Java Code Examples for gnu.trove.list.array.TDoubleArrayList#get()

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Example 1
Source File: InteractionAnalysisDetermineDirection.java    From systemsgenetics with GNU General Public License v3.0 4 votes vote down vote up 
public EffectDiffResult calculateEffectDifference(String snpId, String geneName, String covariateName, Allele assessedAllele, double fractionOfSamplesPerGroup) {

		if (!variantIdMap.containsKey(snpId)) {
			return new EffectDiffResult(Double.NaN, Double.NaN);
		}

		if (!expressionData.containsRow(geneName)) {
			return new EffectDiffResult(Double.NaN, Double.NaN);
		}

		if (!covariatesData.containsRow(covariateName)) {
			return new EffectDiffResult(Double.NaN, Double.NaN);
		}

		if (fractionOfSamplesPerGroup <= 0 || fractionOfSamplesPerGroup >= 1) {
			throw new RuntimeException("Fraction must be between 0 and 1");
		}

		GeneticVariant variant = variantIdMap.get(snpId);
		Alleles variantAlleles = variant.getVariantAlleles();

		if (!variantAlleles.contains(assessedAllele)) {
			return new EffectDiffResult(Double.NaN, Double.NaN);
		}

		if (variantAlleles.getAlleleCount() != 2) {
			return new EffectDiffResult(Double.NaN, Double.NaN);
		}

		float[] dosagesAll = variant.getSampleDosages();
		String[] genotypedSamples = genotypeData.getSampleNames();

		LinkedHashSet<String> includedGenotypedSamples = new LinkedHashSet<>();
		TDoubleArrayList dosages = new TDoubleArrayList(dosagesAll.length);

		for (int i = 0; i < dosagesAll.length; ++i) {
			if (dosagesAll[i] >= 0 && gte.containsKey(genotypedSamples[i])) {
				includedGenotypedSamples.add(genotypedSamples[i]);
				dosages.add(dosagesAll[i]);
			}
		}

		System.out.println("Included samples: " + includedGenotypedSamples.size());

		double[] expressionLevels = new double[includedGenotypedSamples.size()];
		double[] covariateLevels = new double[includedGenotypedSamples.size()];

		int s = 0;
		for (String genotypeSample : includedGenotypedSamples) {
			expressionLevels[s] = expressionData.getElement(geneName, gte.get(genotypeSample));
			covariateLevels[s] = covariatesData.getElement(covariateName, gte.get(genotypeSample));
			++s;
		}

		if (assessedAllele != variantAlleles.get(0)) {
			for (int i = 0; i < dosages.size(); ++i) {
				dosages.setQuick(i, dosages.getQuick(i) * -1);
			}
		}

		double[] covariateRanks = COV_RANKER.rank(covariateLevels);

		int samplesPerGroup = (int) Math.floor(covariateRanks.length * fractionOfSamplesPerGroup);

		System.out.println("Samples per group: " + samplesPerGroup);

		double[] dosagesLow = new double[samplesPerGroup];
		double[] expressionLow = new double[samplesPerGroup];

		double[] dosagesHigh = new double[samplesPerGroup];
		double[] expressionHigh = new double[samplesPerGroup];

		for (int i = 0; i < samplesPerGroup; ++i) {
			dosagesLow[i] = dosages.get((int) covariateRanks[i]);
			expressionLow[i] = expressionLevels[(int) covariateRanks[i]];
			dosagesHigh[i] = dosages.get((int) covariateRanks[covariateRanks.length - 1 - i]);
			expressionHigh[i] = expressionLevels[(int) covariateRanks[covariateRanks.length - 1 - i]];
		}

		double rhoLow = spearmanCalculator.correlation(dosagesLow, expressionLow);
		double rhoHigh = spearmanCalculator.correlation(dosagesHigh, expressionHigh);

		System.out.println("rho low:" + rhoLow);
		System.out.println("rho high:" + rhoHigh);

		return new EffectDiffResult(rhoLow, rhoHigh);

	}