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Added Bustard vs. Four-prob percent bases consistent output. 

git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@710 348d0f76-0448-11de-a6fe-93d51630548a
This commit is contained in:
kiran 2009-05-14 18:01:41 +00:00
parent 7a1f85ff86
commit 3761c0900b
1 changed files with 27 additions and 3 deletions
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30
java/src/org/broadinstitute/sting/secondarybase/AnnotateSecondaryBase.java
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@ -2,6 +2,7 @@ package org.broadinstitute.sting.secondarybase;
import org.broadinstitute.sting.utils.cmdLine.CommandLineProgram;
import org.broadinstitute.sting.utils.cmdLine.Argument;
import org.broadinstitute.sting.utils.BaseUtils;
import org.broadinstitute.sting.secondarybase.BasecallingReadModel;
import java.io.File;
@ -38,37 +39,60 @@ public class AnnotateSecondaryBase extends CommandLineProgram {
if (SAM_IN == null || !SAM_IN.exists()) {
// Iterate through raw Firecrest data and store the first N reads up to TRAINING_LIMIT
System.out.println("Training from the first " + TRAINING_LIMIT + " reads in the raw data.");
System.out.println("Loading training set from the first " + TRAINING_LIMIT + " reads in the raw data...");
trainingSet.loadFirstNUnambiguousReadsTrainingSet();
} else {
// Find alignments with zero mismatches and store them until we've picked up TRAINING_LIMIT alignments
System.out.println("Training from the first " + TRAINING_LIMIT + " perfect reads in the aligned data.");
System.out.println("Loading training set from the first " + TRAINING_LIMIT + " perfect reads in the aligned data...");
trainingSet.loadPreAlignedTrainingSet(SAM_IN, REFERENCE);
}
// Iterate through the stored training data and add the info to the BasecallingReadModel
System.out.println("Applying training set...");
BasecallingReadModel model = new BasecallingReadModel(CYCLE_END - CYCLE_BEGIN + 1, CONTEXT);
model.train(trainingSet);
// Call bases and write results
System.out.println("Calling bases and writing SAM file...");
SAMFileHeader sfh = new SAMFileHeader();
SAMFileWriter sfw = new SAMFileWriterFactory().makeSAMOrBAMWriter(sfh, false, SAM_OUT);
IlluminaParser iparser = new IlluminaParser(BUSTARD_DIR, LANE, CYCLE_BEGIN, CYCLE_END);
int basesConsistent = 0, basesTotal = 0;
RawRead rr;
while ((rr = iparser.next()) != null) {
FourProbRead fpr = model.call(rr);
SAMRecord sr = constructSAMRecord(rr, fpr, sfh, RUN_BARCODE);
sfw.addAlignment(sr);
for (int cycle = 0; cycle < fpr.size(); cycle++) {
int rawBaseIndex = BaseUtils.simpleBaseToBaseIndex((char) rr.getSequence()[cycle]);
int fpBaseIndex = fpr.get(cycle).indexAtRank(0);
if (rawBaseIndex >= 0 && fpBaseIndex >= 0) {
basesTotal++;
if (rawBaseIndex == fpBaseIndex) {
basesConsistent++;
}
}
}
if (basesTotal % 10000 == 0 && basesTotal > 0) {
System.out.printf("%% bases consistent: %d/%d (%4.4f)\r", basesConsistent, basesTotal, ((double) basesConsistent)/((double) basesTotal));
}
}
iparser.close();
sfw.close();
return 0;
System.out.println("Done.");
return 0;
}
private SAMRecord constructSAMRecord(RawRead rr, FourProbRead fpr, SAMFileHeader sfh, String runBarcode) {