HKA.cc

/*

Copyright (C) 2003-2009 Kevin Thornton, krthornt[]@[]uci.edu

Remove the brackets to email me.

This file is part of libsequence.

libsequence is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

libsequence is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
long with libsequence.  If not, see <http://www.gnu.org/licenses/>.

*/

#include <Sequence/HKA.hpp>
#include <cmath>
#ifdef HAVE_IEEEFP_H
#include <ieeefp.h>
#endif

using std::isfinite;

namespace 
{
  double Cn(unsigned n)
  {
    double cn=0.;
    for(unsigned i=1;i<n;++i)
      {
        cn += 1./double(i);
      }
    return cn;
  }

  double Cnsq(unsigned n)
  {
    double cn=0.;
    for(unsigned i=1;i<n;++i)
      {
        cn += 1./double(i*i);
      }
    return cn;
  }
}

namespace Sequence
{
  HKAdata::HKAdata() : SA(0),SB(0),D(0),nA(0),nB(0)
  {
  }

  HKAdata::HKAdata(const HKAdata & d) : 
    SA(d.SA),SB(d.SB),D(d.D),nA(d.nA),nB(d.nB)
  {
  }
  HKAdata::HKAdata(unsigned sa,unsigned sb,double d,
          unsigned na,unsigned nb) :
    SA(sa),SB(sb),D(d),nA(na),nB(nb)
  {
  }

  HKAresults::HKAresults (const std::vector<double> & _thetas,
                          const std::vector< chisq_tuple > & _chisquareds,
                          const double & _fhat, const double & _That,
                          const double & _xsq,
                          const double & _xsqA,
                          const double & _xsqB)
    : thetas(_thetas),chisquareds(_chisquareds),fhat(_fhat),
      That(_That),xsq(_xsq),xsqA(_xsqA),xsqB(_xsqB)
  {
  }

  HKAresults calcHKA ( const std::vector< HKAdata > & data )
  {
    double sumD=0.;
    //get some summary stats that we need
    double sumTheta = 0.;
    double fhat = 0.;
    double cna,cnb=0.;
    double that=0.;
    unsigned n=0,sumSb=0;
    for(unsigned i=0;i<data.size();++i)
      {
        sumD += data[i].D;   // sum of divergence accross loci
        cna = Cn(data[i].nA);
        cnb += (data[i].nB > 1) ? Cn(data[i].nB) : 0.;
        sumTheta += double(data[i].SA)/cna;
        sumSb += data[i].SB;
        n += (data[i].nB>1)?1:0;
        //double f = (data[i].nB>1 && data[i].SA>0) ? (double(data[i].SB)*cna)/(double(data[i].SA)*cnb): 1.;
        //      n += (data[i].nB>=1 && data[i].SA>0) ? 1 : 0;
        //      fhat += f;
      }
    cnb /= n;
    fhat = ( isfinite(cnb) && cnb > 0. ) ? double(sumSb)/(sumTheta*cnb) : 1.;
    that = double(sumD)/sumTheta - (0.5*(1.+fhat));
    std::vector<double> thetas(data.size());
    std::vector< HKAresults::chisq_tuple > chisquareds;
    double xsq = 0.,xsqA = 0., xsqB = 0;
    //now, get the theta estimates for each locus,
    //and count up the xsq statistic

    double ESA,VSA,ESB,VSB,ED,VD;
    for(unsigned i=0;i<data.size();++i)
      {
        cna = Cn(data[i].nA);
        cnb = Cn(data[i].nB);
        thetas[i] = double(double(data[i].SA) +
                           double(data[i].SB)+ 
                           data[i].D)/
          (that+0.5*(1+fhat)+cna+fhat*cnb);
        
        ESA = thetas[i]*cna; 
        VSA = ESA + thetas[i]*thetas[i]*Cnsq(data[i].nA);
        ESB =  fhat*thetas[i]*cnb;
        VSB =  ESB + fhat*fhat*thetas[i]*thetas[i]*Cnsq(data[i].nB);
        ED = thetas[i]*(that + 0.5*(1.+fhat));
        VD = ED + (thetas[i]*0.5*(1.+fhat))*(thetas[i]*0.5*(1.+fhat));
        double xsq_t=0.,xsqA_t=0.,xsqB_t=0.,xsqpoly=0.;
        const double spA = (double(data[i].SA)-ESA)*(double(data[i].SA)-ESA)/VSA;
        xsq_t += spA;
        xsqA_t += spA;
        xsqpoly = xsqA_t;
        const double sp2 = (double(data[i].SB)-ESB)*(double(data[i].SB)-ESB)/VSB;
        if (isfinite(sp2)) 
          {
            xsq_t += sp2;
            xsqpoly += sp2;
          }
        xsqB_t += sp2; //this will be not finite if n=1 in species 2, which is the desired behavior
        const double d = (data[i].D-ED)*(data[i].D-ED)/VD;
        xsq_t += d;
        chisquareds.push_back( boost::make_tuple(xsqpoly,d,xsqA_t,xsqB_t) );
        xsq += xsq_t;
        xsqA_t += d;
        xsqB_t += d;
        xsqA += xsqA_t;
        xsqB += xsqB_t;
      }
    return HKAresults( thetas,chisquareds,fhat,that,xsq,xsqA,xsqB );
  }
}

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