Mercurial > repos > galaxyp > maldi_quant_peak_detection
diff maldi_quant_peakdetection.xml @ 7:160538a890a6 draft default tip
planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/MALDIquant commit f1e1cd260ef2884d0ba12e2b614df3c72d0934dc
| author | galaxyp |
|---|---|
| date | Sat, 04 Mar 2023 19:14:04 +0000 |
| parents | d286ff4600dd |
| children |
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--- a/maldi_quant_peakdetection.xml Thu Apr 16 17:53:18 2020 -0400 +++ b/maldi_quant_peakdetection.xml Sat Mar 04 19:14:04 2023 +0000 @@ -1,4 +1,4 @@ -<tool id="maldi_quant_peak_detection" name="MALDIquant peak detection" version="@VERSION@.6"> +<tool id="maldi_quant_peak_detection" name="MALDIquant peak detection" version="@VERSION@.0"> <description> Peak detection, binning and filtering for mass-spectrometry imaging data </description> @@ -15,8 +15,6 @@ cp '${infile.extra_files_path}/hdr' infile.hdr && cp '${infile.extra_files_path}/img' infile.img && cp '${infile.extra_files_path}/t2m' infile.t2m && - #else - ln -s '$infile' infile.RData && #end if cat '${maldi_quant_peak_detection}' && Rscript '${maldi_quant_peak_detection}' && @@ -36,14 +34,18 @@ print('Reading mask region') - ## Import imzML file - coordinate_matrix = as.matrix(read.delim("$restriction_conditional.coordinates_file", header = $restriction_conditional.coordinates_header, stringsAsFactors = FALSE))[,1:2] - coordinate_matrix = coordinate_matrix[,c($restriction_conditional.column_x, $restriction_conditional.column_y)] - - maldi_data <- importImzMl('infile.imzML', - coordinates = coordinate_matrix, centroided = $centroids) - pixelnames = paste("xy", coordinates(maldi_data)[,1],coordinates(maldi_data)[,2], sep="_") - + ## Import imzML file + coordinate_matrix = read.delim("$restriction_conditional.coordinates_file", header = $restriction_conditional.coordinates_header, stringsAsFactors = FALSE) + coordinate_matrix = coordinate_matrix[,c($restriction_conditional.column_x, $restriction_conditional.column_y)] + #if str($centroids) == "TRUE" + peaks <- importImzMl('infile.imzML', + coordinates = as.matrix(coordinate_matrix), centroided = $centroids) + pixelnames = paste("xy", coordinates(peaks)[,1],coordinates(peaks)[,2], sep="_") + #else + maldi_data <- importImzMl('infile.imzML', + coordinates = as.matrix(coordinate_matrix), centroided = $centroids) + pixelnames = paste("xy", coordinates(maldi_data)[,1],coordinates(maldi_data)[,2], sep="_") + #end if #else: @@ -77,40 +79,6 @@ peaks[[spectra]] = single_peaks } - #else - print('rdata file') - loadRData <- function(fileName){ - #loads an RData file, and returns it - load(fileName) - get(ls()[ls() != "fileName"]) - } - msidata = loadRData('infile.RData') - centroided(msidata) = $centroids - ## change to correct pixelnames - - x_coords = unlist(lapply(strsplit(names(Cardinal::pixels(msidata)), ","), `[[`, 1)) - y_coords = unlist(lapply(strsplit(names(Cardinal::pixels(msidata)), ","), `[[`, 2)) - x_coordinates = gsub("x = ","",x_coords) - y_coordinates = gsub(" y = ","",y_coords) - pixelnames = paste0("xy_", x_coordinates, "_", y_coordinates) - - cardinal_coordinates = as.matrix(Cardinal::coord(msidata)[,1:2]) - - if (centroided(msidata) == FALSE){ - ## create mass spectrum object - cardinal_mzs = Cardinal::mz(msidata) - maldi_data = list() - for(number_spectra in 1:ncol(msidata)){ - maldi_data[[number_spectra]] = createMassSpectrum(mass = cardinal_mzs, intensity = iData(msidata)[,number_spectra])} - coordinates_info = cbind(cardinal_coordinates, c(1:length(maldi_data))) - }else{ - peaks = list() - for (spectra in 1:ncol(msidata)) - { - single_peaks = createMassPeaks(Cardinal::mz(msidata), Cardinal::spectra(msidata)[,spectra], snr=as.numeric(rep("NA", nrow(msidata)))) - peaks[[spectra]] = single_peaks - } - coordinates_info = cbind(cardinal_coordinates, c(1:length(peaks)))} #end if #end if @@ -129,8 +97,7 @@ ## plot input file spectrum: #if $centroids: ## Choose random spectra for QC plots - print(length(peaks)) - random_spectra = sample(1:length(peaks), 4, replace=FALSE) + random_spectra = sample(1:length(peaks), size=4, replace=length(peaks)<4)## in case dataset has less than 4 spectra, same spetra are allowed to be sampled random_spectra_name = pixelnames[random_spectra] par(mfrow = c(2, 2), oma=c(0,0,2,0)) for (random_sample in random_spectra){ @@ -139,7 +106,7 @@ #else ## Choose random spectra for QC plots - random_spectra = sample(1:length(maldi_data), 4, replace=FALSE) + random_spectra = sample(1:length(maldi_data), size=4, replace=length(maldi_data)<4)## in case dataset has less than 4 spectra, same spetra are allowed to be sampled par(mfrow = c(2, 2), oma=c(0,0,2,0)) for (random_sample in random_spectra){ plot(maldi_data[[random_sample]],sub="", main=paste0("spectrum ", pixelnames[random_sample])) @@ -147,7 +114,6 @@ title("Input spectra", outer=TRUE, line=0) #end if - ## QC numbers for input file #if str($centroids) == "TRUE" pixel_number = length(peaks) @@ -156,8 +122,9 @@ mean_features = round(length(unlist(lapply(peaks,mass)))/length(peaks), digits=2) medint = round(median(unlist(lapply(peaks,intensity))), digits=2) number_features = length(unique(unlist(lapply(peaks,mass)))) - inputdata = c(minmz, maxmz,number_features,mean_features, medint) - QC_numbers= data.frame(inputdata = c(minmz, maxmz,number_features, mean_features, medint)) + number_spectra = length(peaks) + inputdata = c(minmz, maxmz,number_features,mean_features, medint, number_spectra) + QC_numbers= data.frame(inputdata = c(minmz, maxmz,number_features, mean_features, medint, number_spectra)) vectorofactions = "inputdata" #else pixel_number = length(maldi_data) @@ -166,8 +133,9 @@ mean_features = round(length(unlist(lapply(maldi_data,mass)))/length(maldi_data), digits=2) medint = round(median(unlist(lapply(maldi_data,intensity))), digits=2) number_features = length(unique(unlist(lapply(maldi_data,mass)))) - inputdata = c(minmz, maxmz,number_features,mean_features, medint) - QC_numbers= data.frame(inputdata = c(minmz, maxmz,number_features, mean_features, medint)) + number_spectra = length(maldi_data) + inputdata = c(minmz, maxmz,number_features,mean_features, medint, number_spectra) + QC_numbers= data.frame(inputdata = c(minmz, maxmz,number_features, mean_features, medint, number_spectra)) vectorofactions = "inputdata" #end if @@ -176,6 +144,7 @@ ## read and extract x,y,annotation information input_tabular = read.delim("$tabular_annotation.annotation_file", header = $tabular_annotation.tabular_header, stringsAsFactors = FALSE) annotation_input = input_tabular[,c($tabular_annotation.column_x, $tabular_annotation.column_y, $tabular_annotation.column_names)] + annotation_input[,3] <- as.character(annotation_input[,3]) ## make sure annotations are character colnames(annotation_input) = c("x", "y", "annotation") ## rename annotations header to default name "annotation" ## merge provided annotation with coordinate information of MSI data @@ -186,7 +155,7 @@ merged_annotation = merged_annotation[order(merged_annotation\$pixel_index),] samples = as.factor(merged_annotation\$annotation) -## print annotation overview into PDF output + ## print annotation overview into PDF output combine_plot = ggplot(merged_annotation, aes(x=x, y=y, fill=annotation))+ geom_tile() + @@ -244,7 +213,8 @@ mean_features = round(length(unlist(lapply(peaks,mass)))/length(peaks), digits=2) medint = round(median(unlist(lapply(peaks,intensity))), digits=2) number_features = length(unique(unlist(lapply(peaks,mass)))) - peaks_picked = c(minmz, maxmz,number_features,mean_features, medint) + number_spectra = length(peaks) + peaks_picked = c(minmz, maxmz,number_features,mean_features, medint, number_spectra) QC_numbers= cbind(QC_numbers, peaks_picked) vectorofactions = append(vectorofactions, "peaks_picked") @@ -293,7 +263,8 @@ mean_features = round(length(unlist(lapply(peaks,mass)))/length(peaks), digits=2) medint = round(median(unlist(lapply(peaks,intensity))), digits=2) number_features = length(unique(unlist(lapply(peaks,mass)))) - monoisotopes = c(minmz, maxmz,number_features,mean_features, medint) + number_spectra = length(peaks) + monoisotopes = c(minmz, maxmz,number_features,mean_features, medint, number_spectra) QC_numbers= cbind(QC_numbers, monoisotopes) vectorofactions = append(vectorofactions, "monoisotopes") @@ -374,9 +345,6 @@ if (length(findEmptyMassObjects(peaks))>0) { - #if $infile.ext == 'rdata' - cardinal_coordinates = cardinal_coordinates[-findEmptyMassObjects(peaks),,drop=FALSE] ## remove coordinates of empty spectra for Cardinal RData input - #end if peaks = removeEmptyMassObjects(peaks) pixelnames = paste("xy", coordinates(peaks)[,1],coordinates(peaks)[,2], sep="_") @@ -404,7 +372,8 @@ mean_features = round(length(unlist(lapply(peaks,mass)))/length(peaks), digits=2) medint = round(median(unlist(lapply(peaks,intensity))), digits=2) number_features = length(unique(unlist(lapply(peaks,mass)))) - aligned = c(minmz, maxmz,number_features,mean_features, medint) + number_spectra = length(peaks) + aligned = c(minmz, maxmz,number_features,mean_features, medint, number_spectra) QC_numbers= cbind(QC_numbers, aligned) vectorofactions = append(vectorofactions, "aligned") @@ -426,6 +395,7 @@ #elif str( $method.methods_conditional.method ) == 'Binning': + print('binning') ##m/z binning @@ -452,7 +422,8 @@ mean_features = round(length(unlist(lapply(peaks,mass)))/length(peaks), digits=2) medint =round( median(unlist(lapply(peaks,intensity))), digits=2) number_features = length(unique(unlist(lapply(peaks,mass)))) - binned = c(minmz, maxmz,number_features,mean_features, medint) + number_spectra = length(peaks) + binned = c(minmz, maxmz,number_features,mean_features, medint, number_spectra) QC_numbers= cbind(QC_numbers, binned) vectorofactions = append(vectorofactions, "binned") @@ -477,21 +448,20 @@ print('filtering') ##m/z filtering - ## filtering on all pixels or on pixel groups: - #if str($method.methods_conditional.filter_annot_groups ) == 'FALSE': - - peaks <- filterPeaks(peaks, - minFrequency=$method.methods_conditional.minFrequency, - minNumber=$method.methods_conditional.minNumber, - mergeWhitelists=$method.methods_conditional.mergeWhitelists) - #elif str( $method.methods_conditional.filter_annot_groups ) == 'TRUE': + peaks <- filterPeaks(peaks + #if str( $method.methods_conditional.filter_type.filter_params ) != 'min_Number': + ,minFrequency=$method.methods_conditional.filter_type.minFrequency + #end if + #if str( $method.methods_conditional.filter_type.filter_params ) != 'min_Frequency': + ,minNumber=$method.methods_conditional.filter_type.minNumber + #end if + ## in case of group wise filtering set grouping conditions + #if str( $method.methods_conditional.filter_groups.filter_annot_groups ) == 'yes_grouping': + ,mergeWhitelists=$method.methods_conditional.filter_groups.mergeWhitelists, label = samples + #end if + ) ## finishes filterPeaks function - peaks <- filterPeaks(peaks, - minFrequency=$method.methods_conditional.minFrequency, - minNumber=$method.methods_conditional.minNumber, - mergeWhitelists=$method.methods_conditional.mergeWhitelists, label = samples) - #end if ##QC plot and numbers par(mfrow = c(2, 2), oma=c(0,0,2,0)) @@ -508,13 +478,15 @@ ) } + ## QC numbers for filtered file title("Filtered spectra", outer=TRUE, line=0) minmz = round(min(unlist(lapply(peaks,mass))), digits=4) maxmz = round(max(unlist(lapply(peaks,mass))), digits=4) mean_features = round(length(unlist(lapply(peaks,mass)))/length(peaks), digits=2) medint = round(median(unlist(lapply(peaks,intensity))), digits=2) number_features = length(unique(unlist(lapply(peaks,mass)))) - filtered = c(minmz, maxmz,number_features,mean_features, medint) + number_spectra = length(peaks) + filtered = c(minmz, maxmz,number_features,mean_features, medint, number_spectra) QC_numbers= cbind(QC_numbers, filtered) vectorofactions = append(vectorofactions, "filtered") @@ -531,7 +503,12 @@ }else{print("There are no spectra with peaks left") featureMatrix2 = matrix(0, ncol=1, nrow=1)} write.table(featureMatrix2, file="$intensity_matrix", quote = FALSE, row.names = TRUE, col.names=FALSE, sep = "\t") + + #elif str( $method.methods_conditional.method ) == 'skip_preprocessing': + ##for now as option to filter large files + #end if + #end for if (length(peaks[!sapply(peaks, isEmpty)])>0){ @@ -547,12 +524,13 @@ }else{print("There are no spectra with peaks left")} ## print table with QC values -rownames(QC_numbers) = c("min m/z", "max mz", "# features", "median \n# peaks (int.>0)", "median\nintensity") +rownames(QC_numbers) = c("min m/z", "max mz", "# features", "median \n# peaks (int.>0)", "median\nintensity", "# spectra") plot(0,type='n',axes=FALSE,ann=FALSE) grid.table(t(QC_numbers)) dev.off() + if (summarized_spectra == FALSE){ #if $infile.ext == 'imzml' MALDIquantForeign::exportImzMl(peaks, file="out.imzMl", processed=TRUE) @@ -561,8 +539,6 @@ ## extract x and y values and create the coordinate matrix in case tabular was input peaklist_coordinates = unique(cbind(as.numeric(masspeaks_coordinates[,2]), as.numeric(masspeaks_coordinates[,3]))) exportImzMl(peaks, file="out.imzMl", processed=TRUE, coordinates=peaklist_coordinates) - #elif $infile.ext == 'rdata' - MALDIquantForeign::exportImzMl(peaks, file="out.imzMl", processed=TRUE, coordinates=cardinal_coordinates) #end if } @@ -571,11 +547,11 @@ </configfile> </configfiles> <inputs> - <param name="infile" type="data" format="imzml,tabular,rdata" label="MSI data" help="Input file as imzML (composite upload), tabular peaklist or Cardinal MSImageSet saved as RData (regular upload)"/> + <param name="infile" type="data" format="imzml,tabular" label="MSI data" help="Input file as imzML (composite upload) or tabular peaklist (regular upload)"/> <param name="centroids" type="boolean" label="Centroided input" help="Choose Yes if peak detection has already been done. Peak detection cannot be run again on centroided data" truevalue="TRUE" falsevalue="FALSE"/> <conditional name="restriction_conditional"> <param name="restriction" type="select" label="Use only spectra of interest" help="This option only works for imzML files"> - <option value="no_restriction" selected="True">No, calculate on entire file</option> + <option value="no_restriction" selected="True">No, use all spectra</option> <option value="restrict">Yes, restrict to spectra of interest</option> </param> <when value="restrict"> @@ -610,6 +586,7 @@ <option value="Align">Align Spectra (warping/phase correction)</option> <option value="Binning">Binning</option> <option value="Filtering">Filtering</option> + <option value="skip_preprocessing">No method</option> </param> <when value="Peak_detection"> <param name="peak_method" type="select" label="Noise estimation function"> @@ -660,7 +637,7 @@ help="Maximal relative deviation of a peak position (m/z) to be considered as identical. For 50ppm use 0.00005 or 5e-5" /> <param name="allow_nomatch" type="boolean" label="Don't throw an error when less than 2 reference m/z were found in a spectrum" truevalue="TRUE" falsevalue="FALSE"/> <param name="empty_nomatch" type="boolean" label="If TRUE the intensity values of MassSpectrum or MassPeaks objects with missing (NA) warping functions are set to zero" truevalue="TRUE" falsevalue="FALSE"/> - <param name="remove_empty" type="boolean" label="Should empty spectra be removed" truevalue="TRUE" falsevalue="FALSE" help="For Cardinal RData files this step can only be performed if pixel annotations were provided"/> + <param name="remove_empty" type="boolean" label="Should empty spectra be removed" truevalue="TRUE" falsevalue="FALSE"/> <conditional name="reference_for_alignment"> <param name="align_ref" type="select" label="Reference" help="If given, samples will be aligned to reference, use internal calibrants to perform m/z calibration"> @@ -690,14 +667,36 @@ </param> </when> <when value="Filtering"> - <param name="minFrequency" type="float" value="0.25" - label="Removal of all peaks which occur in less than minFrequency spectra" help="Relative threshold. The higher value from relative and absolute threshold is taken. Set one value to zero to be sure it will not be used."/> - <param name="minNumber" type="float" value="1.0" - label="Removal of all peaks which occur in less than minNumber spectra" help="Absolute threshold. The higher value from relative and absolute threshold is taken. Set one value to zero to be sure it will not be used."/> - <param name="filter_annot_groups" type="boolean" label="Group wise filtering with pixel annotations." help="If not specified a single group is assumed or when filtering has been done group wise it will automatically be group wise when selecting filtering on all pixel" truevalue="TRUE" falsevalue="FALSE"/> - <param name="mergeWhitelists" type="boolean" truevalue="TRUE" falsevalue="FALSE" - label="mergeWhitelists" help="Yes means that peaks that survive the filtering in one annotation group are also kept in other groups regardless if the filtering criteria are met in these groups"/> + <conditional name="filter_groups"> + <param name="filter_annot_groups" type="select" label="m/z filtering parameters are applied to all spectra or groups of spectra" help="By default a single group is assumed and filtering will be done based on all pixels. To filter groups of spectra, an annotation annotation file has to be specified above"> + <option value="no_grouping" selected="True">use single group</option> + <option value="yes_grouping">use spectra groups from annotation file</option> + </param> + <when value="no_grouping"/> + <when value="yes_grouping"> + <param name="mergeWhitelists" type="boolean" truevalue="TRUE" falsevalue="FALSE" + label="mergeWhitelists" help="Yes means that peaks that survive the filtering in one annotation group are also kept in other groups regardless if the filtering criteria are met in these groups"/> + </when> + </conditional> + <conditional name="filter_type"> + <param name="filter_params" type="select" label="m/z filtering parameters" help="minFrequency: Removal of all peaks which occur in less than minFrequency spectra (relative treshold). minNumber: Removal of all peaks which ocur in lass than minNumber spectra (absolute threshold). If both are set the higher value from relative and absolute threshold is taken."> + <option value="min_Frequency" selected="True">minFrequency</option> + <option value="min_Number">minNumber</option> + <option value="both">both</option> + </param> + <when value="min_Frequency"> + <param name="minFrequency" type="float" value="0.25" label="Removal of all peaks which occur in less than minFrequency spectra" /> + </when> + <when value="min_Number"> + <param name="minNumber" type="float" value="1.0" label="Removal of all peaks which occur in less than minNumber spectra" /> + </when> + <when value="both"> + <param name="minFrequency" type="float" value="0.25" label="Removal of all peaks which occur in less than minFrequency spectra" /> + <param name="minNumber" type="float" value="1.0" label="Removal of all peaks which occur in less than minNumber spectra" /> + </when> + </conditional> </when> + <when value="skip_preprocessing"/> </conditional> </repeat> </inputs> @@ -744,7 +743,7 @@ <param name="method" value="monoisotopic_peaks"/> <param name="tolerance" value="0.0004"/> <param name="size" value="3"/> - </conditional> + </conditional> </repeat> <output name="plots" file="peakdetection2_QC.pdf" compare="sim_size"/> <output name="masspeaks" file="masspeaks2.tabular"/> @@ -754,7 +753,7 @@ <extra_files type="file" file="peak_detection2.ibd" name="ibd" compare="sim_size"/> </output> </test> - <test> + <test> <param name="infile" value="" ftype="imzml"> <composite_data value="Example_Continuous.imzML"/> <composite_data value="Example_Continuous.ibd"/> @@ -771,48 +770,85 @@ <conditional name="methods_conditional"> <param name="method" value="Peak_detection"/> <param name="peak_method" value="MAD"/> - <param name="halfWindowSize" value="1"/> + <param name="halfWindowSize" value="10"/> <param name="snr" value="2"/> </conditional> </repeat> + <repeat name="methods"> + <conditional name="methods_conditional"> + <param name="method" value="Filtering"/> + <conditional name="filter_groups"> + <param name="filter_annot_groups" value="yes_grouping"/> + <param name="mergeWhitelists" value="FALSE"/> + </conditional> + <conditional name="filter_type"> + <param name="filter_params" value="min_Frequency"/> + <param name="minFrequency" value="0.25"/> + </conditional> + </conditional> + </repeat> + <output name="plots" file="peakdetection3_QC.pdf" compare="sim_size"/> + <output name="intensity_matrix" file="int3.tabular"/> + <output name="masspeaks" file="masspeaks3.tabular"/> + <output name="outfile_imzml" ftype="imzml" file="peak_detection3.imzml.txt" lines_diff="4"> + <extra_files type="file" file="peak_detection3.imzml" name="imzml" lines_diff="6"/> + <extra_files type="file" file="peak_detection3.ibd" name="ibd" compare="sim_size"/> + </output> + </test> + <test> + <param name="infile" value="" ftype="imzml"> + <composite_data value="Example_Processed.imzML"/> + <composite_data value="Example_Processed.ibd"/> + </param> + <repeat name="methods"> + <conditional name="methods_conditional"> + <param name="method" value="Peak_detection"/> + <param name="peak_method" value="SuperSmoother"/> + <param name="halfWindowSize" value="5"/> + <param name="snr" value="3"/> + </conditional> + </repeat> <repeat name="methods"> <conditional name="methods_conditional"> <param name="method" value="Binning"/> <param name="bin_tolerance" value="0.01"/> </conditional> </repeat> - <repeat name="methods"> - <conditional name="methods_conditional"> - <param name="method" value="Filtering"/> - <param name="minFrequency" value="0.5"/> - <param name="minNumber" value="3"/> - <param name="filter_annot_groups" value="TRUE"/> - <param name="mergeWhitelists" value="FALSE"/> - </conditional> - </repeat> - <output name="plots" file="peakdetection3_QC.pdf" compare="sim_size"/> - <output name="intensity_matrix" file="intensity_matrix3.tabular"/> - <output name="masspeaks" file="masspeaks3.tabular"/> - <output name="outfile_imzml" ftype="imzml" file="peak_detection3.imzml.txt" lines_diff="4"> - <extra_files type="file" file="peak_detection3.imzml" name="imzml" lines_diff="6"/> - <extra_files type="file" file="peak_detection3.ibd" name="ibd" compare="sim_size"/> - </output> - </test> - <test> - <param name="infile" value="testfile_squares.rdata" ftype="rdata"/> - <param name="method" value="Peak_detection"/> - <param name="peak_method" value="MAD"/> - <param name="halfWindowSize" value="20"/> - <param name="snr" value="2"/> <output name="plots" file="peakdetection4_QC.pdf" compare="sim_size"/> - <output name="intensity_matrix" file="intensity_matrix4.tabular"/> + <output name="intensity_matrix" file="int4.tabular"/> <output name="masspeaks" file="masspeaks4.tabular"/> <output name="outfile_imzml" ftype="imzml" file="peak_detection4.imzml.txt" lines_diff="4"> <extra_files type="file" file="peak_detection4.imzml" name="imzml" lines_diff="6"/> <extra_files type="file" file="peak_detection4.ibd" name="ibd" compare="sim_size"/> </output> </test> + <test> + <param name="infile" value="" ftype="imzml"> + <composite_data value="preprocessing_results3.imzML"/> + <composite_data value="preprocessing_results3.ibd"/> + </param> + <param name="centroids" value="TRUE"/> + <conditional name="restriction_conditional"> + <param name="restriction" value="restrict"/> + <param name="coordinates_file" value="annotations.tabular"/> + <param name="column_x" value="1"/> + <param name="column_y" value="2"/> + <param name="coordinates_header" value="TRUE"/> + </conditional> + <repeat name="methods"> + <conditional name="methods_conditional"> + <param name="method" value="skip_preprocessing"/> + </conditional> + </repeat> + <output name="plots" file="peakdetection5_QC.pdf" compare="sim_size"/> + <output name="masspeaks" file="masspeaks5.tabular"/> + <output name="outfile_imzml" ftype="imzml" file="peak_detection5.imzml.txt" lines_diff="4"> + <extra_files type="file" file="peak_detection5.imzml" name="imzml" lines_diff="6"/> + <extra_files type="file" file="peak_detection5.ibd" name="ibd" compare="sim_size"/> + </output> + </test> </tests> + <help> <![CDATA[ @@ -824,8 +860,7 @@ - MSI data: 3 types of input data can be used: - - imzml file (upload imzml and ibd file via the "composite" function) `Introduction to the imzml format <https://ms-imaging.org/wp/imzml/>`_ - - Cardinal "MSImageSet" data saved as .RData + - imzml file (upload imzml and ibd file via the "composite" function) `Introduction to the imzml format <https://ms-imaging.org/imzml/>`_ - MSI data as peak list (tabular file) with the columns named "snr", "mass", "intensity" and "spectrum". The spectrum has to be in the following format: xy_1_1 (for pixel coordinates x1y1). The header must have exactly the four column names. ::