Checkin of the Multi-Sample SNP caller.
Doesn't work yet; same command I used to use now causes GATK to throw an exception. Will check with Matt & Aaron tomorrow, then do a regression test. git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1509 348d0f76-0448-11de-a6fe-93d51630548a
This commit is contained in:
jmaguire
parent
e2a79c5cd9
commit
e2780c17af
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@ -9,8 +9,7 @@ import org.broadinstitute.sting.gatk.contexts.AlignmentContext;
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import org.broadinstitute.sting.gatk.contexts.ReferenceContext;
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import org.broadinstitute.sting.gatk.refdata.RefMetaDataTracker;
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import org.broadinstitute.sting.gatk.walkers.LocusWalker;
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import org.broadinstitute.sting.gatk.walkers.genotyper.OldAndBustedGenotypeLikelihoods;
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import org.broadinstitute.sting.gatk.walkers.genotyper.DiploidGenotypePriors;
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import org.broadinstitute.sting.playground.utils.*;
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import org.broadinstitute.sting.utils.*;
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import org.broadinstitute.sting.utils.ReadBackedPileup;
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import org.broadinstitute.sting.utils.cmdLine.Argument;
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@ -28,17 +27,26 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
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@Argument(required=false, shortName="max_iterations", doc="Maximum number of iterations for EM") public int MAX_ITERATIONS = 10;
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@Argument(fullName="discovery_output", shortName="discovery_output", required=true, doc="file to write SNP discovery output to") public String DISCOVERY_OUTPUT;
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@Argument(fullName="individual_output", shortName="individual_output", required=true, doc="file to write individual SNP calls to") public String INDIVIDUAL_OUTPUT;
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@Argument(fullName="stats_output", shortName="stats_output", required=false, doc="file to write stats to") public String STATS_OUTPUT = "/dev/null";
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@Argument(fullName="sample_name_regex", shortName="sample_name_regex", required=false, doc="sample_name_regex") public String SAMPLE_NAME_REGEX = null;
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@Argument(fullName="call_indels", shortName="call_indels", required=false, doc="call indels?") public boolean CALL_INDELS = false;
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@Argument(fullName="weight_samples", shortName="weight_samples", required=false, doc="rw-weight samples during EM?") public boolean WEIGHT_SAMPLES = false;
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@Argument(fullName="theta", shortName="theta", required=false, doc="rate of sequence divergence") public double THETA = 1e-3;
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@Argument(fullName="allele_frequency_prior", shortName="allele_frequency_prior", required=false, doc="use prior on allele frequencies? (P(f) = theta/(N*f)") public boolean ALLELE_FREQUENCY_PRIOR = false;
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@Argument(fullName="confusion_matrix_file", shortName="confusion_matrix_file", required=false, doc="file containing confusion matrix for all three technologies") public String CONFUSION_MATRIX_FILE = null;
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// Private state.
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protected List<String> sample_names;
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protected SAMFileHeader header;
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protected PrintStream individual_output_file;
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protected PrintStream discovery_output_file;
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protected PrintStream stats_output_file;
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class MultiSampleCallResult
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{
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GenomeLoc location;
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char ref;
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char alt;
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EM_Result em_result;
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@ -52,8 +60,10 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
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int n_hom;
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int EM_N;
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double alt_freq;
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public MultiSampleCallResult(char ref, char alt, EM_Result em_result, double lod, double strand_score, double pD, double pNull, String in_dbsnp, int n_ref, int n_het, int n_hom, int EM_N, double alt_freq)
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public MultiSampleCallResult(GenomeLoc location, char ref, char alt, EM_Result em_result, double lod, double strand_score, double pD, double pNull, String in_dbsnp, int n_ref, int n_het, int n_hom, int EM_N, double alt_freq)
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{
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this.location = location;
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this.ref = ref;
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this.alt = alt;
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this.em_result = em_result;
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@ -68,6 +78,102 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
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this.EM_N = EM_N;
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this.alt_freq = alt_freq;
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}
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public MultiSampleCallResult() { } // this is just so I can do new MultiSampleCallResult().header(). "inner classes cannot have static declarations" :(
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public String header()
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{
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return new String("loc ref alt lod strand_score pD pNull in_dbsnp pA pC pG pT EM_alt_freq EM_N n_ref n_het n_hom");
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}
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public String toString()
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{
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String s = "";
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s = s + String.format("%s %c %c %f %f %f %f %s ", location, ref, alt, lod, strand_score, pD, pNull, in_dbsnp);
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for (int i = 0; i < 4; i++) { s = s + String.format("%f ", em_result.allele_likelihoods[i]); }
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s = s + String.format("%f %d %d %d %d", alt_freq, em_result.EM_N, n_ref, n_het, n_hom);
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return s;
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}
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}
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public static class DepthStats
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{
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public static String Header()
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{
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return "loc ref depth A C G T a c g t mq_min mq_mean mq_median mq_max mq_sd";
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}
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public static String Row(char ref, AlignmentContext context)
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{
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String ans = "";
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List<SAMRecord> reads = context.getReads();
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List<Integer> offsets = context.getOffsets();
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Pileup pileup = new ReadBackedPileup(ref, context);
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ans += String.format("%s ", context.getLocation());
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ans += String.format("%c ", ref);
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ans += String.format("%d ", reads.size());
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ans += String.format("%d ", countBase(context, 'A', "+"));
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ans += String.format("%d ", countBase(context, 'C', "+"));
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ans += String.format("%d ", countBase(context, 'G', "+"));
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ans += String.format("%d ", countBase(context, 'T', "+"));
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ans += String.format("%d ", countBase(context, 'A', "-"));
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ans += String.format("%d ", countBase(context, 'C', "-"));
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ans += String.format("%d ", countBase(context, 'G', "-"));
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ans += String.format("%d ", countBase(context, 'T', "-"));
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ans += String.format("%s ", Stats(BasicPileup.mappingQualPileup(reads)));
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return ans;
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}
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static int countBase(AlignmentContext context, char base, String strand)
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{
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int count = 0;
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List<SAMRecord> reads = context.getReads();
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List<Integer> offsets = context.getOffsets();
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for (int i = 0; i < reads.size(); i++)
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{
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if (reads.get(i).getReadString().charAt(offsets.get(i)) == base)
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{
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if (strand.equals("+") && (reads.get(i).getReadNegativeStrandFlag()==false)) { count += 1; }
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else if (strand.equals("-") && (reads.get(i).getReadNegativeStrandFlag()==true)) { count += 1; }
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else if (! (strand.equals("+") || strand.equals("-"))) { count += 1; }
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}
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}
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return count;
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}
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public static String Stats(ArrayList<Byte> X)
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{
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Collections.sort(X);
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long count = 0;
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long sum = 0;
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long min = X.get(0);
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long max = X.get(0);
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long median = X.get(0);
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for (int i = 0; i < X.size(); i++)
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{
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int x = X.get(i);
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if (x < min) { min = x; }
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if (x > max) { max = x; }
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sum += x;
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count += 1;
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if (i == X.size()/2) { median = x; }
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}
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double mean = sum/count;
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for (int i = 0; i < X.size(); i++)
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{
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int x = X.get(i);
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sum += (x-mean)*(x-mean);
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count += 1;
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}
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double sd = Math.sqrt(sum/count);
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return String.format("%d %f %d %d %f", min, mean, median, max, sd);
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}
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}
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@ -75,13 +181,20 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
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// Walker Interface Functions
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public void initialize()
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{
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System.out.printf("\n\n\n\n");
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(new ClassicGenotypeLikelihoods()).TEST();
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try
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{
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discovery_output_file = new PrintStream(DISCOVERY_OUTPUT);
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individual_output_file = new PrintStream(new GZIPOutputStream(new FileOutputStream(INDIVIDUAL_OUTPUT)));
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discovery_output_file.println("loc ref alt lod strand_score pD pNull discovery_lod in_dbsnp pA pC pG pT EM_alt_freq EM_N n_ref n_het n_hom");
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discovery_output_file.println(new MultiSampleCallResult().header());
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individual_output_file.println("loc ref sample_name genotype lodVsNextBest lodVsRef in_dbsnp AA AC AG AT CC CG CT GG GT TT");
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stats_output_file = new PrintStream(STATS_OUTPUT);
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stats_output_file.println(DepthStats.Header());
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}
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catch (Exception e)
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{
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@ -89,10 +202,9 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
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System.exit(-1);
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}
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GenomeAnalysisEngine toolkit = this.getToolkit();
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this.header = toolkit.getSAMFileHeader();
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List<SAMReadGroupRecord> read_groups = header.getReadGroups();
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GenomeAnalysisEngine toolkit = this.getToolkit();
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this.header = toolkit.getSAMFileHeader();
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List<SAMReadGroupRecord> read_groups = header.getReadGroups();
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sample_names = new ArrayList<String>();
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@ -101,27 +213,49 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
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for (int i = 0; i < read_groups.size(); i++)
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{
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String sample_name = read_groups.get(i).getSample();
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String platform = (String)(read_groups.get(i).getAttribute(SAMReadGroupRecord.PLATFORM_TAG));
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if (SAMPLE_NAME_REGEX != null) { sample_name = sample_name.replaceAll(SAMPLE_NAME_REGEX, "$1"); }
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System.out.printf("SAMPLE: %s %s\n", sample_name, platform);
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if (unique_sample_names.contains(sample_name)) { continue; }
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unique_sample_names.add(sample_name);
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sample_names.add(sample_name);
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System.out.println("SAMPLE: " + sample_name);
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System.out.printf("UNIQUE_SAMPLE: %s %s\n", sample_name, platform);
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}
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// Load the confusion matrix if it exists
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if (CONFUSION_MATRIX_FILE != null)
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{
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this.confusion_matrix = new ConfusionMatrix(CONFUSION_MATRIX_FILE);
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}
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}
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public MultiSampleCallResult map(RefMetaDataTracker tracker, ReferenceContext ref, AlignmentContext context)
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public MultiSampleCallResult map(RefMetaDataTracker tracker, ReferenceContext ref, AlignmentContext context)
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{
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context = filter_each_read(context);
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if (ref.getBase() == 'N') { return null; }
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if (context.getReads().size() <= 0) { return null; }
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this.ref = ref.getBase();
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MultiSampleCallResult result = this.MultiSampleCall(tracker, ref.getBase(), context, sample_names);
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stats_output_file.println(DepthStats.Row(ref.getBase(), context));
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return result;
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}
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public void onTraversalDone(String sum)
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{
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discovery_output_file.flush();
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discovery_output_file.close();
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stats_output_file.flush();
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stats_output_file.close();
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out.println("MultiSampleCaller done.");
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return;
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}
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@ -133,6 +267,10 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
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public String reduce(MultiSampleCallResult record, String sum)
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{
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if (record != null)
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{
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discovery_output_file.printf(record.toString() + "\n");
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}
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return null;
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}
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@ -144,15 +282,16 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
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// Calling Functions
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char ref;
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protected ConfusionMatrix confusion_matrix;
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OldAndBustedGenotypeLikelihoods Genotype(AlignmentContext context, double[] allele_likelihoods, double indel_alt_freq)
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ClassicGenotypeLikelihoods Genotype(AlignmentContext context, double[] allele_likelihoods, double indel_alt_freq)
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{
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ReadBackedPileup pileup = new ReadBackedPileup(ref, context);
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String bases = pileup.getBases();
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if (bases.length() == 0)
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{
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OldAndBustedGenotypeLikelihoods G = new OldAndBustedGenotypeLikelihoods(DiploidGenotypePriors.HUMAN_HETEROZYGOSITY);
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ClassicGenotypeLikelihoods G = new ClassicGenotypeLikelihoods();
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return G;
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}
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@ -161,17 +300,33 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
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ref = Character.toUpperCase(ref);
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// Handle single-base polymorphisms.
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OldAndBustedGenotypeLikelihoods G = new OldAndBustedGenotypeLikelihoods(DiploidGenotypePriors.HUMAN_HETEROZYGOSITY);
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ClassicGenotypeLikelihoods G = new ClassicGenotypeLikelihoods();
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for ( int i = 0; i < reads.size(); i++ )
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{
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//System.out.printf("DBG: %s\n", context.getLocation());
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SAMRecord read = reads.get(i);
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int offset = offsets.get(i);
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G.add(ref, read.getReadString().charAt(offset), read.getBaseQualities()[offset]);
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if (CONFUSION_MATRIX_FILE == null)
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{
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G.add(ref, read.getReadString().charAt(offset), read.getBaseQualities()[offset]);
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}
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else
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{
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String RG = (String)(read.getAttribute("RG"));
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assert(header != null);
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assert(header.getReadGroup(RG) != null);
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String platform = (String)(header.getReadGroup(RG).getAttribute(SAMReadGroupRecord.PLATFORM_TAG));
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G.add(ref, read.getReadString().charAt(offset), read.getBaseQualities()[offset], confusion_matrix, platform);
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}
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}
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G.applyPrior(ref, allele_likelihoods);
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G.ApplyPrior(ref, allele_likelihoods);
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// Handle indels
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/* if (CALL_INDELS)
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if (CALL_INDELS)
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{
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String[] indels = BasicPileup.indelPileup(reads, offsets);
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IndelLikelihood indel_call = new IndelLikelihood(indels, indel_alt_freq);
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@ -183,7 +338,7 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
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{
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G.addIndelLikelihood(null);
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}
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}*/
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}
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/*
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// Handle 2nd-best base calls.
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@ -196,15 +351,17 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
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return G;
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}
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double[] CountFreqs(OldAndBustedGenotypeLikelihoods[] genotype_likelihoods)
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double[] CountFreqs_gold(ClassicGenotypeLikelihoods[] genotype_likelihoods)
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{
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double[] allele_likelihoods = new double[4];
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for (int x = 0; x < genotype_likelihoods.length; x++)
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{
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if (genotype_likelihoods[x].coverage == 0) { continue; }
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ClassicGenotypeLikelihoods G = genotype_likelihoods[x];
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if (G.coverage == 0) { continue; }
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double Z = 0;
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for(int k = 0; k < 10; k++) { Z += Math.pow(10,genotype_likelihoods[x].likelihoods[k]); }
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for(int k = 0; k < 10; k++) { Z += Math.pow(10,G.likelihoods[k]); }
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Z = Math.log10(Z);
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double[] personal_allele_likelihoods = new double[4];
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@ -213,8 +370,9 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
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{
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for (int j = i; j < 4; j++)
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{
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personal_allele_likelihoods[i] += Math.pow(10,genotype_likelihoods[x].likelihoods[k]-Z);
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personal_allele_likelihoods[j] += Math.pow(10,genotype_likelihoods[x].likelihoods[k]-Z);
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double likelihood = Math.pow(10,G.likelihoods[k]-Z);
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personal_allele_likelihoods[i] += likelihood;
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personal_allele_likelihoods[j] += likelihood;
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k++;
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}
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}
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@ -231,7 +389,45 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
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return allele_likelihoods;
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}
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/* double CountIndelFreq(OldAndBustedGenotypeLikelihoods[] genotype_likelihoods)
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// This version is a little faster.
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double[] CountFreqs(ClassicGenotypeLikelihoods[] genotype_likelihoods)
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{
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double[] allele_likelihoods = new double[4];
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for (int x = 0; x < genotype_likelihoods.length; x++)
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{
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ClassicGenotypeLikelihoods G = genotype_likelihoods[x];
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if (G.coverage == 0) { continue; }
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double Z = 0;
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double[] personal_allele_likelihoods = new double[4];
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int k = 0;
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for (int i = 0; i < 4; i++)
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{
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for (int j = i; j < 4; j++)
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{
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double likelihood = Math.pow(10,G.likelihoods[k]);
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Z += likelihood;
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personal_allele_likelihoods[i] += likelihood;
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personal_allele_likelihoods[j] += likelihood;
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k++;
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}
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}
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double sum = 0;
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for (int y = 0; y < 4; y++) { sum += personal_allele_likelihoods[y]; }
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for (int y = 0; y < 4; y++) { personal_allele_likelihoods[y] /= sum; }
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for (int y = 0; y < 4; y++) { allele_likelihoods[y] += personal_allele_likelihoods[y]; }
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}
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double sum = 0;
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for (int i = 0; i < 4; i++) { sum += allele_likelihoods[i]; }
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for (int i = 0; i < 4; i++) { allele_likelihoods[i] /= sum; }
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return allele_likelihoods;
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}
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double CountIndelFreq(ClassicGenotypeLikelihoods[] genotype_likelihoods)
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{
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HashMap<String, Double> indel_allele_likelihoods = new HashMap<String, Double>();
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@ -258,10 +454,10 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
|
|||
pAlt = pAlt / (pRef + pAlt);
|
||||
|
||||
return pAlt;
|
||||
}*/
|
||||
}
|
||||
|
||||
// Potential precision error here.
|
||||
double Compute_pD(OldAndBustedGenotypeLikelihoods[] genotype_likelihoods)
|
||||
double Compute_pD(ClassicGenotypeLikelihoods[] genotype_likelihoods, double[] sample_weights)
|
||||
{
|
||||
double pD = 0;
|
||||
for (int i = 0; i < sample_names.size(); i++)
|
||||
|
|
@ -271,22 +467,45 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
|
|||
{
|
||||
sum += Math.pow(10, genotype_likelihoods[i].likelihoods[j]);
|
||||
}
|
||||
pD += Math.log10(sum);
|
||||
pD += Math.log10(sample_weights[i] * sum);
|
||||
}
|
||||
return pD;
|
||||
}
|
||||
|
||||
double Compute_pNull(AlignmentContext[] contexts)
|
||||
double Compute_pNull(AlignmentContext[] contexts, double[] sample_weights)
|
||||
{
|
||||
double[] allele_likelihoods = new double[4];
|
||||
for (int i = 0; i < 4; i++) { allele_likelihoods[i] = 1e-6/3.0; }
|
||||
allele_likelihoods[BaseUtils.simpleBaseToBaseIndex(ref)] = 1.0-1e-6;
|
||||
OldAndBustedGenotypeLikelihoods[] G = new OldAndBustedGenotypeLikelihoods[sample_names.size()];
|
||||
ClassicGenotypeLikelihoods[] G = new ClassicGenotypeLikelihoods[sample_names.size()];
|
||||
for (int j = 0; j < sample_names.size(); j++)
|
||||
{
|
||||
G[j] = Genotype(contexts[j], allele_likelihoods, 1e-6);
|
||||
}
|
||||
return Compute_pD(G);
|
||||
return Compute_pD(G, sample_weights);
|
||||
}
|
||||
|
||||
double[] Compute_SampleWeights(ClassicGenotypeLikelihoods[] genotype_likelihoods)
|
||||
{
|
||||
double[] pD = new double[sample_names.size()];
|
||||
double total_pD = 0;
|
||||
for (int i = 0; i < sample_names.size(); i++)
|
||||
{
|
||||
double sum = 0;
|
||||
for (int j = 0; j < 10; j++)
|
||||
{
|
||||
sum += Math.pow(10, genotype_likelihoods[i].likelihoods[j]);
|
||||
}
|
||||
pD[i] = sum;
|
||||
total_pD += pD[i];
|
||||
}
|
||||
|
||||
for (int i = 0; i < sample_names.size(); i++)
|
||||
{
|
||||
pD[i] /= total_pD;
|
||||
}
|
||||
|
||||
return pD;
|
||||
}
|
||||
|
||||
// Some globals to cache results.
|
||||
|
|
@ -297,9 +516,32 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
|
|||
double LOD(AlignmentContext[] contexts)
|
||||
{
|
||||
em_result = EM(contexts);
|
||||
OldAndBustedGenotypeLikelihoods[] G = em_result.genotype_likelihoods;
|
||||
pD = Compute_pD(G);
|
||||
pNull = Compute_pNull(contexts);
|
||||
ClassicGenotypeLikelihoods[] G = em_result.genotype_likelihoods;
|
||||
pD = Compute_pD(G, em_result.sample_weights);
|
||||
pNull = Compute_pNull(contexts, em_result.sample_weights);
|
||||
|
||||
if (ALLELE_FREQUENCY_PRIOR)
|
||||
{
|
||||
// Apply p(f).
|
||||
double pVar = 0.0;
|
||||
for (int i = 1; i < em_result.EM_N; i++) { pVar += THETA/(double)i; }
|
||||
|
||||
double p0 = Math.log10(1 - pVar);
|
||||
double pF;
|
||||
|
||||
double MAF = Compute_alt_freq(ref, em_result.allele_likelihoods);
|
||||
|
||||
if (MAF < 1/(2.0*em_result.EM_N)) { pF = p0; }
|
||||
else { pF = Math.log10(THETA/(2.0*em_result.EM_N * MAF)); }
|
||||
|
||||
//System.out.printf("DBG %s %c %f %f %f %f (%.20f) %f ", contexts[0].getLocation(), ref, pD, pF, pNull, p0, Compute_alt_freq(ref, em_result.allele_likelihoods), 2.0 * em_result.EM_N);
|
||||
//for (int i = 0; i < 4; i++) { System.out.printf("%f ", em_result.allele_likelihoods[i]); }
|
||||
//System.out.printf("\n");
|
||||
|
||||
pD = pD + pF;
|
||||
pNull = pNull + p0;
|
||||
}
|
||||
|
||||
lod = pD - pNull;
|
||||
return lod;
|
||||
}
|
||||
|
|
@ -307,23 +549,27 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
|
|||
class EM_Result
|
||||
{
|
||||
String[] sample_names;
|
||||
OldAndBustedGenotypeLikelihoods[] genotype_likelihoods;
|
||||
ClassicGenotypeLikelihoods[] genotype_likelihoods;
|
||||
double[] allele_likelihoods;
|
||||
double[] sample_weights;
|
||||
int EM_N;
|
||||
|
||||
public EM_Result(List<String> sample_names, OldAndBustedGenotypeLikelihoods[] genotype_likelihoods, double[] allele_likelihoods)
|
||||
public EM_Result(List<String> sample_names, ClassicGenotypeLikelihoods[] genotype_likelihoods, double[] allele_likelihoods, double[] sample_weights)
|
||||
{
|
||||
this.sample_names = new String[1];
|
||||
this.sample_names = sample_names.toArray(this.sample_names);
|
||||
this.genotype_likelihoods = genotype_likelihoods;
|
||||
this.allele_likelihoods = allele_likelihoods;
|
||||
this.sample_weights = sample_weights;
|
||||
|
||||
EM_N = 0;
|
||||
for (int i = 0; i < genotype_likelihoods.length; i++)
|
||||
{
|
||||
if (genotype_likelihoods[i].coverage > 0) { EM_N += 1; }
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
EM_Result EM(AlignmentContext[] contexts)
|
||||
|
|
@ -338,43 +584,70 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
|
|||
}
|
||||
double indel_alt_freq = 1e-4;
|
||||
|
||||
OldAndBustedGenotypeLikelihoods[] G = new OldAndBustedGenotypeLikelihoods[sample_names.size()];
|
||||
double[] sample_weights = new double[sample_names.size()];
|
||||
for (int i = 0; i < sample_weights.length; i++)
|
||||
{
|
||||
//sample_weights[i] = 1.0/(double)i;
|
||||
sample_weights[i] = 1.0;
|
||||
}
|
||||
|
||||
ClassicGenotypeLikelihoods[] G = new ClassicGenotypeLikelihoods[sample_names.size()];
|
||||
ClassicGenotypeLikelihoods[] Weighted_G = new ClassicGenotypeLikelihoods[sample_names.size()];
|
||||
for (int i = 0; i < MAX_ITERATIONS; i++)
|
||||
{
|
||||
for (int j = 0; j < sample_names.size(); j++)
|
||||
{
|
||||
G[j] = Genotype(contexts[j], allele_likelihoods, indel_alt_freq);
|
||||
if (WEIGHT_SAMPLES) { G[j].ApplyWeight(sample_weights[j]); }
|
||||
}
|
||||
|
||||
|
||||
allele_likelihoods = CountFreqs(G);
|
||||
|
||||
// if (CALL_INDELS)
|
||||
// {
|
||||
// indel_alt_freq = CountIndelFreq(G);
|
||||
// }
|
||||
if (CALL_INDELS)
|
||||
{
|
||||
indel_alt_freq = CountIndelFreq(G);
|
||||
}
|
||||
|
||||
if (WEIGHT_SAMPLES)
|
||||
{
|
||||
sample_weights = Compute_SampleWeights(G);
|
||||
}
|
||||
}
|
||||
|
||||
return new EM_Result(sample_names, G, allele_likelihoods);
|
||||
return new EM_Result(sample_names, G, allele_likelihoods, sample_weights);
|
||||
}
|
||||
|
||||
// Hacky global variables for debugging.
|
||||
double StrandScore(AlignmentContext context)
|
||||
{
|
||||
//AlignmentContext[] contexts = filterAlignmentContextBySample(context, sample_names, 0);
|
||||
//AlignmentContext[] contexts = filterAlignmentContext(context, sample_names, 0);
|
||||
|
||||
AlignmentContext fw = filterAlignmentContextByStrand(context, "+");
|
||||
AlignmentContext bw = filterAlignmentContextByStrand(context, "-");
|
||||
AlignmentContext[] contexts_fw = filterAlignmentContextBySample(fw, sample_names, 0);
|
||||
AlignmentContext[] contexts_bw = filterAlignmentContextBySample(bw, sample_names, 0);
|
||||
AlignmentContext fw = filterAlignmentContext(context, "+");
|
||||
AlignmentContext bw = filterAlignmentContext(context, "-");
|
||||
AlignmentContext[] contexts_fw = filterAlignmentContext(fw, sample_names, 0);
|
||||
AlignmentContext[] contexts_bw = filterAlignmentContext(bw, sample_names, 0);
|
||||
|
||||
EM_Result em_fw = EM(contexts_fw);
|
||||
EM_Result em_bw = EM(contexts_bw);
|
||||
|
||||
double pNull_fw = Compute_pNull(contexts_fw);
|
||||
double pNull_bw = Compute_pNull(contexts_bw);
|
||||
double pNull_fw = Compute_pNull(contexts_fw, em_fw.sample_weights);
|
||||
double pNull_bw = Compute_pNull(contexts_bw, em_bw.sample_weights);
|
||||
|
||||
double pD_fw = Compute_pD(em_fw.genotype_likelihoods);
|
||||
double pD_bw = Compute_pD(em_bw.genotype_likelihoods);
|
||||
double pD_fw = Compute_pD(em_fw.genotype_likelihoods, em_fw.sample_weights);
|
||||
double pD_bw = Compute_pD(em_bw.genotype_likelihoods, em_bw.sample_weights);
|
||||
|
||||
if (ALLELE_FREQUENCY_PRIOR)
|
||||
{
|
||||
// Apply p(f).
|
||||
double pVar = 0.0;
|
||||
for (int i = 1; i < em_result.EM_N; i++) { pVar += THETA/(double)i; }
|
||||
|
||||
pD_fw = pD_fw + Math.log10(THETA/(2.0*em_fw.EM_N * Compute_alt_freq(ref, em_fw.allele_likelihoods)));
|
||||
pNull_fw = pNull_fw + Math.log10(1 - pVar);
|
||||
|
||||
pD_bw = pD_bw + Math.log10(THETA/(2.0*em_bw.EM_N * Compute_alt_freq(ref, em_bw.allele_likelihoods)));
|
||||
pNull_bw = pNull_bw + Math.log10(1 - pVar);
|
||||
}
|
||||
|
||||
double EM_alt_freq_fw = Compute_alt_freq(ref, em_fw.allele_likelihoods);
|
||||
double EM_alt_freq_bw = Compute_alt_freq(ref, em_bw.allele_likelihoods);
|
||||
|
|
@ -388,9 +661,9 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
|
|||
return strand_score;
|
||||
}
|
||||
|
||||
OldAndBustedGenotypeLikelihoods HardyWeinberg(double[] allele_likelihoods)
|
||||
ClassicGenotypeLikelihoods HardyWeinberg(double[] allele_likelihoods)
|
||||
{
|
||||
OldAndBustedGenotypeLikelihoods G = new OldAndBustedGenotypeLikelihoods(DiploidGenotypePriors.HUMAN_HETEROZYGOSITY);
|
||||
ClassicGenotypeLikelihoods G = new ClassicGenotypeLikelihoods();
|
||||
int k = 0;
|
||||
for (int i = 0; i < 4; i++)
|
||||
{
|
||||
|
|
@ -410,7 +683,7 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
|
|||
else { return BaseUtils.baseIndexToSimpleBase(perm[2]); }
|
||||
}
|
||||
|
||||
double Compute_discovery_lod(char ref, OldAndBustedGenotypeLikelihoods[] genotype_likelihoods)
|
||||
double Compute_discovery_lod(char ref, ClassicGenotypeLikelihoods[] genotype_likelihoods)
|
||||
{
|
||||
double pBest = 0;
|
||||
double pRef = 0;
|
||||
|
|
@ -428,7 +701,7 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
|
|||
return allele_likelihoods[BaseUtils.simpleBaseToBaseIndex(PickAlt(ref, allele_likelihoods))];
|
||||
}
|
||||
|
||||
int Compute_n_ref(char ref, OldAndBustedGenotypeLikelihoods[] genotype_likelihoods)
|
||||
int Compute_n_ref(char ref, ClassicGenotypeLikelihoods[] genotype_likelihoods)
|
||||
{
|
||||
int n = 0;
|
||||
for (int i = 0; i < genotype_likelihoods.length; i++)
|
||||
|
|
@ -440,7 +713,7 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
|
|||
return n;
|
||||
}
|
||||
|
||||
int Compute_n_het(char ref, OldAndBustedGenotypeLikelihoods[] genotype_likelihoods)
|
||||
int Compute_n_het(char ref, ClassicGenotypeLikelihoods[] genotype_likelihoods)
|
||||
{
|
||||
int n = 0;
|
||||
for (int i = 0; i < genotype_likelihoods.length; i++)
|
||||
|
|
@ -453,7 +726,7 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
|
|||
return n;
|
||||
}
|
||||
|
||||
int Compute_n_hom(char ref, OldAndBustedGenotypeLikelihoods[] genotype_likelihoods)
|
||||
int Compute_n_hom(char ref, ClassicGenotypeLikelihoods[] genotype_likelihoods)
|
||||
{
|
||||
int n = 0;
|
||||
for (int i = 0; i < genotype_likelihoods.length; i++)
|
||||
|
|
@ -466,16 +739,16 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
|
|||
}
|
||||
|
||||
// This should actually return a GLF Record
|
||||
MultiSampleCallResult MultiSampleCall(RefMetaDataTracker tracker, char ref, AlignmentContext context, List<String> sample_names)
|
||||
MultiSampleCallResult MultiSampleCall(RefMetaDataTracker tracker, char ref, AlignmentContext context, List<String> sample_names)
|
||||
{
|
||||
String in_dbsnp;
|
||||
if (tracker.lookup("DBSNP", null) != null) { in_dbsnp = "known"; } else { in_dbsnp = "novel"; }
|
||||
|
||||
AlignmentContext[] contexts = filterAlignmentContextBySample(context, sample_names, 0);
|
||||
AlignmentContext[] contexts = filterAlignmentContext(context, sample_names, 0);
|
||||
double lod = LOD(contexts);
|
||||
double strand_score = StrandScore(context);
|
||||
//EM_Result em_result = EM(contexts);
|
||||
OldAndBustedGenotypeLikelihoods population_genotype_likelihoods = HardyWeinberg(em_result.allele_likelihoods);
|
||||
ClassicGenotypeLikelihoods population_genotype_likelihoods = HardyWeinberg(em_result.allele_likelihoods);
|
||||
|
||||
//double pD = Compute_pD(em_result.genotype_likelihoods);
|
||||
//double pNull = Compute_pNull(contexts);
|
||||
|
|
@ -483,16 +756,13 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
|
|||
double discovery_lod = Compute_discovery_lod(ref, em_result.genotype_likelihoods);
|
||||
double alt_freq = Compute_alt_freq(ref, em_result.allele_likelihoods);
|
||||
|
||||
char alt = 'N';
|
||||
if (lod > 0.0) { alt = PickAlt(ref, em_result.allele_likelihoods); }
|
||||
|
||||
int n_ref = Compute_n_ref(ref, em_result.genotype_likelihoods);
|
||||
int n_het = Compute_n_het(ref, em_result.genotype_likelihoods);
|
||||
int n_hom = Compute_n_hom(ref, em_result.genotype_likelihoods);
|
||||
|
||||
discovery_output_file.printf("%s %c %c %f %f %f %f %f %s ", context.getLocation(), ref, alt, lod, strand_score, pD, pNull, discovery_lod, in_dbsnp);
|
||||
for (int i = 0; i < 4; i++) { discovery_output_file.printf("%f ", em_result.allele_likelihoods[i]); }
|
||||
discovery_output_file.printf("%f %d %d %d %d\n", alt_freq, em_result.EM_N, n_ref, n_het, n_hom);
|
||||
char alt = 'N';
|
||||
//if (lod > 0.0) { alt = PickAlt(ref, em_result.allele_likelihoods); }
|
||||
if ((n_het > 0) || (n_hom > 0)) { alt = PickAlt(ref, em_result.allele_likelihoods); }
|
||||
|
||||
for (int i = 0; i < em_result.genotype_likelihoods.length; i++)
|
||||
{
|
||||
|
|
@ -512,7 +782,7 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
|
|||
individual_output_file.printf("\n");
|
||||
}
|
||||
|
||||
return new MultiSampleCallResult(ref, alt, em_result, lod, strand_score, pD, pNull, in_dbsnp, n_ref, n_het, n_hom, em_result.EM_N, alt_freq);
|
||||
return new MultiSampleCallResult(context.getLocation(), ref, alt, em_result, lod, strand_score, pD, pNull, in_dbsnp, n_ref, n_het, n_hom, em_result.EM_N, alt_freq);
|
||||
}
|
||||
|
||||
// END Calling Functions
|
||||
|
|
@ -522,7 +792,7 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
|
|||
// Utility Functions
|
||||
|
||||
/// Filter a locus context by forward and backward
|
||||
private AlignmentContext filterAlignmentContextByStrand(AlignmentContext context, String strand)
|
||||
private AlignmentContext filterAlignmentContext(AlignmentContext context, String strand)
|
||||
{
|
||||
ArrayList<SAMRecord> reads = new ArrayList<SAMRecord>();
|
||||
ArrayList<Integer> offsets = new ArrayList<Integer>();
|
||||
|
|
@ -542,7 +812,7 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
|
|||
}
|
||||
|
||||
// Filter a locus context by sample ID
|
||||
private AlignmentContext[] filterAlignmentContextBySample(AlignmentContext context, List<String> sample_names, int downsample)
|
||||
protected AlignmentContext[] filterAlignmentContext(AlignmentContext context, List<String> sample_names, int downsample)
|
||||
{
|
||||
HashMap<String,Integer> index = new HashMap<String,Integer>();
|
||||
for (int i = 0; i < sample_names.size(); i++)
|
||||
|
|
@ -608,6 +878,36 @@ public class MultiSampleCaller extends LocusWalker<MultiSampleCaller.MultiSample
|
|||
return contexts;
|
||||
}
|
||||
|
||||
private AlignmentContext filter_each_read(AlignmentContext L)
|
||||
{
|
||||
ArrayList<SAMRecord> reads = new ArrayList<SAMRecord>();
|
||||
ArrayList<Integer> offsets = new ArrayList<Integer>();
|
||||
|
||||
for (int i = 0; i < L.getReads().size(); i++)
|
||||
{
|
||||
SAMRecord read = L.getReads().get(i);
|
||||
Integer offset = L.getOffsets().get(i);
|
||||
String RG = (String)(read.getAttribute("RG"));
|
||||
|
||||
assert(this.header != null);
|
||||
//assert(this.header.getReadGroup(RG) != null);
|
||||
if (this.header.getReadGroup(RG) == null) { continue; }
|
||||
|
||||
// skip bogus data
|
||||
if (read.getMappingQuality() == 0) { continue; }
|
||||
|
||||
String sample = this.header.getReadGroup(RG).getSample();
|
||||
//if (SAMPLE_NAME_REGEX != null) { sample = sample.replaceAll(SAMPLE_NAME_REGEX, "$1"); }
|
||||
|
||||
reads.add(read);
|
||||
offsets.add(offset);
|
||||
}
|
||||
|
||||
AlignmentContext ans = new AlignmentContext(L.getLocation(), reads, offsets);
|
||||
|
||||
return ans;
|
||||
}
|
||||
|
||||
// END Utility functions
|
||||
/////////
|
||||
|
||||
|
|
|
|||
|
|
@ -0,0 +1,469 @@
|
|||
package org.broadinstitute.sting.playground.utils;
|
||||
|
||||
import org.broadinstitute.sting.utils.*;
|
||||
import org.broadinstitute.sting.utils.Utils;
|
||||
import org.broadinstitute.sting.utils.QualityUtils;
|
||||
|
||||
import static java.lang.Math.log10;
|
||||
import static java.lang.Math.pow;
|
||||
import java.util.HashMap;
|
||||
|
||||
public class ClassicGenotypeLikelihoods {
|
||||
// precalculate these for performance (pow/log10 is expensive!)
|
||||
private static final double[] oneMinusData = new double[Byte.MAX_VALUE];
|
||||
|
||||
static {
|
||||
for (int qual = 0; qual < Byte.MAX_VALUE; qual++) {
|
||||
oneMinusData[qual] = log10(1.0 - pow(10, (qual / -10.0)));
|
||||
//oneMinusData[qual] = log10(1.0 - QualityUtils.qualToProb(qual));
|
||||
}
|
||||
}
|
||||
|
||||
private static double getOneMinusQual(final byte qual) {
|
||||
return oneMinusData[qual];
|
||||
}
|
||||
|
||||
private static final double[] oneHalfMinusData = new double[Byte.MAX_VALUE];
|
||||
|
||||
static {
|
||||
for (int qual = 0; qual < Byte.MAX_VALUE; qual++) {
|
||||
oneHalfMinusData[qual] = log10(0.5 - pow(10, (qual / -10.0)) / 2.0);
|
||||
//oneHalfMinusData[qual] = log10(0.5 - QualityUtils.qualToProb(qual) / 2.0);
|
||||
}
|
||||
}
|
||||
|
||||
private static double getOneHalfMinusQual(final byte qual) {
|
||||
return oneHalfMinusData[qual];
|
||||
}
|
||||
|
||||
public double[] likelihoods;
|
||||
public String[] genotypes;
|
||||
public int coverage;
|
||||
|
||||
// The genotype priors;
|
||||
private double priorHomRef;
|
||||
private double priorHet;
|
||||
private double priorHomVar;
|
||||
|
||||
// Store the 2nd-best base priors for on-genotype primary bases
|
||||
private HashMap<String, Double> onNextBestBasePriors = new HashMap<String, Double>();
|
||||
|
||||
// Store the 2nd-best base priors for off-genotype primary bases
|
||||
private HashMap<String, Double> offNextBestBasePriors = new HashMap<String, Double>();
|
||||
|
||||
public ClassicGenotypeLikelihoods() {
|
||||
double[] p2ndon = {0.000, 0.302, 0.366, 0.142, 0.000, 0.548, 0.370, 0.000, 0.319, 0.000};
|
||||
double[] p2ndoff = {0.480, 0.769, 0.744, 0.538, 0.575, 0.727, 0.768, 0.589, 0.762, 0.505};
|
||||
|
||||
initialize(1.0 - 1e-3, 1e-3, 1e-5, p2ndon, p2ndoff);
|
||||
}
|
||||
|
||||
public ClassicGenotypeLikelihoods(double priorHomRef, double priorHet, double priorHomVar) {
|
||||
double[] p2ndon = {0.000, 0.302, 0.366, 0.142, 0.000, 0.548, 0.370, 0.000, 0.319, 0.000};
|
||||
double[] p2ndoff = {0.480, 0.769, 0.744, 0.538, 0.575, 0.727, 0.768, 0.589, 0.762, 0.505};
|
||||
|
||||
initialize(priorHomRef, priorHet, priorHomVar, p2ndon, p2ndoff);
|
||||
}
|
||||
|
||||
public ClassicGenotypeLikelihoods(double priorHomRef, double priorHet, double priorHomVar, double[] p2ndon, double[] p2ndoff) {
|
||||
initialize(priorHomRef, priorHet, priorHomVar, p2ndon, p2ndoff);
|
||||
}
|
||||
|
||||
private void initialize(double priorHomRef, double priorHet, double priorHomVar, double[] p2ndon, double[] p2ndoff) {
|
||||
this.priorHomRef = priorHomRef;
|
||||
this.priorHet = priorHet;
|
||||
this.priorHomVar = priorHomVar;
|
||||
|
||||
likelihoods = new double[10];
|
||||
genotypes = new String[10];
|
||||
coverage = 0;
|
||||
|
||||
for (int i = 0; i < likelihoods.length; i++) { likelihoods[i] = Math.log10(0.1); }
|
||||
|
||||
genotypes[0] = "AA";
|
||||
genotypes[1] = "AC";
|
||||
genotypes[2] = "AG";
|
||||
genotypes[3] = "AT";
|
||||
genotypes[4] = "CC";
|
||||
genotypes[5] = "CG";
|
||||
genotypes[6] = "CT";
|
||||
genotypes[7] = "GG";
|
||||
genotypes[8] = "GT";
|
||||
genotypes[9] = "TT";
|
||||
|
||||
for (int genotypeIndex = 0; genotypeIndex < 10; genotypeIndex++) {
|
||||
onNextBestBasePriors.put(genotypes[genotypeIndex], p2ndon[genotypeIndex]);
|
||||
offNextBestBasePriors.put(genotypes[genotypeIndex], p2ndoff[genotypeIndex]);
|
||||
}
|
||||
}
|
||||
|
||||
public double getHomRefPrior() {
|
||||
return priorHomRef;
|
||||
}
|
||||
|
||||
public void setHomRefPrior(double priorHomRef) {
|
||||
this.priorHomRef = priorHomRef;
|
||||
}
|
||||
|
||||
public double getHetPrior() {
|
||||
return priorHet;
|
||||
}
|
||||
|
||||
public void setHetPrior(double priorHet) {
|
||||
this.priorHet = priorHet;
|
||||
}
|
||||
|
||||
public double getHomVarPrior() {
|
||||
return priorHomVar;
|
||||
}
|
||||
|
||||
public void setHomVarPrior(double priorHomVar) {
|
||||
this.priorHomVar = priorHomVar;
|
||||
}
|
||||
|
||||
public double[] getOnGenotypeSecondaryPriors() {
|
||||
double[] p2ndon = new double[10];
|
||||
|
||||
for (int genotypeIndex = 0; genotypeIndex < 10; genotypeIndex++) {
|
||||
p2ndon[genotypeIndex] = onNextBestBasePriors.get(genotypes[genotypeIndex]);
|
||||
}
|
||||
|
||||
return p2ndon;
|
||||
}
|
||||
|
||||
public void setOnGenotypeSecondaryPriors(double[] p2ndon) {
|
||||
for (int genotypeIndex = 0; genotypeIndex < 10; genotypeIndex++) {
|
||||
onNextBestBasePriors.put(genotypes[genotypeIndex], p2ndon[genotypeIndex]);
|
||||
}
|
||||
}
|
||||
|
||||
public double[] getOffGenotypeSecondaryPriors() {
|
||||
double[] p2ndoff = new double[10];
|
||||
|
||||
for (int genotypeIndex = 0; genotypeIndex < 10; genotypeIndex++) {
|
||||
p2ndoff[genotypeIndex] = offNextBestBasePriors.get(genotypes[genotypeIndex]);
|
||||
}
|
||||
|
||||
return p2ndoff;
|
||||
}
|
||||
|
||||
public void setOffGenotypeSecondaryPriors(double[] p2ndoff) {
|
||||
for (int genotypeIndex = 0; genotypeIndex < 10; genotypeIndex++) {
|
||||
offNextBestBasePriors.put(genotypes[genotypeIndex], p2ndoff[genotypeIndex]);
|
||||
}
|
||||
}
|
||||
|
||||
public void add(char ref, char read, byte qual)
|
||||
{
|
||||
if (qual <= 0) { qual = 1; }
|
||||
|
||||
if (coverage == 0)
|
||||
{
|
||||
for (int i = 0; i < likelihoods.length; i++)
|
||||
{
|
||||
likelihoods[i] = 0;
|
||||
}
|
||||
}
|
||||
double sum = 0.0;
|
||||
for (int i = 0; i < genotypes.length; i++)
|
||||
{
|
||||
double likelihood = calculateAlleleLikelihood(ref, read, genotypes[i], qual);
|
||||
likelihoods[i] += likelihood;
|
||||
}
|
||||
coverage += 1;
|
||||
}
|
||||
|
||||
public void add(char ref, char read, byte qual, ConfusionMatrix matrix, String platform)
|
||||
{
|
||||
if (qual <= 0) { qual = 1; }
|
||||
if (platform == null) { platform = "ILLUMINA"; }
|
||||
if (read == 'N') { return; }
|
||||
|
||||
if (coverage == 0)
|
||||
{
|
||||
for (int i = 0; i < likelihoods.length; i++)
|
||||
{
|
||||
likelihoods[i] = 0;
|
||||
}
|
||||
}
|
||||
double sum = 0.0;
|
||||
for (int i = 0; i < genotypes.length; i++)
|
||||
{
|
||||
char h1 = genotypes[i].charAt(0);
|
||||
char h2 = genotypes[i].charAt(1);
|
||||
|
||||
double p1 = matrix.lookup(platform, read, h1);
|
||||
double p2 = matrix.lookup(platform, read, h2);
|
||||
|
||||
double likelihood = calculateAlleleLikelihood(ref, read, genotypes[i], qual, p1, p2);
|
||||
|
||||
//System.out.printf("DBG: %c %c %s %d %f %f %f\n", ref, read, genotypes[i], qual, p1, p2, likelihood);
|
||||
|
||||
likelihoods[i] += likelihood;
|
||||
}
|
||||
coverage += 1;
|
||||
}
|
||||
|
||||
private double calculateAlleleLikelihood(char ref, char read, String genotype, byte qual) {
|
||||
if (qual == 0) {
|
||||
qual = 1;
|
||||
} // zero quals are wrong.
|
||||
|
||||
char h1 = genotype.charAt(0);
|
||||
char h2 = genotype.charAt(1);
|
||||
|
||||
double p_base;
|
||||
|
||||
if ((h1 == h2) && (h1 == read)) {
|
||||
// hom
|
||||
p_base = getOneMinusQual(qual);
|
||||
} else if ((h1 != h2) && ((h1 == read) || (h2 == read))) {
|
||||
// het
|
||||
p_base = getOneHalfMinusQual(qual);
|
||||
} else {
|
||||
// error
|
||||
p_base = qual / -10.0;
|
||||
}
|
||||
|
||||
return p_base;
|
||||
}
|
||||
|
||||
public void TEST()
|
||||
{
|
||||
double p_A2A = 1.00;
|
||||
double p_T2T = 1.00;
|
||||
|
||||
double p_A2T = 0.75;
|
||||
double p_T2A = 0.25;
|
||||
|
||||
char ref = 'A';
|
||||
|
||||
System.out.printf("\tA\tT\n");
|
||||
System.out.printf("A\t%.02f\t%.02f\n", p_A2A, p_A2T);
|
||||
System.out.printf("T\t%.02f\t%.02f\n", p_T2A, p_T2T);
|
||||
System.out.printf("\n");
|
||||
|
||||
System.out.printf("P(A,Q20|AA) = %f\n", calculateAlleleLikelihood(ref, 'A', "AA", (byte)20, p_A2A, p_A2A));
|
||||
System.out.printf("P(A,Q20|AT) = %f\n", calculateAlleleLikelihood(ref, 'A', "AT", (byte)20, p_A2A, p_A2T));
|
||||
System.out.printf("P(A,Q20|TT) = %f\n", calculateAlleleLikelihood(ref, 'A', "TT", (byte)20, p_A2T, p_A2T));
|
||||
|
||||
System.out.printf("P(T,Q20|AA) = %f\n", calculateAlleleLikelihood(ref, 'T', "AA", (byte)20, p_T2A, p_T2A));
|
||||
System.out.printf("P(T,Q20|AT) = %f\n", calculateAlleleLikelihood(ref, 'T', "AT", (byte)20, p_T2A, p_T2T));
|
||||
System.out.printf("P(T,Q20|TT) = %f\n", calculateAlleleLikelihood(ref, 'T', "TT", (byte)20, p_T2T, p_T2T));
|
||||
|
||||
//System.exit(0);
|
||||
}
|
||||
|
||||
private double calculateAlleleLikelihood(char ref, char read, String genotype, byte qual, double p1, double p2) {
|
||||
if (qual == 0) {
|
||||
qual = 1;
|
||||
} // zero quals are wrong.
|
||||
|
||||
char h1 = genotype.charAt(0);
|
||||
char h2 = genotype.charAt(1);
|
||||
|
||||
double perr = Math.pow(10.0,qual/-10.0);
|
||||
|
||||
double p_base = 0;
|
||||
|
||||
if (read == h1)
|
||||
{
|
||||
p_base += (1.0 - perr);
|
||||
}
|
||||
else
|
||||
{
|
||||
p_base += perr * p1;
|
||||
}
|
||||
|
||||
if (read == h2)
|
||||
{
|
||||
p_base += (1.0 - perr);
|
||||
}
|
||||
else
|
||||
{
|
||||
p_base += perr * p2;
|
||||
}
|
||||
|
||||
p_base = Math.log10(p_base/2.0);
|
||||
|
||||
return p_base;
|
||||
}
|
||||
|
||||
public String[] sorted_genotypes;
|
||||
public double[] sorted_likelihoods;
|
||||
|
||||
public void sort() {
|
||||
Integer[] permutation = Utils.SortPermutation(likelihoods);
|
||||
|
||||
Integer[] reverse_permutation = new Integer[permutation.length];
|
||||
for (int i = 0; i < reverse_permutation.length; i++) {
|
||||
reverse_permutation[i] = permutation[(permutation.length - 1) - i];
|
||||
}
|
||||
|
||||
sorted_genotypes = Utils.PermuteArray(genotypes, reverse_permutation);
|
||||
sorted_likelihoods = Utils.PermuteArray(likelihoods, reverse_permutation);
|
||||
}
|
||||
|
||||
public String toString(char ref) {
|
||||
this.sort();
|
||||
double sum = 0;
|
||||
String s = String.format("%s %f %f ", this.BestGenotype(), this.LodVsNextBest(), this.LodVsRef(ref));
|
||||
for (int i = 0; i < sorted_genotypes.length; i++) {
|
||||
if (i != 0) {
|
||||
s = s + " ";
|
||||
}
|
||||
s = s + sorted_genotypes[i] + ":" + String.format("%.2f", sorted_likelihoods[i]);
|
||||
sum += Math.pow(10,sorted_likelihoods[i]);
|
||||
}
|
||||
s = s + String.format(" %f", sum);
|
||||
return s;
|
||||
}
|
||||
|
||||
public void ApplyPrior(char ref, double[] allele_likelihoods)
|
||||
{
|
||||
int k = 0;
|
||||
for (int i = 0; i < 4; i++)
|
||||
{
|
||||
for (int j = i; j < 4; j++)
|
||||
{
|
||||
if (i == j)
|
||||
{
|
||||
this.likelihoods[k] += Math.log10(allele_likelihoods[i]) + Math.log10(allele_likelihoods[j]);
|
||||
}
|
||||
else
|
||||
{
|
||||
this.likelihoods[k] += Math.log10(allele_likelihoods[i]) + Math.log10(allele_likelihoods[j]) + Math.log10(2);
|
||||
}
|
||||
k++;
|
||||
}
|
||||
}
|
||||
this.sort();
|
||||
}
|
||||
|
||||
public void ApplyPrior(char ref, char alt, double p_alt) {
|
||||
for (int i = 0; i < genotypes.length; i++) {
|
||||
if ((p_alt == -1) || (p_alt <= 1e-6)) {
|
||||
if ((genotypes[i].charAt(0) == ref) && (genotypes[i].charAt(1) == ref)) {
|
||||
// hom-ref
|
||||
likelihoods[i] += Math.log10(priorHomRef);
|
||||
} else if ((genotypes[i].charAt(0) != ref) && (genotypes[i].charAt(1) != ref)) {
|
||||
// hom-nonref
|
||||
likelihoods[i] += Math.log10(priorHomVar);
|
||||
} else {
|
||||
// het
|
||||
likelihoods[i] += Math.log10(priorHet);
|
||||
}
|
||||
if (Double.isInfinite(likelihoods[i])) {
|
||||
likelihoods[i] = -1000;
|
||||
}
|
||||
} else {
|
||||
if ((genotypes[i].charAt(0) == ref) && (genotypes[i].charAt(1) == ref)) {
|
||||
// hom-ref
|
||||
likelihoods[i] += 2.0 * Math.log10(1.0 - p_alt);
|
||||
} else if ((genotypes[i].charAt(0) == alt) && (genotypes[i].charAt(1) == alt)) {
|
||||
// hom-nonref
|
||||
likelihoods[i] += 2.0 * Math.log10(p_alt);
|
||||
} else if (((genotypes[i].charAt(0) == alt) && (genotypes[i].charAt(1) == ref)) ||
|
||||
((genotypes[i].charAt(0) == ref) && (genotypes[i].charAt(1) == alt))) {
|
||||
// het
|
||||
likelihoods[i] += Math.log10((1.0 - p_alt) * p_alt * 2.0);
|
||||
} else {
|
||||
// something else (noise!)
|
||||
likelihoods[i] += Math.log10(1e-5);
|
||||
}
|
||||
|
||||
if (Double.isInfinite(likelihoods[i])) {
|
||||
likelihoods[i] = -1000;
|
||||
}
|
||||
}
|
||||
}
|
||||
this.sort();
|
||||
}
|
||||
|
||||
public void ApplyWeight(double weight)
|
||||
{
|
||||
for (int i = 0; i < genotypes.length; i++) { likelihoods[i] += Math.log10(weight); }
|
||||
this.sort();
|
||||
}
|
||||
|
||||
public void applySecondBaseDistributionPrior(String primaryBases, String secondaryBases) {
|
||||
for (int genotypeIndex = 0; genotypeIndex < genotypes.length; genotypeIndex++) {
|
||||
char firstAllele = genotypes[genotypeIndex].charAt(0);
|
||||
char secondAllele = genotypes[genotypeIndex].charAt(1);
|
||||
|
||||
int offIsGenotypic = 0;
|
||||
int offTotal = 0;
|
||||
|
||||
int onIsGenotypic = 0;
|
||||
int onTotal = 0;
|
||||
|
||||
for (int pileupIndex = 0; pileupIndex < primaryBases.length(); pileupIndex++) {
|
||||
char primaryBase = primaryBases.charAt(pileupIndex);
|
||||
|
||||
if (secondaryBases != null) {
|
||||
char secondaryBase = secondaryBases.charAt(pileupIndex);
|
||||
|
||||
if (primaryBase != firstAllele && primaryBase != secondAllele) {
|
||||
if (secondaryBase == firstAllele || secondaryBase == secondAllele) {
|
||||
offIsGenotypic++;
|
||||
}
|
||||
offTotal++;
|
||||
} else {
|
||||
if (secondaryBase == firstAllele || secondaryBase == secondAllele) {
|
||||
onIsGenotypic++;
|
||||
}
|
||||
onTotal++;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
double offPrior = MathUtils.binomialProbability(offIsGenotypic, offTotal, offNextBestBasePriors.get(genotypes[genotypeIndex]));
|
||||
double onPrior = MathUtils.binomialProbability(onIsGenotypic, onTotal, onNextBestBasePriors.get(genotypes[genotypeIndex]));
|
||||
|
||||
likelihoods[genotypeIndex] += Math.log10(offPrior) + Math.log10(onPrior);
|
||||
}
|
||||
this.sort();
|
||||
}
|
||||
|
||||
public double LodVsNextBest() {
|
||||
this.sort();
|
||||
return sorted_likelihoods[0] - sorted_likelihoods[1];
|
||||
}
|
||||
|
||||
double ref_likelihood = Double.NaN;
|
||||
|
||||
public double LodVsRef(char ref) {
|
||||
if ((this.BestGenotype().charAt(0) == ref) && (this.BestGenotype().charAt(1) == ref)) {
|
||||
ref_likelihood = sorted_likelihoods[0];
|
||||
return (-1.0 * this.LodVsNextBest());
|
||||
} else {
|
||||
for (int i = 0; i < genotypes.length; i++) {
|
||||
if ((genotypes[i].charAt(0) == ref) && (genotypes[i].charAt(1) == ref)) {
|
||||
ref_likelihood = likelihoods[i];
|
||||
}
|
||||
}
|
||||
}
|
||||
return sorted_likelihoods[0] - ref_likelihood;
|
||||
}
|
||||
|
||||
public String BestGenotype() {
|
||||
this.sort();
|
||||
return this.sorted_genotypes[0];
|
||||
}
|
||||
|
||||
public double BestPosterior() {
|
||||
this.sort();
|
||||
return this.sorted_likelihoods[0];
|
||||
}
|
||||
|
||||
public double RefPosterior(char ref)
|
||||
{
|
||||
this.LodVsRef(ref);
|
||||
return this.ref_likelihood;
|
||||
}
|
||||
|
||||
private IndelLikelihood indel_likelihood;
|
||||
public void addIndelLikelihood(IndelLikelihood indel_likelihood) { this.indel_likelihood = indel_likelihood; }
|
||||
public IndelLikelihood getIndelLikelihood() { return this.indel_likelihood; }
|
||||
|
||||
}
|
||||
|
|
@ -0,0 +1,65 @@
|
|||
package org.broadinstitute.sting.playground.utils;
|
||||
|
||||
import java.lang.*;
|
||||
import java.util.*;
|
||||
import java.io.*;
|
||||
|
||||
import org.broadinstitute.sting.utils.*;
|
||||
|
||||
public class ConfusionMatrix
|
||||
{
|
||||
private double[][] ILLUMINA;
|
||||
private double[][] solid;
|
||||
private double[][] LS454;
|
||||
|
||||
public ConfusionMatrix(String file_name)
|
||||
{
|
||||
//System.out.println("DBG: ConfusionMatrix constructor! (" + file_name + ")");
|
||||
|
||||
ILLUMINA = new double[4][4];
|
||||
solid = new double[4][4];
|
||||
LS454 = new double[4][4];
|
||||
|
||||
try
|
||||
{
|
||||
Scanner sc = new Scanner(new File(file_name));
|
||||
while (sc.hasNext())
|
||||
{
|
||||
String platform = sc.next();
|
||||
char read = sc.next().charAt(0);
|
||||
char ref = sc.next().charAt(0);
|
||||
double p = sc.nextDouble();
|
||||
|
||||
int read_i = BaseUtils.simpleBaseToBaseIndex(read);
|
||||
int ref_i = BaseUtils.simpleBaseToBaseIndex(ref);
|
||||
|
||||
if (platform.equals("ILLUMINA")) { ILLUMINA[read_i][ref_i] = p; }
|
||||
if (platform.equals("solid")) { solid[read_i][ref_i] = p; }
|
||||
if (platform.equals("LS454")) { LS454[read_i][ref_i] = p; }
|
||||
|
||||
//System.out.println("DBG: " + key + " " + p);
|
||||
}
|
||||
}
|
||||
catch (Exception e)
|
||||
{
|
||||
e.printStackTrace();
|
||||
System.exit(-1);
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
double lookup(String platform, char read, char truth)
|
||||
{
|
||||
int read_i = BaseUtils.simpleBaseToBaseIndex(read);
|
||||
int truth_i = BaseUtils.simpleBaseToBaseIndex(truth);
|
||||
|
||||
double d = 0;
|
||||
|
||||
if (platform.equals("ILLUMINA")) { d = ILLUMINA[read_i][truth_i]; }
|
||||
else if (platform.equals("solid")) { d = solid[read_i][truth_i]; }
|
||||
else if (platform.equals("LS454")) { d = LS454[read_i][truth_i]; }
|
||||
else { assert(false); }
|
||||
|
||||
return d;
|
||||
}
|
||||
}
|
||||
Loading…
Reference in New Issue