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main.cpp
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#include "BA3.h"
#include <boost/program_options.hpp>
#include <algorithm>
namespace opt = boost::program_options;
// global variables
gsl_rng * r;
std::ofstream mcmcout;
std::ofstream tracefile;
std::ofstream indivout;
std::ifstream mcmcin;
typedef std::map<string, unsigned int> IndivMap;
// map between indivID and name in input file
IndivMap indivIDMap;
// map between poplnID and popln name in input file
IndivMap poplnIDMap;
// map between locusID and locus name in input file
IndivMap locusIDMap;
// map between alleleID and allele name at each locus
std::vector<IndivMap> alleleIDMap;
// debugging variables
bool NOMIGRATEMCMC=false;
bool NOANCMCMC=false;
bool NOALLELEMCMC=false;
bool NOFSTATMCMC=false;
bool NOMISSINGDATA=false;
bool NOLIKELIHOOD=false;
int main( int argc, char **argv )
{
/* parse command line options */
string infileName;
int seed;
unsigned int mciter;
unsigned int sampling;
unsigned int burnin;
string outfileName;
double deltaM;
double deltaA;
double deltaF;
bool verbose;
bool settings;
bool genotypes;
bool trace;
bool debug;
bool nolikelihood;
int MAXLOCI;
parseComLine(argc, argv, infileName, seed, mciter, sampling, burnin, outfileName, deltaM, deltaA, deltaF, verbose, settings, genotypes, trace, debug, nolikelihood, MAXLOCI);
/* get input file name */
unsigned int noIndiv=0;
unsigned int noLoci=0;
unsigned int noPopln=0;
unsigned int noMissingGenotypes=0;
unsigned int noAlleles[MAXLOCI];
alleleIDMap.resize(MAXLOCI); //resize the alleleIDMap after getting MAXLOCI from command line
printBanner();
const char * outname = outfileName.c_str(); //convert string to const char
mcmcout.open(outname, std::ios::out);
//create file names for printing trace and genotypes files
std::string prefix = remove_extension(infileName);
std::string tracefileName = prefix + ".trace.txt";
std::string indivfileName = prefix + ".indiv.txt";
if (trace == true)
{
tracefile.open(tracefileName.c_str(), std::ios::out);
}
if (genotypes == true)
{
indivout.open(indivfileName.c_str(), std::ios::out);
}
if (nolikelihood == true)
{
NOLIKELIHOOD=true;
}
const char * inname = infileName.c_str(); //convert string to const char
mcmcin.open(inname, std::ios::in);
if (!mcmcin)
{
std::cerr << "\nerror: cannot open file: " << infileName << " quitting...\n";
exit(1);
}
// initialize gsl random number generator and specify a seed
r = gsl_rng_alloc (gsl_rng_taus);
gsl_rng_set(r,seed);
// initialize dynamic structures for data and parameters
//Indiv *sampleIndiv = new Indiv(MAXLOCI);
Indiv **sampleIndiv;
sampleIndiv = new Indiv *[MAXINDIV];
for(int i=0; i<MAXINDIV; i++)
sampleIndiv[i] = new Indiv(MAXLOCI);
std::cout << "Made new Indiv object" << std::endl;
//indiv *sampleIndiv = new indiv[MAXINDIV];
if(sampleIndiv==NULL) cerr << "ran out of memory";
// check that proposal step parameters are sane (e.g., <0 and <=1)
if((deltaM<=0)||(deltaM>1))
{ std::cerr << "\nerror: deltaM=" << deltaM << " not in interval (0,1]. " << infileName << " quitting...\n";
exit(1); }
if((deltaA<=0)||(deltaA>1))
{ std::cerr << "\nerror: deltaA=" << deltaA << " not in interval (0,1]. " << infileName << " quitting...\n";
exit(1); }
if((deltaF<=0)||(deltaF>1))
{ std::cerr << "\nerror: deltaF=" << deltaF << " not in interval (0,1]. " << infileName << " quitting...\n";
exit(1); }
vector<int> missingData;
std::cout << "Going to read input file" << std::endl;
// read input file
readInputFile(sampleIndiv, noIndiv, noLoci, noPopln, noAlleles, infileName, MAXLOCI);
std::cout << "Read input file" << std::endl;
double ***ancP;
if((ancP = new double**[noIndiv])==0) cerr << "ran out of memory";
for(unsigned int i = 0; i < noIndiv; i++)
{
ancP[i] = new double*[noPopln];
for(unsigned int j = 0; j < noPopln; j++)
ancP[i][j] = new double[3];
}
for (unsigned int j=0; j<noIndiv; j++)
{
for(unsigned int l=0;l<noPopln;l++)
{
ancP[j][l][0]=0.0;
ancP[j][l][1]=0.0;
ancP[j][l][2]=0.0;
}
}
// identify missing data and initialize imputed genotypes
for (unsigned int i=0; i<noIndiv; i++)
{
bool hasMissing=false;
for (unsigned int j=0; j<noLoci; j++)
{
if((sampleIndiv[i]->getAllele(j,0) == -1)||(sampleIndiv[i]->getAllele(j,1) == -1))
{
if(noAlleles[j] == 0)
{
std::cout << "\nAt least one locus may contain no data for all samples in your input file.\n";
}
noMissingGenotypes+=1;
sampleIndiv[i]->pushMissing(j);
sampleIndiv[i]->setAllele(j,0,gsl_rng_uniform_int(r,noAlleles[j]));
sampleIndiv[i]->setAllele(j,1,gsl_rng_uniform_int(r,noAlleles[j]));
if (!hasMissing)
{
missingData.push_back(i);
hasMissing=true;
}
}
}
}
size_t N=noIndiv;
gsl_permutation * p = gsl_permutation_alloc (N);
if (verbose)
{
cout << "\nInput file: " << infileName;
cout << "\nOutput file: " << outfileName << "\n";
cout << "Individuals: " << noIndiv << " Populations: " << noPopln << " Loci: " << noLoci;
cout << " Missing genotypes: " << noMissingGenotypes << "\n\n";
cout << "Locus:(Number of Alleles)\n";
for(unsigned int l=0; l<noLoci; l++)
{
string locusName;
IndivMap::iterator iterLocus = locusIDMap.begin();
while (iterLocus != locusIDMap.end())
{
if(iterLocus->second == l)
locusName=iterLocus->first;
iterLocus++;
}
if((l % 10)==0) cout << "\n";
cout << locusName << ":" << noAlleles[l] << " ";
}
cout << "\n\n";
}
double ***alleleFreqs;
alleleFreqs = new double**[noPopln];
for(unsigned int i = 0; i < noPopln; i++)
{
alleleFreqs[i] = new double*[noLoci];
for(unsigned int j = 0; j < noLoci; j++)
alleleFreqs[i][j] = new double[MAXALLELE];
}
double ***avgAlleleFreqs;
avgAlleleFreqs = new double**[noPopln];
for(unsigned int i = 0; i < noPopln; i++)
{
avgAlleleFreqs[i] = new double*[noLoci];
for(unsigned int j = 0; j < noLoci; j++)
avgAlleleFreqs[i][j] = new double[MAXALLELE];
}
for(unsigned int l = 0; l < noPopln; l++)
for(unsigned int i = 0; i < noLoci; i++)
for(unsigned int j = 0; j < noAlleles[i]; j++)
avgAlleleFreqs[l][i][j]=0.0;
double ***varAlleleFreqs;
varAlleleFreqs = new double**[noPopln];
for(unsigned int i = 0; i < noPopln; i++)
{
varAlleleFreqs[i] = new double*[noLoci];
for(unsigned int j = 0; j < noLoci; j++)
varAlleleFreqs[i][j] = new double[MAXALLELE];
}
for(unsigned int l = 0; l < noPopln; l++)
for(unsigned int i = 0; i < noLoci; i++)
for(unsigned int j = 0; j < noAlleles[i]; j++)
varAlleleFreqs[l][i][j]=0.0;
double **migrationRates;
migrationRates = new double*[noPopln];
for(unsigned int i = 0; i < noPopln; i++)
migrationRates[i] = new double[noPopln+1];
double **avgMigrationRates;
avgMigrationRates = new double*[noPopln];
for(unsigned int i = 0; i < noPopln; i++)
avgMigrationRates[i] = new double[noPopln+1];
for(unsigned int i = 0; i < noPopln; i++)
for (unsigned int j = 0; j < noPopln; j++)
avgMigrationRates[i][j]=0.0;
double **varMigrationRates;
varMigrationRates = new double*[noPopln];
for(unsigned int i = 0; i < noPopln; i++)
varMigrationRates[i] = new double[noPopln+1];
for(unsigned int i = 0; i < noPopln; i++)
for (unsigned int j = 0; j < noPopln; j++)
varMigrationRates[i][j]=0.0;
long int ***migrantCounts;
migrantCounts = new long int**[noPopln];
for(unsigned int i = 0; i < noPopln; i++)
{
migrantCounts[i] = new long int*[noPopln];
for(unsigned int j = 0; j < noPopln; j++)
migrantCounts[i][j] = new long int[3];
}
for(unsigned int i = 0; i < noPopln; i++)
for(unsigned int j = 0; j < noPopln; j++)
for(int k = 0; k < 3; k++)
migrantCounts[i][j][k]=0;
double *FStat = new double[noPopln];
double *avgFStat = new double[noPopln];
double *varFStat = new double[noPopln];
for(unsigned int i=0; i< noPopln; i++)
{
FStat[i]=0.0;
avgFStat[i]=0.0;
varFStat[i]=0.0;
}
for(unsigned int l=0; l<noPopln; l++)
{
for(unsigned int k=0; k<=noPopln; k++)
if((l!=k)&&(k!=noPopln))
migrationRates[l][k] = (1.0/3.0)*(1.0/noPopln);
migrationRates[l][l] = 1.0-(1.0/3.0)*((noPopln-1.0)/noPopln);
migrationRates[l][noPopln] = (1.0/3.0)*((noPopln-1.0)/noPopln);
}
getEmpiricalAlleleFreqs(alleleFreqs,sampleIndiv,noAlleles,noPopln,noLoci,noIndiv,debug);
/* uncomment for uniform distn of identical freqs in all populations */
/* for(int i=0; i < noPopln; i++)
for(int j=0; j < noLoci; j++)
for(int l=0; l < noAlleles[j]; l++)
alleleFreqs[i][j][l] = 1.0/noAlleles[j]; */
if(debug)
{
for(unsigned int i=0; i < noPopln; i++)
for(unsigned int j=0; j < noLoci; j++)
{
cout << "aF[" << i << "][" << j << "]";
for(unsigned int l=0; l < noAlleles[j]; l++)
{
std::cout.setf(std::ios::fixed, std::ios::floatfield);
cout << setprecision(3) << "[" << l << "]:" << alleleFreqs[i][j][l] << " ";
}
cout << "\n";
}
}
for(unsigned int l = 0; l < noIndiv; l++)
{
//sampleIndiv[l]->migrantAge=0;
sampleIndiv[l]->setMigrantAge(0);
//sampleIndiv[l]->migrantPopln=sampleIndiv[l]->samplePopln;
sampleIndiv[l]->setMigrantPopln(sampleIndiv[l]->getSamplePopln());
}
fillMigrantCounts(sampleIndiv,migrantCounts,noIndiv,noPopln);
for(unsigned int i = 0; i < noIndiv; i++)
//sampleIndiv[i]->logL = logLik(sampleIndiv[i],alleleFreqs,FStat,noLoci);
sampleIndiv[i]->setLogL(logLik(sampleIndiv[i],alleleFreqs,FStat,noLoci));
if(debug)
{
std::cout << "mCLp: " << migCountLogProb(migrantCounts,migrationRates,noPopln) << "\n";
for(unsigned int i = 0; i < noPopln; i++)
for(unsigned int j = 0; j < noPopln; j++)
for(int k = 0; k < 3; k++)
{
std::cout << "migrantCounts[" << i << "][" << j << "][" << k << "]:";
std::cout << (int) migrantCounts[i][j][k] << "\n";
}
}
/* Metropolis-Hastings algorithm */
/* Loop for mciter */
/* debugging variables */
unsigned long int iter=0;
double migrationAcceptRate=0.0;
double ancestryAcceptRate=0.0;
double allelefreqAcceptRate=0.0;
double FStatAcceptRate=0.0;
double GenotypeAcceptRate=0.0;
gsl_permutation_init (p);
for(unsigned int i = 1; i <= mciter; i++)
{
//indiv tempIndiv;
Indiv *tempIndiv = new Indiv(MAXLOCI);
//Indiv tempIndiv(MAXLOCI);
long int chosenIndiv;
unsigned int migrantPopln, migrantAge, samplePopln;
unsigned int migrantPopAdd, migrantAgeAdd;
double alpha;
double logPrMHR;
double logLprop;
double dtLogL;
if(!NOANCMCMC)
{
/* propose modified migrant ancestry for a random individual */
samplePopln = gsl_rng_uniform_int(r, noPopln);
proposeMigrantAncDrop(migrantPopln, migrantAge, samplePopln, noPopln, migrantCounts);
gsl_ran_shuffle (r, p->data, N, sizeof(size_t));
bool foundIndiv=false;
int k=0;
while (!foundIndiv)
{
/*if((sampleIndiv[gsl_permutation_get(p,k)].migrantPopln == migrantPopln) &&
(sampleIndiv[gsl_permutation_get(p,k)].migrantAge == migrantAge) &&
(sampleIndiv[gsl_permutation_get(p,k)].samplePopln == samplePopln))*/
if((sampleIndiv[gsl_permutation_get(p,k)]->getMigrantPopln() == migrantPopln) &&
(sampleIndiv[gsl_permutation_get(p,k)]->getMigrantAge() == migrantAge) &&
(sampleIndiv[gsl_permutation_get(p,k)]->getSamplePopln() == samplePopln))
{
chosenIndiv=gsl_permutation_get(p,k);
foundIndiv = true;
}else{
k++;
}
}
proposeMigrantAncAdd(migrantPopAdd, migrantAgeAdd,migrantPopln, migrantAge, samplePopln, noPopln);
//tempIndiv->samplePopln = sampleIndiv[chosenIndiv].samplePopln;
//tempIndiv->migrantPopln = migrantPopAdd;
//tempIndiv->migrantAge = migrantAgeAdd;
tempIndiv->setSamplePopln(sampleIndiv[chosenIndiv]->getSamplePopln());
tempIndiv->setMigrantPopln(migrantPopAdd);
tempIndiv->setMigrantAge(migrantAgeAdd);
for(unsigned int j = 0; j < noLoci; j++)
{
//tempIndiv->genotype[j][0] = sampleIndiv[chosenIndiv].genotype[j][0];
//tempIndiv->genotype[j][1] = sampleIndiv[chosenIndiv].genotype[j][1];
tempIndiv->setAllele(j,0,sampleIndiv[chosenIndiv]->getAllele(j,0));
tempIndiv->setAllele(j,1,sampleIndiv[chosenIndiv]->getAllele(j,1));
}
// calculate change of logL for genetic data with new migrant ancestry
if (!NOLIKELIHOOD)
{
logLprop = logLik(tempIndiv,alleleFreqs,FStat,noLoci);
//dtLogL = logLprop - sampleIndiv[chosenIndiv].logL;
dtLogL = logLprop - sampleIndiv[chosenIndiv]->getLogL();
}
// calculate change of logPr for migrant counts with new migrant ancestry
double dtLogPrCount=0.0;
//if ((tempIndiv->migrantPopln != sampleIndiv[chosenIndiv].migrantPopln) || (tempIndiv->migrantAge != sampleIndiv[chosenIndiv].migrantAge))
if ((tempIndiv->getMigrantPopln() != sampleIndiv[chosenIndiv]->getMigrantPopln()) || (tempIndiv->getMigrantAge() != sampleIndiv[chosenIndiv]->getMigrantAge()))
{
//if(tempIndiv->migrantAge == 0)
if(tempIndiv->getMigrantAge() == 0)
{
//dtLogPrCount += (log(1.0-3.0*migrationRates[tempIndiv->samplePopln][noPopln])-log(migrantCounts[tempIndiv->samplePopln][tempIndiv->migrantPopln][0]+1.0));
dtLogPrCount += (log(1.0-3.0*migrationRates[tempIndiv->getSamplePopln()][noPopln])-log(migrantCounts[tempIndiv->getSamplePopln()][tempIndiv->getMigrantPopln()][0]+1.0));
}
//else if (tempIndiv->migrantAge == 1)
else if (tempIndiv->getMigrantAge() == 1)
{
//dtLogPrCount += (log(migrationRates[tempIndiv->samplePopln][tempIndiv->migrantPopln])-log(migrantCounts[tempIndiv->samplePopln][tempIndiv->migrantPopln][1]+1.0));
dtLogPrCount += (log(migrationRates[tempIndiv->getSamplePopln()][tempIndiv->getMigrantPopln()])-log(migrantCounts[tempIndiv->getSamplePopln()][tempIndiv->getMigrantPopln()][1]+1.0));
}
//else if(tempIndiv->migrantAge == 2)
else if(tempIndiv->getMigrantAge() == 2)
{
//dtLogPrCount += (log(2.0*migrationRates[tempIndiv->samplePopln][tempIndiv->migrantPopln])-log(migrantCounts[tempIndiv->samplePopln][tempIndiv->migrantPopln][2]+1.0));
dtLogPrCount += (log(2.0*migrationRates[tempIndiv->getSamplePopln()][tempIndiv->getMigrantPopln()])-log(migrantCounts[tempIndiv->getSamplePopln()][tempIndiv->getMigrantPopln()][2]+1.0));
}
//if(sampleIndiv[chosenIndiv].migrantAge == 0)
if(sampleIndiv[chosenIndiv]->getMigrantAge() == 0)
{
//dtLogPrCount -= (log(1.0-3.0*migrationRates[sampleIndiv[chosenIndiv].samplePopln][noPopln]) - log(migrantCounts[sampleIndiv[chosenIndiv].samplePopln][sampleIndiv[chosenIndiv].migrantPopln][0]));
dtLogPrCount -= (log(1.0-3.0*migrationRates[sampleIndiv[chosenIndiv]->getSamplePopln()][noPopln]) - log(migrantCounts[sampleIndiv[chosenIndiv]->getSamplePopln()][sampleIndiv[chosenIndiv]->getMigrantPopln()][0]));
}
//else if (sampleIndiv[chosenIndiv].migrantAge == 1)
else if (sampleIndiv[chosenIndiv]->getMigrantAge() == 1)
{
//dtLogPrCount -= (log(migrationRates[sampleIndiv[chosenIndiv].samplePopln][sampleIndiv[chosenIndiv].migrantPopln]) - log(migrantCounts[sampleIndiv[chosenIndiv].samplePopln][sampleIndiv[chosenIndiv].migrantPopln][1]));
dtLogPrCount -= (log(migrationRates[sampleIndiv[chosenIndiv]->getSamplePopln()][sampleIndiv[chosenIndiv]->getMigrantPopln()]) - log(migrantCounts[sampleIndiv[chosenIndiv]->getSamplePopln()][sampleIndiv[chosenIndiv]->getMigrantPopln()][1]));
}
//else if(sampleIndiv[chosenIndiv].migrantAge == 2)
else if(sampleIndiv[chosenIndiv]->getMigrantAge() == 2)
{
//dtLogPrCount -= (log(2.0*migrationRates[sampleIndiv[chosenIndiv].samplePopln][sampleIndiv[chosenIndiv].migrantPopln]) - log(migrantCounts[sampleIndiv[chosenIndiv].samplePopln][sampleIndiv[chosenIndiv].migrantPopln][2]));
dtLogPrCount -= (log(2.0*migrationRates[sampleIndiv[chosenIndiv]->getSamplePopln()][sampleIndiv[chosenIndiv]->getMigrantPopln()]) - log(migrantCounts[sampleIndiv[chosenIndiv]->getSamplePopln()][sampleIndiv[chosenIndiv]->getMigrantPopln()][2]));
}
}
// Acceptance-rejection step
alpha = gsl_rng_uniform(r);
if(!NOLIKELIHOOD)
logPrMHR = dtLogPrCount + dtLogL;
else
logPrMHR = dtLogPrCount;
if(alpha <= exp(logPrMHR))
{
/*sampleIndiv[chosenIndiv].migrantAge = tempIndiv->migrantAge;
sampleIndiv[chosenIndiv].migrantPopln = tempIndiv->migrantPopln;
sampleIndiv[chosenIndiv].logL = logLprop;*/
sampleIndiv[chosenIndiv]->setMigrantAge(tempIndiv->getMigrantAge());
sampleIndiv[chosenIndiv]->setMigrantPopln(tempIndiv->getMigrantPopln());
sampleIndiv[chosenIndiv]->setLogL(logLprop);
fillMigrantCounts(sampleIndiv,migrantCounts,noIndiv,noPopln);
ancestryAcceptRate = (1.0/i)+((i-1.0)/i)*ancestryAcceptRate;
}
else ancestryAcceptRate = ((i-1.0)/i)*ancestryAcceptRate;
}
if(!NOMIGRATEMCMC)
{
/* propose a change to migration matrix */
double propMigrationRates[MAXPOPLN];
unsigned int sourcePopln;
sourcePopln = gsl_rng_uniform_int(r,noPopln);
migrantPopln = gsl_rng_uniform_int(r,noPopln-1);
if(migrantPopln >= sourcePopln) migrantPopln += 1;
for (unsigned int j=0; j < noPopln; j++)
{
if(j != migrantPopln)
propMigrationRates[j] = migrationRates[sourcePopln][j];
else
{
propMigrationRates[j] = deltaM*(gsl_rng_uniform(r)-0.5) + migrationRates[sourcePopln][j];
while ((propMigrationRates[j]<0)||(propMigrationRates[j]>(1.0/3.0-migrationRates[sourcePopln][noPopln]+migrationRates[sourcePopln][j])))
{
if (propMigrationRates[j]<0) {
propMigrationRates[j]=abs(propMigrationRates[j]);
}
if (propMigrationRates[j]>(1.0/3.0-migrationRates[sourcePopln][noPopln]+migrationRates[sourcePopln][j]))
propMigrationRates[j]=2.0*(1.0/3.0-migrationRates[sourcePopln][noPopln]+migrationRates[sourcePopln][j])-propMigrationRates[j];
}
}
}
propMigrationRates[noPopln] = migrationRates[sourcePopln][noPopln] - migrationRates[sourcePopln][migrantPopln] + propMigrationRates[migrantPopln];
propMigrationRates[sourcePopln] = 1.0 - propMigrationRates[noPopln];
double logPrCurr=0.0, logPrProp=0.0;
for(unsigned int l = 0; l < noPopln; l++)
if(sourcePopln != l)
{
logPrCurr += migrantCounts[sourcePopln][l][1]*log(migrationRates[sourcePopln][l])-gsl_sf_lnfact(migrantCounts[sourcePopln][l][1]);
logPrCurr += migrantCounts[sourcePopln][l][2]*log(2.0*migrationRates[sourcePopln][l])-gsl_sf_lnfact(migrantCounts[sourcePopln][l][2]);
}
logPrCurr += migrantCounts[sourcePopln][sourcePopln][0]*log(1.0-3*migrationRates[sourcePopln][noPopln]) - gsl_sf_lnfact(migrantCounts[sourcePopln][sourcePopln][0]);
for(unsigned int l = 0; l < noPopln; l++)
if(sourcePopln != l)
{
logPrProp += migrantCounts[sourcePopln][l][1]*log(propMigrationRates[l])-gsl_sf_lnfact(migrantCounts[sourcePopln][l][1]);
logPrProp += migrantCounts[sourcePopln][l][2]*log(2.0*propMigrationRates[l])-gsl_sf_lnfact(migrantCounts[sourcePopln][l][2]);
}
logPrProp += migrantCounts[sourcePopln][sourcePopln][0]*log(1.0-3*propMigrationRates[noPopln]) - gsl_sf_lnfact(migrantCounts[sourcePopln][sourcePopln][0]);
// Acceptance-rejection step
alpha = gsl_rng_uniform(r);
// debugging
// alpha = 0;
logPrMHR = logPrProp - logPrCurr;
if(alpha <= exp(logPrMHR))
{
for (unsigned int k=0; k<=noPopln; k++)
migrationRates[sourcePopln][k] = propMigrationRates[k];
migrationAcceptRate = (1.0/i)+((i-1.0)/i)*migrationAcceptRate;
}
else migrationAcceptRate = ((i-1.0)/i)*migrationAcceptRate;
}
if(!NOALLELEMCMC)
{
/* propose a change to a population allele frequency */
double propAlleleFreq[MAXALLELE];
double origAlleleFreq[MAXALLELE];
unsigned int chosenPopln = gsl_rng_uniform_int(r,noPopln);
unsigned int chosenLocus = gsl_rng_uniform_int(r,noLoci);
unsigned int chosenAllele = gsl_rng_uniform_int(r,noAlleles[chosenLocus]);
double logLOrig[MAXINDIV], logLProposed[MAXINDIV];
if (!NOLIKELIHOOD)
{
for (unsigned int l=0; l<noIndiv; l++)
logLOrig[l] = oneLocusLogLik(sampleIndiv[l],alleleFreqs,FStat,chosenLocus);
}
propAlleleFreq[chosenAllele] = abs(alleleFreqs[chosenPopln][chosenLocus][chosenAllele]+(gsl_rng_uniform(r)-0.5)*deltaA);
// added July 20, 2011 (further modified Nov 7, 2011)
if (propAlleleFreq[chosenAllele] > 1.0) {
propAlleleFreq[chosenAllele] = abs(1.0 - propAlleleFreq[chosenAllele]);
}
for (unsigned int l=0; l<noAlleles[chosenLocus]; l++)
if(l!=chosenAllele)
{
propAlleleFreq[l] = exp(log(alleleFreqs[chosenPopln][chosenLocus][l])+
log(1.0-propAlleleFreq[chosenAllele])-log(1.0-alleleFreqs[chosenPopln][chosenLocus][chosenAllele]));
}
// check that allele freqs sum to one and correct if needed.
double sum=0.0;
for (unsigned int l=0; l<noAlleles[chosenLocus]; l++)
sum+=propAlleleFreq[l];
if (sum>1.0001||sum<0.9999) {
for(unsigned int l=0; l<noAlleles[chosenLocus];l++)
propAlleleFreq[l]=propAlleleFreq[l]/sum;
/* double sum2=0.0;
for (int l=0; l<noAlleles[chosenLocus]-1; l++)
sum2+=propAlleleFreq[l];
propAlleleFreq[noAlleles[chosenLocus]] = 1.0 - sum2; */
}
for (unsigned int l=0; l<noAlleles[chosenLocus]; l++)
{
origAlleleFreq[l] = alleleFreqs[chosenPopln][chosenLocus][l];
alleleFreqs[chosenPopln][chosenLocus][l] = propAlleleFreq[l];
}
if (!NOLIKELIHOOD)
{
for (unsigned int l=0; l<noIndiv; l++)
logLProposed[l] = oneLocusLogLik(sampleIndiv[l],alleleFreqs,FStat,chosenLocus);
logLprop=0; dtLogL=0;
for (unsigned int l=0; l<noIndiv; l++)
{
dtLogL += (logLProposed[l] - logLOrig[l]);
}
}
// Acceptance-rejection step
alpha = gsl_rng_uniform(r);
if (!NOLIKELIHOOD)
{
logPrMHR = dtLogL;
}
else
{
logPrMHR = 1;
}
if(alpha <= exp(logPrMHR))
{
if (!NOLIKELIHOOD)
{
for (unsigned int k=0; k<noIndiv; k++)
//sampleIndiv[k]->logL = sampleIndiv[k]->logL - logLOrig[k] + logLProposed[k];
sampleIndiv[k]->setLogL(sampleIndiv[k]->getLogL() - logLOrig[k] + logLProposed[k]);
}
allelefreqAcceptRate = (1.0/i)+((i-1.0)/i)*allelefreqAcceptRate;
}
else
{
for (unsigned int k=0; k<noAlleles[chosenLocus]; k++)
alleleFreqs[chosenPopln][chosenLocus][k] = origAlleleFreq[k];
allelefreqAcceptRate = ((i-1.0)/i)*allelefreqAcceptRate;
}
}
if(!NOFSTATMCMC)
{
/* propose a change to a population inbreeding coefficient */
double origLik=0.0,propLik=0.0;
double logLVec[MAXINDIV];
double propFStat[MAXPOPLN];
for (unsigned int l=0; l<noPopln; l++)
propFStat[l]=FStat[l];
unsigned int chosenPopln = gsl_rng_uniform_int(r,noPopln);
double prop=abs(FStat[chosenPopln]+(gsl_rng_uniform(r)-0.5)*deltaF);
if (prop<=1)
propFStat[chosenPopln] = prop;
else
propFStat[chosenPopln] = 2.0-prop;
if (!NOLIKELIHOOD)
{
for(unsigned int l=0; l<noIndiv; l++)
{
//origLik+=sampleIndiv[l]->logL;
origLik+=sampleIndiv[l]->getLogL();
//if((sampleIndiv[l]->samplePopln==chosenPopln) || (sampleIndiv[l]->migrantPopln==chosenPopln))
if((sampleIndiv[l]->getSamplePopln()==chosenPopln) || (sampleIndiv[l]->getMigrantPopln()==chosenPopln))
{
logLVec[l]=logLik(sampleIndiv[l],alleleFreqs,propFStat,noLoci);
}
else
{
//logLVec[l]=sampleIndiv[l]->logL;
logLVec[l]=sampleIndiv[l]->getLogL();
}
propLik+=logLVec[l];
}
}
// Acceptance-rejection step
alpha = gsl_rng_uniform(r);
if (!NOLIKELIHOOD)
{
logPrMHR = propLik - origLik;
}
else
{
logPrMHR = 1;
}
if(alpha <= exp(logPrMHR))
{
FStat[chosenPopln] = propFStat[chosenPopln];
if (!NOLIKELIHOOD)
{
for(unsigned int l=0; l<noIndiv; l++)
{
//sampleIndiv[l]->logL = logLVec[l];
sampleIndiv[l]->setLogL(logLVec[l]);
}
}
FStatAcceptRate = (1.0/i)+((i-1.0)/i)*FStatAcceptRate;
}
else
FStatAcceptRate = ((i-1.0)/i)*FStatAcceptRate;
}
if(!NOMISSINGDATA)
{
/* propose a change to a missing genotype */
if(noMissingGenotypes>0)
{
double propLogL=0.0, origLogL=0.0;
int chooseIndiv = missingData[gsl_rng_uniform_int(r, missingData.size())];
//int chosenLocus = sampleIndiv[chooseIndiv]->missingGenotypes[gsl_rng_uniform_int(r, sampleIndiv[chooseIndiv]->missingGenotypes.size())];
int chosenLocus = sampleIndiv[chooseIndiv]->getMissingGenotype(gsl_rng_uniform_int(r, sampleIndiv[chooseIndiv]->getMissingGenSize()));
origLogL=oneLocusLogLik(sampleIndiv[chooseIndiv],alleleFreqs,FStat,chosenLocus);
//int origAllele1=sampleIndiv[chooseIndiv]->genotype[chosenLocus][0];
//int origAllele2=sampleIndiv[chooseIndiv]->genotype[chosenLocus][1];
int origAllele1=sampleIndiv[chooseIndiv]->getAllele(chosenLocus,0);
int origAllele2=sampleIndiv[chooseIndiv]->getAllele(chosenLocus,1);
//sampleIndiv[chooseIndiv]->genotype[chosenLocus][0] = gsl_rng_uniform_int(r, noAlleles[chosenLocus]);
//sampleIndiv[chooseIndiv]->genotype[chosenLocus][1] = gsl_rng_uniform_int(r, noAlleles[chosenLocus]);
sampleIndiv[chooseIndiv]->setAllele(chosenLocus,0,gsl_rng_uniform_int(r, noAlleles[chosenLocus]));
sampleIndiv[chooseIndiv]->setAllele(chosenLocus,1,gsl_rng_uniform_int(r, noAlleles[chosenLocus]));
propLogL=oneLocusLogLik(sampleIndiv[chooseIndiv],alleleFreqs,FStat,chosenLocus);
// Acceptance-rejection step
alpha = gsl_rng_uniform(r);
if (!NOLIKELIHOOD)
{
logPrMHR = propLogL - origLogL;
}
else
{
logPrMHR = 1;
}
if(alpha <= exp(logPrMHR))
{
GenotypeAcceptRate = (1.0/i)+((i-1.0)/i)*GenotypeAcceptRate;
//sampleIndiv[chooseIndiv]->logL = sampleIndiv[chooseIndiv]->logL - origLogL + propLogL;
sampleIndiv[chooseIndiv]->setLogL(sampleIndiv[chooseIndiv]->getLogL() - origLogL + propLogL);
}
else
{
//sampleIndiv[chooseIndiv]->genotype[chosenLocus][0] = origAllele1;
//sampleIndiv[chooseIndiv]->genotype[chosenLocus][1] = origAllele2;
sampleIndiv[chooseIndiv]->setAllele(chosenLocus,0,origAllele1);
sampleIndiv[chooseIndiv]->setAllele(chosenLocus,1,origAllele2);
GenotypeAcceptRate = ((i-1.0)/i)*GenotypeAcceptRate;
}
}
}
// Print logL to trace file
if (i==1) {
tracefile << "State\t" << "LogProb\t";
}
if(trace && ((i % sampling)==0))
{
double logLG=0.0, logLM=0.0;
//for (unsigned int m=0; m < noIndiv; m++) { logLG += sampleIndiv[m]->logL; }
for (unsigned int m=0; m < noIndiv; m++)
{
logLG += sampleIndiv[m]->getLogL();
}
logLM = migCountLogProb(migrantCounts,migrationRates,noPopln);
tracefile << i << "\t" << logLM + logLG << "\t";
}
// Summarize mcmc samples and print likelihoods to screen
if(verbose)
{
if((i % 10000)==0)
{
double logLG=0.0, logLM=0.0;
if (!NOLIKELIHOOD)
{
for(unsigned int m=0; m < noIndiv; m++)
{
//logLG += sampleIndiv[m]->logL;
logLG += sampleIndiv[m]->getLogL();
}
}
else
{
logLG=0;
}
logLM = migCountLogProb(migrantCounts,migrationRates,noPopln);
std::cout.setf(std::ios::fixed, std::ios::floatfield);
std::cout << std::setprecision(2) << "logP(M): " << logLM << " logL(G): ";
std::cout << logLG << " logL: " << logLM + logLG << " \% done: " << std::flush;
if(i < burnin)
std::cout << "[" << i/(mciter*1.0) << "]" << std::flush;
else
std::cout << "(" << i/(mciter*1.0) << ")" << std::flush;
std::cout << " \% accepted: (" << migrationAcceptRate << ", " << ancestryAcceptRate << ", " << allelefreqAcceptRate << ", ";
std::cout << FStatAcceptRate << ", " << GenotypeAcceptRate << ")" << "\r" << std::flush;
}
if((i % (mciter/10))==0)
{
double logLG=0.0, logLM=0.0;
if (!NOLIKELIHOOD)
{
for(unsigned int m=0; m < noIndiv; m++)
{
//logLG += sampleIndiv[m]->logL;
logLG += sampleIndiv[m]->getLogL();
}
}
else
{
logLG=0;
}
logLM = migCountLogProb(migrantCounts,migrationRates,noPopln);
std::cout.setf(std::ios::fixed, std::ios::floatfield);
std::cout << std::setprecision(2) << "logP(M): " << logLM << " logL(G): " << logLG << " logL: ";
std::cout << logLM + logLG << " \% done: "<< std::flush;
if(i < burnin)
std::cout << "[" << i/(mciter*1.0) << "]" << std::flush;
else
std::cout << "(" << i/(mciter*1.0) << ")" << std::flush;
std::cout << " \% accepted: (" << migrationAcceptRate << ", " << ancestryAcceptRate << ", " << allelefreqAcceptRate << ", ";
std::cout << FStatAcceptRate << ", " << GenotypeAcceptRate << ")" << "\n" << std::flush;
}
}
else
{
std::cout.setf(std::ios::fixed, std::ios::floatfield);
std::cout << std::setprecision(2);
if((i % (mciter/100))==0)
{
int l=0;
cout << "\r \% done: " << i/(mciter*1.0) << " | " << flush;
while(l <= (50*(i/(mciter*1.0))))
{
cout << "=" << flush;
l++;
}
}
}
// Print migration rates to trace file
if ((i==1) && trace)
{
for (unsigned int l = 0; l < noPopln; l++)
for (unsigned int k = 0; k < noPopln; k++)
tracefile << "m[" << l << "][" << k << "]\t";
tracefile << "\n";
}
if(trace && ((i % sampling)==0))
{
for (unsigned int l = 0; l < noPopln; l++)
for (unsigned int k = 0; k < noPopln; k++)
tracefile << migrationRates[l][k] << "\t" ;
tracefile << "\n";
}
if(((i % sampling)==0)&&(i > burnin))
{
double sqrDiffMean=0.0;
for (unsigned int l = 0; l < noPopln; l++)
for (unsigned int k = 0; k < noPopln; k++)
{
if(iter > 1)
{
sqrDiffMean=(migrationRates[l][k]-avgMigrationRates[l][k])*(migrationRates[l][k]-avgMigrationRates[l][k])/(iter+1.0);
varMigrationRates[l][k] = ((iter-1.0)/iter)*varMigrationRates[l][k]+sqrDiffMean;
}
avgMigrationRates[l][k] = avgMigrationRates[l][k]+(migrationRates[l][k]-avgMigrationRates[l][k])/(1.0+iter);
}
for (unsigned int l = 0; l < noPopln; l++)
for (unsigned int k = 0; k < noLoci; k++)
for(unsigned int m = 0; m < noAlleles[k]; m++)
{
if(iter > 1)
{
sqrDiffMean=(alleleFreqs[l][k][m]-avgAlleleFreqs[l][k][m])*(alleleFreqs[l][k][m]-avgAlleleFreqs[l][k][m])/(iter+1.0);
varAlleleFreqs[l][k][m] = ((iter-1.0)/iter)*varAlleleFreqs[l][k][m]+sqrDiffMean;
}
avgAlleleFreqs[l][k][m] = avgAlleleFreqs[l][k][m]+(alleleFreqs[l][k][m]-avgAlleleFreqs[l][k][m])/(1.0+iter);
}
for (unsigned int l=0; l < noPopln; l++)
{
if(iter > 1)
{
sqrDiffMean=(FStat[l]-avgFStat[l])*(FStat[l]-avgFStat[l])/(iter+1.0);
varFStat[l] = ((iter-1.0)/iter)*varFStat[l]+sqrDiffMean;
}
avgFStat[l] = avgFStat[l]+(FStat[l]-avgFStat[l])/(1.0+iter);
}
for (unsigned int l=0; l < noIndiv; l++)
{
//if (sampleIndiv[l]->migrantAge == 0)
if (sampleIndiv[l]->getMigrantAge() == 0)
{
//ancP[l][sampleIndiv[l]->samplePopln][0] = ancP[l][sampleIndiv[l]->samplePopln][0]*(iter/(iter+1.0))+(1.0/(iter+1.0));
ancP[l][sampleIndiv[l]->getSamplePopln()][0] = ancP[l][sampleIndiv[l]->getSamplePopln()][0]*(iter/(iter+1.0))+(1.0/(iter+1.0));
for(unsigned int k=0; k<noPopln; k++)
for(int b=0; b<3; b++)
//if (!((k==sampleIndiv[l]->samplePopln)&&(b==0)))
if (!((k==sampleIndiv[l]->getSamplePopln())&&(b==0)))
{
ancP[l][k][b]=ancP[l][k][b]*(iter/(iter+1.0));
}
}
else if (sampleIndiv[l]->getMigrantAge() == 1)
//if (sampleIndiv[l]->migrantAge == 1)
{
//ancP[l][sampleIndiv[l]->migrantPopln][1] = ancP[l][sampleIndiv[l]->migrantPopln][1]*(iter/(iter+1.0))+(1.0/(iter+1.0));
ancP[l][sampleIndiv[l]->getMigrantPopln()][1] = ancP[l][sampleIndiv[l]->getMigrantPopln()][1]*(iter/(iter+1.0))+(1.0/(iter+1.0));
for(unsigned int k=0; k<noPopln; k++)
{
for(unsigned int b=0; b<3; b++)
{
//if (!((k==sampleIndiv[l]->migrantPopln)&&(b==1)))
if (!((k==sampleIndiv[l]->getMigrantPopln())&&(b==1)))
{
ancP[l][k][b]=ancP[l][k][b]*(iter/(iter+1.0));
}
}
}
}
//else if(sampleIndiv[l]->migrantAge == 2)
else if(sampleIndiv[l]->getMigrantAge() == 2)
{
//ancP[l][sampleIndiv[l]->migrantPopln][2]=ancP[l][sampleIndiv[l]->migrantPopln][2]*(iter/(iter+1.0))+(1.0/(iter+1.0));
ancP[l][sampleIndiv[l]->getMigrantPopln()][2]=ancP[l][sampleIndiv[l]->getMigrantPopln()][2]*(iter/(iter+1.0))+(1.0/(iter+1.0));
for(unsigned int k=0; k<noPopln; k++)
{
for(unsigned int b=0; b<3; b++)
{
//if (!((k==sampleIndiv[l]->migrantPopln)&&(b==2)))
if (!((k==sampleIndiv[l]->getMigrantPopln())&&(b==2)))
{
ancP[l][k][b]=ancP[l][k][b]*(iter/(iter+1.0));
}
}
}
}
}
iter+=1;
}
delete tempIndiv;
}
if (!verbose)
{
cout << " | \n";
}
if(debug)
{
for(unsigned int l = 0; l < noPopln; l++)
{
for(unsigned int j = 0; j < noPopln; j++)
{
for(int k = 0; k < 3; k++)
{
std::cout << "\nmigrantCounts[" << l << "][" << j << "][" << k << "]:";
std::cout << migrantCounts[l][j][k];
}
}
}
for (unsigned int l = 0; l < noIndiv; l++)
{
///std::cout << "\nIndivID: " << l << " migrantPop: " << sampleIndiv[l]->migrantPopln << " migrantAge: " << sampleIndiv[l]->migrantAge;
std::cout << "\nIndivID: " << l << " migrantPop: " << sampleIndiv[l]->getMigrantPopln() << " migrantAge: " << sampleIndiv[l]->getMigrantAge();
//std::cout << " samplePop: " << sampleIndiv[l]->samplePopln;