comparison msi_qualitycontrol.xml @ 6:5c63fe03ed9e draft

planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/msi_qualitycontrol commit 06c2b45d8644b1d7fc01622a5c59dcbf8886d0f1

5:ac786240ef07

<tool id="mass_spectrometry_imaging_qc" name="MSI Qualitycontrol" version="1.7.0.4">
    <description>
        mass spectrometry imaging QC
    </description>
    <requirements>
        <requirement type="package" version="1.7.0">bioconductor-cardinal</requirement>

    ############################################################################

    ## 1) Acquisition image

    pixelnumber = 1:pixelcount
    pixelxyarray=cbind(coord(msidata),pixelnumber)

    print(ggplot(pixelxyarray, aes(x=x, y=y, fill=pixelnumber))
     + geom_tile() + coord_fixed()
     + ggtitle("1) Order of Acquisition")
     +theme_bw()
     + scale_fill_gradientn(colours = c("blue", "purple" , "red","orange"), 
                            space = "Lab", na.value = "black", name = "Acq"))

    ## 2) Number of calibrants per spectrum

            }
          pixelmatrix = rbind(pixelmatrix, calibrantintensity)
        }

        countvector= as.factor(colSums(pixelmatrix>0))
        countdf= cbind(coord(msidata), countvector)
        mycolours = c("black","grey", "darkblue", "blue", "green" , "red", "yellow", "magenta", "olivedrab1", "lightseagreen")

        print(ggplot(countdf, aes(x=x, y=y, fill=countvector))
           + geom_tile() + coord_fixed() 
          + ggtitle("2) Number of calibrants per pixel")
          + theme_bw() 
          + theme(text=element_text(family="ArialMT", face="bold", size=12))
          + scale_fill_manual(values = mycolours[1:length(countvector)], 
                                na.value = "black", name = "# calibrants"))
    }else{print("2) The inputcalibrant masses were not provided or outside the mass range")}

            mass1vector = spectra(msidata)[features(msidata, mz = maxmass1),]
            mass2vector = spectra(msidata)[features(msidata, mz = maxmass2),]
            foldchange = log2(mass1vector/mass2vector)

            ratiomatrix = cbind(foldchange, coord(msidata))

            print(ggplot(ratiomatrix, aes(x=x, y=y, fill=foldchange), colour=colo)
             + geom_tile() + coord_fixed()
             + ggtitle("$label")
             + theme_bw()

    par(mfrow=c(1,1), mar=c(5.1, 4.1, 4.1, 2.1), mgp=c(3, 1, 0), las=0)
    if (length(inputmasses) != 0)
    {   for (mass in 1:length(inputmasses))
        {
          image(msidata, mz=inputmasses[mass], plusminus=$plusminus_dalton, 
          main= paste0("3", LETTERS[mass], ") ", inputnames[mass], " (", round(inputmasses[mass], digits = 2)," ± ", $plusminus_dalton, " Da)"),
                contrast.enhance = "histogram", ylim=c(maximumy+2, 0))
        }
    } else {print("3) The inputpeptide masses were not provided or outside the mass range")}


    ## 4) Number of peaks per pixel - image

    peaksperpixel = colSums(spectra(msidata)[]> 0)
    peakscoordarray=cbind(coord(msidata), peaksperpixel)

    print(ggplot(peakscoordarray, aes(x=x, y=y, fill=peaksperpixel), colour=colo)
    + geom_tile() + coord_fixed() 
     + ggtitle("4) Number of peaks per pixel")
     + theme_bw() 
     + 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 = "# peaks"))

    ## 5) TIC image 
    TICcoordarray=cbind(coord(msidata), TICs)
    colo = colorRampPalette(
    c("blue", "cyan", "green", "yellow","red"))
    print(ggplot(TICcoordarray, aes(x=x, y=y, fill=TICs), colour=colo)
     + geom_tile() + coord_fixed() 
     + ggtitle("5) Total Ion Chromatogram")
     + theme_bw() 
     + 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 = "TIC"))

    ## 6) Most abundant mass image 

    highestmz = apply(spectra(msidata)[],2,which.max) 
    highestmz_matrix = cbind(coord(msidata),mz(msidata)[highestmz])
    colnames(highestmz_matrix)[3] = "highestmzinDa"

    print(ggplot(highestmz_matrix, aes(x=x, y=y, fill=highestmzinDa))
    + geom_tile() + coord_fixed() 
    + ggtitle("6) Most abundant m/z in each pixel")
    + theme_bw() 
    + scale_fill_gradientn(colours = c("blue", "purple" , "red","orange"), space = "Lab", na.value = "black", name = "m/z", 
                           labels = as.character(pretty(highestmz_matrix\$highestmzinDa)[c(1,3,5,7)]),
                           breaks = pretty(highestmz_matrix\$highestmzinDa)[c(1,3,5,7)], limits=c(min(highestmz_matrix\$highestmzinDa), max(highestmz_matrix\$highestmzinDa)))
    + theme(text=element_text(family="ArialMT", face="bold", size=12)))

    secondhighestmz_pixel = which(round(highestmz_matrix\$highestmzinDa, digits=0) == secondhighestmz)[1]

    ## 7) pca image for two components
    pca = PCA(msidata, ncomp=2) 
    par(mfrow = c(2,1))
    plot(pca, col=c("black", "darkgrey"), main="7) PCA for two components")
    image(pca, col=c("black", "white"),ylim=c(maximumy+2, 0),  strip=FALSE)


    ############################# III) properties over acquisition (spectra index)##########
    ##############################################################################

    par(mfrow = c(2,1), mar=c(5,6,4,2))

    ## 8a) number of peaks per spectrum - scatterplot
    plot_colorByDensity(pixels(msidata), peaksperpixel, ylab = "", xlab = "", main="8a) Number of peaks per spectrum")
    title(xlab="Spectra index \n (= Acquisition time)", line=3)
    title(ylab="Number of peaks", line=4)

    ## 8b) number of peaks per spectrum - histogram
    hist(peaksperpixel, main="", las=1, xlab = "Number of peaks per spectrum", ylab="") 
    title(main="8b) Number of peaks per spectrum", line=2)
    title(ylab="Frequency = # spectra", line=4)
    abline(v=median(peaksperpixel), col="blue")

    ## 9a) TIC per spectrum - density scatterplot
    zero=0
    par(mfrow = c(2,1), mar=c(5,6,4,2))
    plot_colorByDensity(pixels(msidata), TICs,  ylab = "", xlab = "", main="9a) TIC per pixel")
    title(xlab="Spectra index \n (= Acquisition time)", line=3)
    title(ylab = "Total ion chromatogram intensity", line=4)

    ## 9b) TIC per spectrum -  histogram
    hist(log(TICs), main="", las=1, xlab = "log(TIC per spectrum)", ylab="")
    title(main= "9b) TIC per spectrum", line=2)
    title(ylab="Frequency = # spectra", line=4)
    abline(v=median(log(TICs[TICs>0])), col="blue") 


    ################################## IV) changes over mz ############################

    ## 11) Number of peaks per mz
    ## Number of peaks per mz - number across all pixel
    peakspermz = rowSums(spectra(msidata)[] > 0 )

    par(mfrow = c(2,1), mar=c(5,6,4,4.5))
    ## 11a) Number of peaks per mz - scatterplot
    plot_colorByDensity(mz(msidata),peakspermz, main= "11a) Number of peaks for each mz", ylab ="")
    title(xlab="mz in Dalton", 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)

    # make plot smaller to fit axis and labels, add second y axis with %
    ## 11b) Number of peaks per mz - histogram
    hist(peakspermz, main="", las=1, ylab="")
    title(ylab = "Frequency", line=4)
    title(main="11b) Number of peaks per mz", xlab = "Number of peaks per mz", line=2)
    abline(v=median(peakspermz), col="blue") 


    ## 12) Sum of intensities per mz

    ## Sum of all intensities for each mz (like TIC, but for mz instead of pixel)
    mzTIC = rowSums(spectra(msidata)[]) # calculate intensity sum for each mz

    par(mfrow = c(2,1), mar=c(5,6,4,2))
    # 12a) sum of intensities per mz - scatterplot
    plot_colorByDensity(mz(msidata),mzTIC,  main= "12a) Sum of all peak intensities for each mz", ylab ="")
    title(xlab="mz in Dalton", line=2.5)
    title(ylab="Intensity sum", line=4)
    # 12b) sum of intensities per mz - histogram
    hist(log(mzTIC), main="", xlab = "", las=1, ylab="")
    title(main="12b) Sum of intensities per mz", line=2, ylab="")
    title(xlab = "log (sum of intensities per mz)")
    title(ylab = "Frequency", line=4)
    abline(v=median(log(mzTIC[mzTIC>0])), col="blue")

    ################################## V) general plots ############################

    par(mfrow = c(2,1), mar=c(5,6,4,2))

    ## 13a) Intensity histogram: 
    hist(log2(spectra(msidata)[]), main="", xlab = "", ylab="", las=1)
    title(main="13a) Log2-transformed intensities", line=2)
    title(xlab="log2 intensities")
    title(ylab="Frequency", line=4)
    abline(v=median(log2(spectra(msidata)[(spectra(msidata)>0)])), col="blue")

    ## 13b) Median intensity over spectra
    medianint_spectra = apply(spectra(msidata), 2, median)
    plot(medianint_spectra, main="13b) Median intensity per spectrum",las=1, xlab="Spectra index \n (= Acquisition time)", ylab="")
    title(ylab="Median spectrum intensity", line=4)

    ## 14) Mass spectra 

    par(mfrow = c(2, 2))
    plot(msidata, pixel = 1:length(pixelnumber), main= "Average spectrum")
    plot(msidata, pixel =round(length(pixelnumber)/2, digits=0), main="Spectrum in middle of acquisition")
    plot(msidata, pixel = highestmz_pixel, main= paste0("Spectrum at ", rownames(coord(msidata)[highestmz_pixel,])))
    plot(msidata, pixel = secondhighestmz_pixel, main= paste0("Spectrum at ", rownames(coord(msidata)[secondhighestmz_pixel,])))

    ## 15) Zoomed in mass spectra for calibrants
    plusminusvalue = $plusminus_dalton
    x = 1
    if (length(inputcalibrantmasses) != 0)

          par(mfrow = c(2, 2), oma=c(0,0,2,0))
          plot(msidata[minmasspixel:maxmasspixel,], pixel = 1:length(pixelnumber), main= "average spectrum")
          abline(v=c(calibrant-plusminusvalue, calibrant,calibrant+plusminusvalue), col="blue", lty=c(3,5,3))
          plot(msidata[minmasspixel:maxmasspixel,], pixel =round(length(pixelnumber)/2, digits=0), main="pixel in middle of acquisition")
          abline(v=c(calibrant-plusminusvalue, calibrant,calibrant+plusminusvalue), col="blue", lty=c(3,5,3))
          plot(msidata[minmasspixel:maxmasspixel,], pixel = highestmz_pixel,main= paste0("Spectrum at ", rownames(coord(msidata)[highestmz_pixel,])))
          abline(v=c(calibrant-plusminusvalue, calibrant,calibrant+plusminusvalue), col="blue", lty=c(3,5,3))
          plot(msidata[minmasspixel:maxmasspixel,], pixel = secondhighestmz_pixel,  main= paste0("Spectrum at ", rownames(coord(msidata)[secondhighestmz_pixel,])))
          abline(v=c(calibrant-plusminusvalue, calibrant,calibrant+plusminusvalue), col="blue", lty=c(3,5,3))
          title(paste0(inputcalibrants[x,1]), outer=TRUE)
          x=x+1
        }

    }else{print("15) The inputcalibrant masses were not provided or outside the mass range")}

dev.off()
}else{
  print("inputfile has no intensities > 0")
dev.off()
}

            <param name="distance" value="0.25" type="float" label="Distance in Dalton" help="Distance in Da used to find peak maximum from input masses in both directions"/>
            <param name="filenameratioplot" type="text" optional="true" label="Title" help="Optional title for fold change plot."/>
        </repeat>
    </inputs>
    <outputs>
        <data format="pdf" name="plots" from_work_dir="qualitycontrol.pdf" label = "${tool.name} on $infile.display_name"/>
    </outputs>

    <tests>
        <test>
            <param name="infile" value="" ftype="imzml">

6:5c63fe03ed9e

<tool id="mass_spectrometry_imaging_qc" name="MSI Qualitycontrol" version="1.7.0.5">
    <description>
        mass spectrometry imaging QC
    </description>
    <requirements>
        <requirement type="package" version="1.7.0">bioconductor-cardinal</requirement>

    ############################################################################

    ## 1) Acquisition image

    pixelnumber = 1:pixelcount
    pixelxyarray=cbind(coord(msidata)[,1:2],pixelnumber)

    print(ggplot(pixelxyarray, aes(x=x, y=y, fill=pixelnumber))
     + geom_tile() + coord_fixed()
     + ggtitle("Order of Acquisition")
     +theme_bw()
     + scale_fill_gradientn(colours = c("blue", "purple" , "red","orange"), 
                            space = "Lab", na.value = "black", name = "Acq"))

    ## 2) Number of calibrants per spectrum

            }
          pixelmatrix = rbind(pixelmatrix, calibrantintensity)
        }

        countvector= as.factor(colSums(pixelmatrix>0))
        countdf= cbind(coord(msidata)[,1:2], countvector)
        mycolours = c("black","grey", "darkblue", "blue", "green" , "red", "yellow", "magenta", "olivedrab1", "lightseagreen")

        print(ggplot(countdf, aes(x=x, y=y, fill=countvector))
           + geom_tile() + coord_fixed() 
          + ggtitle("Number of calibrants per pixel")
          + theme_bw() 
          + theme(text=element_text(family="ArialMT", face="bold", size=12))
          + scale_fill_manual(values = mycolours[1:length(countvector)], 
                                na.value = "black", name = "# calibrants"))
    }else{print("2) The inputcalibrant masses were not provided or outside the mass range")}

            mass1vector = spectra(msidata)[features(msidata, mz = maxmass1),]
            mass2vector = spectra(msidata)[features(msidata, mz = maxmass2),]
            foldchange = log2(mass1vector/mass2vector)

            ratiomatrix = cbind(foldchange, coord(msidata)[,1:2])

            print(ggplot(ratiomatrix, aes(x=x, y=y, fill=foldchange), colour=colo)
             + geom_tile() + coord_fixed()
             + ggtitle("$label")
             + theme_bw()

    par(mfrow=c(1,1), mar=c(5.1, 4.1, 4.1, 2.1), mgp=c(3, 1, 0), las=0)
    if (length(inputmasses) != 0)
    {   for (mass in 1:length(inputmasses))
        {
          image(msidata, mz=inputmasses[mass], plusminus=$plusminus_dalton, 
          main= paste0(inputnames[mass], " (", round(inputmasses[mass], digits = 2)," ± ", $plusminus_dalton, " Da)"),
                contrast.enhance = "histogram", ylim=c(maximumy+2, 0))
        }
    } else {print("3) The inputpeptide masses were not provided or outside the mass range")}


    ## 4) Number of peaks per pixel - image

    peaksperpixel = colSums(spectra(msidata)[]> 0)
    peakscoordarray=cbind(coord(msidata)[,1:2], peaksperpixel)

    print(ggplot(peakscoordarray, aes(x=x, y=y, fill=peaksperpixel), colour=colo)
    + geom_tile() + coord_fixed() 
     + ggtitle("Number of peaks per pixel")
     + theme_bw() 
     + 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 = "# peaks"))

    ## 5) TIC image 
    TICcoordarray=cbind(coord(msidata)[,1:2], TICs)
    colo = colorRampPalette(
    c("blue", "cyan", "green", "yellow","red"))
    print(ggplot(TICcoordarray, aes(x=x, y=y, fill=TICs), colour=colo)
     + geom_tile() + coord_fixed() 
     + ggtitle("Total Ion Chromatogram")
     + theme_bw() 
     + 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 = "TIC"))

    ## 6) Most abundant mass image 

    highestmz = apply(spectra(msidata)[],2,which.max) 
    highestmz_matrix = cbind(coord(msidata)[,1:2],mz(msidata)[highestmz])
    colnames(highestmz_matrix)[3] = "highestmzinDa"

    print(ggplot(highestmz_matrix, aes(x=x, y=y, fill=highestmzinDa))
    + geom_tile() + coord_fixed() 
    + ggtitle("Most abundant m/z in each pixel")
    + theme_bw() 
    + scale_fill_gradientn(colours = c("blue", "purple" , "red","orange"), space = "Lab", na.value = "black", name = "m/z", 
                           labels = as.character(pretty(highestmz_matrix\$highestmzinDa)[c(1,3,5,7)]),
                           breaks = pretty(highestmz_matrix\$highestmzinDa)[c(1,3,5,7)], limits=c(min(highestmz_matrix\$highestmzinDa), max(highestmz_matrix\$highestmzinDa)))
    + theme(text=element_text(family="ArialMT", face="bold", size=12)))

    secondhighestmz_pixel = which(round(highestmz_matrix\$highestmzinDa, digits=0) == secondhighestmz)[1]

    ## 7) pca image for two components
    pca = PCA(msidata, ncomp=2) 
    par(mfrow = c(2,1))
    plot(pca, col=c("black", "darkgrey"), main="PCA for two components")
    image(pca, col=c("black", "white"),ylim=c(maximumy+2, 0),  strip=FALSE)


    ############################# III) properties over acquisition (spectra index)##########
    ##############################################################################

    par(mfrow = c(2,1), mar=c(5,6,4,2))

    ## 8a) number of peaks per spectrum - scatterplot
    plot_colorByDensity(pixels(msidata), peaksperpixel, ylab = "", xlab = "", main="Number of peaks per spectrum")
    title(xlab="Spectra index \n (= Acquisition time)", line=3)
    title(ylab="Number of peaks", line=4)

    ## 8b) number of peaks per spectrum - 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")

    ## 9a) TIC per spectrum - density scatterplot
    zero=0
    par(mfrow = c(2,1), mar=c(5,6,4,2))
    plot_colorByDensity(pixels(msidata), TICs,  ylab = "", xlab = "", main="TIC per spectrum")
    title(xlab="Spectra index \n (= Acquisition time)", line=3)
    title(ylab = "Total ion chromatogram intensity", line=4)

    ## 9b) TIC per spectrum -  histogram
    hist(log(TICs), main="", las=1, xlab = "log(TIC per spectrum)", ylab="")
    title(main= "TIC per spectrum", line=2)
    title(ylab="Frequency = # spectra", line=4)
    abline(v=median(log(TICs[TICs>0])), col="blue") 


    ################################## IV) changes over mz ############################

    ## 11) Number of peaks per mz
    ## Number of peaks per mz - number across all pixel
    peakspermz = rowSums(spectra(msidata)[] > 0 )

    par(mfrow = c(2,1), mar=c(5,6,4,4.5))
    ## Number of peaks per mz - scatterplot
    plot_colorByDensity(mz(msidata),peakspermz, main= "Number of peaks per mz", ylab ="")
    title(xlab="mz in Dalton", 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)

    # make plot smaller to fit axis and labels, add second y axis with %
    ## Number of peaks per mz - histogram
    hist(peakspermz, main="", las=1, ylab="", xlab="")
    title(ylab = "Frequency", line=4)
    title(main="Number of peaks per mz", xlab = "Number of peaks per mz", line=2)
    abline(v=median(peakspermz), col="blue") 


    ## 12) Sum of intensities per mz

    ## Sum of all intensities for each mz (like TIC, but for mz instead of pixel)
    mzTIC = rowSums(spectra(msidata)[]) # calculate intensity sum for each mz

    par(mfrow = c(2,1), mar=c(5,6,4,2))
    # 12a) sum of intensities per mz - scatterplot
    plot_colorByDensity(mz(msidata),mzTIC,  main= "Sum of intensities per mz", ylab ="")
    title(xlab="mz in Dalton", line=2.5)
    title(ylab="Intensity sum", line=4)
    # 12b) sum of intensities per mz - histogram
    hist(log(mzTIC), main="", xlab = "", las=1, ylab="")
    title(main="Sum of intensities per mz", line=2, ylab="")
    title(xlab = "log (sum of intensities per mz)")
    title(ylab = "Frequency", line=4)
    abline(v=median(log(mzTIC[mzTIC>0])), col="blue")

    ################################## V) general plots ############################

    par(mfrow = c(2,1), mar=c(5,6,4,2))

    ## 13a) Intensity histogram: 
    hist(log2(spectra(msidata)[]), main="", xlab = "", ylab="", las=1)
    title(main="Log2-transformed intensities", line=2)
    title(xlab="log2 intensities")
    title(ylab="Frequency", line=4)
    abline(v=median(log2(spectra(msidata)[(spectra(msidata)>0)])), col="blue")

    ## 13b) Median intensity over spectra
    medianint_spectra = apply(spectra(msidata), 2, median)
    plot(medianint_spectra, main="Median intensity per spectrum",las=1, xlab="Spectra index \n (= Acquisition time)", ylab="")
    title(ylab="Median spectrum intensity", line=4)

    ## 13c) Histogram on mz values
    par(mfrow = c(1, 1))
    hist(mz(msidata), xlab = "mz in Dalton", main="Histogram of mz values")


    ## 14) Mass spectra 

    par(mfrow = c(2, 2))
    plot(msidata, pixel = 1:length(pixelnumber), main= "Average spectrum")
    plot(msidata, pixel =round(length(pixelnumber)/2, digits=0), main="Spectrum in middle of acquisition")
    plot(msidata, pixel = highestmz_pixel, main= paste0("Spectrum at ", rownames(coord(msidata)[highestmz_pixel,1:2])))
    plot(msidata, pixel = secondhighestmz_pixel, main= paste0("Spectrum at ", rownames(coord(msidata)[secondhighestmz_pixel,1:2])))

    ## 15) Zoomed in mass spectra for calibrants
    plusminusvalue = $plusminus_dalton
    x = 1
    if (length(inputcalibrantmasses) != 0)

          par(mfrow = c(2, 2), oma=c(0,0,2,0))
          plot(msidata[minmasspixel:maxmasspixel,], pixel = 1:length(pixelnumber), main= "average spectrum")
          abline(v=c(calibrant-plusminusvalue, calibrant,calibrant+plusminusvalue), col="blue", lty=c(3,5,3))
          plot(msidata[minmasspixel:maxmasspixel,], pixel =round(length(pixelnumber)/2, digits=0), main="pixel in middle of acquisition")
          abline(v=c(calibrant-plusminusvalue, calibrant,calibrant+plusminusvalue), col="blue", lty=c(3,5,3))
          plot(msidata[minmasspixel:maxmasspixel,], pixel = highestmz_pixel,main= paste0("Spectrum at ", rownames(coord(msidata)[highestmz_pixel,1:2])))
          abline(v=c(calibrant-plusminusvalue, calibrant,calibrant+plusminusvalue), col="blue", lty=c(3,5,3))
          plot(msidata[minmasspixel:maxmasspixel,], pixel = secondhighestmz_pixel,  main= paste0("Spectrum at ", rownames(coord(msidata)[secondhighestmz_pixel,1:2])))
          abline(v=c(calibrant-plusminusvalue, calibrant,calibrant+plusminusvalue), col="blue", lty=c(3,5,3))
          title(paste0(inputcalibrants[x,1]), outer=TRUE)
          x=x+1
        }

    }else{print("15) The inputcalibrant masses were not provided or outside the mass range")}

    ## 16) ppm accuracy measured vs. theoretical calibrant mass

    if (length(inputcalibrantmasses) != 0)
    {
        par(mfrow = c(1, 1))

        differencevector = vector()

        for (mass in 1:length(inputcalibrantmasses))
        {mznumber = features(msidata, mz = inputcalibrantmasses[mass]) ### this gives the featurenumber which is closest to given mz
        mzvalue = mz(msidata)[mznumber] ### gives the mz in Da which is closest to the given mz (using the featurenumber)
        mzdifference = inputcalibrantmasses[mass] - mzvalue ### difference in Da: theoretical value - closest mz value
        ppmdifference = mzdifference/inputcalibrantmasses[mass]*1000000 ### calculate ppm for accuracy measurement
        differencevector[mass] = ppmdifference }
        differencevector = round(differencevector, digits=2)

        ### plot the ppm difference theor. mz value to closest mz value: 

        calibrant_names = as.character(calibrant_list[,2])
        diff_df = data.frame(differencevector, calibrant_names)        
        diff_plot<-ggplot(data=diff_df, aes(x=calibrant_names, y=differencevector)) + geom_col() + theme_minimal() +
        labs(title="Theoretical calibrant mz vs. closest measured mz", x="calibrants", y = "Difference in ppm")+
        geom_text(aes(label=differencevector), vjust=-0.3, size=3.5, col="blue")

        print(diff_plot)

    }else{print("16) The inputcalibrant masses were not provided or outside the mass range")}


dev.off()

}else{
  print("inputfile has no intensities > 0")
dev.off()
}

            <param name="distance" value="0.25" type="float" label="Distance in Dalton" help="Distance in Da used to find peak maximum from input masses in both directions"/>
            <param name="filenameratioplot" type="text" optional="true" label="Title" help="Optional title for fold change plot."/>
        </repeat>
    </inputs>
    <outputs>
        <data format="pdf" name="plots" from_work_dir="qualitycontrol.pdf" label = "${tool.name} ${on_string}"/>
    </outputs>

    <tests>
        <test>
            <param name="infile" value="" ftype="imzml">