minor edits

bump to 1.4.6
harmjanwestra · Jul 23, 2019 · 33903c6 · 33903c6
1 parent 3125831
commit 33903c6
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Showing 3 changed files with 30 additions and 23 deletions.
diff --git a/eqtl-mapping-pipeline/pom.xml b/eqtl-mapping-pipeline/pom.xml
@@ -7,7 +7,7 @@
         <version>1.0.3-SNAPSHOT</version>
     </parent>
     <artifactId>eqtl-mapping-pipeline</artifactId>
-    <version>1.4.5-SNAPSHOT</version>
+    <version>1.4.6-SNAPSHOT</version>
     <packaging>jar</packaging>
     <modelVersion>4.0.0</modelVersion>
     <dependencies>

diff --git a/...e/src/main/java/eqtlmappingpipeline/conditionalanalysis/IterativeConditionalAnalysis.java b/...e/src/main/java/eqtlmappingpipeline/conditionalanalysis/IterativeConditionalAnalysis.java
@@ -6,6 +6,7 @@
 
 import eqtlmappingpipeline.metaqtl3.EQTLRegression;
 import eqtlmappingpipeline.metaqtl3.MetaQTL3;
+import eqtlmappingpipeline.normalization.Normalizer;
 import eqtlmappingpipeline.util.QTLFileMerger;
 import gnu.trove.set.hash.THashSet;
 import umcg.genetica.console.ConsoleGUIElems;
@@ -32,6 +33,15 @@ public class IterativeConditionalAnalysis extends MetaQTL3 {
 
 	public static void main(String[] args) {
 
+//		Normalizer z = new Normalizer();
+//		try {
+//			z.rank("D:\\Sync\\SyncThing\\Data\\Ref\\geuvadis\\rnaseq-EUR\\GD660.GeneQuantCount-EUR-CPM-TMM.txt.gz",
+//					"D:\\Sync\\SyncThing\\Data\\Ref\\geuvadis\\rnaseq-EUR\\GD660.GeneQuantCount-EUR-CPM-TMM-ranked.txt.gz");
+//		} catch (IOException e) {
+//			e.printStackTrace();
+//		}
+//		System.exit(0);
+
 		IterativeConditionalAnalysis s = new IterativeConditionalAnalysis();
 		try {
 			s.run("D:\\Sync\\SyncThing\\Data\\Ref\\geuvadis\\2019-07-18-GEUVADIS.xml", null,
@@ -46,14 +56,11 @@ public static void main(String[] args) {
 	private Integer startIter = 1;
 
 
-
 	public void run(String xmlSettingsFile, String texttoreplace, String texttoreplacewith,
 					String ingt, String inexp, String inexpplatform, String inexpannot, String gte,
 					String out, boolean cis, boolean trans, int perm, boolean textout, boolean binout, String snpfile, Integer threads) throws IOException, Exception {
 
 
-
-
 		initialize(xmlSettingsFile, texttoreplace, texttoreplacewith, ingt, inexp, inexpplatform, inexpannot, gte, out, cis, trans, perm, textout, binout, snpfile, threads, null, null, null, true, true, null, null, null);
 
 		double fdrthreshold = m_settings.fdrCutOff;
@@ -124,7 +131,7 @@ public void run(String xmlSettingsFile, String texttoreplace, String texttorepla
 //					 recalculate mean and SD
 					for (int i = 0; i < m_gg.length; i++) {
 //						if (!m_settings.performParametricAnalysis) {
-							m_gg[i].getExpressionData().rankAllExpressionData(m_settings.equalRankForTies);
+//						m_gg[i].getExpressionData().rankAllExpressionData(m_settings.equalRankForTies);
 //						}
 //						m_gg[i].getExpressionData().calcAndSubtractMean();
 //						m_gg[i].getExpressionData().calcMeanAndVariance();

diff --git a/eqtl-mapping-pipeline/src/main/java/eqtlmappingpipeline/metaqtl3/EQTLRegression.java b/eqtl-mapping-pipeline/src/main/java/eqtlmappingpipeline/metaqtl3/EQTLRegression.java
@@ -393,27 +393,27 @@ private void regressOutEQTLEffects() throws IOException {
 							}
 						}
 
-//						if (atLeastOnePCANotRegressedOut) {
-						//Provide information on the PCAs:
-						System.out.println("There is at least one PCA that has not been regressed out as it does not explain a lot of genetic variation!:");
-						for (int pca = 0; pca < nrSNPs; pca++) {
-							double[] x = dataMatrixPCScores[pca];
-							double correlation = JSci.maths.ArrayMath.correlation(x, y);
-							double r2 = correlation * correlation;
-							int pcaNr = pca + 1;
-							String snpsStronglyCorrelatedWithPCA = "";
-							for (int snp = 0; snp < nrSNPs; snp++) {
-								double correlationPCASNP = Math.abs(JSci.maths.ArrayMath.correlation(x, dataMatrix[snp]));
-								double r2PCASNP = correlationPCASNP * correlationPCASNP;
-								if (r2PCASNP > 0.1) {
-									snpsStronglyCorrelatedWithPCA += "\t" + snpsForProbe.get(snp).getName() + ", " + r2PCASNP;
+						if (atLeastOnePCANotRegressedOut) {
+							//Provide information on the PCAs:
+							System.out.println("There is at least one PCA that has not been regressed out as it does not explain a lot of genetic variation!:");
+							for (int pca = 0; pca < nrSNPs; pca++) {
+								double[] x = dataMatrixPCScores[pca];
+								double correlation = JSci.maths.ArrayMath.correlation(x, y);
+								double r2 = correlation * correlation;
+								int pcaNr = pca + 1;
+								String snpsStronglyCorrelatedWithPCA = "";
+								for (int snp = 0; snp < nrSNPs; snp++) {
+									double correlationPCASNP = Math.abs(JSci.maths.ArrayMath.correlation(x, dataMatrix[snp]));
+									double r2PCASNP = correlationPCASNP * correlationPCASNP;
+									if (r2PCASNP > 0.1) {
+										snpsStronglyCorrelatedWithPCA += "\t" + snpsForProbe.get(snp).getName() + ", " + r2PCASNP;
+									}
 								}
+								System.out.println(probes[p] + "\tPCA" + pcaNr + "\tExplainedVariance:\t" + PCA.getEigenValueVar(eigenValues, pca) + "\tEigenvalue:\t" + eigenValues[eigenValues.length - 1 - pca] + "\tPCATraitR2:\t" + r2 + "\tSNPsStronglyCorrelatedWithPCA:\t" + snpsStronglyCorrelatedWithPCA);
+								System.out.println("PC" + pcaNr + " correlation with phenotype: " + JSci.maths.ArrayMath.correlation(y, dataMatrix[pca]));
 							}
-							System.out.println(probes[p] + "\tPCA" + pcaNr + "\tExplainedVariance:\t" + PCA.getEigenValueVar(eigenValues, pca) + "\tEigenvalue:\t" + eigenValues[eigenValues.length - 1 - pca] + "\tPCATraitR2:\t" + r2 + "\tSNPsStronglyCorrelatedWithPCA:\t" + snpsStronglyCorrelatedWithPCA);
-							System.out.println("PC" + pcaNr + " correlation with phenotype: " + JSci.maths.ArrayMath.correlation(y, dataMatrix[pca]));
+							System.out.println("");
 						}
-						System.out.println("");
-//						}
 
 						//Process each PC, determine total amount of variation explained by the combination of PCs:
 						double propExplainedVarianceTrait = 0;