Mercurial > repos > galaxyp > cardinal_quality_report
changeset 10:e4dda61bb5c8 draft
"planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/cardinal commit c8d3adac445b4e08e2724e22d7201bfc38bbf40f"
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--- a/macros.xml Wed May 13 17:55:17 2020 +0000 +++ b/macros.xml Sun Aug 29 07:16:49 2021 +0000 @@ -1,10 +1,10 @@ <macros> - <token name="@VERSION@">2.4.0</token> + <token name="@VERSION@">2.10.0</token> <xml name="requirements"> <requirements> <requirement type="package" version="@VERSION@">bioconductor-cardinal</requirement> - <requirement type="package" version="3.6.1">r-base</requirement> + <!--requirement type="package" version="3.6.1">r-base</requirement--> <yield/> </requirements> </xml> @@ -117,6 +117,13 @@ <token name="@DATA_PROPERTIES_INRAM@"><![CDATA[ ########################### QC numbers ######################## ## including intensity calculations which need data in RAM + + int_matrix = as.matrix(spectra(msidata)) ## only load once into RAM, then re-use + ## Number of NA in spectra matrix + NAcount = sum(is.na(int_matrix)) + ## replace NA with zero to calculate data properties based on intensity matrix, no change in msidata + int_matrix[is.na(int_matrix)] <- 0 + ## Number of features (mz) maxfeatures = length(features(msidata)) ## Range mz @@ -131,14 +138,12 @@ minimumy = min(coord(msidata)[,2]) maximumy = max(coord(msidata)[,2]) ## Range of intensities - minint = round(min(as.matrix(spectra(msidata)), na.rm=TRUE), digits=2) - maxint = round(max(as.matrix(spectra(msidata)), na.rm=TRUE), digits=2) + minint = round(min(int_matrix), digits=2) + maxint = round(max(int_matrix), digits=2) ## Number of intensities > 0, for if conditions - npeaks= sum(as.matrix(spectra(msidata))>0, na.rm=TRUE) + npeaks= sum(int_matrix>0) ## Number of NA in spectra matrix - NAcount = sum(is.na(spectra(msidata))) - ## Number of NA in spectra matrix - infcount = sum(is.infinite(as.matrix(spectra(msidata)))) + infcount = sum(is.infinite(int_matrix)) ## Number of duplicated coordinates dupl_coord = sum(duplicated(coord(msidata))) properties = c("Number of m/z features", @@ -175,7 +180,7 @@ - imzml file (upload imzml and ibd file via the "composite" function) `Introduction to the imzml format <https://ms-imaging.org/wp/imzml/>`_ - Analyze7.5 (upload hdr, img and t2m file via the "composite" function) - - Cardinal "MSImageSet" data saved as .RData + - Cardinal "MSImageSet" or "MSImagingExperiment" saved as .RData ]]></token> <token name="@MZ_TABULAR_INPUT_DESCRIPTION@"><![CDATA[ - Optional tabular file with m/z values: @@ -243,7 +248,7 @@ </param> <when value="no_processed"/> <when value="processed"> - <param name="accuracy" type="float" value="50" label="Mass accuracy to which the m/z values will be binned" help="This should be set to the native accuracy of the mass spectrometer, if known"/> + <param name="accuracy" type="float" value="50" label="Mass accuracy to which the m/z values will be binned"/> <param name="units" display="radio" type="select" label="Unit of the mass accuracy" help="either m/z or ppm"> <option value="mz" >mz</option> <option value="ppm" selected="True" >ppm</option>
--- a/quality_report.xml Wed May 13 17:55:17 2020 +0000 +++ b/quality_report.xml Sun Aug 29 07:16:49 2021 +0000 @@ -1,4 +1,4 @@ -<tool id="cardinal_quality_report" name="MSI Qualitycontrol" version="@VERSION@.1"> +<tool id="cardinal_quality_report" name="MSI Qualitycontrol" version="@VERSION@.0"> <description> mass spectrometry imaging QC </description> @@ -7,11 +7,11 @@ </macros> <expand macro="requirements"> <requirement type="package" version="2.3">r-gridextra</requirement> - <requirement type="package" version="3.2.1">r-ggplot2</requirement> + <requirement type="package" version="3.3.5">r-ggplot2</requirement> <requirement type="package" version="1.1_2">r-rcolorbrewer</requirement> - <requirement type="package" version="2.23_16">r-kernsmooth</requirement> - <requirement type="package" version="1.1.0">r-scales</requirement> - <requirement type="package" version="1.0.12"> r-pheatmap</requirement> + <requirement type="package" version="2.23_20">r-kernsmooth</requirement> + <requirement type="package" version="1.1.1">r-scales</requirement> + <requirement type="package" version="1.0.12">r-pheatmap</requirement> </expand> <command detect_errors="exit_code"> <![CDATA[ @@ -60,7 +60,7 @@ merged_annotation = merge(msidata_coordinates, annotation_input, by=c("x", "y"), all.x=TRUE) merged_annotation[is.na(merged_annotation)] = "NA" merged_annotation = merged_annotation[order(merged_annotation\$pixel_index),] - msidata\$annotation = as.factor(merged_annotation[,4]) + msidata\$annotation = as.character(merged_annotation[,4]) #end if @@ -68,13 +68,13 @@ @DATA_PROPERTIES_INRAM@ ## Median intensities -medint = round(median(spectra(msidata), na.rm=TRUE), digits=2) +medint = round(median(int_matrix), digits=2) ## Spectra multiplied with m/z (potential number of peaks) -numpeaks = ncol(msidata)*nrow(msidata) +numpeaks = as.numeric(ncol(msidata)*nrow(msidata)) ## Percentage of intensities > 0 percpeaks = round(npeaks/numpeaks*100, digits=2) ## Number of empty TICs -TICs = pixelApply(msidata, sum) +TICs = pixelApply(msidata, sum, na.rm=TRUE) NumemptyTIC = sum(TICs == 0) ## Median und sd TIC medTIC = round(median(TICs), digits=1) @@ -82,6 +82,8 @@ ## Median and sd # peaks per spectrum medpeaks = round(median(colSums(spectra(msidata)>0, na.rm=TRUE), na.rm=TRUE), digits=0) sdpeaks = round(sd(colSums(spectra(msidata)>0, na.rm=TRUE), na.rm=TRUE), digits=0) +##max window size +max_window = round(mz(msidata)[nrow(msidata)]-mz(msidata)[nrow(msidata)-1], digits=2) ## Processing informations centroidedinfo = centroided(msidata) @@ -137,6 +139,7 @@ "Number of empty spectra", "Median TIC ± sd", "Median # peaks per spectrum ± sd", + "maximum m/z window size", "Centroided", paste0("input m/z (#valid/#input) in \n", "$calibrant_file.display_name")) @@ -145,6 +148,7 @@ paste0(NumemptyTIC), paste0(medTIC, " ± ", sdTIC), paste0(medpeaks, " ± ",sdpeaks), + paste0(max_window), paste0(centroidedinfo), paste0(number_calibrants_valid, " / ", number_calibrants_in)) @@ -183,12 +187,13 @@ ### only for previously combined data, same plot as in combine QC pdf - if (!is.null(levels(msidata\$annotation))){ + if (!is.null(unique(msidata\$annotation))){ - number_combined = length(levels(msidata\$annotation)) + number_combined = length(unique(msidata\$annotation)) position_df = data.frame(coord(msidata)\$x, coord(msidata)\$y, msidata\$annotation) colnames(position_df) = c("x", "y","annotation") + print(position_df) combine_plot = ggplot(position_df, aes(x=x, y=y, fill=annotation))+ geom_tile() + @@ -220,7 +225,7 @@ pixelxyarray=data.frame(coord(msidata)\$x, coord(msidata)\$y,pixelnumber) colnames(pixelxyarray) = c("x", "y", "pixelnumber") gg_title = "Pixel order" - + print(ggplot(pixelxyarray, aes(x=x, y=y, fill=pixelnumber))+ geom_tile() + coord_fixed()+ ggtitle(gg_title) + theme_bw()+ @@ -354,24 +359,29 @@ #end if #################### 4) m/z heatmaps ####################################### - par(mfrow=c(1,1), mar=c(5.1, 4.1, 4.1, 2.1), mgp=c(3, 1, 0), las=0) - if (length(inputcalibrants[,1]) != 0){ - for (mass in 1:length(inputcalibrants[,1])){ - par(oma=c(0,0,0,1))## margin for image legend + + #if $report_depth: + + par(mfrow=c(1,1), mar=c(5.1, 4.1, 4.1, 2.1), mgp=c(3, 1, 0), las=0) + if (length(inputcalibrants[,1]) != 0){ + for (mass in 1:length(inputcalibrants[,1])){ + par(oma=c(0,0,0,1))## margin for image legend - tryCatch( - { - print(image(msidata, mz=inputcalibrants[,1][mass], plusminus=plusminusvalues[mass], - main= paste0(inputcalibrants[,2][mass], ": ", round(inputcalibrants[,1][mass], digits = 2)," (±",$plusminus_ppm, " ppm)"), - contrast.enhance = "histogram", strip=FALSE, ylim= c(maximumy,minimumy))) - }, - error=function(cond) { - ## if there are not enough intensities in the mz range skip creating an image - print(paste0("Not enough intensities > 0 for m/z ", inputcalibrants[,1][mass])) - } - ) - } - } else {print("4) The input peptide and calibrant m/z were not provided or outside the m/z range")} + tryCatch( + { + print(image(msidata, mz=inputcalibrants[,1][mass], plusminus=plusminusvalues[mass], + main= paste0(inputcalibrants[,2][mass], ": ", round(inputcalibrants[,1][mass], digits = 2)," (±",$plusminus_ppm, " ppm)"), + contrast.enhance = "histogram", strip=FALSE, ylim= c(maximumy,minimumy))) + }, + error=function(cond) { + ## if there are not enough intensities in the mz range skip creating an image + print(paste0("Not enough intensities > 0 for m/z ", inputcalibrants[,1][mass])) + } + ) + } + } else {print("4) The input peptide and calibrant m/z were not provided or outside the m/z range")} + + #end if #################### 5) Number of peaks per pixel - image ################## @@ -414,72 +424,75 @@ ############################### 6b) median int image ############################### - median_int = pixelApply(msidata, median) + #if $report_depth: + + median_int = pixelApply(msidata, median, na.rm=TRUE) - median_coordarray=data.frame(coord(msidata)\$x, coord(msidata)\$y, median_int) - colnames(median_coordarray) = c("x", "y", "median_int") - print(ggplot(median_coordarray, aes(x=x, y=y, fill=median_int))+ - geom_tile() + coord_fixed() + - ggtitle("Median intensity per spectrum")+ - theme_bw() + - theme(plot.title = element_text(hjust = 0.5))+ - theme(text=element_text(family="ArialMT", face="bold", size=12))+ - scale_fill_gradientn(colours = c("blue", "purple" , "red","orange") - ,space = "Lab", na.value = "black", name = "median\nintensity")) + median_coordarray=data.frame(coord(msidata)\$x, coord(msidata)\$y, median_int) + colnames(median_coordarray) = c("x", "y", "median_int") + print(ggplot(median_coordarray, aes(x=x, y=y, fill=median_int))+ + geom_tile() + coord_fixed() + + ggtitle("Median intensity per spectrum")+ + theme_bw() + + theme(plot.title = element_text(hjust = 0.5))+ + theme(text=element_text(family="ArialMT", face="bold", size=12))+ + scale_fill_gradientn(colours = c("blue", "purple" , "red","orange") + ,space = "Lab", na.value = "black", name = "median\nintensity")) - ## remove median_coordarray to clean up RAM space - rm(median_coordarray) - gc() + ## remove median_coordarray to clean up RAM space + rm(median_coordarray) + gc() - ############################### 6c) max int image ############################### - - max_int = pixelApply(msidata, max) + ############################### 6c) max int image ############################### + + max_int = pixelApply(msidata, max, na.rm=TRUE) - max_coordarray=data.frame(coord(msidata)\$x, coord(msidata)\$y, max_int) - colnames(max_coordarray) = c("x", "y", "max_int") - print(ggplot(max_coordarray, aes(x=x, y=y, fill=max_int))+ - geom_tile() + coord_fixed() + - ggtitle("Maximum intensity per spectrum")+ - theme_bw() + - theme(plot.title = element_text(hjust = 0.5))+ - theme(text=element_text(family="ArialMT", face="bold", size=12))+ - scale_fill_gradientn(colours = c("blue", "purple" , "red","orange") - ,space = "Lab", na.value = "black", name = "max\nintensity")) + max_coordarray=data.frame(coord(msidata)\$x, coord(msidata)\$y, max_int) + colnames(max_coordarray) = c("x", "y", "max_int") + print(ggplot(max_coordarray, aes(x=x, y=y, fill=max_int))+ + geom_tile() + coord_fixed() + + ggtitle("Maximum intensity per spectrum")+ + theme_bw() + + theme(plot.title = element_text(hjust = 0.5))+ + theme(text=element_text(family="ArialMT", face="bold", size=12))+ + scale_fill_gradientn(colours = c("blue", "purple" , "red","orange") + ,space = "Lab", na.value = "black", name = "max\nintensity")) - ## remove median_coordarray to clean up RAM space - rm(max_coordarray) - gc() + ## remove median_coordarray to clean up RAM space + rm(max_coordarray) + gc() + + ############################### 7) Most abundant m/z image ################# + + ## for each spectrum find the row (m/z) with the highest intensity + highestmz = pixelApply(msidata, which.max) - ############################### 7) Most abundant m/z image ################# - - ## for each spectrum find the row (m/z) with the highest intensity - highestmz = pixelApply(msidata, which.max) + ## in case for some spectra max returns integer(0), highestmz is a list and integer(0) have to be replaced with NA and unlisted + if (class(highestmz) == "list"){ + ##find zero-length values + zero_entry <- !(sapply(highestmz, length)) + ### replace these values with NA + highestmz[zero_entry] <- NA + ### unlist list to get a vector + highestmz = unlist(highestmz)} - ## in case for some spectra max returns integer(0), highestmz is a list and integer(0) have to be replaced with NA and unlisted - if (class(highestmz) == "list"){ - ##find zero-length values - zero_entry <- !(sapply(highestmz, length)) - ### replace these values with NA - highestmz[zero_entry] <- NA - ### unlist list to get a vector - highestmz = unlist(highestmz)} - - highestmz_matrix = data.frame(coord(msidata)\$x, coord(msidata)\$y,mz(msidata)[highestmz]) - colnames(highestmz_matrix) = c("x", "y", "highestmzinDa") + highestmz_matrix = data.frame(coord(msidata)\$x, coord(msidata)\$y,mz(msidata)[highestmz]) + colnames(highestmz_matrix) = c("x", "y", "highestmzinDa") - print(ggplot(highestmz_matrix, aes(x=x, y=y, fill=highestmzinDa))+ - geom_tile() + coord_fixed() + - ggtitle("Most abundant m/z in each spectrum")+ - theme_bw() + - theme(plot.title = element_text(hjust = 0.5))+ - scale_fill_gradientn(colours = c("blue", "purple" , "red","orange"), space = "Lab", na.value = "black", name = "m/z", - limits=c(min(highestmz_matrix\$highestmzinDa), max(highestmz_matrix\$highestmzinDa)))+ - theme(text=element_text(family="ArialMT", face="bold", size=12))) + print(ggplot(highestmz_matrix, aes(x=x, y=y, fill=highestmzinDa))+ + geom_tile() + coord_fixed() + + ggtitle("Most abundant m/z in each spectrum")+ + theme_bw() + + theme(plot.title = element_text(hjust = 0.5))+ + scale_fill_gradientn(colours = c("blue", "purple" , "red","orange"), space = "Lab", na.value = "black", name = "m/z", + limits=c(min(highestmz_matrix\$highestmzinDa), max(highestmz_matrix\$highestmzinDa)))+ + theme(text=element_text(family="ArialMT", face="bold", size=12))) - ## remove highestmz_matrix to clean up RAM space - rm(highestmz_matrix) - gc() + ## remove highestmz_matrix to clean up RAM space + rm(highestmz_matrix) + gc() + #end if ########################## 8) optional pca image for two components ################# @@ -495,7 +508,7 @@ par(oma=c(0,0,0,1))## margin for image legend print(image(pca, column = "PC1" , strip=FALSE, superpose = FALSE, main="PC1", col.regions = risk.colors(100), layout=c(2,1), ylim= c(maximumy+0.2*maximumy,minimumy-1))) print(image(pca, column = "PC2" , strip=FALSE, superpose = FALSE, main="PC2", col.regions = risk.colors(100), layout=FALSE, ylim= c(maximumy+0.2*maximumy,minimumy-1))) - ## remove pca to clean up RAM space + ## remove pca to clean up space rm(pca) gc() @@ -508,38 +521,44 @@ ########################## 9) number of peaks per spectrum ################# ## 9a) scatterplot + + #if $report_depth: - plot_colorByDensity(pixels(msidata), peaksperpixel, ylab = "", xlab = "", main="Number of peaks per spectrum") - title(xlab="Spectra index", line=3) - title(ylab="Number of peaks", line=4) + plot_colorByDensity(pixels(msidata), peaksperpixel, ylab = "", xlab = "", main="Number of peaks per spectrum") + title(xlab="Spectra index", line=3) + title(ylab="Number of peaks", line=4) - if (!is.null(levels(msidata\$annotation))){ - abline(v=abline_vector, lty = 3)} - - ## 9b) histogram + if (!is.null(unique(msidata\$annotation))){ + abline(v=abline_vector, lty = 3)} + + ## 9b) histogram + - hist(peaksperpixel, main="", las=1, xlab = "Number of peaks per spectrum", ylab="") - title(main="Number of peaks per spectrum", line=2) - title(ylab="Frequency = # spectra", line=4) - abline(v=median(peaksperpixel), col="blue") + + hist(peaksperpixel, main="", las=1, xlab = "Number of peaks per spectrum", ylab="") + title(main="Number of peaks per spectrum", line=2) + title(ylab="Frequency = # spectra", line=4) + abline(v=median(peaksperpixel), col="blue") - ## 9c) additional histogram to show contribution of annotation groups + ## 9c) additional histogram to show contribution of annotation groups - if (!is.null(levels(msidata\$annotation))){ - - df_9 = data.frame(peaksperpixel, msidata\$annotation) - colnames(df_9) = c("Npeaks", "annotation") + if (!is.null(unique(msidata\$annotation))){ - hist_9 = ggplot(df_9, aes(x=Npeaks, fill=annotation)) + - geom_histogram()+ theme_bw()+ - theme(text=element_text(family="ArialMT", face="bold", size=12))+ - theme(plot.title = element_text(hjust = 0.5))+ - theme(legend.key.size = unit(0.2, "line"), legend.text = element_text(size = 8))+ - theme(legend.position="bottom",legend.direction="vertical")+ - labs(title="Number of peaks per spectrum and annotation group", x="Number of peaks per spectrum", y = "Frequency = # spectra") + - guides(fill=guide_legend(ncol=5,byrow=TRUE))+ - geom_vline(xintercept = median(peaksperpixel), size = 1, colour = "black",linetype = "dashed") - print(hist_9)} + df_9 = data.frame(peaksperpixel, msidata\$annotation) + colnames(df_9) = c("Npeaks", "annotation") + + hist_9 = ggplot(df_9, aes(x=Npeaks, fill=annotation)) + + geom_histogram()+ theme_bw()+ + theme(text=element_text(family="ArialMT", face="bold", size=12))+ + theme(plot.title = element_text(hjust = 0.5))+ + theme(legend.key.size = unit(0.2, "line"), legend.text = element_text(size = 8))+ + theme(legend.position="bottom",legend.direction="vertical")+ + labs(title="Number of peaks per spectrum and annotation group", x="Number of peaks per spectrum", y = "Frequency = # spectra") + + guides(fill=guide_legend(ncol=5,byrow=TRUE))+ + geom_vline(xintercept = median(peaksperpixel), size = 1, colour = "black",linetype = "dashed") + print(hist_9)} + + #end if ########################## 10) TIC per spectrum ########################### @@ -555,17 +574,17 @@ title(xlab="Spectra index", line=3) title(ylab = "Total ion current intensity", line=4) - if (!is.null(levels(msidata\$annotation))){ + if (!is.null(unique(msidata\$annotation))){ abline(v=abline_vector, lty = 3)} ## 10b) histogram - hist((TICs), main="", las=1, xlab = "TIC per spectrum", ylab="") + hist(TICs, main="", las=1, xlab = "TIC per spectrum", ylab="") title(main= "TIC per spectrum", line=2) title(ylab="Frequency = # spectra", line=4) abline(v=median(TICs[TICs>0]), col="blue") ## 10c) additional histogram to show annotation contributions - if (!is.null(levels(msidata\$annotation))){ + if (!is.null(unique(msidata\$annotation))){ df_10 = data.frame((TICs), msidata\$annotation) colnames(df_10) = c("TICs", "annotation") @@ -591,68 +610,71 @@ ########################## 12) Number of peaks per m/z ##################### - peakspermz = rowSums(spectra(msidata) > 0, na.rm=TRUE) + #if $report_depth: + + peakspermz = rowSums(spectra(msidata) > 0, na.rm=TRUE) - par(mfrow = c(2,1), mar=c(5,6,4,4.5)) - ## 12a) scatterplot - plot_colorByDensity(mz(msidata),peakspermz, main= "Number of peaks per m/z", ylab ="") - title(xlab="m/z", line=2.5) - title(ylab = "Number of peaks", line=4) - axis(4, at=pretty(peakspermz),labels=as.character(round((pretty(peakspermz)/pixelcount*100), digits=1)), las=1) - mtext("Coverage of spectra [%]", 4, line=3, adj=1) + par(mfrow = c(2,1), mar=c(5,6,4,4.5)) + ## 12a) scatterplot + plot_colorByDensity(mz(msidata),peakspermz, main= "Number of peaks per m/z", ylab ="") + title(xlab="m/z", line=2.5) + title(ylab = "Number of peaks", line=4) + axis(4, at=pretty(peakspermz),labels=as.character(round((pretty(peakspermz)/pixelcount*100), digits=1)), las=1) + mtext("Coverage of spectra [%]", 4, line=3, adj=1) - ## 12b) histogram - hist(peakspermz, main="", las=1, ylab="", xlab="") - title(ylab = "Frequency", line=4) - title(main="Number of peaks per m/z", xlab = "Number of peaks per m/z", line=2) - abline(v=median(peakspermz), col="blue") + ## 12b) histogram + hist(peakspermz, main="", las=1, ylab="", xlab="") + title(ylab = "Frequency", line=4) + title(main="Number of peaks per m/z", xlab = "Number of peaks per m/z", line=2) + abline(v=median(peakspermz), col="blue") - ########################## 13) Sum of intensities per m/z ################## + ########################## 13) Sum of intensities per m/z ################## - ## Sum of all intensities for each m/z (like TIC, but for m/z instead of pixel) - mzTIC = featureApply(msidata, sum, na.rm=TRUE) ## calculate intensity sum for each m/z + ## Sum of all intensities for each m/z (like TIC, but for m/z instead of pixel) + mzTIC = featureApply(msidata, sum, na.rm=TRUE) ## calculate intensity sum for each m/z - par(mfrow = c(2,1), mar=c(5,6,4,2)) - ## 13a) scatterplot - plot_colorByDensity(mz(msidata),mzTIC, main= "Sum of intensities per m/z", ylab ="") - title(xlab="m/z", line=2.5) - title(ylab="Intensity sum", line=4) + par(mfrow = c(2,1), mar=c(5,6,4,2)) + ## 13a) scatterplot + plot_colorByDensity(mz(msidata),mzTIC, main= "Sum of intensities per m/z", ylab ="") + title(xlab="m/z", line=2.5) + title(ylab="Intensity sum", line=4) - ## 13b) histogram - hist(mzTIC, main="", xlab = "", las=1, ylab="") - title(main="Sum of intensities per m/z", line=2, ylab="") - title(xlab = "sum of intensities per m/z") - title(ylab = "Frequency", line=4) - abline(v=median(mzTIC[mzTIC>0]), col="blue") + ## 13b) histogram + hist(mzTIC, main="", xlab = "", las=1, ylab="") + title(main="Sum of intensities per m/z", line=2, ylab="") + title(xlab = "sum of intensities per m/z") + title(ylab = "Frequency", line=4) + abline(v=median(mzTIC[mzTIC>0]), col="blue") - ################################## V) intensity plots ######################## - ############################################################################ - print("intensity plots") - ########################## 14) Intensity distribution ###################### + ################################## V) intensity plots ######################## + ############################################################################ + print("intensity plots") + ########################## 14) Intensity distribution ###################### - par(mfrow = c(2,1), mar=c(5,6,4,2)) + par(mfrow = c(2,1), mar=c(5,6,4,2)) - ## 14a) Median intensity over spectra - medianint_spectra = pixelApply(msidata, median) - plot(medianint_spectra, main="Median intensity per spectrum",las=1, xlab="Spectra index", ylab="") - title(ylab="Median spectrum intensity", line=4) - if (!is.null(levels(msidata\$annotation))){ - abline(v=abline_vector, lty = 3)} + ## 14a) Median intensity over spectra + medianint_spectra = pixelApply(msidata, median, na.rm=TRUE) + plot(medianint_spectra, main="Median intensity per spectrum",las=1, xlab="Spectra index", ylab="") + title(ylab="Median spectrum intensity", line=4) + if (!is.null(unique(msidata\$annotation))){ + abline(v=abline_vector, lty = 3)} - ## 14b) histogram: - hist(as.matrix(spectra(msidata)), main="", xlab = "", ylab="", las=1) - title(main="Intensity histogram", line=2) - title(xlab="intensities") - title(ylab="Frequency", line=4) - abline(v=median(as.matrix(spectra(msidata))[(as.matrix(spectra(msidata))>0)], na.rm=TRUE), col="blue") + ## 14b) histogram: + hist(int_matrix, main="", xlab = "", ylab="", las=1) + title(main="Intensity histogram", line=2) + title(xlab="intensities") + title(ylab="Frequency", line=4) + abline(v=median(int_matrix)[(as.matrix(spectra(msidata))>0)], col="blue") + #end if ## 14c) histogram to show contribution of annotation groups - if (!is.null(levels(msidata\$annotation))){ + if (!is.null(unique(msidata\$annotation))){ df_13 = data.frame(matrix(,ncol=2, nrow=0)) - for (subsample in levels(msidata\$annotation)){ + for (subsample in unique(msidata\$annotation)){ log2_int_subsample = spectra(msidata)[,msidata\$annotation==subsample] df_subsample = data.frame(as.numeric(log2_int_subsample)) df_subsample\$annotation = subsample @@ -668,43 +690,43 @@ theme(legend.position="bottom",legend.direction="vertical")+ theme(legend.key.size = unit(0.2, "line"), legend.text = element_text(size = 8))+ guides(fill=guide_legend(ncol=5,byrow=TRUE))+ - geom_vline(xintercept = median(spectra(msidata)[(spectra(msidata)>0)]), size = 1, colour = "black",linetype = "dashed") + geom_vline(xintercept = median(int_matrix)[(int_matrix>0)], size = 1, colour = "black",linetype = "dashed") print(hist_13) ## 14d) boxplots to visualize in a different way the intensity distributions - par(mfrow = c(1,1), cex.axis=1.3, cex.lab=1.3, mar=c(13.1,4.1,5.1,2.1)) + par(mfrow = c(1,1), cex.axis=1.3, cex.lab=1.3, mar=c(10,4.1,5.1,2.1)) mean_matrix = matrix(,ncol=0, nrow = nrow(msidata)) - for (subsample in levels(msidata\$annotation)){ + for (subsample in unique(msidata\$annotation)){ mean_mz_sample = rowMeans(spectra(msidata)[,msidata\$annotation==subsample],na.rm=TRUE) mean_matrix = cbind(mean_matrix, mean_mz_sample)} - - boxplot(log10(mean_matrix), ylab = "Log10 mean intensity per m/z", main="Log10 mean m/z intensities per annotation group", xaxt = "n") - (axis(1, at = c(1:number_combined), labels=levels(msidata\$annotation), las=2)) + + boxplot(log10(as.data.frame(mean_matrix)), ylab = "Log10 mean intensity per m/z", main="Log10 mean m/z intensities per annotation group", xaxt = "n") + (axis(1, at = c(1:number_combined), cex.axis=0.9, labels=unique(msidata\$annotation), las=2)) ## 14e) Heatmap of mean intensities of annotation groups - colnames(mean_matrix) = levels(msidata\$annotation) + colnames(mean_matrix) = unique(msidata\$annotation) mean_matrix[is.na(mean_matrix)] = 0 heatmap.parameters <- list(mean_matrix, show_rownames = T, show_colnames = T, main = "Heatmap of mean intensities per annotation group") - par(oma=c(3,0,0,0)) - print(heatmap(mean_matrix),margins = c(10, 10)) + par(oma=c(5,0,0,0)) + heatmap(mean_matrix) ## 14f) PCA of mean intensities of annotation groups - + par(mar=c(4.1, 4.1, 4.1, 8.5)) ## define annotation by colour - annotation_colour = rainbow(length(levels(msidata\$annotation)))[as.factor(levels(msidata\$annotation))] + annotation_colour = rainbow(length(unique(msidata\$annotation)))[as.factor(unique(msidata\$annotation))] ## transform and scale dataframe pca = prcomp(t(mean_matrix),center=FALSE,scale.=FALSE) ## plot single plot plot(pca\$x[,c(1,2)],col=annotation_colour,pch=19) + legend("topright",xpd=TRUE, bty="n", inset=c(-0.3,0), cex=0.8, legend=unique(msidata\$annotation), col=rainbow(length(unique(msidata\$annotation))), pch=19) ## plot pca with colours for max first 5 PCs pc_comp = ifelse(ncol(pca\$x)<5 , ncol(pca\$x), 5) pairs(pca\$x[,1:pc_comp],col=annotation_colour,pch=19) - legend("bottom", horiz = TRUE, legend=levels(msidata\$annotation), col=rainbow(length(levels(msidata\$annotation))), pch=19) } @@ -714,36 +736,40 @@ ############################ 15) Mass spectra ############################## + ## replace any NA with 0, otherwise plot function will not work at all msidata_no_NA = msidata + + #if $report_depth: - ## find three equal m/z ranges for the average mass spectra plots: - third_mz_range = round(nrow(msidata_no_NA)/3,0) + ## find three equal m/z ranges for the average mass spectra plots: + third_mz_range = round(nrow(msidata_no_NA)/3,0) - par(cex.axis=1, cex.lab=1, mar=c(5.1,4.1,4.1,2.1)) - print(plot(msidata_no_NA, run="infile", layout=c(2,2), strip=FALSE, main= "Average spectrum")) - print(plot(msidata_no_NA[1:third_mz_range,], layout=FALSE, run="infile", strip=FALSE, main="Zoomed average spectrum")) - print(plot(msidata_no_NA[third_mz_range:(2*third_mz_range),], layout=FALSE, run="infile", strip=FALSE, main="Zoomed average spectrum")) - print(plot(msidata_no_NA[(2*third_mz_range):nrow(msidata_no_NA),], layout=FALSE, run="infile", strip=FALSE, main="Zoomed average spectrum")) + par(cex.axis=1, cex.lab=1, mar=c(5.1,4.1,4.1,2.1)) + print(plot(msidata_no_NA, run="infile", layout=c(2,2), strip=FALSE, main= "Average spectrum", col="black")) + print(plot(msidata_no_NA[1:third_mz_range,], layout=FALSE, run="infile", strip=FALSE, main="Zoomed average spectrum", col="black")) + print(plot(msidata_no_NA[third_mz_range:(2*third_mz_range),], layout=FALSE, run="infile", strip=FALSE, main="Zoomed average spectrum", col="black")) + print(plot(msidata_no_NA[(2*third_mz_range):nrow(msidata_no_NA),], layout=FALSE, run="infile", strip=FALSE, main="Zoomed average spectrum", col="black")) - ## plot one average mass spectrum for each pixel annotation group + ## plot one average mass spectrum for each pixel annotation group - if (!is.null(levels(msidata\$annotation))){ - ## print legend only for less than 10 samples - if (length(levels(msidata\$annotation)) < 10){ - key_legend = TRUE - }else{key_legend = FALSE} - par(mfrow = c(1,1), cex.axis=1, cex.lab=1, mar=c(5.1,4.1,4.1,2.1)) - print(plot(msidata, run="infile", pixel.groups=msidata\$annotation, key=key_legend, col=hue_pal()(length(levels(msidata\$annotation))),superpose=TRUE, main="Average mass spectra for annotation groups")) - } + if (!is.null(unique(msidata\$annotation))){ + ## print legend only for less than 10 samples + if (length(unique(msidata\$annotation)) < 10){ + key_legend = TRUE + }else{key_legend = FALSE} + par(mfrow = c(1,1), cex.axis=1, cex.lab=1, mar=c(5.1,4.1,4.1,2.1)) + print(plot(msidata, run="infile", pixel.groups=msidata\$annotation, key=key_legend, col=hue_pal()(length(unique(msidata\$annotation))),superpose=TRUE, main="Average mass spectra for annotation groups")) + } - ## plot 4 random mass spectra - ## find four random, not empty pixel to plot their spectra in the following plots: - pixel_vector = sample(which(TICs != 0),4) + ## plot 4 random mass spectra + ## find four random, not empty pixel to plot their spectra in the following plots: + pixel_vector = sample(which(TICs != 0),4) - par(mfrow = c(2, 2), cex.axis=1, cex.lab=1, mar=c(5.1,4.1,4.1,2.1)) - print(plot(msidata_no_NA, pixel = pixel_vector)) + par(mfrow = c(2, 2), cex.axis=1, cex.lab=1, mar=c(5.1,4.1,4.1,2.1)) + print(plot(msidata_no_NA, pixel = pixel_vector, col="black")) + #end if ################### 16) Zoomed in mass spectra for calibrants ############## @@ -753,6 +779,7 @@ if (length(inputcalibrantmasses) != 0){ + ### calculate plusminus values in m/z for each calibrant, this is used for all following plots plusminusvalues = rep($plusminus_ppm/1000000, length(inputcalibrantmasses)) * inputcalibrantmasses @@ -765,6 +792,17 @@ maxmasspixel2 = features(msidata_no_NA, mz=inputcalibrantmasses[mass]+0.5) minmasspixel3 = features(msidata_no_NA, mz=inputcalibrantmasses[mass]-1.5) maxmasspixel3 = features(msidata_no_NA, mz=inputcalibrantmasses[mass]+3) + + ## test if some values are lower than min(mz) + minmasspixel1 = ifelse(length(minmasspixel1)>0, minmasspixel1, 1) + minmasspixel2 = ifelse(length(minmasspixel2)>0, minmasspixel2, 1) + minmasspixel3 = ifelse(length(minmasspixel3)>0, minmasspixel3, 1) + + ## test if min and max are same (more likely for centroided data): + maxmasspixel1 = ifelse(minmasspixel1 != maxmasspixel1, maxmasspixel1, maxmasspixel1 + 1) + maxmasspixel2 = ifelse(minmasspixel2 != maxmasspixel2, maxmasspixel2, maxmasspixel1 + 1) + maxmasspixel3 = ifelse(minmasspixel3 != maxmasspixel3, maxmasspixel3, maxmasspixel1 + 1) + ### find m/z with the highest mean intensity in m/z range (red line in plot 16) and calculate ppm difference for plot 17 filtered_data = msidata_no_NA[mz(msidata_no_NA) >= inputcalibrantmasses[mass]-plusminusvalues[mass] & mz(msidata_no_NA) <= inputcalibrantmasses[mass]+plusminusvalues[mass],] @@ -790,20 +828,20 @@ par(oma=c(0,0,2,0)) ## average plot - print(plot(msidata_no_NA[minmasspixel1:maxmasspixel1,], run="infile", layout=c(2,2), strip=FALSE, main= "Average spectrum")) + print(plot(msidata_no_NA[minmasspixel1:maxmasspixel1,], run="infile", layout=c(2,2), strip=FALSE, main= "Average spectrum", col="black")) abline(v=c(inputcalibrantmasses[mass] -plusminusvalues[count], inputcalibrantmasses[mass] ,inputcalibrantmasses[mass] +plusminusvalues[count]), col="blue", lty=c(3,5,3)) abline(v=c(maxvalue), col="red", lty=2) abline(v=c(mzvalue), col="green2", lty=4) ## average plot including points per data point - print(plot(msidata_no_NA[minmasspixel1:maxmasspixel1,], run="infile", layout=FALSE, strip=FALSE, main="Average spectrum with data points")) + print(plot(msidata_no_NA[minmasspixel1:maxmasspixel1,], run="infile", layout=FALSE, strip=FALSE, main="Average spectrum with data points", col="black")) points(mz(msidata_no_NA[minmasspixel1:maxmasspixel1,]), rowMeans(spectra(msidata_no_NA)[minmasspixel1:maxmasspixel1,,drop=FALSE]), col="blue", pch=20) ## plot of third average plot - print(plot(msidata_no_NA[minmasspixel2:maxmasspixel2,], run="infile", layout=FALSE, strip=FALSE, main= "Average spectrum")) + print(plot(msidata_no_NA[minmasspixel2:maxmasspixel2,], run="infile", layout=FALSE, strip=FALSE, main= "Average spectrum", col="black")) abline(v=c(inputcalibrantmasses[mass] -plusminusvalues[count], inputcalibrantmasses[mass] ,inputcalibrantmasses[mass] +plusminusvalues[count]), col="blue", lty=c(3,5,3)) abline(v=c(maxvalue), col="red", lty=2) abline(v=c(mzvalue), col="green2", lty=4) ## plot of fourth average plot - print(plot(msidata_no_NA[minmasspixel3:maxmasspixel3,], run="infile", layout=FALSE, strip=FALSE, main= "Average spectrum")) + print(plot(msidata_no_NA[minmasspixel3:maxmasspixel3,], run="infile", layout=FALSE, strip=FALSE, main= "Average spectrum", col="black")) abline(v=c(inputcalibrantmasses[mass] -plusminusvalues[count], inputcalibrantmasses[mass] ,inputcalibrantmasses[mass] +plusminusvalues[count]), col="blue", lty=c(3,5,3)) abline(v=c(maxvalue), col="red", lty=2) abline(v=c(mzvalue), col="green2", lty=4) @@ -813,7 +851,7 @@ ### 16b) one large extra plot with different colours for different pixel annotation groups - if (!is.null(levels(msidata\$annotation))){ + if (!is.null(unique(msidata\$annotation))){ if (number_combined < 10){ key_zoomed = TRUE }else{key_zoomed = FALSE} @@ -831,12 +869,16 @@ ######### 17) ppm difference input calibrant m/z and m/z with max intensity in given m/z range######### + #if $report_depth: + par(mfrow = c(1,1)) ### plot the ppm difference calculated above: theor. m/z value to highest m/z value: calibrant_names = as.character(inputcalibrants[,2]) + diff_df = data.frame(differencevector, calibrant_names) + if (sum(is.na(diff_df[,1])) == nrow(diff_df)){ plot(0,type='n',axes=FALSE,ann=FALSE) title(main=paste("plot 17: no peaks in the chosen region, repeat with higher ppm range")) @@ -866,6 +908,8 @@ theme(axis.text.x = element_text(angle = 90, hjust = 1, size=14)) print(diff_plot2) + + #end if #################### 19) ppm difference over pixels ##################### @@ -910,11 +954,12 @@ for (each_cal in 1:ncol(ppm_df)){ lines(ppm_df[,each_cal], col=mycolours[each_cal], type="p")} legend("topright", inset=c(-0.2,0), xpd = TRUE, bty="n", cex=0.8,legend=inputcalibrantmasses, col=mycolours[1:ncol(ppm_df)],lty=1) - if (!is.null(levels(msidata\$annotation))){ + if (!is.null(unique(msidata\$annotation))){ abline(v=abline_vector, lty = 3)}} ### make x-y-images for mz accuracy + #if $report_depth: ppm_dataframe = data.frame(coord(msidata)\$x, coord(msidata)\$y, ppm_df) colnames(ppm_dataframe) = c("x", "y", "ppm_df") @@ -931,6 +976,7 @@ theme(text=element_text(family="ArialMT", face="bold", size=12))+ scale_fill_gradient2(low = "navy", mid = "grey", high = "red", midpoint = 0 ,space = "Lab", na.value = "black", name = "ppm\nerror"))} + #end if }else{print("plot 16+17+18+19) The inputcalibrant m/z were not provided or outside the m/z range")} }else{ @@ -957,6 +1003,7 @@ <expand macro="reading_2_column_mz_tabular" optional="true"/> <param name="plusminus_ppm" value="200" type="float" label="ppm range" help="Will be added in both directions to input calibrant m/z"/> <param name="do_pca" type="boolean" label="PCA with 2 components"/> + <param name="report_depth" type="boolean" label="Generate full QC report" truevalue="TRUE" falsevalue="FALSE" checked="True" help="No: does not generate all plots but only the most informatives"/> <repeat name="calibrantratio" title="Plot fold change of two m/z" min="0" max="10"> <param name="mass1" value="1111" type="float" label="M/z 1" help="First m/z"/> <param name="mass2" value="2222" type="float" label="M/z 2" help="Second m/z"/> @@ -982,7 +1029,7 @@ </param> <conditional name="processed_cond"> <param name="processed_file" value="processed"/> - <param name="accuracy" value="200"/> + <param name="accuracy" value="400"/> <param name="units" value="ppm"/> </conditional> <conditional name="tabular_annotation"> @@ -1002,7 +1049,6 @@ </repeat> <output name="QC_report" file="QC_imzml.pdf" compare="sim_size"/> </test> - <test> <expand macro="infile_analyze75"/> <conditional name="tabular_annotation"> @@ -1012,7 +1058,6 @@ <param name="do_pca" value="True"/> <output name="QC_report" file="QC_analyze75.pdf" compare="sim_size"/> </test> - <test> <param name="infile" value="3_files_combined.RData" ftype="rdata"/> <conditional name="tabular_annotation"> @@ -1043,6 +1088,25 @@ <param name="do_pca" value="False"/> <output name="QC_report" file="QC_empty_spectra.pdf" compare="sim_size"/> </test> + <test> + <param name="infile" value="" ftype="imzml"> + <composite_data value="Example_Processed.imzML"/> + <composite_data value="Example_Processed.ibd"/> + </param> + <conditional name="processed_cond"> + <param name="processed_file" value="processed"/> + <param name="accuracy" value="200"/> + <param name="units" value="ppm"/> + </conditional> + <conditional name="tabular_annotation"> + <param name="load_annotation" value="no_annotation"/> + </conditional> + <param name="calibrant_file" value="inputcalibrantfile1.tabular" ftype="tabular"/> + <param name="mz_column" value="1"/> + <param name="name_column" value="1"/> + <param name="report_depth" value="False"/> + <output name="QC_report" file="QC_imzml_shortreport.pdf" compare="sim_size"/> + </test> </tests> <help> <![CDATA[
--- a/test-data/112_auto_combined.imzml Wed May 13 17:55:17 2020 +0000 +++ b/test-data/112_auto_combined.imzml Sun Aug 29 07:16:49 2021 +0000 @@ -9,8 +9,8 @@ <fileContent> <cvParam cvRef="MS" accession="MS:1000579" name="MS1 spectrum" value="" /> <cvParam cvRef="MS" accession="MS:1000128" name="profile spectrum" value="" /> - <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="de720b1f-c3fa-4596-b054-284efaff29fc" /> - <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="040b9782d76e25ebe9a6b7c27fdda7e27e711674" /> + <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="23f1e1c8-aaa5-4d04-ab81-da14f7d24507" /> + <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="b2e009b6e72791420e704b751b4fc1a0f36bf420" /> <cvParam cvRef="IMS" accession="IMS:1000030" name="continuous" value="" /> </fileContent> </fileDescription> @@ -42,7 +42,7 @@ </sample> </sampleList> <softwareList count="1"> - <software id="Cardinal" version="2.4.0"> + <software id="Cardinal" version="2.6.0"> <cvParam cvRef="MS" accession="MS:1000799" name="custom unreleased software tool" value="" /> </software> </softwareList>
--- a/test-data/112_auto_combined.imzml.txt Wed May 13 17:55:17 2020 +0000 +++ b/test-data/112_auto_combined.imzml.txt Sun Aug 29 07:16:49 2021 +0000 @@ -1,4 +1,4 @@ imzML file: total 556 --rw-r--r-- 1 meli meli 537552 Apr 21 12:46 ibd --rw-r--r-- 1 meli meli 27497 Apr 21 12:46 imzml +-rw-rw-r-- 1 meli meli 537552 Aug 30 13:50 ibd +-rw-rw-r-- 1 meli meli 27497 Aug 30 13:50 imzml
--- a/test-data/123_combined.imzml Wed May 13 17:55:17 2020 +0000 +++ b/test-data/123_combined.imzml Sun Aug 29 07:16:49 2021 +0000 @@ -9,8 +9,8 @@ <fileContent> <cvParam cvRef="MS" accession="MS:1000579" name="MS1 spectrum" value="" /> <cvParam cvRef="MS" accession="MS:1000128" name="profile spectrum" value="" /> - <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="c9f19079-a92c-4995-b4ee-48d2766994a8" /> - <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="889b1020d3d844330f13a360be4b2bd0b65d11a1" /> + <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="383dcc6e-fa4e-4ffe-8523-9cd0c3bd2571" /> + <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="2cd98028c7ab9bd53b698168b508a0ac74f256c9" /> <cvParam cvRef="IMS" accession="IMS:1000030" name="continuous" value="" /> </fileContent> </fileDescription> @@ -42,7 +42,7 @@ </sample> </sampleList> <softwareList count="1"> - <software id="Cardinal" version="2.4.0"> + <software id="Cardinal" version="2.6.0"> <cvParam cvRef="MS" accession="MS:1000799" name="custom unreleased software tool" value="" /> </software> </softwareList>
--- a/test-data/123_combined.imzml.txt Wed May 13 17:55:17 2020 +0000 +++ b/test-data/123_combined.imzml.txt Sun Aug 29 07:16:49 2021 +0000 @@ -1,4 +1,4 @@ imzML file: total 452 --rw-r--r-- 1 meli meli 436764 Apr 21 12:41 ibd --rw-r--r-- 1 meli meli 22855 Apr 21 12:41 imzml +-rw-rw-r-- 1 meli meli 436764 Aug 30 13:46 ibd +-rw-rw-r-- 1 meli meli 22855 Aug 30 13:46 imzml
--- a/test-data/123_combined_auto.imzml Wed May 13 17:55:17 2020 +0000 +++ b/test-data/123_combined_auto.imzml Sun Aug 29 07:16:49 2021 +0000 @@ -9,8 +9,8 @@ <fileContent> <cvParam cvRef="MS" accession="MS:1000579" name="MS1 spectrum" value="" /> <cvParam cvRef="MS" accession="MS:1000128" name="profile spectrum" value="" /> - <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="386d1a7c-e065-4bf1-96a6-019586133b29" /> - <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="9bdafd878211e7d0c8fd0ef11bd534cbacfe7d40" /> + <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="ae23e625-6ac2-4a33-be4a-b73af67bc0dd" /> + <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="1b81e4b14567ea9da1177c0490f636d0823b2aac" /> <cvParam cvRef="IMS" accession="IMS:1000030" name="continuous" value="" /> </fileContent> </fileDescription> @@ -42,7 +42,7 @@ </sample> </sampleList> <softwareList count="1"> - <software id="Cardinal" version="2.4.0"> + <software id="Cardinal" version="2.6.0"> <cvParam cvRef="MS" accession="MS:1000799" name="custom unreleased software tool" value="" /> </software> </softwareList>
--- a/test-data/123_combined_auto.imzml.txt Wed May 13 17:55:17 2020 +0000 +++ b/test-data/123_combined_auto.imzml.txt Sun Aug 29 07:16:49 2021 +0000 @@ -1,4 +1,4 @@ imzML file: total 452 --rw-r--r-- 1 meli meli 436764 Apr 21 12:43 ibd --rw-r--r-- 1 meli meli 22860 Apr 21 12:43 imzml +-rw-rw-r-- 1 meli meli 436764 Aug 30 13:48 ibd +-rw-rw-r-- 1 meli meli 22860 Aug 30 13:48 imzml
--- a/test-data/12_combined.imzml Wed May 13 17:55:17 2020 +0000 +++ b/test-data/12_combined.imzml Sun Aug 29 07:16:49 2021 +0000 @@ -9,8 +9,8 @@ <fileContent> <cvParam cvRef="MS" accession="MS:1000579" name="MS1 spectrum" value="" /> <cvParam cvRef="MS" accession="MS:1000128" name="profile spectrum" value="" /> - <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="57f26041-833d-4843-ba25-0037f2c35f51" /> - <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="c271b37214900da9960cd3bcb748cc5bc377cfec" /> + <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="85ec7820-8e87-4fb2-b74a-5b9cd8cf24d6" /> + <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="d8a4e14091441873e8969f3b6b249f55b4d95146" /> <cvParam cvRef="IMS" accession="IMS:1000030" name="continuous" value="" /> </fileContent> </fileDescription> @@ -42,7 +42,7 @@ </sample> </sampleList> <softwareList count="1"> - <software id="Cardinal" version="2.4.0"> + <software id="Cardinal" version="2.6.0"> <cvParam cvRef="MS" accession="MS:1000799" name="custom unreleased software tool" value="" /> </software> </softwareList>
--- a/test-data/12_combined.imzml.txt Wed May 13 17:55:17 2020 +0000 +++ b/test-data/12_combined.imzml.txt Sun Aug 29 07:16:49 2021 +0000 @@ -1,4 +1,4 @@ imzML file: total 352 --rw-r--r-- 1 meli meli 335976 Apr 21 12:45 ibd --rw-r--r-- 1 meli meli 18225 Apr 21 12:45 imzml +-rw-rw-r-- 1 meli meli 335976 Aug 30 13:49 ibd +-rw-rw-r-- 1 meli meli 18225 Aug 30 13:49 imzml
--- a/test-data/2123_auto_combined.imzml Wed May 13 17:55:17 2020 +0000 +++ b/test-data/2123_auto_combined.imzml Sun Aug 29 07:16:49 2021 +0000 @@ -9,8 +9,8 @@ <fileContent> <cvParam cvRef="MS" accession="MS:1000579" name="MS1 spectrum" value="" /> <cvParam cvRef="MS" accession="MS:1000128" name="profile spectrum" value="" /> - <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="1c0a127a-8417-47ef-a049-553b9d56de81" /> - <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="5113bf7d09e0b1a584238aa6c5242f50eeef839b" /> + <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="d5abe155-9afd-4249-aaf3-8fc631c1fd10" /> + <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="3c93096f299dc50ca088d712feca19f8bf2d5152" /> <cvParam cvRef="IMS" accession="IMS:1000030" name="continuous" value="" /> </fileContent> </fileDescription> @@ -42,7 +42,7 @@ </sample> </sampleList> <softwareList count="1"> - <software id="Cardinal" version="2.4.0"> + <software id="Cardinal" version="2.6.0"> <cvParam cvRef="MS" accession="MS:1000799" name="custom unreleased software tool" value="" /> </software> </softwareList>
--- a/test-data/2123_auto_combined.imzml.txt Wed May 13 17:55:17 2020 +0000 +++ b/test-data/2123_auto_combined.imzml.txt Sun Aug 29 07:16:49 2021 +0000 @@ -1,4 +1,4 @@ imzML file: total 656 --rw-r--r-- 1 meli meli 638340 Apr 21 12:46 ibd --rw-r--r-- 1 meli meli 32132 Apr 21 12:46 imzml +-rw-rw-r-- 1 meli meli 638340 Aug 30 13:50 ibd +-rw-rw-r-- 1 meli meli 32132 Aug 30 13:50 imzml
--- a/test-data/out3.imzml Wed May 13 17:55:17 2020 +0000 +++ b/test-data/out3.imzml Sun Aug 29 07:16:49 2021 +0000 @@ -9,8 +9,8 @@ <fileContent> <cvParam cvRef="MS" accession="MS:1000579" name="MS1 spectrum" value="" /> <cvParam cvRef="MS" accession="MS:1000128" name="profile spectrum" value="" /> - <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="7cde7a72-9a6b-4ed9-a809-79ca20bf45b4" /> - <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="4a26497a6ddfc9a61e9c0e463e4c246c5d734f80" /> + <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="97f42eea-750c-49e4-b46d-08c548dc3b9d" /> + <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="4e046226f81e9c78255df625ca3546ef26dd0693" /> <cvParam cvRef="IMS" accession="IMS:1000030" name="continuous" value="" /> </fileContent> </fileDescription> @@ -42,7 +42,7 @@ </sample> </sampleList> <softwareList count="1"> - <software id="Cardinal" version="2.4.0"> + <software id="Cardinal" version="2.6.0"> <cvParam cvRef="MS" accession="MS:1000799" name="custom unreleased software tool" value="" /> </software> </softwareList>
--- a/test-data/out3.imzml.txt Wed May 13 17:55:17 2020 +0000 +++ b/test-data/out3.imzml.txt Sun Aug 29 07:16:49 2021 +0000 @@ -1,4 +1,4 @@ imzML file: total 24 --rw-r--r-- 1 meli meli 9616 Mär 24 20:25 ibd --rw-r--r-- 1 meli meli 8958 Mär 24 20:25 imzml +-rw-rw-r-- 1 meli meli 9616 Sep 27 10:51 ibd +-rw-rw-r-- 1 meli meli 8958 Sep 27 10:51 imzml
--- a/test-data/out4.imzml Wed May 13 17:55:17 2020 +0000 +++ b/test-data/out4.imzml Sun Aug 29 07:16:49 2021 +0000 @@ -9,8 +9,8 @@ <fileContent> <cvParam cvRef="MS" accession="MS:1000579" name="MS1 spectrum" value="" /> <cvParam cvRef="MS" accession="MS:1000128" name="profile spectrum" value="" /> - <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="b0dec95e-b66f-4c3f-86df-166d942f42c3" /> - <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="d9b557cf2c0e15a0cdd863e50897b07a55a26f31" /> + <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="37f3f75a-82c4-47c5-b78e-28fb8697e59b" /> + <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="1746fd2ec8a12707330a78ff5a0ff98cb53dca42" /> <cvParam cvRef="IMS" accession="IMS:1000030" name="continuous" value="" /> </fileContent> </fileDescription> @@ -42,7 +42,7 @@ </sample> </sampleList> <softwareList count="1"> - <software id="Cardinal" version="2.4.0"> + <software id="Cardinal" version="2.6.0"> <cvParam cvRef="MS" accession="MS:1000799" name="custom unreleased software tool" value="" /> </software> </softwareList>
--- a/test-data/out4.imzml.txt Wed May 13 17:55:17 2020 +0000 +++ b/test-data/out4.imzml.txt Sun Aug 29 07:16:49 2021 +0000 @@ -1,4 +1,4 @@ imzML file: total 44 --rw-r--r-- 1 meli meli 28792 Mär 24 19:23 ibd --rw-r--r-- 1 meli meli 12046 Mär 24 19:23 imzml +-rw-rw-r-- 1 meli meli 28792 Sep 27 10:52 ibd +-rw-rw-r-- 1 meli meli 12046 Sep 27 10:52 imzml
--- a/test-data/out5.imzml Wed May 13 17:55:17 2020 +0000 +++ b/test-data/out5.imzml Sun Aug 29 07:16:49 2021 +0000 @@ -9,8 +9,8 @@ <fileContent> <cvParam cvRef="MS" accession="MS:1000579" name="MS1 spectrum" value="" /> <cvParam cvRef="MS" accession="MS:1000128" name="profile spectrum" value="" /> - <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="87b0ab73-abe6-4eb6-91ba-b6d493a343bc" /> - <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="9de3a02d0943ecda0717845511a8f7b8f58d1db7" /> + <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="37236c7e-6e93-4ccc-9111-1b1153aac713" /> + <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="ccb886aaf3cb7564f518884413ea988c59a1de57" /> <cvParam cvRef="IMS" accession="IMS:1000030" name="continuous" value="" /> </fileContent> </fileDescription> @@ -42,7 +42,7 @@ </sample> </sampleList> <softwareList count="1"> - <software id="Cardinal" version="2.4.0"> + <software id="Cardinal" version="2.6.0"> <cvParam cvRef="MS" accession="MS:1000799" name="custom unreleased software tool" value="" /> </software> </softwareList>
--- a/test-data/out5.imzml.txt Wed May 13 17:55:17 2020 +0000 +++ b/test-data/out5.imzml.txt Sun Aug 29 07:16:49 2021 +0000 @@ -1,4 +1,4 @@ imzML file: total 20 --rw-r--r-- 1 meli meli 380 Mär 24 19:24 ibd --rw-r--r-- 1 meli meli 13525 Mär 24 19:24 imzml +-rw-rw-r-- 1 meli meli 380 Sep 27 10:53 ibd +-rw-rw-r-- 1 meli meli 13525 Sep 27 10:53 imzml
--- a/test-data/out6.imzml Wed May 13 17:55:17 2020 +0000 +++ b/test-data/out6.imzml Sun Aug 29 07:16:49 2021 +0000 @@ -9,8 +9,8 @@ <fileContent> <cvParam cvRef="MS" accession="MS:1000579" name="MS1 spectrum" value="" /> <cvParam cvRef="MS" accession="MS:1000128" name="profile spectrum" value="" /> - <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="8b625a26-987e-4e32-b7d4-729efe840814" /> - <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="78e6eb56507d789575ee0495e60f9d44a192c0dd" /> + <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="734d4b50-4440-4747-a0e9-de78974d1487" /> + <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="b1636b28fd4e0ab9caf5aaa4c1a40760030a4e73" /> <cvParam cvRef="IMS" accession="IMS:1000030" name="continuous" value="" /> </fileContent> </fileDescription> @@ -42,7 +42,7 @@ </sample> </sampleList> <softwareList count="1"> - <software id="Cardinal" version="2.4.0"> + <software id="Cardinal" version="2.6.0"> <cvParam cvRef="MS" accession="MS:1000799" name="custom unreleased software tool" value="" /> </software> </softwareList>
--- a/test-data/out6.imzml.txt Wed May 13 17:55:17 2020 +0000 +++ b/test-data/out6.imzml.txt Sun Aug 29 07:16:49 2021 +0000 @@ -1,4 +1,4 @@ imzML file: total 164 --rw-r--r-- 1 meli meli 146896 Mär 24 19:25 ibd --rw-r--r-- 1 meli meli 18221 Mär 24 19:25 imzml +-rw-rw-r-- 1 meli meli 146896 Sep 27 10:53 ibd +-rw-rw-r-- 1 meli meli 18221 Sep 27 10:53 imzml
--- a/test-data/out7.imzml Wed May 13 17:55:17 2020 +0000 +++ b/test-data/out7.imzml Sun Aug 29 07:16:49 2021 +0000 @@ -9,8 +9,8 @@ <fileContent> <cvParam cvRef="MS" accession="MS:1000579" name="MS1 spectrum" value="" /> <cvParam cvRef="MS" accession="MS:1000128" name="profile spectrum" value="" /> - <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="bf61653e-aa1a-4f9a-a84d-3ff3435ee7fe" /> - <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="352c33defde6728b7dfb83e18ed1c433fa4b8697" /> + <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="f81632b3-50b0-4a57-88a2-5f7cf97f9bae" /> + <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="9f88294c3cff3e8c30e80632d6ad616b7db18089" /> <cvParam cvRef="IMS" accession="IMS:1000030" name="continuous" value="" /> </fileContent> </fileDescription> @@ -42,7 +42,7 @@ </sample> </sampleList> <softwareList count="1"> - <software id="Cardinal" version="2.4.0"> + <software id="Cardinal" version="2.6.0"> <cvParam cvRef="MS" accession="MS:1000799" name="custom unreleased software tool" value="" /> </software> </softwareList>
--- a/test-data/out7.imzml.txt Wed May 13 17:55:17 2020 +0000 +++ b/test-data/out7.imzml.txt Sun Aug 29 07:16:49 2021 +0000 @@ -1,4 +1,4 @@ imzML file: total 116 --rw-r--r-- 1 meli meli 95976 Mär 24 19:26 ibd --rw-r--r-- 1 meli meli 18199 Mär 24 19:26 imzml +-rw-rw-r-- 1 meli meli 95976 Sep 27 10:54 ibd +-rw-rw-r-- 1 meli meli 18199 Sep 27 10:54 imzml
--- a/test-data/out8.imzml Wed May 13 17:55:17 2020 +0000 +++ b/test-data/out8.imzml Sun Aug 29 07:16:49 2021 +0000 @@ -9,9 +9,9 @@ <fileContent> <cvParam cvRef="MS" accession="MS:1000579" name="MS1 spectrum" value="" /> <cvParam cvRef="MS" accession="MS:1000128" name="profile spectrum" value="" /> - <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="ace74b18-25e2-4722-89f4-6eedc2b62ed8" /> - <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="41d580d8acf3e67df8b63f001fe941da7334861b" /> - <cvParam cvRef="IMS" accession="IMS:1000031" name="processed" value="" /> + <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="02059ae7-7beb-4ecf-92ae-7a767e04bf43" /> + <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="dc3960918fa3008824889b4ac142be1d0534ded8" /> + <cvParam cvRef="IMS" accession="IMS:1000030" name="continuous" value="" /> </fileContent> </fileDescription> <referenceableParamGroupList count="4"> @@ -42,7 +42,7 @@ </sample> </sampleList> <softwareList count="1"> - 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--- a/test-data/out8.imzml.txt Wed May 13 17:55:17 2020 +0000 +++ b/test-data/out8.imzml.txt Sun Aug 29 07:16:49 2021 +0000 @@ -1,4 +1,4 @@ imzML file: -total 348 --rw-r--r-- 1 meli meli 335976 Mär 24 19:27 ibd --rw-r--r-- 1 meli meli 12402 Mär 24 19:27 imzml +total 260 +-rw-rw-r-- 1 meli meli 248824 Sep 27 11:44 ibd +-rw-rw-r-- 1 meli meli 12397 Sep 27 11:44 imzml
--- a/test-data/picked.imzml Wed May 13 17:55:17 2020 +0000 +++ b/test-data/picked.imzml Sun Aug 29 07:16:49 2021 +0000 @@ -8,8 +8,8 @@ <fileDescription> <fileContent> <cvParam cvRef="MS" accession="MS:1000579" name="MS1 spectrum"/> - <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="{cb7c9edc-eee3-4159-a8a1-efdf5fc56a13}"/> - <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="f3e61f4699108e65bb678cfbbd6208be562f11c9"/> + <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="{19bd2a62-4cc1-4316-b173-25f1de3871f6}"/> + <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="ca84032e28aa3c04e4f41b74b85ccd1bd6e44107"/> <cvParam cvRef="IMS" accession="IMS:1000031" name="processed"/> <userParam name="MALDIquantForeign" value="MALDIquant object(s) exported to mzML"/> </fileContent>
--- a/test-data/picked.imzml.txt Wed May 13 17:55:17 2020 +0000 +++ b/test-data/picked.imzml.txt Sun Aug 29 07:16:49 2021 +0000 @@ -1,4 +1,4 @@ imzML file: total 192 --rw-r--r-- 1 meli meli 157984 Apr 21 12:42 ibd --rw-r--r-- 1 meli meli 35012 Apr 21 12:42 imzml +-rw-rw-r-- 1 meli meli 157984 Aug 30 13:47 ibd +-rw-rw-r-- 1 meli meli 35012 Aug 30 13:47 imzml
--- a/test-data/pixels_test6.tabular Wed May 13 17:55:17 2020 +0000 +++ b/test-data/pixels_test6.tabular Sun Aug 29 07:16:49 2021 +0000 @@ -1,25 +1,25 @@ -pixel names x y predicted condition -xy_1_1 1 1 A -xy_2_1 2 1 A -xy_3_1 3 1 B -xy_4_1 4 1 C -xy_1_2 1 2 C -xy_2_2 2 2 C -xy_3_2 3 2 A -xy_4_2 4 2 A -xy_1_3 1 3 A -xy_2_3 2 3 B -xy_3_3 3 3 C -xy_4_3 4 3 A -xy_10_1 10 1 C -xy_11_1 11 1 C -xy_12_1 12 1 C -xy_13_1 13 1 B -xy_10_2 10 2 C -xy_11_2 11 2 B -xy_12_2 12 2 C -xy_13_2 13 2 C -xy_10_3 10 3 C -xy_11_3 11 3 C -xy_12_3 12 3 B -xy_13_3 13 3 C +pixel names x y predicted condition A B C +xy_1_1 1 1 A 0.434439526064797 0.195646317191818 0.369914156743386 +xy_2_1 2 1 A 0.38219998209377 0.242372158141275 0.375427859764956 +xy_3_1 3 1 B 0.312531499299517 0.385612104162858 0.301856396537625 +xy_4_1 4 1 C 0.393153488582866 0.191107087820634 0.4157394235965 +xy_1_2 1 2 C 0.366986470447772 0.216121568441093 0.416891961111135 +xy_2_2 2 2 C 0.381682206547616 0.213188918797062 0.405128874655322 +xy_3_2 3 2 A 0.376695037169723 0.260689491088564 0.362615471741713 +xy_4_2 4 2 A 0.42305935188829 0.174038449100755 0.402902199010954 +xy_1_3 1 3 A 0.382420991383021 0.249364697048677 0.368214311568302 +xy_2_3 2 3 B 0.272145998315727 0.446525938567718 0.281328063116555 +xy_3_3 3 3 C 0.36296987427851 0.255631013944556 0.381399111776934 +xy_4_3 4 3 A 0.444812272103175 0.132274264153212 0.422913463743613 +xy_10_1 10 1 C 0.376216993893763 0.227584528606788 0.39619847749945 +xy_11_1 11 1 C 0.358430578177403 0.236120068794936 0.405449353027661 +xy_12_1 12 1 C 0.359751662628136 0.218620985552221 0.421627351819643 +xy_13_1 13 1 B 0.101486342705225 0.813997511218961 0.0845161460758142 +xy_10_2 10 2 C 0.354612526523361 0.272635192773437 0.372752280703202 +xy_11_2 11 2 B 0.291635599769993 0.444466545540823 0.263897854689184 +xy_12_2 12 2 C 0.36763798979782 0.203911653614431 0.428450356587749 +xy_13_2 13 2 C 0.344608135177236 0.304026642707691 0.351365222115073 +xy_10_3 10 3 C 0.37046458150651 0.205561286708086 0.423974131785404 +xy_11_3 11 3 C 0.358113833435286 0.262878459144526 0.379007707420187 +xy_12_3 12 3 B 0.180921926305915 0.66902588624642 0.150052187447665 +xy_13_3 13 3 C 0.378266307042675 0.20859472985319 0.413138963104135
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--- a/test-data/preprocessing_results1.imzml.txt Wed May 13 17:55:17 2020 +0000 +++ b/test-data/preprocessing_results1.imzml.txt Sun Aug 29 07:16:49 2021 +0000 @@ -1,4 +1,4 @@ imzML file: total 24 --rw-r--r-- 1 meli meli 216 Mai 10 17:37 ibd --rw-r--r-- 1 meli meli 18090 Mai 10 17:37 imzml +-rw-rw-r-- 1 meli meli 336 Nov 29 01:14 ibd +-rw-rw-r-- 1 meli meli 18092 Nov 29 01:14 imzml
--- a/test-data/preprocessing_results2.imzml Wed May 13 17:55:17 2020 +0000 +++ b/test-data/preprocessing_results2.imzml Sun Aug 29 07:16:49 2021 +0000 @@ -9,8 +9,8 @@ <fileContent> <cvParam cvRef="MS" accession="MS:1000579" name="MS1 spectrum" value="" /> <cvParam cvRef="MS" accession="MS:1000127" name="centroid spectrum" value="" /> - <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="fa59b434-12e0-47fe-b338-814c92daa7d6" /> - <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="5764be27b51a23d8c23e4c93befb9d8e57161bd9" /> + <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="ebbd9c5a-19a7-4db5-91e0-858065743606" /> + <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="471a838ffd01331ad8e6d23a59004e05745bf39c" /> <cvParam cvRef="IMS" accession="IMS:1000030" name="continuous" value="" /> </fileContent> </fileDescription> @@ -42,7 +42,7 @@ </sample> </sampleList> <softwareList count="1"> - <software id="Cardinal" version="2.4.0"> + <software id="Cardinal" version="2.6.0"> <cvParam cvRef="MS" accession="MS:1000799" name="custom unreleased software tool" value="" /> </software> </softwareList>
--- a/test-data/preprocessing_results2.imzml.txt Wed May 13 17:55:17 2020 +0000 +++ b/test-data/preprocessing_results2.imzml.txt Sun Aug 29 07:16:49 2021 +0000 @@ -1,4 +1,4 @@ imzML file: total 64 --rw-r--r-- 1 meli meli 37404 Mai 10 17:38 ibd --rw-r--r-- 1 meli meli 22796 Mai 10 17:38 imzml +-rw-rw-r-- 1 meli meli 37404 Nov 29 18:03 ibd +-rw-rw-r-- 1 meli meli 22796 Nov 29 18:03 imzml
--- a/test-data/preprocessing_results3.imzml Wed May 13 17:55:17 2020 +0000 +++ b/test-data/preprocessing_results3.imzml Sun Aug 29 07:16:49 2021 +0000 @@ -9,9 +9,9 @@ <fileContent> <cvParam cvRef="MS" accession="MS:1000579" name="MS1 spectrum" value="" /> <cvParam cvRef="MS" accession="MS:1000127" name="centroid spectrum" value="" /> - <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="d11b7693-3397-4d1f-9e67-29d952701100" /> - <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="94906879d47bbdcf97126d50c906dfd76e6681e4" /> - <cvParam cvRef="IMS" accession="IMS:1000031" name="processed" value="" /> + <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="476b127d-a8e1-4595-aae9-e9245db50d28" /> + <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="8a36ea2658fcfc8cfa9ae4d0dd73cd7ed2f5b96f" /> + <cvParam cvRef="IMS" accession="IMS:1000030" name="continuous" value="" /> </fileContent> </fileDescription> <referenceableParamGroupList count="4"> @@ -42,7 +42,7 @@ </sample> </sampleList> <softwareList count="1"> - 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--- a/test-data/preprocessing_results3.imzml.txt Wed May 13 17:55:17 2020 +0000 +++ b/test-data/preprocessing_results3.imzml.txt Sun Aug 29 07:16:49 2021 +0000 @@ -1,4 +1,4 @@ imzML file: total 24 --rw-r--r-- 1 meli meli 960 Mai 10 17:39 ibd --rw-r--r-- 1 meli meli 18112 Mai 10 17:39 imzml +-rw-rw-r-- 1 meli meli 1456 Nov 29 18:04 ibd +-rw-rw-r-- 1 meli meli 18133 Nov 29 18:04 imzml
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--- a/test-data/preprocessing_results5.imzml Wed May 13 17:55:17 2020 +0000 +++ b/test-data/preprocessing_results5.imzml Sun Aug 29 07:16:49 2021 +0000 @@ -9,8 +9,8 @@ <fileContent> <cvParam cvRef="MS" accession="MS:1000579" name="MS1 spectrum" value="" /> <cvParam cvRef="MS" accession="MS:1000128" name="profile spectrum" value="" /> - <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="3aff713c-00ec-422d-b63d-efd45fbdd7cc" /> - <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="9316138c1e7484662943bb206c79c2d074121530" /> + <cvParam cvRef="IMS" accession="IMS:1000080" name="universally unique identifier" value="56965a72-6fd7-4879-bb80-b72cb3af4a62" /> + <cvParam cvRef="IMS" accession="IMS:1000091" name="ibd SHA-1" value="5e07e272de044937cd6be7bfdbf2f4730aad10a9" /> <cvParam cvRef="IMS" accession="IMS:1000030" name="continuous" value="" /> </fileContent> </fileDescription> @@ -42,7 +42,7 @@ </sample> </sampleList> <softwareList count="1"> - <software id="Cardinal" version="2.4.0"> + <software id="Cardinal" version="2.6.0"> <cvParam cvRef="MS" accession="MS:1000799" name="custom unreleased software tool" value="" /> </software> </softwareList>
--- a/test-data/preprocessing_results5.imzml.txt Wed May 13 17:55:17 2020 +0000 +++ b/test-data/preprocessing_results5.imzml.txt Sun Aug 29 07:16:49 2021 +0000 @@ -1,4 +1,4 @@ imzML file: total 428 --rw-r--r-- 1 meli meli 415936 Mai 10 17:40 ibd --rw-r--r-- 1 meli meli 18569 Mai 10 17:40 imzml +-rw-rw-r-- 1 meli meli 415936 Oct 5 19:59 ibd +-rw-rw-r-- 1 meli meli 18569 Oct 5 19:59 imzml