comparison msi_qualitycontrol.xml @ 5:ac786240ef07 draft

planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_qualitycontrol commit ed7d3e6f1a09c78c8f71cc1bdc1a20249767f646

4:fef8bd551236

<tool id="mass_spectrometry_imaging_qc" name="MSI Qualitycontrol" version="1.7.0.3">
    <description>
        mass spectrometry imaging QC
    </description>
    <requirements>
        <requirement type="package" version="1.7.0">bioconductor-cardinal</requirement>

        }

        ### calculate how many input peptide masses are valid: 
        inputpeptides = input_list[input_list[,1]>minmz & input_list[,1]<maxmz,]
        number_peptides_in = length(input_list[,1])
        number_peptides_valid = length(inputpeptides)

#else
    inputpeptides = data.frame(0,0)
    number_peptides_in = 0
    number_peptides_valid = 0
#end if

colnames(inputpeptides) = c("mz", "name")

            calibrant_list = cbind(calibrant_list, calibrant_list)
         }
        ### calculate how many input calibrant masses are valid: 
        inputcalibrants = calibrant_list[calibrant_list[,1]>minmz & calibrant_list[,1]<maxmz,]
        number_calibrants_in = length(calibrant_list[,1])
        number_calibrants_valid = length(inputcalibrants)
#else
    inputcalibrants = data.frame(0,0)
    number_calibrants_in = 0
    number_calibrants_valid = 0
#end if

colnames(inputcalibrants) = c("mz", "name")

### bind inputcalibrants and inputpeptides together, to make heatmap on both lists

inputs_all = rbind(inputcalibrants[,1:2], inputpeptides[,1:2])
inputmasses = inputs_all[,1]
inputnames = inputs_all[,2]


properties = c("Number of mz features",
               "Range of mz values [Da]",
               "Number of pixels", 

               "Normalization", 
               "Smoothing",
               "Baseline reduction",
               "Peak picking",
               "Centroided", 
               paste0("# peptides in ", "$peptide_file.display_name"), 
               paste0("# calibrants in ", "$calibrant_file.display_name"))

values = c(paste0(maxfeatures), 
           paste0(minmz, " - ", maxmz), 
           paste0(pixelcount), 
           paste0(minimumx, " - ", maximumx),  

        {
          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 outside the mass range")}

    ## 4) Number of peaks per pixel - image

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

    ## 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))


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

    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") 


    ## 10) intensity of chosen peptides over acquisition (pixel index)

    if (length(inputcalibrants[,1]) != 0)
    {   
        par(mfrow = c(3, 2), oma=c(0,0,2,0))
        intensityvector = vector()
        for (mzvalue in 1:length(inputcalibrants[,1]))
        {
            mznumber = features(msidata, mz = inputcalibrants[,1][mzvalue])
            intensityvector = spectra(msidata)[][mznumber,] 
            plot(intensityvector, main=inputnames[mzvalue], xlab="Spectra index \n (= Acquisition time)")
        }
      title("10) intensity of calibrants over acquisition", outer=TRUE)
    }else{print("10) The inputcalibrant masses were outside the mass range")}

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

    ## 11) Number of peaks per mz

          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 outside the mass range")}

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

            <output name="plots" file="Testfile_qualitycontrol_analyze75.pdf" compare="sim_size" delta="20000"/>
        </test>

        <test>
            <param name="infile" value="preprocessing_results1.RData" ftype="rdata"/>
            <param name="peptide_file" value="inputpeptides.csv" ftype="txt"/>
            <param name="calibrant_file" ftype="txt" value="inputcalibrantfile1.txt"/>
            <param name="plusminus_dalton" value="0.1"/>
            <param name="filename" value="Testfile_rdata"/>
            <output name="plots" file="Testfile_qualitycontrol_rdata.pdf" compare="sim_size" delta="20000"/>
        </test>
        <test>

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>

        }

        ### calculate how many input peptide masses are valid: 
        inputpeptides = input_list[input_list[,1]>minmz & input_list[,1]<maxmz,]
        number_peptides_in = length(input_list[,1])
        number_peptides_valid = length(inputpeptides[,1])

#else
    ###inputpeptides = data.frame(0,0)
    inputpeptides = as.data.frame(matrix(, nrow = 0, ncol = 2))
    number_peptides_in = 0
    number_peptides_valid = 0
#end if

colnames(inputpeptides) = c("mz", "name")

            calibrant_list = cbind(calibrant_list, calibrant_list)
         }
        ### calculate how many input calibrant masses are valid: 
        inputcalibrants = calibrant_list[calibrant_list[,1]>minmz & calibrant_list[,1]<maxmz,]
        number_calibrants_in = length(calibrant_list[,1])
        number_calibrants_valid = length(inputcalibrants[,1])
#else
    ###inputcalibrants = data.frame(0,0)

    inputcalibrants = as.data.frame(matrix(, nrow = 0, ncol = 2))

    number_calibrants_in = 0
    number_calibrants_valid = 0
#end if

colnames(inputcalibrants) = c("mz", "name")

### bind inputcalibrants and inputpeptides together, to make heatmap on both lists

inputs_all = rbind(inputcalibrants[,1:2], inputpeptides[,1:2])
inputmasses = inputs_all[,1]
inputnames = inputs_all[,2]



properties = c("Number of mz features",
               "Range of mz values [Da]",
               "Number of pixels", 

               "Normalization", 
               "Smoothing",
               "Baseline reduction",
               "Peak picking",
               "Centroided", 
               paste0("# peptides in \n", "$peptide_file.display_name"), 
               paste0("# calibrants in \n", "$calibrant_file.display_name"))

values = c(paste0(maxfeatures), 
           paste0(minmz, " - ", maxmz), 
           paste0(pixelcount), 
           paste0(minimumx, " - ", maximumx),  

        {
          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)

    ## 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)##########
    ##############################################################################

    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

          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()

            <output name="plots" file="Testfile_qualitycontrol_analyze75.pdf" compare="sim_size" delta="20000"/>
        </test>

        <test>
            <param name="infile" value="preprocessing_results1.RData" ftype="rdata"/>
            <param name="plusminus_dalton" value="0.1"/>
            <param name="filename" value="Testfile_rdata"/>
            <output name="plots" file="Testfile_qualitycontrol_rdata.pdf" compare="sim_size" delta="20000"/>
        </test>
        <test>