Examples with PeakListRow net.sf.mzmine.datamodel.PeakListRow used on opensource projects

Example 36 with PeakListRow

use of net.sf.mzmine.datamodel.PeakListRow in project mzmine2 by mzmine.

the class PeakComparisonRowFilterTask method copyPeakRow.

/**
 * Create a copy of a feature list row.
 *
 * @param row the row to copy.
 * @return the newly created copy.
 */
private static PeakListRow copyPeakRow(final PeakListRow row) {
    // Copy the feature list row.
    final PeakListRow newRow = new SimplePeakListRow(row.getID());
    PeakUtils.copyPeakListRowProperties(row, newRow);
    // Copy the peaks.
    for (final Feature peak : row.getPeaks()) {
        final Feature newPeak = new SimpleFeature(peak);
        PeakUtils.copyPeakProperties(peak, newPeak);
        newRow.addPeak(peak.getDataFile(), newPeak);
    }
    return newRow;
}

Example 37 with PeakListRow

use of net.sf.mzmine.datamodel.PeakListRow in project mzmine2 by mzmine.

the class PeakComparisonRowFilterTask method filterPeakListRows.

/**
 * Filter the feature list rows by comparing peaks within a row.
 *
 * @param peakList feature list to filter.
 * @return a new feature list with rows of the original feature list that pass the filtering.
 */
private PeakList filterPeakListRows(final PeakList peakList) {
    // Create new feature list.
    final PeakList newPeakList = new SimplePeakList(peakList.getName() + ' ' + parameters.getParameter(PeakComparisonRowFilterParameters.SUFFIX).getValue(), peakList.getRawDataFiles());
    // Copy previous applied methods.
    for (final PeakListAppliedMethod method : peakList.getAppliedMethods()) {
        newPeakList.addDescriptionOfAppliedTask(method);
    }
    // Add task description to peakList.
    newPeakList.addDescriptionOfAppliedTask(new SimplePeakListAppliedMethod(getTaskDescription(), parameters));
    // Get parameters.
    final boolean evalutateFoldChange = parameters.getParameter(PeakComparisonRowFilterParameters.FOLD_CHANGE).getValue();
    final boolean evalutatePPMdiff = parameters.getParameter(PeakComparisonRowFilterParameters.MZ_PPM_DIFF).getValue();
    final boolean evalutateRTdiff = parameters.getParameter(PeakComparisonRowFilterParameters.RT_DIFF).getValue();
    final int columnIndex1 = parameters.getParameter(PeakComparisonRowFilterParameters.COLUMN_INDEX_1).getValue();
    final int columnIndex2 = parameters.getParameter(PeakComparisonRowFilterParameters.COLUMN_INDEX_2).getValue();
    final Range<Double> foldChangeRange = parameters.getParameter(PeakComparisonRowFilterParameters.FOLD_CHANGE).getEmbeddedParameter().getValue();
    final Range<Double> ppmDiffRange = parameters.getParameter(PeakComparisonRowFilterParameters.FOLD_CHANGE).getEmbeddedParameter().getValue();
    final Range<Double> rtDiffRange = parameters.getParameter(PeakComparisonRowFilterParameters.FOLD_CHANGE).getEmbeddedParameter().getValue();
    // Setup variables
    final PeakListRow[] rows = peakList.getRows();
    RawDataFile rawDataFile1;
    RawDataFile rawDataFile2;
    Feature peak1;
    Feature peak2;
    totalRows = rows.length;
    final RawDataFile[] rawDataFiles = peakList.getRawDataFiles();
    boolean allCriteriaMatched = true;
    // doesn't exist.
    if (columnIndex1 > rawDataFiles.length) {
        setErrorMessage("Column 1 set too large.");
        setStatus(TaskStatus.ERROR);
        return null;
    }
    if (columnIndex2 > rawDataFiles.length) {
        setErrorMessage("Column 2 set too large.");
        setStatus(TaskStatus.ERROR);
        return null;
    }
    // Loop over the rows & filter
    for (processedRows = 0; !isCanceled() && processedRows < totalRows; processedRows++) {
        if (isCanceled())
            return null;
        allCriteriaMatched = true;
        // Default value in case of null peak
        double peak1Area = 1.0;
        double peak2Area = 1.0;
        double peak1MZ = -1.0;
        double peak2MZ = -1.0;
        double peak1RT = -1.0;
        double peak2RT = -1.0;
        double foldChange = 0.0;
        double ppmDiff = 0.0;
        double rtDiff = 0.0;
        final PeakListRow row = rows[processedRows];
        rawDataFile1 = rawDataFiles[columnIndex1];
        rawDataFile2 = rawDataFiles[columnIndex2];
        peak1 = row.getPeak(rawDataFile1);
        peak2 = row.getPeak(rawDataFile2);
        if (peak1 != null) {
            peak1Area = peak1.getArea();
            peak1MZ = peak1.getMZ();
            peak1RT = peak1.getRT();
        }
        if (peak2 != null) {
            peak2Area = peak2.getArea();
            peak2MZ = peak2.getMZ();
            peak2RT = peak2.getRT();
        }
        // Fold change criteria checking.
        if (evalutateFoldChange) {
            foldChange = Math.log(peak1Area / peak2Area) / Math.log(2);
            if (!foldChangeRange.contains(foldChange))
                allCriteriaMatched = false;
            // PPM difference evaluation
            if (evalutatePPMdiff) {
                ppmDiff = (peak1MZ - peak2MZ) / peak1MZ * 1E6;
                if (!ppmDiffRange.contains(ppmDiff))
                    allCriteriaMatched = false;
            }
            // RT difference evaluation
            if (evalutateRTdiff) {
                rtDiff = peak1RT - peak2RT;
                if (!rtDiffRange.contains(rtDiff))
                    allCriteriaMatched = false;
            }
        }
        // Good row?
        if (allCriteriaMatched)
            newPeakList.addRow(copyPeakRow(row));
    }
    return newPeakList;
}

Example 38 with PeakListRow

use of net.sf.mzmine.datamodel.PeakListRow in project mzmine2 by mzmine.

the class DuplicateFilterTask method filterDuplicatePeakListRows.

/**
 * Filter our duplicate feature list rows.
 *
 * @param origPeakList the original feature list.
 * @param suffix the suffix to apply to the new feature list name.
 * @param mzTolerance m/z tolerance.
 * @param rtTolerance RT tolerance.
 * @param requireSameId must duplicate peaks have the same identities?
 * @return the filtered feature list.
 */
private PeakList filterDuplicatePeakListRows(final PeakList origPeakList, final String suffix, final MZTolerance mzTolerance, final RTTolerance rtTolerance, final boolean requireSameId, FilterMode mode) {
    final PeakListRow[] peakListRows = origPeakList.getRows();
    final int rowCount = peakListRows.length;
    RawDataFile[] rawFiles = origPeakList.getRawDataFiles();
    // Create the new feature list.
    final PeakList newPeakList = new SimplePeakList(origPeakList + " " + suffix, origPeakList.getRawDataFiles());
    // sort rows
    if (mode.equals(FilterMode.OLD_AVERAGE))
        Arrays.sort(peakListRows, new PeakListRowSorter(SortingProperty.Area, SortingDirection.Descending));
    else
        Arrays.sort(peakListRows, new PeakListRowSorter(SortingProperty.ID, SortingDirection.Ascending));
    // filter by average mz and rt
    boolean filterByAvgRTMZ = !mode.equals(FilterMode.SINGLE_FEATURE);
    // Loop through all feature list rows
    processedRows = 0;
    int n = 0;
    totalRows = rowCount;
    for (int firstRowIndex = 0; !isCanceled() && firstRowIndex < rowCount; firstRowIndex++) {
        final PeakListRow mainRow = peakListRows[firstRowIndex];
        if (mainRow != null) {
            // copy first row
            PeakListRow firstRow = copyRow(mainRow);
            for (int secondRowIndex = firstRowIndex + 1; !isCanceled() && secondRowIndex < rowCount; secondRowIndex++) {
                final PeakListRow secondRow = peakListRows[secondRowIndex];
                if (secondRow != null) {
                    // Compare identifications
                    final boolean sameID = !requireSameId || PeakUtils.compareIdentities(firstRow, secondRow);
                    boolean sameMZRT = // average or single feature
                    filterByAvgRTMZ ? checkSameAverageRTMZ(firstRow, secondRow, mzTolerance, rtTolerance) : checkSameSingleFeatureRTMZ(rawFiles, firstRow, secondRow, mzTolerance, rtTolerance);
                    // Duplicate peaks?
                    if (sameID && sameMZRT) {
                        // create consensus row in new filter
                        if (!mode.equals(FilterMode.OLD_AVERAGE)) {
                            // copy all detected features of row2 into row1
                            // to exchange gap-filled against detected features
                            createConsensusFirstRow(rawFiles, firstRow, secondRow);
                        }
                        // second row deleted
                        n++;
                        peakListRows[secondRowIndex] = null;
                    }
                }
            }
            // add to new list
            newPeakList.addRow(firstRow);
        }
        processedRows++;
    }
    // finalize
    if (!isCanceled()) {
        // Load previous applied methods.
        for (final PeakListAppliedMethod method : origPeakList.getAppliedMethods()) {
            newPeakList.addDescriptionOfAppliedTask(method);
        }
        // Add task description to peakList
        newPeakList.addDescriptionOfAppliedTask(new SimplePeakListAppliedMethod("Duplicate feature list rows filter", parameters));
        LOG.info("Removed " + n + " duplicate rows");
    }
    return newPeakList;
}

Example 39 with PeakListRow

use of net.sf.mzmine.datamodel.PeakListRow in project mzmine2 by mzmine.

the class DuplicateFilterTask method copyRow.

public PeakListRow copyRow(PeakListRow row) {
    // Copy the feature list row.
    final PeakListRow newRow = new SimplePeakListRow(row.getID());
    PeakUtils.copyPeakListRowProperties(row, newRow);
    // Copy the peaks.
    for (final Feature peak : row.getPeaks()) {
        newRow.addPeak(peak.getDataFile(), copyPeak(peak));
    }
    return newRow;
}

Example 40 with PeakListRow

use of net.sf.mzmine.datamodel.PeakListRow in project mzmine2 by mzmine.

the class CameraSearchTask method addPseudoSpectraIdentities.

/**
 * Add pseudo-spectra identities.
 *
 * @param peaks peaks to annotate with identities.
 * @param spectraExp the pseudo-spectra ids vector.
 * @param isotopeExp the isotopes vector.
 */
private void addPseudoSpectraIdentities(final Feature[] peaks, final int[] spectra, final String[] isotopes, final String[] adducts) {
    // Add identities for each peak.
    int peakIndex = 0;
    for (final Feature peak : peaks) {
        // Create pseudo-spectrum identity
        final SimplePeakIdentity identity = new SimplePeakIdentity("Pseudo-spectrum #" + String.format("%03d", spectra[peakIndex]));
        identity.setPropertyValue(PeakIdentity.PROPERTY_METHOD, "Bioconductor CAMERA");
        // Add isotope info, if any.
        if (isotopes != null) {
            final String isotope = isotopes[peakIndex].trim();
            if (isotope.length() > 0) {
                // Parse the isotope pattern.
                final Matcher matcher = ISOTOPE_PATTERN.matcher(isotope);
                if (matcher.matches()) {
                    // identity.setPropertyValue("Isotope", matcher.group(1));
                    identity.setPropertyValue("Isotope", isotope);
                } else {
                    LOG.warning("Irregular isotope value: " + isotope);
                }
            }
        }
        if (adducts != null) {
            final String adduct = adducts[peakIndex].trim();
            if (adduct.length() > 0)
                identity.setPropertyValue("Adduct", adduct);
        }
        // Add identity to peak's row.
        PeakListRow row = peakList.getPeakRow(peak);
        for (PeakIdentity peakIdentity : row.getPeakIdentities()) row.removePeakIdentity(peakIdentity);
        peakList.getPeakRow(peak).addPeakIdentity(identity, true);
        peakIndex++;
    }
}