comparison preprocessing.xml @ 8:87bb011a4ee8 draft

"planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/cardinal commit d008f6ea0f5c8435fb975a34cb99ea4d42c5ebd2"

7:44a4b31fcbf3

<tool id="cardinal_preprocessing" name="MSI preprocessing" version="@VERSION@.1">
    <description>
        mass spectrometry imaging preprocessing
    </description>
    <macros>
        <import>macros.xml</import>

            if (class(msidata) == "MSProcessedImagingExperiment"){
                msidata = as(msidata, "MSContinuousImagingExperiment")
            }

            msidata = normalize(msidata, method="tic")
            msidata <- process(msidata, BPPARAM=MulticoreParam(workers=number_cpu))


            ############################### QC ###########################

            smoothed = c(minmz, maxmz,maxfeatures, pixelcount)
            QC_numbers= cbind(QC_numbers, smoothed)
            vectorofactions = append(vectorofactions, "smoothed")
            print(plot(msidata, pixel=random_spectra))
            title("Spectra after smoothing", outer=TRUE, line=0)

    ############################### Peak picking ###########################

        #elif str( $method.methods_conditional.preprocessing_method) == 'Peak_picking':
            #set $used_peak_picking = True

            <conditional name="methods_conditional">
                <param name="preprocessing_method" type="select" label="Preprocessing methods">
                    <option value="Normalization" selected="True">Intensity Normalization</option>
                    <option value="Baseline_reduction">Baseline Reduction</option>
                    <option value="Smoothing">Peak smoothing</option>
                    <option value="Peak_picking">Peak picking</option>
                    <option value="Peak_alignment">Peak alignment</option>
                    <option value="Peak_filtering">Peak filtering</option>
                    <option value="Peak_binning">Peak binning to reference peaks</option>
                    <option value="Data_reduction">Data reduction</option>

                                   label="The coefficients for the moving average filter"/>
                        </when>
                    </conditional>
                    <param name="window_smoothing" type="float" value="8"
                                label="Window size"/>
                </when>
                <when value="Peak_picking">
                    <param name="SNR_picking_method" type="float" value="6"
                        label="Signal to noise ratio"
                        help="The minimal signal to noise ratio for peaks to be considered as a valid peak."/>

                            <option value="mz">m/z</option>
                    </param>
                    <conditional name="align_ref_type">
                        <param name="align_reference_datatype" type="select" label="Choose reference">
                            <option value="align_noref" selected="True">no reference</option>
                            <option value="align_table" >tabular file as reference</option>
                        </param>
                        <when value="align_noref"/>
                        <when value="align_table">
                            <expand macro="reading_1_column_mz_tabular" label="Tabular file with m/z features to use for alignment. Only the m/z values from the tabular file will be kept."/>
                        </when>

                    <param name="frequ_filtering" type="float" value="0.01" max="1" min="0" label="Minimum frequency" help="Peaks that occur in the dataset in lesser proportion than this will be dropped (0.01 --> filtering for 1% of spectra)"/>
                </when>
                <when value="Peak_binning">
                    <expand macro="reading_1_column_mz_tabular" label="A reference to which the peaks are binned." help="Tabular file with m/z features to extract from input file"/>
                    <param name="peakbin_tol" value="NA" type="text" label="The tolerance to be used when matching the m/z features in the dataset to the reference. If this is NA, then automatically guess a resolution from the data." >
                        <sanitizer invalid_char="">
                            <valid initial="string.digits">
                                <add value="NA" />
                            </valid>
                        </sanitizer>
                    </param>
                    <param name="peakbin_units" display="radio" type="select" label="The units to use for the tolerance.">
                        <option value="mz" >mz</option>

                    <param name="normalization_method" value="tic"/>
                </conditional>
            </repeat>
            <repeat name="methods">
                <conditional name="methods_conditional">
                    <param name="preprocessing_method" value="Data_reduction"/>
                    <conditional name="methods_for_reduction">
                        <param name="reduction_method" value="bin"/>
                        <param name="bin_width" value="0.1"/>
                    </conditional>

            <repeat name="methods">
                <conditional name="methods_conditional">
                    <param name="preprocessing_method" value="Baseline_reduction"/>
                </conditional>
            </repeat>
            <output name="QC_overview" file="preprocessing_results5.pdf" compare="sim_size"/>
            <output name="outfile_imzml" ftype="imzml" file="preprocessing_results5.imzml.txt" compare="sim_size">
                <extra_files type="file" file="preprocessing_results5.imzml" name="imzml" lines_diff="6"/>
                <extra_files type="file" file="preprocessing_results5.ibd" name="ibd" compare="sim_size"/>
            </output>
        </test>

8:87bb011a4ee8

<tool id="cardinal_preprocessing" name="MSI preprocessing" version="@VERSION@.2">
    <description>
        mass spectrometry imaging preprocessing
    </description>
    <macros>
        <import>macros.xml</import>

            if (class(msidata) == "MSProcessedImagingExperiment"){
                msidata = as(msidata, "MSContinuousImagingExperiment")
            }

            msidata = normalize(msidata, method="$method.methods_conditional.methods_for_normalization.normalization_method")
            msidata <- process(msidata, BPPARAM=MulticoreParam(workers=number_cpu))


            ############################### QC ###########################

            smoothed = c(minmz, maxmz,maxfeatures, pixelcount)
            QC_numbers= cbind(QC_numbers, smoothed)
            vectorofactions = append(vectorofactions, "smoothed")
            print(plot(msidata, pixel=random_spectra))
            title("Spectra after smoothing", outer=TRUE, line=0)


    ############################### Mz alignment ###########################

        #elif str( $method.methods_conditional.preprocessing_method ) == 'mz_alignment':
            print('M/z alignment')
            ## M/z alignment

            #if str( $method.methods_conditional.mzalign_ref_type.align_reference_datatype) == 'align_table':

                reference_mz = read.delim("$method.methods_conditional.mzalign_ref_type.mz_tabular", header = $method.methods_conditional.mzalign_ref_type.feature_header, stringsAsFactors = FALSE)
                reference_mz = reference_mz[,$method.methods_conditional.mzalign_ref_type.feature_column]

                msidata = mzAlign(msidata, ref=reference_mz, tolerance = $method.methods_conditional.alignment_tol, units = "$method.methods_conditional.alignment_units", quantile = $method.methods_conditional.quantile, span = $method.methods_conditional.span)


            #elif str( $method.methods_conditional.mzalign_ref_type.align_reference_datatype) == 'align_noref':

                msidata = mzAlign(msidata,tolerance = $method.methods_conditional.alignment_tol, units = "$method.methods_conditional.alignment_units", , quantile = $method.methods_conditional.quantile, span = $method.methods_conditional.span)

            #end if

            msidata <- process(msidata, BPPARAM=MulticoreParam(workers=number_cpu))

            ############################### QC ###########################

            maxfeatures =nrow(msidata)
            pixelcount = ncol(msidata)
            minmz = round(min(mz(msidata)), digits=2)
            maxmz = round(max(mz(msidata)), digits=2)
            mz_aligned = c(minmz, maxmz,maxfeatures, pixelcount)
            QC_numbers= cbind(QC_numbers, mz_aligned)
            vectorofactions = append(vectorofactions, "mz aligned")
            print(plot(msidata, pixel=random_spectra))
            title("Spectra after m/z alignment", outer=TRUE, line=0)


    ############################### Peak picking ###########################

        #elif str( $method.methods_conditional.preprocessing_method) == 'Peak_picking':
            #set $used_peak_picking = True

            <conditional name="methods_conditional">
                <param name="preprocessing_method" type="select" label="Preprocessing methods">
                    <option value="Normalization" selected="True">Intensity Normalization</option>
                    <option value="Baseline_reduction">Baseline Reduction</option>
                    <option value="Smoothing">Peak smoothing</option>
                    <option value="mz_alignment">m/z alignment</option>
                    <option value="Peak_picking">Peak picking</option>
                    <option value="Peak_alignment">Peak alignment</option>
                    <option value="Peak_filtering">Peak filtering</option>
                    <option value="Peak_binning">Peak binning to reference peaks</option>
                    <option value="Data_reduction">Data reduction</option>

                                   label="The coefficients for the moving average filter"/>
                        </when>
                    </conditional>
                    <param name="window_smoothing" type="float" value="8"
                                label="Window size"/>
                </when>
                <when value="mz_alignment">
                    <param name="alignment_tol" type="text" value="NA"
                           label="tolerance" help="The tolerance to be used when matching the peaks in the unaligned spectra to the reference spectrum. If this is NA, then automatically guess a tolerance from the data.">
                       <sanitizer>
                            <valid initial="string.digits">
                                <add value="N" />
                                <add value="A" />
                            </valid>
                        </sanitizer>
                    </param>
                    <param name="alignment_units" type="select" display="radio" optional="False" label="The units to use for the tolerance.">
                            <option value="ppm" selected="True">ppm</option>
                            <option value="mz">m/z</option>
                    </param>
                    <conditional name="mzalign_ref_type">
                        <param name="align_reference_datatype" type="select" label="Choose reference">
                            <option value="align_noref" selected="True">use mean spectrum as reference</option>
                            <option value="align_table" >m/z values from tabular file as reference</option>
                        </param>
                        <when value="align_noref"/>
                        <when value="align_table">
                            <expand macro="reading_1_column_mz_tabular" label="Tabular file with m/z features to use for alignment. Only the m/z values from the tabular file will be kept."/>
                        </when>
                    </conditional>
                    <param name="quantile" type="float" value="0.2"
                        label="quantile" help="The top quantile of reference points (peaks detected via local maxima) to use from the reference spectrum."/>
                    <param name="span" type="float" value="0.75"
                        label="span" help="The smoothing parameter for the local polynomial regression used to determine the warping function."/>
                </when>
                <when value="Peak_picking">
                    <param name="SNR_picking_method" type="float" value="6"
                        label="Signal to noise ratio"
                        help="The minimal signal to noise ratio for peaks to be considered as a valid peak."/>

                            <option value="mz">m/z</option>
                    </param>
                    <conditional name="align_ref_type">
                        <param name="align_reference_datatype" type="select" label="Choose reference">
                            <option value="align_noref" selected="True">no reference</option>
                            <option value="align_table" >m/z values from tabular file as reference</option>
                        </param>
                        <when value="align_noref"/>
                        <when value="align_table">
                            <expand macro="reading_1_column_mz_tabular" label="Tabular file with m/z features to use for alignment. Only the m/z values from the tabular file will be kept."/>
                        </when>

                    <param name="frequ_filtering" type="float" value="0.01" max="1" min="0" label="Minimum frequency" help="Peaks that occur in the dataset in lesser proportion than this will be dropped (0.01 --> filtering for 1% of spectra)"/>
                </when>
                <when value="Peak_binning">
                    <expand macro="reading_1_column_mz_tabular" label="A reference to which the peaks are binned." help="Tabular file with m/z features to extract from input file"/>
                    <param name="peakbin_tol" value="NA" type="text" label="The tolerance to be used when matching the m/z features in the dataset to the reference. If this is NA, then automatically guess a resolution from the data." >
                        <sanitizer>
                            <valid initial="string.digits">
                                <add value="N" />
                                <add value="A" />
                            </valid>
                        </sanitizer>
                    </param>
                    <param name="peakbin_units" display="radio" type="select" label="The units to use for the tolerance.">
                        <option value="mz" >mz</option>

                    <param name="normalization_method" value="tic"/>
                </conditional>
            </repeat>
            <repeat name="methods">
                <conditional name="methods_conditional">
                    <param name="preprocessing_method" value="mz_alignment"/>
                </conditional>
            </repeat>
            <repeat name="methods">
                <conditional name="methods_conditional">
                    <param name="preprocessing_method" value="Data_reduction"/>
                    <conditional name="methods_for_reduction">
                        <param name="reduction_method" value="bin"/>
                        <param name="bin_width" value="0.1"/>
                    </conditional>

            <repeat name="methods">
                <conditional name="methods_conditional">
                    <param name="preprocessing_method" value="Baseline_reduction"/>
                </conditional>
            </repeat>
            <output name="QC_overview" file="preprocessing_results5.pdf" compare="sim_size" delta="13000"/>
            <output name="outfile_imzml" ftype="imzml" file="preprocessing_results5.imzml.txt" compare="sim_size">
                <extra_files type="file" file="preprocessing_results5.imzml" name="imzml" lines_diff="6"/>
                <extra_files type="file" file="preprocessing_results5.ibd" name="ibd" compare="sim_size"/>
            </output>
        </test>