Single-tailed hypothesis testing in MWU

git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@5533 348d0f76-0448-11de-a6fe-93d51630548a

java/src/org/broadinstitute/sting/utils/MannWhitneyU.java

@@ -41,8 +41,22 @@ public class MannWhitneyU {
     }
 
     /**
-     * temporary method that will be generalized. Runs the standard two-sided test,
-     * returns the u and p values.
+     * Runs the one-sided test under the hypothesis that the data in set "lessThanOther" stochastically
+     * dominates the other set
+     * @param lessThanOther - either Set1 or Set2
+     * @return - u-based z-approximation, and p-value associated with the test (p-value is exact for small n,m)
+     */
+    public Pair<Double,Double> runOneSidedTest(USet lessThanOther) {
+        long u = calculateOneSidedU(observations, lessThanOther);
+        int n = lessThanOther == USet.SET1 ? sizeSet1 : sizeSet2;
+        int m = lessThanOther == USet.SET1 ? sizeSet2 : sizeSet1;
+        double pval = calculateP(n,m,u,false);
+        return new Pair<Double,Double>(getZApprox(n,m,u),pval);
+    }
+
+    /**
+     * Runs the standard two-sided test,
+     * returns the u-based z-approximate and p values.
      * @Returns a pair holding the u and p-value.
      */
     public Pair<Double,Double> runTwoSidedTest() {
@@ -185,6 +199,27 @@ public class MannWhitneyU {
         return uSet1DomSet2 < uSet2DomSet1 ? new Pair<Long,USet>(uSet1DomSet2,USet.SET1) : new Pair<Long,USet>(uSet2DomSet1,USet.SET2);
     }
 
+    /**
+     * Calculates the U-statistic associated with the one-sided hypothesis that "dominator" stochastically dominates
+     * the other U-set
+     * @param observed - the observed data points, tagged by each set
+     * @param dominator - the set that is hypothesized to be stochastically dominating
+     * @return the u-statistic associated with the hypothesis
+     */
+    public static long calculateOneSidedU(TreeSet<Pair<Number,USet>> observed,USet dominator) {
+        long domninatorBeforeOther = 0l;
+        int domSeenSoFar = 0;
+        for ( Pair<Number,USet> dataPoint : observed ) {
+            if ( dataPoint.second == dominator ) {
+                ++domSeenSoFar;
+            } else {
+                domninatorBeforeOther += domSeenSoFar;
+            }
+        }
+
+        return domninatorBeforeOther;
+    }
+
     /**
      * The Mann-Whitney U statistic follows a recursive equation (that enumerates the proportion of possible
      * binary strings of "n" zeros, and "m" ones, where a one precedes a zero "u" times). This accessor
@@ -219,6 +254,16 @@ public class MannWhitneyU {
         return (((double)n)/(n+m))*cpr(n-1,m,u-m) + (((double)m)/(n+m))*cpr(n,m-1,u);
     }
 
+    /**
+     * hook into the data tree, for testing purposes only
+     * @return  observations
+     * @deprecated - only for testing
+     */
+    @Deprecated
+    public TreeSet<Pair<Number,USet>> getObservations() {
+        return observations;
+    }
+
     /**
      * A comparator class which uses dithering on tie-breaking to ensure that the internal treeset drops no values
      * and to ensure that rank ties are broken at random.

java/test/org/broadinstitute/sting/oneoffprojects/walkers/RegionalAssociationUnitTest.java

@@ -2,6 +2,7 @@ package org.broadinstitute.sting.oneoffprojects.walkers;
 
 import org.broadinstitute.sting.oneoffprojects.walkers.association.statistics.casecontrol.UStatistic;
 import org.broadinstitute.sting.oneoffprojects.walkers.association.statistics.casecontrol.ZStatistic;
+import org.broadinstitute.sting.utils.MannWhitneyU;
 import org.broadinstitute.sting.utils.MathUtils;
 import org.broadinstitute.sting.BaseTest;
 import org.broadinstitute.sting.oneoffprojects.walkers.association.AssociationTestRunner;
@@ -96,6 +97,27 @@ public class RegionalAssociationUnitTest extends BaseTest {
 
     }
 
+    @Test
+    private void testMWU() {
+        logger.warn("Testing MWU");
+        MannWhitneyU mwu = new MannWhitneyU();
+        mwu.add(0, MannWhitneyU.USet.SET1);
+        mwu.add(1,MannWhitneyU.USet.SET2);
+        mwu.add(2,MannWhitneyU.USet.SET2);
+        mwu.add(3,MannWhitneyU.USet.SET2);
+        mwu.add(4,MannWhitneyU.USet.SET2);
+        mwu.add(5,MannWhitneyU.USet.SET2);
+        mwu.add(6,MannWhitneyU.USet.SET1);
+        mwu.add(7,MannWhitneyU.USet.SET1);
+        mwu.add(8,MannWhitneyU.USet.SET1);
+        mwu.add(9,MannWhitneyU.USet.SET1);
+        mwu.add(10,MannWhitneyU.USet.SET1);
+        mwu.add(11,MannWhitneyU.USet.SET2);
+        Assert.assertEquals(MannWhitneyU.calculateOneSidedU(mwu.getObservations(), MannWhitneyU.USet.SET1),11l);
+        Assert.assertEquals(MannWhitneyU.calculateOneSidedU(mwu.getObservations(),MannWhitneyU.USet.SET2),25l);
+
+    }
+
 
     private class TTest extends TStatistic {
         Map<Cohort,Collection<Number>> toTest = new HashMap<Cohort,Collection<Number>>(2);