64 lines
2.2 KiB
Java
Executable File
64 lines
2.2 KiB
Java
Executable File
package org.broadinstitute.sting.playground.utils;
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import org.broadinstitute.sting.playground.gatk.walkers.AlleleFrequencyWalker;
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public class AlleleFrequencyEstimate {
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//AlleleFrequencyEstimate();
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public String location;
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public char ref;
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public char alt;
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public int N;
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public double qhat;
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public double qstar;
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public double LOD;
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public int depth;
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public double getQstar()
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{
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return qstar;
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}
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public double getLOD()
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{
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return LOD;
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}
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public AlleleFrequencyEstimate(String location, char ref, char alt, int N, double qhat, double qstar, double LOD, int depth)
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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.N = N;
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this.qhat = qhat;
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this.qstar = qstar;
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this.LOD = LOD;
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this.depth = depth;
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}
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public String asTabularString() {
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return String.format("RESULT %s %c %c %f %f %f %d\n",
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location,
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ref,
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alt,
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qhat,
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qstar,
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LOD,
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depth);
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}
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public String asString() {
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// Print out the called bases
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// Notes: switched from qhat to qstar because qhat doesn't work at n=1 (1 observed base) where having a single non-ref
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// base has you calculate qstar = 0.0 and qhat = 0.49 and that leads to a genotype predicition of AG according
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// to qhat, but AA according to qstar. This needs to be further investigated to see whether we really want
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// to use qstar, but make N (number of chormosomes) switch to n (number of reads at locus) for n=1
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long numNonrefBases = Math.round(qstar * N);
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long numRefBases = N - numNonrefBases;
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if (ref < alt) { // order bases alphabetically
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return AlleleFrequencyWalker.repeat(ref, numRefBases) + AlleleFrequencyWalker.repeat(alt, numNonrefBases);
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}else{
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return AlleleFrequencyWalker.repeat(alt, numNonrefBases) + AlleleFrequencyWalker.repeat(ref, numRefBases);
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}
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}
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}
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