Examples with Chromosome uk.ac.babraham.SeqMonk.DataTypes.Genome.Chromosome used on opensource projects

Example 11 with Chromosome

use of uk.ac.babraham.SeqMonk.DataTypes.Genome.Chromosome in project SeqMonk by s-andrews.

the class DataSet method finalise.

/**
 * This call optimises the data structure from a flexible structure
 * which can accept more data, to a fixed structure optimised for
 * size and speed of access.  If required it can also cache the data
 * to disk.
 *
 * This call should only be made by DataParsers who know that no
 * more data will be added.
 */
public synchronized void finalise() {
    if (isFinalised)
        return;
    // To make querying the data more efficient we're going to convert
    // all of the vectors in our data structure into SequenceRead arrays
    // which are sorted by start position.  This means that subsequent
    // access will be a lot more efficient.
    Enumeration<Chromosome> e = readData.keys();
    chromosomesStillToFinalise = new ThreadSafeIntCounter();
    while (e.hasMoreElements()) {
        while (chromosomesStillToFinalise.value() >= MAX_CONCURRENT_FINALISE) {
            try {
                Thread.sleep(20);
            } catch (InterruptedException ex) {
            }
        }
        Chromosome c = e.nextElement();
        chromosomesStillToFinalise.increment();
        readData.get(c).finalise();
    }
    while (chromosomesStillToFinalise.value() > 0) {
        try {
            Thread.sleep(20);
        } catch (InterruptedException ex) {
        }
    }
    isFinalised = true;
}

Example 12 with Chromosome

use of uk.ac.babraham.SeqMonk.DataTypes.Genome.Chromosome in project SeqMonk by s-andrews.

the class DataSet method run.

/* (non-Javadoc)
	 * @see java.lang.Runnable#run()
	 */
public void run() {
    // We need to delete any cache files we're still holding
    Enumeration<Chromosome> e = readData.keys();
    while (e.hasMoreElements()) {
        Chromosome c = e.nextElement();
        File f = readData.get(c).readsWithCountsTempFile;
        if (f != null) {
            if (!f.delete())
                System.err.println("Failed to delete cache file " + f.getAbsolutePath());
        }
    }
}

Example 13 with Chromosome

use of uk.ac.babraham.SeqMonk.DataTypes.Genome.Chromosome in project SeqMonk by s-andrews.

the class PairedDataSet method finalise.

/**
 * This call optimises the data structure from a flexible structure
 * which can accept more data, to a fixed structure optimised for
 * size and speed of access.  If required it can also cache the data
 * to disk.
 *
 * This call should only be made by DataParsers who know that no
 * more data will be added.
 */
public synchronized void finalise() {
    if (isFinalised)
        return;
    // To make querying the data more efficient we're going to convert
    // all of the vectors in our data structure into SequenceRead arrays
    // which are sorted by start position.  This means that subsequent
    // access will be a lot more efficient.
    long finaliseStartTime = System.currentTimeMillis();
    Enumeration<Chromosome> e = readData.keys();
    chromosomesStillToFinalise = new ThreadSafeIntCounter();
    while (e.hasMoreElements()) {
        while (chromosomesStillToFinalise.value() >= MAX_CONCURRENT_FINALISE) {
            try {
                Thread.sleep(20);
            } catch (InterruptedException ex) {
            }
        }
        Chromosome c = e.nextElement();
        chromosomesStillToFinalise.increment();
        readData.get(c).finalise();
    }
    while (chromosomesStillToFinalise.value() > 0) {
        try {
            Thread.sleep(20);
        } catch (InterruptedException ex) {
        }
    }
    isFinalised = true;
    long finaliseEndTime = System.currentTimeMillis();
    // Finally, now that we've sent all of the correct data up to the superclass
    // we can let that finalise itself.
    long superSubEndTime = System.currentTimeMillis();
    super.finalise();
    long superFinaliseEndTime = System.currentTimeMillis();
    System.err.println("HiC finalise=" + ((finaliseEndTime - finaliseStartTime) / 1000d) + " super submit=" + ((superSubEndTime - finaliseEndTime) / 1000d) + " super finalise=" + ((superFinaliseEndTime - superSubEndTime) / 1000d));
}

Example 14 with Chromosome

use of uk.ac.babraham.SeqMonk.DataTypes.Genome.Chromosome in project SeqMonk by s-andrews.

the class DistanceToFeatureQuantitation method run.

/* (non-Javadoc)
	 * @see java.lang.Runnable#run()
	 */
public void run() {
    Probe[] probes = application.dataCollection().probeSet().getAllProbes();
    Feature[] features = null;
    Chromosome lastChromsome = null;
    int lastIndex = 0;
    for (int p = 0; p < probes.length; p++) {
        // See if we need to quit
        if (cancel) {
            progressCancelled();
            return;
        }
        // See if we're on the same chromosome as last time
        if (lastChromsome == null || probes[p].chromosome() != lastChromsome) {
            lastChromsome = probes[p].chromosome();
            features = application.dataCollection().genome().annotationCollection().getFeaturesForType(lastChromsome, selectedFeature);
            System.err.println("Found " + features.length + " features of type " + selectedFeature + " on chr " + lastChromsome);
            lastIndex = 0;
        }
        int closestDistance = lastChromsome.length();
        int bestIndex = lastIndex;
        for (int i = lastIndex; i >= 0 && i < features.length; i--) {
            int thisDistance = getDistanceToFeature(probes[p], features[i]);
            if (thisDistance < closestDistance) {
                closestDistance = thisDistance;
                bestIndex = i;
            }
            if (features[i].location().end() < probes[p].start())
                break;
        }
        // Now we go forward until we hit the end or we're after the end of the last best feature
        for (int i = lastIndex + 1; i < features.length; i++) {
            int thisDistance = getDistanceToFeature(probes[p], features[i]);
            if (thisDistance < closestDistance) {
                closestDistance = thisDistance;
                bestIndex = i;
            }
            if (features[i].location().start() > Math.max(probes[p].end(), features[lastIndex].location().end()))
                break;
        }
        lastIndex = bestIndex;
        for (int d = 0; d < data.length; d++) {
            if (logTransform.isSelected()) {
                data[d].setValueForProbe(probes[p], (float) (Math.log(closestDistance + 1) / log2));
            } else {
                data[d].setValueForProbe(probes[p], closestDistance);
            }
        }
    }
    quantitatonComplete();
}

Example 15 with Chromosome

use of uk.ac.babraham.SeqMonk.DataTypes.Genome.Chromosome in project SeqMonk by s-andrews.

the class HiCPCADomainQuantitation method run.

/* (non-Javadoc)
	 * @see java.lang.Runnable#run()
	 */
public void run() {
    // We're going to go through the probes one chromosome at a time so we
    // can reduce the complexity we have to deal with
    Chromosome[] chromosomes = application.dataCollection().genome().getAllChromosomes();
    for (int c = 0; c < chromosomes.length; c++) {
        if (cancel) {
            progressCancelled();
            return;
        }
        currentChromosome = chromosomes[c];
        Probe[] probes = application.dataCollection().probeSet().getProbesForChromosome(chromosomes[c]);
        if (probes.length < 5) {
            progressWarningReceived(new SeqMonkException("Too few probes on chromosome " + currentChromosome.name() + " - assigning zero to everything"));
            // It's not worth trying to find domains
            for (int d = 0; d < data.length; d++) {
                for (int p = 0; p < probes.length; p++) {
                    ((DataStore) data[d]).setValueForProbe(probes[p], 0f);
                }
            }
            continue;
        }
        ProbeList thisChrProbes = new ProbeList(application.dataCollection().probeSet(), chromosomes[c].name(), "", null);
        for (int p = 0; p < probes.length; p++) {
            thisChrProbes.addProbe(probes[p], 0f);
        }
        for (int d = 0; d < data.length; d++) {
            if (cancel) {
                progressCancelled();
                return;
            }
            currentStore = data[d];
            current = (d * chromosomes.length) + c;
            total = chromosomes.length * data.length;
            progressUpdated("Processing chromosome " + chromosomes[c].name() + " for " + data[d].name(), current, total);
            HeatmapMatrix matrix = new HeatmapMatrix(data[d], new ProbeList[] { thisChrProbes }, application.dataCollection().genome(), optionsPanel.minDistance(), optionsPanel.maxDistance(), optionsPanel.minStrength(), optionsPanel.maxSignificance(), optionsPanel.minAbsolute(), optionsPanel.correctLinkage());
            matrix.addProgressListener(this);
            wait = true;
            matrix.startCalculating();
            while (wait) {
                try {
                    Thread.sleep(100);
                } catch (InterruptedException e) {
                }
            }
            if (cancel) {
                progressCancelled();
                return;
            }
            if (matrix.filteredInteractions().length < 10) {
                progressWarningReceived(new SeqMonkException("Too few interactions on chromosome " + currentChromosome.name() + " for " + data[d].name() + " - assigning zero to everything"));
                // not going to get a sensible answer anyway.
                for (int p = 0; p < probes.length; p++) {
                    ((DataStore) data[d]).setValueForProbe(probes[p], 0f);
                }
                continue;
            }
            InteractionClusterMatrix clusterMatrix = new InteractionClusterMatrix(matrix.filteredInteractions(), probes.length);
            clusterMatrix.addListener(this);
            wait = true;
            clusterMatrix.startCorrelating();
            while (wait) {
                try {
                    Thread.sleep(100);
                } catch (InterruptedException e) {
                }
            }
            float[][] correlationMatrix = clusterMatrix.correlationMatix();
            // Annoyingly the PCA needs a double [][]
            double[][] correlationMatrixDouble = new double[correlationMatrix.length][];
            for (int i = 0; i < correlationMatrix.length; i++) {
                double[] db = new double[correlationMatrix[i].length];
                for (int j = 0; j < db.length; j++) {
                    db[j] = correlationMatrix[i][j];
                }
                correlationMatrixDouble[i] = db;
            }
            // Now we can calculate the PCA values from the correlation matrix
            PCA pca = new PCA(correlationMatrixDouble);
            pca.addProgressListener(this);
            wait = true;
            pca.startCalculating();
            while (wait) {
                try {
                    Thread.sleep(100);
                } catch (InterruptedException e) {
                }
            }
            double[] extractedEigenValues = pca.extractedEigenValues();
            // for these probes
            for (int p = 0; p < probes.length; p++) {
                ((DataStore) data[d]).setValueForProbe(probes[p], (float) extractedEigenValues[p]);
            }
        }
        thisChrProbes.delete();
    }
    quantitatonComplete();
}