private void initializeVcfWriter() {
final List<String> inputNames = Arrays.asList(validation.getName());
// setup the header fields
Set<VCFHeaderLine> hInfo = new HashSet<VCFHeaderLine>();
hInfo.addAll(VCFUtils.getHeaderFields(getToolkit(), inputNames));
hInfo.add(
new VCFFilterHeaderLine(
"bootstrap",
"This site used for genotype bootstrapping with ProduceBeagleInputWalker"));
bootstrapVCFOutput.writeHeader(
new VCFHeader(hInfo, SampleUtils.getUniqueSamplesFromRods(getToolkit(), inputNames)));
}
public void initialize() {
samples =
SampleUtils.getSampleListWithVCFHeader(
getToolkit(), Arrays.asList(variantCollection.variants.getName()));
beagleWriter.print("marker alleleA alleleB");
for (String sample : samples)
beagleWriter.print(String.format(" %s %s %s", sample, sample, sample));
beagleWriter.println();
if (bootstrapVCFOutput != null) {
initializeVcfWriter();
}
if (VQSRCalibrationFile != null) {
VQSRCalibrator = VQSRCalibrationCurve.readFromFile(VQSRCalibrationFile);
logger.info("Read calibration curve");
VQSRCalibrator.printInfo(logger);
}
}
/**
* Subclasses of CommandLinePrograms can provide their own types of command-line arguments.
*
* @return A collection of type descriptors generating implementation-dependent placeholders.
*/
protected Collection<ArgumentTypeDescriptor> getArgumentTypeDescriptors() {
return Arrays.asList(
new VCFWriterArgumentTypeDescriptor(engine, System.out, argumentSources),
new SAMFileWriterArgumentTypeDescriptor(engine, System.out),
new OutputStreamArgumentTypeDescriptor(engine, System.out));
}
/**
* Converts the input VCF into a format accepted by the Beagle imputation/analysis program.
*
* <p>
*
* <h2>Input</h2>
*
* <p>A VCF with variants to convert to Beagle format
*
* <h2>Outputs</h2>
*
* <p>A single text file which can be fed to Beagle
*
* <p>Optional: A file with a list of markers
*
* <h2>Examples</h2>
*
* <pre>
* java -Xmx2g -jar dist/GenomeAnalysisTK.jar -L 20 \
* -R reffile.fasta -T ProduceBeagleInput \
* -V path_to_input_vcf/inputvcf.vcf -o path_to_beagle_output/beagle_output
* </pre>
*/
public class ProduceBeagleInputWalker extends RodWalker<Integer, Integer> {
@ArgumentCollection
protected StandardVariantContextInputArgumentCollection variantCollection =
new StandardVariantContextInputArgumentCollection();
@Hidden
@Input(
fullName = "validation",
shortName = "validation",
doc = "Validation VCF file",
required = false)
public RodBinding<VariantContext> validation;
@Output(doc = "File to which BEAGLE input should be written", required = true)
protected PrintStream beagleWriter = null;
@Hidden
@Output(
doc = "File to which BEAGLE markers should be written",
shortName = "markers",
fullName = "markers",
required = false)
protected PrintStream markers = null;
int markerCounter = 1;
@Hidden
@Input(doc = "VQSqual calibration file", shortName = "cc", required = false)
protected File VQSRCalibrationFile = null;
protected VQSRCalibrationCurve VQSRCalibrator = null;
@Hidden
@Argument(doc = "VQSqual key", shortName = "vqskey", required = false)
protected String VQSLOD_KEY = "VQSqual";
@Hidden
@Argument(
fullName = "inserted_nocall_rate",
shortName = "nc_rate",
doc = "Rate (0-1) at which genotype no-calls will be randomly inserted, for testing",
required = false)
public double insertedNoCallRate = 0;
@Hidden
@Argument(
fullName = "validation_genotype_ptrue",
shortName = "valp",
doc = "Flat probability to assign to validation genotypes. Will override GL field.",
required = false)
public double validationPrior = -1.0;
@Hidden
@Argument(
fullName = "validation_bootstrap",
shortName = "bs",
doc = "Proportion of records to be used in bootstrap set",
required = false)
public double bootstrap = 0.0;
@Hidden
@Argument(
fullName = "bootstrap_vcf",
shortName = "bvcf",
doc = "Output a VCF with the records used for bootstrapping filtered out",
required = false)
VCFWriter bootstrapVCFOutput = null;
/**
* If sample gender is known, this flag should be set to true to ensure that Beagle treats male
* Chr X properly.
*/
@Argument(
fullName = "checkIsMaleOnChrX",
shortName = "checkIsMaleOnChrX",
doc =
"Set to true when Beagle-ing chrX and want to ensure male samples don't have heterozygous calls.",
required = false)
public boolean CHECK_IS_MALE_ON_CHR_X = false;
@Hidden
@Argument(
fullName = "variant_genotype_ptrue",
shortName = "varp",
doc =
"Flat probability prior to assign to variant (not validation) genotypes. Does not override GL field.",
required = false)
public double variantPrior = 0.96;
private Set<String> samples = null;
private Set<String> BOOTSTRAP_FILTER = new HashSet<String>(Arrays.asList("bootstrap"));
private int bootstrapSetSize = 0;
private int testSetSize = 0;
private CachingFormatter formatter = new CachingFormatter("%5.4f ", 100000);
private int certainFPs = 0;
public void initialize() {
samples =
SampleUtils.getSampleListWithVCFHeader(
getToolkit(), Arrays.asList(variantCollection.variants.getName()));
beagleWriter.print("marker alleleA alleleB");
for (String sample : samples)
beagleWriter.print(String.format(" %s %s %s", sample, sample, sample));
beagleWriter.println();
if (bootstrapVCFOutput != null) {
initializeVcfWriter();
}
if (VQSRCalibrationFile != null) {
VQSRCalibrator = VQSRCalibrationCurve.readFromFile(VQSRCalibrationFile);
logger.info("Read calibration curve");
VQSRCalibrator.printInfo(logger);
}
}
public Integer map(RefMetaDataTracker tracker, ReferenceContext ref, AlignmentContext context) {
if (tracker != null) {
GenomeLoc loc = context.getLocation();
VariantContext variant_eval = tracker.getFirstValue(variantCollection.variants, loc);
VariantContext validation_eval = tracker.getFirstValue(validation, loc);
if (goodSite(variant_eval, validation_eval)) {
if (useValidation(validation_eval, ref)) {
writeBeagleOutput(validation_eval, variant_eval, true, validationPrior);
return 1;
} else {
if (goodSite(variant_eval)) {
writeBeagleOutput(variant_eval, validation_eval, false, variantPrior);
return 1;
} else { // todo -- if the variant site is bad, validation is good, but not in bootstrap
// set -- what do?
return 0;
}
}
} else {
return 0;
}
} else {
return 0;
}
}
public boolean goodSite(VariantContext a, VariantContext b) {
return goodSite(a) || goodSite(b);
}
public boolean goodSite(VariantContext v) {
if (canBeOutputToBeagle(v)) {
if (VQSRCalibrator != null && VQSRCalibrator.certainFalsePositive(VQSLOD_KEY, v)) {
certainFPs++;
return false;
} else {
return true;
}
} else {
return false;
}
}
public static boolean canBeOutputToBeagle(VariantContext v) {
return v != null && !v.isFiltered() && v.isBiallelic() && v.hasGenotypes();
}
public boolean useValidation(VariantContext validation, ReferenceContext ref) {
if (goodSite(validation)) {
// if using record keeps us below expected proportion, use it
logger.debug(
String.format(
"boot: %d, test: %d, total: %d",
bootstrapSetSize, testSetSize, bootstrapSetSize + testSetSize + 1));
if ((bootstrapSetSize + 1.0) / (1.0 + bootstrapSetSize + testSetSize) <= bootstrap) {
if (bootstrapVCFOutput != null) {
bootstrapVCFOutput.add(
new VariantContextBuilder(validation).filters(BOOTSTRAP_FILTER).make());
}
bootstrapSetSize++;
return true;
} else {
if (bootstrapVCFOutput != null) {
bootstrapVCFOutput.add(validation);
}
testSetSize++;
return false;
}
} else {
if (validation != null && bootstrapVCFOutput != null) {
bootstrapVCFOutput.add(validation);
}
return false;
}
}
private static final double[] HAPLOID_FLAT_LOG10_LIKELIHOODS =
MathUtils.toLog10(new double[] {0.5, 0.0, 0.5});
private static final double[] DIPLOID_FLAT_LOG10_LIKELIHOODS =
MathUtils.toLog10(new double[] {0.33, 0.33, 0.33});
public void writeBeagleOutput(
VariantContext preferredVC, VariantContext otherVC, boolean isValidationSite, double prior) {
GenomeLoc currentLoc =
VariantContextUtils.getLocation(getToolkit().getGenomeLocParser(), preferredVC);
StringBuffer beagleOut = new StringBuffer();
String marker = String.format("%s:%d ", currentLoc.getContig(), currentLoc.getStart());
beagleOut.append(marker);
if (markers != null)
markers.append(marker).append("\t").append(Integer.toString(markerCounter++)).append("\t");
for (Allele allele : preferredVC.getAlleles()) {
String bglPrintString;
if (allele.isNoCall() || allele.isNull()) bglPrintString = "-";
else bglPrintString = allele.getBaseString(); // get rid of * in case of reference allele
beagleOut.append(String.format("%s ", bglPrintString));
if (markers != null) markers.append(bglPrintString).append("\t");
}
if (markers != null) markers.append("\n");
GenotypesContext preferredGenotypes = preferredVC.getGenotypes();
GenotypesContext otherGenotypes = goodSite(otherVC) ? otherVC.getGenotypes() : null;
for (String sample : samples) {
boolean isMaleOnChrX = CHECK_IS_MALE_ON_CHR_X && getSample(sample).getGender() == Gender.MALE;
Genotype genotype;
boolean isValidation;
// use sample as key into genotypes structure
if (preferredGenotypes.containsSample(sample)) {
genotype = preferredGenotypes.get(sample);
isValidation = isValidationSite;
} else if (otherGenotypes != null && otherGenotypes.containsSample(sample)) {
genotype = otherGenotypes.get(sample);
isValidation = !isValidationSite;
} else {
// there is magically no genotype for this sample.
throw new StingException(
"Sample "
+ sample
+ " arose with no genotype in variant or validation VCF. This should never happen.");
}
/*
* Use likelihoods if: is validation, prior is negative; or: is not validation, has genotype key
*/
double[] log10Likelihoods = null;
if ((isValidation && prior < 0.0) || genotype.hasLikelihoods()) {
log10Likelihoods = genotype.getLikelihoods().getAsVector();
// see if we need to randomly mask out genotype in this position.
if (GenomeAnalysisEngine.getRandomGenerator().nextDouble() <= insertedNoCallRate) {
// we are masking out this genotype
log10Likelihoods =
isMaleOnChrX ? HAPLOID_FLAT_LOG10_LIKELIHOODS : DIPLOID_FLAT_LOG10_LIKELIHOODS;
}
if (isMaleOnChrX) {
log10Likelihoods[1] = -255; // todo -- warning this is dangerous for multi-allele case
}
}
/** otherwise, use the prior uniformly */
else if (!isValidation && genotype.isCalled() && !genotype.hasLikelihoods()) {
// hack to deal with input VCFs with no genotype likelihoods. Just assume the called
// genotype
// is confident. This is useful for Hapmap and 1KG release VCFs.
double AA = (1.0 - prior) / 2.0;
double AB = (1.0 - prior) / 2.0;
double BB = (1.0 - prior) / 2.0;
if (genotype.isHomRef()) {
AA = prior;
} else if (genotype.isHet()) {
AB = prior;
} else if (genotype.isHomVar()) {
BB = prior;
}
log10Likelihoods = MathUtils.toLog10(new double[] {AA, isMaleOnChrX ? 0.0 : AB, BB});
} else {
log10Likelihoods =
isMaleOnChrX ? HAPLOID_FLAT_LOG10_LIKELIHOODS : DIPLOID_FLAT_LOG10_LIKELIHOODS;
}
writeSampleLikelihoods(beagleOut, preferredVC, log10Likelihoods);
}
beagleWriter.println(beagleOut.toString());
}
private void writeSampleLikelihoods(
StringBuffer out, VariantContext vc, double[] log10Likelihoods) {
if (VQSRCalibrator != null) {
log10Likelihoods =
VQSRCalibrator.includeErrorRateInLikelihoods(VQSLOD_KEY, vc, log10Likelihoods);
}
double[] normalizedLikelihoods = MathUtils.normalizeFromLog10(log10Likelihoods);
// see if we need to randomly mask out genotype in this position.
for (double likeVal : normalizedLikelihoods) {
out.append(formatter.format(likeVal));
// out.append(String.format("%5.4f ",likeVal));
}
}
public Integer reduceInit() {
return 0; // Nothing to do here
}
public Integer reduce(Integer value, Integer sum) {
return value + sum; // count up the sites
}
public void onTraversalDone(Integer includedSites) {
logger.info("Sites included in beagle likelihoods file : " + includedSites);
logger.info(
String.format(
"Certain false positive found from recalibration curve : %d (%.2f%%)",
certainFPs, (100.0 * certainFPs) / (Math.max(certainFPs + includedSites, 1))));
}
private void initializeVcfWriter() {
final List<String> inputNames = Arrays.asList(validation.getName());
// setup the header fields
Set<VCFHeaderLine> hInfo = new HashSet<VCFHeaderLine>();
hInfo.addAll(VCFUtils.getHeaderFields(getToolkit(), inputNames));
hInfo.add(
new VCFFilterHeaderLine(
"bootstrap",
"This site used for genotype bootstrapping with ProduceBeagleInputWalker"));
bootstrapVCFOutput.writeHeader(
new VCFHeader(hInfo, SampleUtils.getUniqueSamplesFromRods(getToolkit(), inputNames)));
}
public static class CachingFormatter {
private int maxCacheSize = 0;
private String format;
private LRUCache<Double, String> cache;
public String getFormat() {
return format;
}
public String format(double value) {
String f = cache.get(value);
if (f == null) {
f = String.format(format, value);
cache.put(value, f);
// if ( cache.usedEntries() < maxCacheSize ) {
// System.out.printf("CACHE size %d%n", cache.usedEntries());
// } else {
// System.out.printf("CACHE is full %f%n", value);
// }
// }
// } else {
// System.out.printf("CACHE hit %f%n", value);
// }
}
return f;
}
public CachingFormatter(String format, int maxCacheSize) {
this.maxCacheSize = maxCacheSize;
this.format = format;
this.cache = new LRUCache<Double, String>(maxCacheSize);
}
}
/**
* An LRU cache, based on <code>LinkedHashMap</code>.
*
* <p>This cache has a fixed maximum number of elements (<code>cacheSize</code>). If the cache is
* full and another entry is added, the LRU (least recently used) entry is dropped.
*
* <p>This class is thread-safe. All methods of this class are synchronized.
*
* <p>Author: Christian d'Heureuse, Inventec Informatik AG, Zurich, Switzerland<br>
* Multi-licensed: EPL / LGPL / GPL / AL / BSD.
*/
public static class LRUCache<K, V> {
private static final float hashTableLoadFactor = 0.75f;
private LinkedHashMap<K, V> map;
private int cacheSize;
/**
* Creates a new LRU cache.
*
* @param cacheSize the maximum number of entries that will be kept in this cache.
*/
public LRUCache(int cacheSize) {
this.cacheSize = cacheSize;
int hashTableCapacity = (int) Math.ceil(cacheSize / hashTableLoadFactor) + 1;
map =
new LinkedHashMap<K, V>(hashTableCapacity, hashTableLoadFactor, true) {
// (an anonymous inner class)
private static final long serialVersionUID = 1;
@Override
protected boolean removeEldestEntry(Map.Entry<K, V> eldest) {
return size() > LRUCache.this.cacheSize;
}
};
}
/**
* Retrieves an entry from the cache.<br>
* The retrieved entry becomes the MRU (most recently used) entry.
*
* @param key the key whose associated value is to be returned.
* @return the value associated to this key, or null if no value with this key exists in the
* cache.
*/
public synchronized V get(K key) {
return map.get(key);
}
/**
* Adds an entry to this cache. The new entry becomes the MRU (most recently used) entry. If an
* entry with the specified key already exists in the cache, it is replaced by the new entry. If
* the cache is full, the LRU (least recently used) entry is removed from the cache.
*
* @param key the key with which the specified value is to be associated.
* @param value a value to be associated with the specified key.
*/
public synchronized void put(K key, V value) {
map.put(key, value);
}
/** Clears the cache. */
public synchronized void clear() {
map.clear();
}
/**
* Returns the number of used entries in the cache.
*
* @return the number of entries currently in the cache.
*/
public synchronized int usedEntries() {
return map.size();
}
/**
* Returns a <code>Collection</code> that contains a copy of all cache entries.
*
* @return a <code>Collection</code> with a copy of the cache content.
*/
public synchronized Collection<Map.Entry<K, V>> getAll() {
return new ArrayList<Map.Entry<K, V>>(map.entrySet());
}
} // end class LRUCache
}
/** Initialize the stratifications, evaluations, evaluation contexts, and reporting object */
public void initialize() {
// Just list the modules, and exit quickly.
if (LIST) {
variantEvalUtils.listModulesAndExit();
}
// maintain the full list of comps
comps.addAll(compsProvided);
if (dbsnp.dbsnp.isBound()) {
comps.add(dbsnp.dbsnp);
knowns.add(dbsnp.dbsnp);
}
// Add a dummy comp track if none exists
if (comps.size() == 0)
comps.add(
new RodBinding<VariantContext>(VariantContext.class, "none", "UNBOUND", "", new Tags()));
// Set up set of additional knowns
for (RodBinding<VariantContext> compRod : comps) {
if (KNOWN_NAMES.contains(compRod.getName())) knowns.add(compRod);
}
// Now that we have all the rods categorized, determine the sample list from the eval rods.
Map<String, VCFHeader> vcfRods = VCFUtils.getVCFHeadersFromRods(getToolkit(), evals);
Set<String> vcfSamples =
SampleUtils.getSampleList(vcfRods, VariantContextUtils.GenotypeMergeType.REQUIRE_UNIQUE);
// Load the sample list
sampleNamesForEvaluation.addAll(
SampleUtils.getSamplesFromCommandLineInput(vcfSamples, SAMPLE_EXPRESSIONS));
numSamples = NUM_SAMPLES > 0 ? NUM_SAMPLES : sampleNamesForEvaluation.size();
if (Arrays.asList(STRATIFICATIONS_TO_USE).contains("Sample")) {
sampleNamesForStratification.addAll(sampleNamesForEvaluation);
}
sampleNamesForStratification.add(ALL_SAMPLE_NAME);
// Initialize select expressions
for (VariantContextUtils.JexlVCMatchExp jexl :
VariantContextUtils.initializeMatchExps(SELECT_NAMES, SELECT_EXPS)) {
SortableJexlVCMatchExp sjexl = new SortableJexlVCMatchExp(jexl.name, jexl.exp);
jexlExpressions.add(sjexl);
}
// Initialize the set of stratifications and evaluations to use
stratificationObjects =
variantEvalUtils.initializeStratificationObjects(
this, NO_STANDARD_STRATIFICATIONS, STRATIFICATIONS_TO_USE);
Set<Class<? extends VariantEvaluator>> evaluationObjects =
variantEvalUtils.initializeEvaluationObjects(NO_STANDARD_MODULES, MODULES_TO_USE);
for (VariantStratifier vs : getStratificationObjects()) {
if (vs.getName().equals("Filter")) byFilterIsEnabled = true;
else if (vs.getName().equals("Sample")) perSampleIsEnabled = true;
}
if (intervalsFile != null) {
boolean fail = true;
for (final VariantStratifier vs : stratificationObjects) {
if (vs.getClass().equals(IntervalStratification.class)) fail = false;
}
if (fail)
throw new UserException.BadArgumentValue(
"ST", "stratIntervals argument provided but -ST IntervalStratification not provided");
}
// Initialize the evaluation contexts
evaluationContexts =
variantEvalUtils.initializeEvaluationContexts(
stratificationObjects, evaluationObjects, null, null);
// Initialize report table
report = variantEvalUtils.initializeGATKReport(stratificationObjects, evaluationObjects);
// Load ancestral alignments
if (ancestralAlignmentsFile != null) {
try {
ancestralAlignments = new IndexedFastaSequenceFile(ancestralAlignmentsFile);
} catch (FileNotFoundException e) {
throw new ReviewedStingException(
String.format(
"The ancestral alignments file, '%s', could not be found",
ancestralAlignmentsFile.getAbsolutePath()));
}
}
// initialize CNVs
if (knownCNVsFile != null) {
knownCNVsByContig = createIntervalTreeByContig(knownCNVsFile);
}
}
/** Set up the VCF writer, the sample expressions and regexs, and the JEXL matcher */
public void initialize() {
// Get list of samples to include in the output
List<String> rodNames = Arrays.asList(variantCollection.variants.getName());
Map<String, VCFHeader> vcfRods = VCFUtils.getVCFHeadersFromRods(getToolkit(), rodNames);
TreeSet<String> vcfSamples =
new TreeSet<String>(
SampleUtils.getSampleList(
vcfRods, VariantContextUtils.GenotypeMergeType.REQUIRE_UNIQUE));
Collection<String> samplesFromFile = SampleUtils.getSamplesFromFiles(sampleFiles);
Collection<String> samplesFromExpressions =
SampleUtils.matchSamplesExpressions(vcfSamples, sampleExpressions);
// first, add any requested samples
samples.addAll(samplesFromFile);
samples.addAll(samplesFromExpressions);
samples.addAll(sampleNames);
// if none were requested, we want all of them
if (samples.isEmpty()) {
samples.addAll(vcfSamples);
NO_SAMPLES_SPECIFIED = true;
}
// now, exclude any requested samples
Collection<String> XLsamplesFromFile = SampleUtils.getSamplesFromFiles(XLsampleFiles);
samples.removeAll(XLsamplesFromFile);
samples.removeAll(XLsampleNames);
if (samples.size() == 0 && !NO_SAMPLES_SPECIFIED)
throw new UserException(
"All samples requested to be included were also requested to be excluded.");
for (String sample : samples) logger.info("Including sample '" + sample + "'");
// if user specified types to include, add these, otherwise, add all possible variant context
// types to list of vc types to include
if (TYPES_TO_INCLUDE.isEmpty()) {
for (VariantContext.Type t : VariantContext.Type.values()) selectedTypes.add(t);
} else {
for (VariantContext.Type t : TYPES_TO_INCLUDE) selectedTypes.add(t);
}
// Initialize VCF header
Set<VCFHeaderLine> headerLines = VCFUtils.smartMergeHeaders(vcfRods.values(), logger);
headerLines.add(new VCFHeaderLine("source", "SelectVariants"));
if (KEEP_ORIGINAL_CHR_COUNTS) {
headerLines.add(
new VCFFormatHeaderLine("AC_Orig", 1, VCFHeaderLineType.Integer, "Original AC"));
headerLines.add(
new VCFFormatHeaderLine("AF_Orig", 1, VCFHeaderLineType.Float, "Original AF"));
headerLines.add(
new VCFFormatHeaderLine("AN_Orig", 1, VCFHeaderLineType.Integer, "Original AN"));
}
vcfWriter.writeHeader(new VCFHeader(headerLines, samples));
for (int i = 0; i < SELECT_EXPRESSIONS.size(); i++) {
// It's not necessary that the user supply select names for the JEXL expressions, since those
// expressions will only be needed for omitting records. Make up the select names here.
selectNames.add(String.format("select-%d", i));
}
jexls = VariantContextUtils.initializeMatchExps(selectNames, SELECT_EXPRESSIONS);
// Look at the parameters to decide which analysis to perform
DISCORDANCE_ONLY = discordanceTrack.isBound();
if (DISCORDANCE_ONLY)
logger.info(
"Selecting only variants discordant with the track: " + discordanceTrack.getName());
CONCORDANCE_ONLY = concordanceTrack.isBound();
if (CONCORDANCE_ONLY)
logger.info(
"Selecting only variants concordant with the track: " + concordanceTrack.getName());
if (MENDELIAN_VIOLATIONS) {
if (FAMILY_STRUCTURE_FILE != null) {
try {
for (final String line : new XReadLines(FAMILY_STRUCTURE_FILE)) {
MendelianViolation mv =
new MendelianViolation(line, MENDELIAN_VIOLATION_QUAL_THRESHOLD);
if (samples.contains(mv.getSampleChild())
&& samples.contains(mv.getSampleDad())
&& samples.contains(mv.getSampleMom())) mvSet.add(mv);
}
} catch (FileNotFoundException e) {
throw new UserException.CouldNotReadInputFile(FAMILY_STRUCTURE_FILE, e);
}
if (outMVFile != null)
try {
outMVFileStream = new PrintStream(outMVFile);
} catch (FileNotFoundException e) {
throw new UserException.CouldNotCreateOutputFile(
outMVFile, "Can't open output file", e);
}
} else
mvSet.add(new MendelianViolation(FAMILY_STRUCTURE, MENDELIAN_VIOLATION_QUAL_THRESHOLD));
} else if (!FAMILY_STRUCTURE.isEmpty()) {
mvSet.add(new MendelianViolation(FAMILY_STRUCTURE, MENDELIAN_VIOLATION_QUAL_THRESHOLD));
MENDELIAN_VIOLATIONS = true;
}
SELECT_RANDOM_NUMBER = numRandom > 0;
if (SELECT_RANDOM_NUMBER) {
logger.info("Selecting " + numRandom + " variants at random from the variant track");
variantArray = new RandomVariantStructure[numRandom];
}
SELECT_RANDOM_FRACTION = fractionRandom > 0;
if (SELECT_RANDOM_FRACTION)
logger.info(
"Selecting approximately "
+ 100.0 * fractionRandom
+ "% of the variants at random from the variant track");
}