Mercurial > repos > galaxyp > msi_qualitycontrol

comparison msi_qualitycontrol.xml @ 15:2d69460669ae draft

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planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_qualitycontrol commit 620a469e20836b921b6c0147421c8a4268b66ebd
author galaxyp
date Wed, 15 Aug 2018 05:40:29 -0400
parents 7c7c39b9ec4a
children ed23ae226cdc
comparison
equal deleted inserted replaced
14:7c7c39b9ec4a 15:2d69460669ae
1 <tool id="mass_spectrometry_imaging_qc" name="MSI Qualitycontrol" version="1.10.0.5"> 1 <tool id="mass_spectrometry_imaging_qc" name="MSI Qualitycontrol" version="1.10.0.6">
2 <description> 2 <description>
3 mass spectrometry imaging QC 3 mass spectrometry imaging QC
4 </description> 4 </description>
5 <requirements> 5 <requirements>
6 <requirement type="package" version="1.10.0">bioconductor-cardinal</requirement> 6 <requirement type="package" version="1.10.0">bioconductor-cardinal</requirement>
284 284
285 ## append list for optional tabular output with spectrum values 285 ## append list for optional tabular output with spectrum values
286 spectrum_list[[list_count]] = position_df 286 spectrum_list[[list_count]] = position_df
287 list_count = list_count+1 287 list_count = list_count+1
288 288
289 colnames(position_df)[3] = "Annotation" 289 colnames(position_df)[3] = "annotation"
290 combine_plot = ggplot(position_df, aes(x=x, y=y, fill=Annotation))+ 290
291 print(position_df)
292 print(class(position_df\$x))
293 print(class(position_df\$annotation))
294
295 combine_plot = ggplot(position_df, aes(x=x, y=y, fill=annotation))+
291 geom_tile() + 296 geom_tile() +
292 coord_fixed()+ 297 coord_fixed()+
293 ggtitle("Spatial orientation of combined data")+ 298 ggtitle("Spatial orientation of pixel annotations")+
294 theme_bw()+ 299 theme_bw()+
295 theme(plot.title = element_text(hjust = 0.5))+ 300 theme(plot.title = element_text(hjust = 0.5))+
296 theme(text=element_text(family="ArialMT", face="bold", size=12))+ 301 theme(text=element_text(family="ArialMT", face="bold", size=12))+
297 theme(legend.position="bottom",legend.direction="vertical")+ 302 theme(legend.position="bottom",legend.direction="vertical")+
298 theme(legend.key.size = unit(0.2, "line"), legend.text = element_text(size = legend_size))+ 303 theme(legend.key.size = unit(0.2, "line"), legend.text = element_text(size = legend_size))+
842 count=count+1 847 count=count+1
843 } 848 }
844 849
845 ######### 17) ppm difference input calibrant m/z and m/z with max intensity in given m/z range######### 850 ######### 17) ppm difference input calibrant m/z and m/z with max intensity in given m/z range#########
846 851
852 par(mfrow = c(1,1))
847 ### plot the ppm difference calculated above: theor. m/z value to highest m/z value: 853 ### plot the ppm difference calculated above: theor. m/z value to highest m/z value:
848 854
849 calibrant_names = as.character(inputcalibrants[,2]) 855 calibrant_names = as.character(inputcalibrants[,2])
850 diff_df = data.frame(differencevector, calibrant_names) 856 diff_df = data.frame(differencevector, calibrant_names)
851 857
852 if (sum(is.na(diff_df[,1])) == nrow(diff_df)){ 858 if (sum(is.na(diff_df[,1])) == nrow(diff_df)){
853 plot(0,type='n',axes=FALSE,ann=FALSE) 859 plot(0,type='n',axes=FALSE,ann=FALSE)
854 title(main=paste("plot 17: no peaks in the chosen region, repeat with higher ppm range")) ## here klammer weggenommen... 860 title(main=paste("plot 17: no peaks in the chosen region, repeat with higher ppm range"))
855 }else{ 861 }else{
856 862
857 diff_plot1=ggplot(data=diff_df, aes(x=calibrant_names, y=differencevector)) + geom_bar(stat="identity", fill = "darkgray") + theme_minimal() + 863 diff_plot1=ggplot(data=diff_df, aes(x=calibrant_names, y=differencevector)) + geom_bar(stat="identity", fill = "darkgray") + theme_minimal() +
858 labs(title="Average m/z error (max. average intensity vs. theor. calibrant m/z)", x="calibrants", y = "Average m/z error in ppm")+ 864 labs(title="Average m/z error (max. average intensity vs. theor. calibrant m/z)", x="calibrants", y = "Average m/z error in ppm")+
859 theme(plot.title = element_text(hjust = 0.5, size=14))+theme(text=element_text(family="ArialMT", face="bold", size=16))+ 865 theme(plot.title = element_text(hjust = 0.5, size=14))+theme(text=element_text(family="ArialMT", face="bold", size=14))+
860 geom_text(aes(label=differencevector), vjust=-0.3, size=5.5, col="blue") + 866 geom_text(aes(label=differencevector), vjust=-0.3, size=5.5, col="blue") +
861 theme(axis.text.x = element_text(angle = 90, hjust = 1, size=16)) 867 theme(axis.text.x = element_text(angle = 90, hjust = 1, size=14))
862 868
863 print(diff_plot1) 869 print(diff_plot1)
864 } 870 }
865 871
866 ######### 18) ppm difference input calibrant m/z and closest m/z ########### 872 ######### 18) ppm difference input calibrant m/z and closest m/z ###########
871 calibrant_names = as.character(inputcalibrants[,2]) 877 calibrant_names = as.character(inputcalibrants[,2])
872 diff_df = data.frame(differencevector2, calibrant_names) 878 diff_df = data.frame(differencevector2, calibrant_names)
873 879
874 diff_plot2=ggplot(data=diff_df, aes(x=calibrant_names, y=differencevector2)) + geom_bar(stat="identity", fill = "darkgray") + theme_minimal() + 880 diff_plot2=ggplot(data=diff_df, aes(x=calibrant_names, y=differencevector2)) + geom_bar(stat="identity", fill = "darkgray") + theme_minimal() +
875 labs(title="Average m/z error (closest measured m/z vs. theor. calibrant m/z)", x="calibrants", y = "Average m/z error in ppm")+ 881 labs(title="Average m/z error (closest measured m/z vs. theor. calibrant m/z)", x="calibrants", y = "Average m/z error in ppm")+
876 theme(plot.title = element_text(hjust = 0.5, size=16))+theme(text=element_text(family="ArialMT", face="bold", size=16))+ 882 theme(plot.title = element_text(hjust = 0.5, size=14))+theme(text=element_text(family="ArialMT", face="bold", size=14))+
877 geom_text(aes(label=differencevector2), vjust=-0.3, size=5.5, col="blue")+ 883 geom_text(aes(label=differencevector2), vjust=-0.3, size=5.5, col="blue")+
878 theme(axis.text.x = element_text(angle = 90, hjust = 1, size=16)) 884 theme(axis.text.x = element_text(angle = 90, hjust = 1, size=14))
879 885
880 print(diff_plot2) 886 print(diff_plot2)
881 887
882 #################### 19) ppm difference over pixels ##################### 888 #################### 19) ppm difference over pixels #####################
883 889