comparison data_exporter.xml @ 17:56da27be956a draft default tip

planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/cardinal commit 91e77c139cb3b7c6d67727dc39140dd79355fa0c

16:bb6397b94018

<tool id="cardinal_data_exporter" name="MSI data exporter" version="@VERSION@.0">
    <description>
        exports imzML and Analyze7.5 to tabular files
    </description>
    <macros>
        <import>macros.xml</import>

            ## calculate mean per annotation group
            sample_matrix = matrix(,ncol=0, nrow=nrow(msidata))
            count = 1
            for (subsample in levels(msidata\$annotation)){
                subsample_pixels = msidata[,msidata\$annotation == subsample]
                subsample_calc = rowMeans(spectra(subsample_pixels), na.rm=TRUE)
                sample_matrix = cbind(sample_matrix, subsample_calc)
                count = count+1}
            sample_matrix_mean = cbind(mz_names,sample_matrix)
            sample_matrix_mean = rbind(c("mz_name", levels(msidata\$annotation)), sample_matrix_mean)
            write.table(sample_matrix_mean, file="$summarized_mean", quote = FALSE, row.names = FALSE, col.names=FALSE, sep = "\t")

            sample_matrix = matrix(,ncol=0, nrow=nrow(msidata))
            count = 1
            for (subsample in levels(msidata\$annotation)){
                subsample_pixels = msidata[,msidata\$annotation == subsample]
                subsample_calc = apply(spectra(subsample_pixels),1,median, na.rm=TRUE)
                sample_matrix = cbind(sample_matrix, subsample_calc)
                count = count+1}
            sample_matrix_median = cbind(mz_names,sample_matrix)
            sample_matrix_median = rbind(c("mz name", levels(msidata\$annotation)), sample_matrix_median)
            write.table(sample_matrix_median, file="$summarized_median", quote = FALSE, row.names = FALSE, col.names=FALSE, sep = "\t")

                ## filter for m/z window of each calibrant and calculate if sum of peak intensities > 0

                for (mass in 1:length(inputcalibrantmasses)){
                    filtered_data = msidata[mz(msidata) >= inputcalibrantmasses[mass]-plusminusvalues[mass] & mz(msidata) <= inputcalibrantmasses[mass]+plusminusvalues[mass],]
                    if (nrow(filtered_data) > 1 & sum(spectra(filtered_data),na.rm=TRUE) > 0){
                        ## intensity of all m/z > 0
                          intensity_sum = colSums(spectra(filtered_data), na.rm=TRUE) > 0

                    }else if(nrow(filtered_data) == 1 & sum(spectra(filtered_data), na.rm=TRUE) > 0){
                        ## intensity of only m/z > 0
                        intensity_sum = spectra(filtered_data) > 0 
                    }else{
                        intensity_sum = rep(FALSE, ncol(filtered_data))}
                    ## for each pixel add sum of intensities > 0 in the given m/z range
                    pixelmatrix = rbind(pixelmatrix, intensity_sum)
                }

                <param name="mz_tabular" ftype="tabular" value = "featuresofinterest5.tabular"/>
                <param name="feature_column" value="1"/>
                <param name="feature_header" value="False"/>
                <param name="plusminus_ppm" value="200"/>
            </conditional>
            <output name="feature_output" file="features_out4.tabular"/>
            <output name="pixel_output" file="pixel_out4.tabular"/>
        </test>
    </tests>
    <help>
        <![CDATA[

17:56da27be956a

<tool id="cardinal_data_exporter" name="MSI data exporter" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="22.05">
    <description>
        exports imzML and Analyze7.5 to tabular files
    </description>
    <macros>
        <import>macros.xml</import>

            ## calculate mean per annotation group
            sample_matrix = matrix(,ncol=0, nrow=nrow(msidata))
            count = 1
            for (subsample in levels(msidata\$annotation)){
                subsample_pixels = msidata[,msidata\$annotation == subsample]
                subsample_calc = rowMeans(as.matrix(spectra(subsample_pixels)), na.rm=TRUE)
                sample_matrix = cbind(sample_matrix, subsample_calc)
                count = count+1}
            sample_matrix_mean = cbind(mz_names,sample_matrix)
            sample_matrix_mean = rbind(c("mz_name", levels(msidata\$annotation)), sample_matrix_mean)
            write.table(sample_matrix_mean, file="$summarized_mean", quote = FALSE, row.names = FALSE, col.names=FALSE, sep = "\t")

            sample_matrix = matrix(,ncol=0, nrow=nrow(msidata))
            count = 1
            for (subsample in levels(msidata\$annotation)){
                subsample_pixels = msidata[,msidata\$annotation == subsample]
                subsample_calc = apply(as.matrix(spectra(subsample_pixels)),1,median, na.rm=TRUE)
                sample_matrix = cbind(sample_matrix, subsample_calc)
                count = count+1}
            sample_matrix_median = cbind(mz_names,sample_matrix)
            sample_matrix_median = rbind(c("mz name", levels(msidata\$annotation)), sample_matrix_median)
            write.table(sample_matrix_median, file="$summarized_median", quote = FALSE, row.names = FALSE, col.names=FALSE, sep = "\t")

                ## filter for m/z window of each calibrant and calculate if sum of peak intensities > 0

                for (mass in 1:length(inputcalibrantmasses)){
                    filtered_data = msidata[mz(msidata) >= inputcalibrantmasses[mass]-plusminusvalues[mass] & mz(msidata) <= inputcalibrantmasses[mass]+plusminusvalues[mass],]
                    if (nrow(filtered_data) > 1 & sum(as.matrix(spectra(filtered_data)), na.rm=TRUE) > 0){
                        ## intensity of all m/z > 0
                          intensity_sum = colSums(as.matrix(spectra(filtered_data)), na.rm=TRUE) > 0

                    }else if(nrow(filtered_data) == 1 & sum(as.matrix(spectra(filtered_data)), na.rm=TRUE) > 0){
                        ## intensity of only m/z > 0
                        intensity_sum = as.matrix(spectra(filtered_data)) > 0
                    }else{
                        intensity_sum = rep(FALSE, ncol(filtered_data))}
                    ## for each pixel add sum of intensities > 0 in the given m/z range
                    pixelmatrix = rbind(pixelmatrix, intensity_sum)
                }

                <param name="mz_tabular" ftype="tabular" value = "featuresofinterest5.tabular"/>
                <param name="feature_column" value="1"/>
                <param name="feature_header" value="False"/>
                <param name="plusminus_ppm" value="200"/>
            </conditional>
            <output name="feature_output">
                <assert_contents>
                    <has_text text="100.120072029209"/>
                </assert_contents>
            </output>
            <output name="pixel_output" file="pixel_out4.tabular"/>
        </test>
    </tests>
    <help>
        <![CDATA[