galaxyp
date Wed, 23 Dec 2020 22:28:42 +0000
parents c5aa9fca18c6
children d333733dd571
comparison
equal deleted inserted replaced
13:c5aa9fca18c6 14:1693b2126f30
1 <tool id="cardinal_spectra_plots" name="MSI plot spectra" version="@VERSION@.2"> 1 <tool id="cardinal_spectra_plots" name="MSI plot spectra" version="@VERSION@.3">
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>
69 #if str($pixel_conditional.single_or_overlaid.plot_type) == 'overlaid_plots': 69 #if str($pixel_conditional.single_or_overlaid.plot_type) == 'overlaid_plots':
70 70
71 spectra_input = spectra_tabular[,c($pixel_conditional.column_pixel_x, $pixel_conditional.column_pixel_y, $pixel_conditional.single_or_overlaid.column_pixel_annotation)] 71 spectra_input = spectra_tabular[,c($pixel_conditional.column_pixel_x, $pixel_conditional.column_pixel_y, $pixel_conditional.single_or_overlaid.column_pixel_annotation)]
72 colnames(spectra_input) = c("x", "y", "annotation") 72 colnames(spectra_input) = c("x", "y", "annotation")
73 spectra_input\$annotation = as.character(spectra_input\$annotation) 73 spectra_input\$annotation = as.character(spectra_input\$annotation)
74 74
75 msidata_coordinates = data.frame(coord(msidata)\$x, coord(msidata)\$y) 75 ## keeping only spectra with annotations
76 colnames(msidata_coordinates) = c("x", "y") 76 input_pixels = paste(spectra_input[,1], spectra_input[,2], sep="_")
77 merged_annotation = merge(msidata_coordinates, spectra_input, by=c("x", "y")) 77 dataset_pixels = paste(coord(msidata)\$x, coord(msidata)\$y, sep="_")
78 pixelsofinterest = dataset_pixels %in% input_pixels
79 msidata = msidata[,pixelsofinterest]
80
81 msidata_coordinates = data.frame(coord(msidata)\$x, coord(msidata)\$y, c(1:ncol(msidata)))
82 colnames(msidata_coordinates) = c("x", "y", "pixel_index")
83 merged_annotation = merge(msidata_coordinates, spectra_input, by=c("x", "y"), all.x=TRUE)
78 merged_annotation[is.na(merged_annotation)] = "NA" 84 merged_annotation[is.na(merged_annotation)] = "NA"
79 85 merged_annotation = merged_annotation[order(merged_annotation\$pixel_index),]
80 merged_annotation = merged_annotation[order(merged_annotation\$annotation),] 86 msidata\$annotation = factor(merged_annotation[,4], levels = unique(as.character(merged_annotation[,4]))) ## keep the right order
81 msidata\$annotation = factor(merged_annotation\$annotation) 87
82 88 print(msidata\$annotation)
83 89 print(merged_annotation)
90
84 ## overview plot over annotated samples 91 ## overview plot over annotated samples
85 number_combined = length(levels(msidata\$annotation)) 92 number_combined = length(levels(msidata\$annotation))
86 93
87 ## the more annotation groups a file has the smaller will be the legend 94 ## the more annotation groups a file has the smaller will be the legend
88 if (number_combined<20){ 95 if (number_combined<20){
103 #set $color_string = ','.join(['"%s"' % $color.annotation_color for $color in $pixel_conditional.single_or_overlaid.colour_conditional.colours]) 110 #set $color_string = ','.join(['"%s"' % $color.annotation_color for $color in $pixel_conditional.single_or_overlaid.colour_conditional.colours])
104 colourvector = c($color_string) 111 colourvector = c($color_string)
105 112
106 #elif str($pixel_conditional.single_or_overlaid.colour_conditional.colour_type) == "colourpalette" 113 #elif str($pixel_conditional.single_or_overlaid.colour_conditional.colour_type) == "colourpalette"
107 114
108 number_levels = (length(levels(msidata\$annotation))) 115 number_levels = (length(levels(msidata\$annotation)))
109 116
110 colourvector = noquote($pixel_conditional.single_or_overlaid.colour_conditional.palettes)(number_levels) 117 colourvector = noquote($pixel_conditional.single_or_overlaid.colour_conditional.palettes)(number_levels)
111 118
112 #end if 119 #end if
113 120
114 position_df = merged_annotation 121 position_df = data.frame(coord(msidata)\$x, coord(msidata)\$y, as.factor(msidata\$annotation))
115 colnames(position_df) = c("x", "y", "sample_name") 122 colnames(position_df) = c("x", "y", "sample_name")
116 123 print(position_df)
117 combine_plot = ggplot(position_df, aes(x=x, y=y, fill=sample_name))+ 124 combine_plot = ggplot(position_df, aes(x=x, y=y, fill=sample_name))+
118 geom_tile(height = 1, width=1)+ 125 geom_tile(height = 1, width=1)+
119 coord_fixed()+ 126 coord_fixed()+
120 ggtitle("Spatial orientation of annotations")+ 127 ggtitle("Spatial orientation of annotations")+
121 theme_bw()+ 128 theme_bw()+
124 theme(legend.position="bottom",legend.direction="vertical")+ 131 theme(legend.position="bottom",legend.direction="vertical")+
125 theme(legend.key.size = unit(0.2, "line"), legend.text = element_text(size = 10))+ 132 theme(legend.key.size = unit(0.2, "line"), legend.text = element_text(size = 10))+
126 guides(fill=guide_legend(ncol=4,byrow=TRUE))+ 133 guides(fill=guide_legend(ncol=4,byrow=TRUE))+
127 scale_discrete_manual(aesthetics = c("colour", "fill"), values = colourvector) 134 scale_discrete_manual(aesthetics = c("colour", "fill"), values = colourvector)
128 135
129
130 coord_labels = aggregate(cbind(x,y)~sample_name, data=position_df, mean, na.rm=TRUE, na.action="na.pass") 136 coord_labels = aggregate(cbind(x,y)~sample_name, data=position_df, mean, na.rm=TRUE, na.action="na.pass")
131 coord_labels\$file_number = 1:length(unique(position_df\$sample_name)) 137 coord_labels\$file_number = 1:nrow(coord_labels)
132 138
133 for(file_count in 1:nrow(coord_labels)) 139 for(file_count in 1:nrow(coord_labels))
134 {combine_plot = combine_plot + annotate("text",x=coord_labels[file_count,"x"], 140 {combine_plot = combine_plot + annotate("text",x=coord_labels[file_count,"x"],
135 y=coord_labels[file_count,"y"],label=toString(coord_labels[file_count,4])) 141 y=coord_labels[file_count,"y"],label=toString(coord_labels[file_count,4]))
136 } 142 }
147 print(plot(msidata, run="infile", pixel.groups=msidata\$annotation, key=key_legend,superpose=TRUE, strip=FALSE, grid=$grid_variable, col = colourvector), main="Average spectrum per group") 153 print(plot(msidata, run="infile", pixel.groups=msidata\$annotation, key=key_legend,superpose=TRUE, strip=FALSE, grid=$grid_variable, col = colourvector), main="Average spectrum per group")
148 #end if 154 #end if
149 155
150 pixeldf = data.frame(table(msidata\$annotation)) 156 pixeldf = data.frame(table(msidata\$annotation))
151 colnames(pixeldf) = c("sample name", "number of pixels") 157 colnames(pixeldf) = c("sample name", "number of pixels")
152
153 158
154 ##################### II) Sample: plot zoom-in mass spectrum ########## 159 ##################### II) Sample: plot zoom-in mass spectrum ##########
155 160
156 #if str($mz_range.mz_range_options) == "manual_mz": 161 #if str($mz_range.mz_range_options) == "manual_mz":
157 162
177 return(features(msidata, mz=max(mz(msidata)))) 182 return(features(msidata, mz=max(mz(msidata))))
178 } 183 }
179 ) 184 )
180 185
181 ## plot single tabular mz, average per annotation, manual zoom 186 ## plot single tabular mz, average per annotation, manual zoom
182
183 print(plot(msidata[minmasspixel:maxmasspixel,], run="infile", strip=FALSE, col = colourvector, 187 print(plot(msidata[minmasspixel:maxmasspixel,], run="infile", strip=FALSE, col = colourvector,
184 xlim= c($token.xlimmin,$token.xlimmax),pixel.groups=msidata\$annotation, grid = $grid_variable, 188 xlim= c($token.xlimmin,$token.xlimmax),pixel.groups=msidata\$annotation, grid = $grid_variable,
185 key=key_legend, superpose=TRUE, main="Average spectrum per group")) 189 key=key_legend, superpose=TRUE, main="Average spectrum per group"))
186 #end for 190 #end for
187 191