comparison msi_preprocessing.xml @ 1:c4abf42419c2 draft

planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/msi_preprocessing commit a8eebad4ad469908f64c25e1e2c705eb637e3cae

0:74fcb3c95a53

<tool id="mass_spectrometry_imaging_preprocessing" name="MSI preprocessing" version="1.7.0">
    <description>
        mass spectrometry imaging preprocessing
    </description>
    <requirements>
        <requirement type="package" version="1.7.0">bioconductor-cardinal</requirement>

    msidata <- readMSIData('infile.hdr')
#else
    load('infile.RData')
#end if

maxpixel = length(pixels(msidata)) 
pixelnumber = c(1:maxpixel)

#for $method in $methods:
    #if str( $method.methods_conditional.preprocessing_method ) == 'Normalization':

        #elif str($method.methods_conditional.methods_for_smoothing.smoothing_method) == 'ma':
            print('sgolay smoothing')
            msidata <- smoothSignal(msidata, method="$method.methods_conditional.methods_for_smoothing.smoothing_method", window=$method.methods_conditional.window_smoothing, coef = $method.methods_conditional.methods_for_smoothing.coefficients_ma_filter)
        #end if

    #elif str( $method.methods_conditional.preprocessing_method) == 'Peak_picking':
        print('Peak_picking')
        ## Peakpicking

        #if str( $method.methods_conditional.methods_for_picking.picking_method) == 'adaptive':

        #elif str( $method.methods_conditional.methods_for_picking.picking_method) == 'simple':
            print('simple peakpicking')
            msidata = peakPick(msidata, pixel=pixelnumber, window = $method.methods_conditional.window_picking, blocks = $method.methods_conditional.blocks_picking, method='$method.methods_conditional.methods_for_picking.picking_method', SNR=$method.methods_conditional.SNR_picking_method)
        #end if

    #elif str( $method.methods_conditional.preprocessing_method ) == 'Peak_alignment':
        print('Peak_alignment')
        ## Peakalignment

        print('Peak_filtering')
        msidata = peakFilter(msidata, method='freq', freq.min = $method.methods_conditional.frequ_filtering)
    #end if
#end for

## save as as (.RData)
save(msidata, file="$msidata_preprocessed")

## save as intensity matrix (.csv)
csvmatrix = spectra(msidata)
rownames(csvmatrix) = mz(msidata)
newmatrix = rbind(pixels(msidata), csvmatrix)
write.csv(newmatrix[2:nrow(newmatrix),], file="$preprocessed_intensity_matrix")

    ]]></configfile>
    </configfiles>
    <inputs>
        <param name="infile" type="data" format="imzml,rdata,analyze75"
               label="MSI rawdata as imzml or Cardinal MSImageSet saved as RData"
               help="load imzml and ibd file by uploading composite datatype imzml"/>

        <repeat name="methods" title="Preprocessing" min="1" max="50">
            <conditional name="methods_conditional">
                <param name="preprocessing_method" type="select" label="Select the preprocessing methods you want to apply">
                    <option value="Normalization" selected="True">Normalization to TIC</option>
                    <option value="Baseline_reduction">Baseline Reduction</option>

                </when>
            </conditional>
        </repeat>
    </inputs>
    <outputs>
        <data format="rdata" name="msidata_preprocessed" label="Preprocessed_output"/>
        <data format="csv" name="preprocessed_intensity_matrix" label="preprocessed intensity matrix" />
    </outputs>
    <tests>
        <test>
            <param name="infile" value="" ftype="imzml">
                <composite_data value="Example_Continuous.imzML" ftype="imzml"/>
                <composite_data value="Example_Continuous.ibd" ftype="ibd"/>
            </param>
            <repeat name="methods">
                <conditional name="methods_conditional">
                    <param name="preprocessing_method" value="Normalization" />
                </conditional>
            </repeat>
            <repeat name="methods">
                <conditional name="methods_conditional">
                    <param name="preprocessing_method" value="Smoothing" />
                    <conditional name="methods_for_smoothing">
                        <param name="smoothing_method" value="sgolay" />
                    </conditional>
                </conditional>
            </repeat>
            <repeat name="methods">
                <conditional name="methods_conditional">

            </repeat>
            <repeat name="methods">
                <conditional name="methods_conditional">
                    <param name="preprocessing_method" value="Peak_alignment" />
                    <conditional name="methods_for_alignment">
                        <param name="alignment_method" value="DP" />
                    </conditional>
                </conditional>
            </repeat>
            <repeat name="methods">
                <conditional name="methods_conditional">
                    <param name="preprocessing_method" value="Peak_filtering" />
                </conditional>
            </repeat>
            <output name="msidata_preprocessed" file="preprocessing_results1.RData" compare="sim_size" />
            <output name="preprocessed_intensity_matrix" file="preprocessing_results1.csv" />
        </test>
        <test>
            <param name="infile" value="LM5_first68pixel.RData" ftype="rdata"/>
            <repeat name="methods">
                <conditional name="methods_conditional">
                    <param name="preprocessing_method" value="Baseline_reduction" />
                    <param name="blocks_baseline" value="50" />
                </conditional>
            </repeat>
            <repeat name="methods">
                <conditional name="methods_conditional">
                    <param name="preprocessing_method" value="Peak_picking" />
                    <param name="blocks_picking" value="3" />
                    <param name="window_picking" value="5" />

                    <param name="preprocessing_method" value="Peak_alignment" />
                    <param name="methods_for_alignment" value="DP" />
                </conditional>
            </repeat>
            <output name="msidata_preprocessed" file="preprocessing_results2.RData" compare="sim_size" />
            <output name="preprocessed_intensity_matrix" file="preprocessing_results2.csv" lines_diff="2"/>
        </test>
        <test>
            <param name="infile" value="" ftype="analyze75">
                <composite_data value="Analyze75.hdr" ftype="hdr"/>
                <composite_data value="Analyze75.img" ftype="img"/>
                <composite_data value="Analyze75.t2m" ftype="t2m"/>
            </param>
            <repeat name="methods">
                <conditional name="methods_conditional">
                    <param name="preprocessing_method" value="Normalization" />
                </conditional>
            </repeat>
            <repeat name="methods">
                <conditional name="methods_conditional">
                    <param name="preprocessing_method" value="Smoothing" />
                    <conditional name="methods_for_smoothing">
                        <param name="smoothing_method" value="gaussian" />
                    </conditional>
                </conditional>
            </repeat>
            <repeat name="methods">
                <conditional name="methods_conditional">
                    <param name="preprocessing_method" value="Peak_picking" />
                    <param name="blocks_picking" value="3" />
                    <param name="window_picking" value="5" />

                    <param name="preprocessing_method" value="Peak_alignment" />
                    <param name="methods_for_alignment" value="diff" />
                </conditional>
            </repeat>
            <output name="msidata_preprocessed" file="preprocessing_results3.RData" compare="sim_size" />
            <output name="preprocessed_intensity_matrix" file="preprocessing_results3.csv" />
        </test>
    </tests>
    <help>
    <![CDATA[
Cardinal is an R package that implements statistical & computational tools for analyzing mass spectrometry imaging datasets.

**Preprocessing steps:**

- Smoothening: Smoothing of the mass peaks reduces noise and improves peak detection

1:c4abf42419c2

<tool id="mass_spectrometry_imaging_preprocessing" name="MSI preprocessing" version="1.7.0.1">
    <description>
        mass spectrometry imaging preprocessing
    </description>
    <requirements>
        <requirement type="package" version="1.7.0">bioconductor-cardinal</requirement>

    msidata <- readMSIData('infile.hdr')
#else
    load('infile.RData')
#end if


maxpixel = length(pixels(msidata)) 
pixelnumber = c(1:maxpixel)

#for $method in $methods:
    #if str( $method.methods_conditional.preprocessing_method ) == 'Normalization':

        #elif str($method.methods_conditional.methods_for_smoothing.smoothing_method) == 'ma':
            print('sgolay smoothing')
            msidata <- smoothSignal(msidata, method="$method.methods_conditional.methods_for_smoothing.smoothing_method", window=$method.methods_conditional.window_smoothing, coef = $method.methods_conditional.methods_for_smoothing.coefficients_ma_filter)
        #end if


    #elif str( $method.methods_conditional.preprocessing_method) == 'Peak_picking':
        print('Peak_picking')
        ## Peakpicking

        #if str( $method.methods_conditional.methods_for_picking.picking_method) == 'adaptive':

        #elif str( $method.methods_conditional.methods_for_picking.picking_method) == 'simple':
            print('simple peakpicking')
            msidata = peakPick(msidata, pixel=pixelnumber, window = $method.methods_conditional.window_picking, blocks = $method.methods_conditional.blocks_picking, method='$method.methods_conditional.methods_for_picking.picking_method', SNR=$method.methods_conditional.SNR_picking_method)
        #end if



    #elif str( $method.methods_conditional.preprocessing_method ) == 'Peak_alignment':
        print('Peak_alignment')
        ## Peakalignment

        print('Peak_filtering')
        msidata = peakFilter(msidata, method='freq', freq.min = $method.methods_conditional.frequ_filtering)
    #end if
#end for


## save as as (.RData)
save(msidata, file="$msidata_preprocessed")

if (length(features(msidata))> 0)
{

## save as intensity matrix
spectramatrix = spectra(msidata)
rownames(spectramatrix) = mz(msidata)
newmatrix = rbind(pixels(msidata), spectramatrix)
write.table(newmatrix[2:nrow(newmatrix),], file="$matrixasoutput", quote = FALSE, row.names = TRUE, col.names=NA, sep = "\t")

}else{
  print("file has no features left")
write.table(matrix(rownames(coord(msidata)), ncol=ncol(msidata), nrow=1), file="$matrixasoutput", quote = FALSE, row.names = FALSE, col.names=FALSE, sep = "\t")
}


    ]]></configfile>
    </configfiles>
    <inputs>
        <param name="infile" type="data" format="imzml,rdata,analyze75"
            label="MSI rawdata as imzml or Cardinal MSImageSet saved as RData"
            help="load imzml and ibd file by uploading composite datatype imzml"/>
        <repeat name="methods" title="Preprocessing" min="1" max="50">
            <conditional name="methods_conditional">
                <param name="preprocessing_method" type="select" label="Select the preprocessing methods you want to apply">
                    <option value="Normalization" selected="True">Normalization to TIC</option>
                    <option value="Baseline_reduction">Baseline Reduction</option>

                </when>
            </conditional>
        </repeat>
    </inputs>
    <outputs>
        <data format="rdata" name="msidata_preprocessed" label="${tool.name} on $infile.display_name"/>
        <data format="tabular" name="matrixasoutput" label="${tool.name} on $infile.display_name" />
    </outputs>
    <tests>
        <test>
            <param name="infile" value="" ftype="imzml">
                <composite_data value="Example_Continuous.imzML"/>
                <composite_data value="Example_Continuous.ibd"/>
            </param>
            <repeat name="methods">
                <conditional name="methods_conditional">
                    <param name="preprocessing_method" value="Normalization" />
                </conditional>
            </repeat>
            <repeat name="methods">
                <conditional name="methods_conditional">
                    <param name="preprocessing_method" value="Baseline_reduction" />
                    <param name="blocks_baseline" value="100" />
                </conditional>
            </repeat>
            <repeat name="methods">
                <conditional name="methods_conditional">
                    <param name="preprocessing_method" value="Smoothing" />
                    <conditional name="methods_for_smoothing">
                        <param name="smoothing_method" value="gaussian" />
                    </conditional>
                </conditional>
            </repeat>
            <repeat name="methods">
                <conditional name="methods_conditional">

            </repeat>
            <repeat name="methods">
                <conditional name="methods_conditional">
                    <param name="preprocessing_method" value="Peak_alignment" />
                    <conditional name="methods_for_alignment">
                        <param name="alignment_method" value="diff" />
                    </conditional>
                </conditional>
            </repeat>
            <!--repeat name="methods">
                <conditional name="methods_conditional">
                    <param name="preprocessing_method" value="Peak_filtering" />
                </conditional>
            </repeat-->
            <output name="msidata_preprocessed" file="preprocessing_results1.RData" compare="sim_size" />
            <output name="matrixasoutput" file="preprocessing_results1.txt" />
        </test>
        <test>
            <param name="infile" value="example_continous.RData" ftype="rdata"/>
            <!--repeat name="methods">
                <conditional name="methods_conditional">
                    <param name="preprocessing_method" value="Baseline_reduction" />
                    <param name="blocks_baseline" value="3" />
                </conditional>
            </repeat-->
            <repeat name="methods">
                <conditional name="methods_conditional">
                    <param name="preprocessing_method" value="Peak_picking" />
                    <param name="blocks_picking" value="3" />
                    <param name="window_picking" value="5" />

                    <param name="preprocessing_method" value="Peak_alignment" />
                    <param name="methods_for_alignment" value="DP" />
                </conditional>
            </repeat>
            <output name="msidata_preprocessed" file="preprocessing_results2.RData" compare="sim_size" />
            <output name="matrixasoutput" file="preprocessing_results2.txt" lines_diff="2" />
        </test>
        <test>
            <param name="infile" value="" ftype="analyze75">
                <composite_data value="Analyze75.hdr"/>
                <composite_data value="Analyze75.img"/>
                <composite_data value="Analyze75.t2m"/>
            </param>
            <repeat name="methods">
                <conditional name="methods_conditional">
                    <param name="preprocessing_method" value="Normalization" />
                </conditional>
            </repeat>
            <!--repeat name="methods">
                <conditional name="methods_conditional">
                    <param name="preprocessing_method" value="Baseline_reduction" />
                    <param name="blocks_baseline" value="50" />
                </conditional>
            </repeat-->
            <repeat name="methods">
                <conditional name="methods_conditional">
                    <param name="preprocessing_method" value="Peak_picking" />
                    <param name="blocks_picking" value="3" />
                    <param name="window_picking" value="5" />

                    <param name="preprocessing_method" value="Peak_alignment" />
                    <param name="methods_for_alignment" value="diff" />
                </conditional>
            </repeat>
            <output name="msidata_preprocessed" file="preprocessing_results3.RData" compare="sim_size" />
            <output name="matrixasoutput" file="preprocessing_results3.txt" />
        </test>

    </tests>
    <help>
        <![CDATA[
Cardinal is an R package that implements statistical & computational tools for analyzing mass spectrometry imaging datasets.

**Preprocessing steps:**

- Smoothening: Smoothing of the mass peaks reduces noise and improves peak detection