analysis: compute OR from logistic regression coefficient, #126

opencb · Jun 9, 2017 · 3e6393d · 3e6393d
1 parent 01f7ead
commit 3e6393d
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Showing 2 changed files with 6 additions and 5 deletions.
diff --git a/...sis/src/main/java/org/opencb/hpg/bigdata/analysis/variant/LogisticRegressionAnalysis.java b/...sis/src/main/java/org/opencb/hpg/bigdata/analysis/variant/LogisticRegressionAnalysis.java
@@ -1,12 +1,14 @@
 package org.opencb.hpg.bigdata.analysis.variant;
 
+import org.apache.spark.ml.classification.BinaryLogisticRegressionSummary;
 import org.apache.spark.ml.classification.LogisticRegression;
 import org.apache.spark.ml.classification.LogisticRegressionModel;
 import org.apache.spark.ml.classification.LogisticRegressionTrainingSummary;
 import org.apache.spark.mllib.linalg.Vectors;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.SparkSession;
+import org.apache.spark.sql.functions;
 
 /**
  * Created by jtarraga on 30/05/17.
@@ -26,13 +28,13 @@ public void execute() {
         // print the coefficients and intercept for linear regression
         System.out.println("Coefficients: "
                 + lrModel.coefficients() + " Intercept: " + lrModel.intercept());
+        System.out.println("OR (for coeff.) = " + Math.exp(lrModel.coefficients().apply(1)));
 
         // summarize the model over the training set and print out some metrics
         LogisticRegressionTrainingSummary trainingSummary = lrModel.summary();
         System.out.println("numIterations: " + trainingSummary.totalIterations());
         System.out.println("objectiveHistory: " + Vectors.dense(trainingSummary.objectiveHistory()));
 
-/*
         // obtain the loss per iteration
         double[] objectiveHistory = trainingSummary.objectiveHistory();
         for (double lossPerIteration : objectiveHistory) {
@@ -58,7 +60,6 @@ public void execute() {
         double bestThreshold = fMeasure.where(fMeasure.col("F-Measure").equalTo(maxFMeasure))
                 .select("threshold").head().getDouble(0);
         lrModel.setThreshold(bestThreshold);
-*/
     }
 
     public LogisticRegressionAnalysis(String datasetName, String studyName, String depVarName, String indepVarName,

diff --git a/hpg-bigdata-app/src/test/java/org/opencb/hpg/bigdata/app/cli/local/VariantAssocCLITest.java b/hpg-bigdata-app/src/test/java/org/opencb/hpg/bigdata/app/cli/local/VariantAssocCLITest.java
@@ -31,9 +31,9 @@ public void assoc() {
             commandLine.append(" -i ").append(inPath);
             commandLine.append(" -o ").append(outPath);
             commandLine.append(" --dataset noname");
-            //commandLine.append(" --logistic");
-            commandLine.append(" --linear");
-            commandLine.append(" --pheno Age:s");
+            commandLine.append(" --logistic");
+            //commandLine.append(" --linear");
+            //commandLine.append(" --pheno Age:s");
 
             VariantQueryCLITest.execute(commandLine.toString());
         } catch (Exception e) {