PCC.java Source code

Introduction

Here is the source code for PCC.java

Source

/*
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import com.google.common.collect.ArrayListMultimap;
import com.google.common.collect.Multimap;
import java.io.BufferedReader;
import java.io.BufferedWriter;
import java.io.FileReader;
import java.io.FileWriter;
import java.io.IOException;
import java.util.ArrayList;
import org.apache.commons.math3.distribution.TDistribution;
import org.apache.commons.math3.stat.correlation.PearsonsCorrelation;

/**
 *
 * @author ajha
 * @date created 24-May-2017
 * 
 * javac -cp ".:guava-19.0.jar:commons-math3-3.6.jar" PCC.java
 * java -cp ".:guava-19.0.jar:commons-math3-3.6.jar:" PCC test_file_for_cor.txt outfile.txt
 *
 */
public class PCC {

    /**
     * @param args the command line arguments
     * @throws java.io.IOException
     */

    public static void main(String[] args) throws IOException {
        // TODO code application logic here

        PearsonsCorrelation corel = new PearsonsCorrelation();
        PCC method = new PCC();
        ArrayList<String> name = new ArrayList<>();
        Multimap<String, String> genes = ArrayListMultimap.create();
        BufferedWriter bw = new BufferedWriter(new FileWriter(args[1]));
        BufferedReader br = new BufferedReader(new FileReader(args[0]));
        String str;
        while ((str = br.readLine()) != null) {
            String[] a = str.split("\t");
            name.add(a[0]);
            for (int i = 1; i < a.length; i++) {
                genes.put(a[0], a[i]);
            }
        }
        for (String key : genes.keySet()) {
            double[] first = new double[genes.get(key).size()];
            int element1 = 0;
            for (String value : genes.get(key)) {
                double d = Double.parseDouble(value);
                first[element1] = d;
                element1++;
            }
            for (String key1 : genes.keySet()) {
                if (!key.equals(key1)) {
                    double[] second = new double[genes.get(key1).size()];
                    int element2 = 0;
                    for (String value : genes.get(key1)) {
                        double d = Double.parseDouble(value);
                        second[element2] = d;
                        element2++;

                    }
                    double corrlation = corel.correlation(first, second);
                    if (corrlation > 0.5) {
                        bw.write(key + "\t" + key1 + "\t" + corrlation + "\t"
                                + method.pvalue(corrlation, second.length) + "\n");
                    }
                }
            }
        }
        br.close();
        bw.close();
    }

    public double pvalue(double corel, double n) {
        double t = Math.abs(corel * Math.sqrt((n - 2.0) / (1.0 - (corel * corel))));
        TDistribution tdist = new TDistribution(n - 2);
        double pvalue = 2 * (1.0 - tdist.cumulativeProbability(t));
        return pvalue;
    }

}