//each thread will run this.
void *slave(void *ptr){
tpars *tp = (tpars *)ptr;
// fprintf(stderr,"from:%d to:%d \n",tp->from,tp->to);
for(int i=tp->from;i<tp->to;i++){
tp->skip=i;
tp->val[i] = kmin_brent(myfun,1e-6,0.5,tp,1e-6,&tp->thetas[i]);
assert(tp->thetas[i]!=1e-6);
}
pthread_exit(0);
}
/* The following function combines EM and Brent's method. When the signal from
* the data is strong, EM is faster but sometimes, EM may converge very slowly.
* When this happens, we switch to Brent's method. The idea is learned from
* Rasmus Nielsen.
*/
static double freqml(double f0, int beg, int end, const double *pdg)
{
int i;
double f;
for (i = 0, f = f0; i < ITER_TRY; ++i)
if (freq_iter(&f, pdg, beg, end) < EPS) break;
if (i == ITER_TRY) { // haven't converged yet; try Brent's method
minaux1_t a;
a.beg = beg; a.end = end; a.pdg = pdg;
kmin_brent(prob1, f0 == f? .5*f0 : f0, f, (void*)&a, EPS, &f);
}
return f;
}
double jackML(allPars *ap,int nthreads,char *fname,int nJack) {
if(nJack==-1)
nJack = ap->len;
else
nJack = std::min(ap->len,nJack);
assert(nJack>0);
double *thetas =new double[nJack];
double *val = new double[nJack];
if(nthreads>1){
pthread_t *thd = new pthread_t[nthreads];
tpars *tp = new tpars[nthreads];
int block = nJack/nthreads;
for(int i=0;i<nthreads;i++){
tp[i].thetas = thetas;
tp[i].val = val;
tp[i].ap = ap;
tp[i].from = i==0?0:tp[i-1].to;
tp[i].to = tp[i].from+block;
}
tp[nthreads-1].to = nJack;
for(int i=0;i<nthreads;i++)
pthread_create(&thd[i],NULL,slave,&tp[i]);
for(int i=0;i<nthreads;i++)
pthread_join(thd[i],NULL);
}else{ //if we do not threads
tpars tp;
tp.ap=ap;
for(int i=0;i<nJack;i++){
tp.skip=i;
val[i]=kmin_brent(myfun,1e-6,0.5-1e-6,&ap,0.0001,thetas+i);
}
}
double esd = sd(thetas,nJack);
if(fname){
FILE *fp =fopen(fname,"w");
for(int i=0;i<nJack;i++){
fprintf(fp,"%e\t%f\t%e\n",thetas[i],val[i],thetas[i]-1e6);
}
fclose(fp);
}
delete [] thetas;
delete [] val;
return esd;
}
void analysis(dat &d,int nThreads,int nJack) {
int *rowSum = new int[d.cn.size()];
int *rowMax = new int[d.cn.size()];
int *rowMaxW = new int[d.cn.size()];
int *error1 = new int[d.cn.size()];//number of non most frequent observed bases
int *error2 = new int[d.cn.size()];//sampled
size_t mat1[4]={0,0,0,0};//matrix used for fisher for method 1
size_t mat2[4]={0,0,0,0};//matrix used for fisher for method 2
size_t tab[2] = {0,0};//used for debug
for(int i=0;i<d.cn.size();i++) {
int s =d.cn[i][0];
int max=s;
int which=0;
for(int j=1;j<4;j++){
s += d.cn[i][j];
if(d.cn[i][j]>max){
max=d.cn[i][j];
which=j;
}
}
rowSum[i] = s;
rowMax[i]=max;
rowMaxW[i]=which;
aMap::iterator it= d.myMap.find(d.pos[i]);
if(it!=d.myMap.end()){//if site is hapmap site
// fprintf(stderr,"posi:%d wmax:%d all1:%d freq:%f\n",it->first,rowMaxW[i],it->second.allele1,it->second.freq);
//if maximum occuring bases is the same as allele1 from hapmap, then set freq to 1-freq
if(rowMaxW[i]==it->second.allele1)
//it->first C++ syntax for getting key of iterator
//it->second C++ syntax for getting value of key of iterator, key->value: key=pos,value=hapSite
it->second.freq=1-it->second.freq;
else
it->second.freq=it->second.freq;
// fprintf(stderr,"posi:%d wmax:%d all1:%d freq:%f\n",it->first,rowMaxW[i],it->second.allele1,it->second.freq);
// exit(0);
}
error1[i] = rowSum[i]-rowMax[i];
error2[i] = simrbinom((1.0*error1[i])/(1.0*rowSum[i]));
// fprintf(stdout,"simrbinom\t%d %d %d %d %d %d\n",rowSum[i],rowMax[i],rowMaxW[i],error1[i],error2[i],d.dist[i]);
if(error1[i]>0)
tab[1]++;
else
tab[0]++;
if(d.dist[i]==0){//this is a snpsite
mat1[0] +=error1[i];
mat1[1] +=rowSum[i]-error1[i];
mat2[0] +=error2[i];
mat2[1] +=1-error2[i];
// fprintf(stdout,"rs %d %d %d %d %d %d %d %f %d %d\n",d.pos[i],rowSum[i],rowMax[i],rowMaxW[i],error1[i],error2[i],d.dist[i],it->second.freq,it->second.allele1,it->second.allele2);
}else{
mat1[2] +=error1[i];
mat1[3] +=rowSum[i]-error1[i];
mat2[2] += error2[i];
mat2[3] += 1-error2[i];
}
}
#if 0
fprintf(stderr,"tab:%lu %lu\n",tab[0],tab[1]);
fprintf(stderr,"mat: %lu %lu %lu %lu\n",mat1[0],mat1[1],mat1[2],mat1[3]);
fprintf(stderr,"mat2: %lu %lu %lu %lu\n",mat2[0],mat2[1],mat2[2],mat2[3]);
#endif
int n11, n12, n21, n22;
double left, right, twotail, prob;
// fprintf(stderr,"--------\nMAIN RESULTS: Fisher exact test:\n");
n11=mat1[0];n12=mat1[2];n21=mat1[1];n22=mat1[3];
prob = kt_fisher_exact(n11, n12, n21, n22, &left, &right, &twotail);
// fprintf(stdout,"Method\t n11 n12 n21 n22 prob left right twotail\n");
//fprintf(stdout,"%s\t%d\t%d\t%d\t%d\t%.6g\t%.6g\t%.6g\t%.6g\n", "method1", n11, n12, n21, n22,
// prob, left, right, twotail);
n11=mat2[0];n12=mat2[2];n21=mat2[1];n22=mat2[3];
prob = kt_fisher_exact(n11, n12, n21, n22, &left, &right, &twotail);
//fprintf(stdout,"%s\t%d\t%d\t%d\t%d\t%.6g\t%.6g\t%.6g\t%.6g\n", "method2", n11, n12, n21, n22,
// prob, left, right, twotail);
//estimate how much contamination
double c= mat1[2]/(1.0*(mat1[2]+mat1[3]));//this is error for flanking site
double err= mat1[0]/(1.0*(mat1[0]+mat1[1]));//this is error for snpsite
fprintf(stderr,"Mismatch_rate_for_flanking:%f MisMatch_rate_for_snpsite:%f \n",c,err);
int *err0 =new int[d.cn.size()/9];//<-nbases of non frequent most occuring at snpsite
int *err1 =new int[d.cn.size()/9];//<-nbases of non frequent most occuring at flanking
int *d0 =new int[d.cn.size()/9];//<-seqdepth for snpsite
int *d1 =new int[d.cn.size()/9];//<-seqdepth for flanking
double *freq =new double[d.cn.size()/9];//<- freq for snpsite
for(int i=0;i<d.cn.size()/9;i++){
int adj=0;
int dep=0;
for(int j=0;j<9;j++){
if(d.dist[i*9+j]!=0){//<- flanking
adj += error1[i*9+j];
dep += rowSum[i*9+j];
}else{ //snpsite
err0[i] = error1[i*9+j];
d0[i] = rowSum[i*9+j];
freq[i] =d.myMap.find(d.pos[i*9+j])->second.freq;
}
}
err1[i] =adj;
d1[i] = dep;
#if 0
if(it==d.myMap.end()){
fprintf(stderr,"Problem finding:%d\n",d.pos[i]);
exit(0);
}
#endif
// fprintf(stdout,"cont\t%d\t%d\t%d\t%d\t%f\n",err0[i],err1[i],d0[i],d1[i],freq[i]);
}
allPars ap;
ap.len=d.cn.size()/9;
ap.seqDepth = d0;
ap.nonMajor = err0;
ap.freq = freq;
ap.eps = c;
ap.newllh =0;
ap.e1 = err1;
ap.d1=d1;
double mom,momJack,ML,mlJack,val;
ap.newllh =0;
mom= likeOldMom(d.cn.size()/9,d0,err0,freq,c,-1);
momJack = jackMom(&ap,nJack);
tpars tp;tp.ap=≈tp.skip=-1;
// print(tp.ap,"asdff1");
kmin_brent(myfun,1e-6,0.5-1e-6,&tp,0.0001,&ML);
mlJack= jackML(&ap,nThreads,NULL,nJack);
fprintf(stderr,"\nMethod1: old_llh Version: MoM:%f SE(MoM):%e ML:%f SE(ML):%e",mom,momJack,ML,mlJack);
ap.newllh =1;
mom=likeNewMom(d.cn.size()/9,d0,err0,freq,c,-1);
momJack= jackMom(&ap,nJack);
//marshall(&ap,"prem1");
val=kmin_brent(myfun,1e-6,0.5-1e-6,&tp,0.0001,&ML);
// fprintf(stderr,"\nM1: ML:%f VAL:%f\n",ML,val);
mlJack= jackML(&ap,nThreads,NULL,nJack);
fprintf(stderr,"\nMethod1: new_llh Version: MoM:%f SE(MoM):%e ML:%f SE(ML):%e",mom,momJack,ML,mlJack);
// fread(error2,sizeof(int),d.cn.size(),fopen("error2.bin","rb"));
//for(int i=0;0&&i<d.cn.size();i++)
// fprintf(stdout,"pik\t%d\n",error2[i]);
//exit(0);
for(int i=0;i<d.cn.size()/9;i++){
int adj=0;
for(int j=0;j<9;j++){
if(d.dist[i*9+j]!=0){
adj += error2[i*9+j];
}else{
err0[i] = error2[i*9+j];
freq[i] =d.myMap.find(d.pos[i*9+j])->second.freq;
// fprintf(stderr,"freq:%f\n",freq[i]);
}
}
err1[i] =adj;
d0[i] = 1;
d1[i] = 8;
#if 0
if(it==d.myMap.end()){
fprintf(stderr,"Problem finding:%d\n",d.pos[i]);
exit(0);
}
#endif
// fprintf(stdout,"cont\t%d\t%d\t%d\t%d\t%f\n",err0[i],err1[i],d0[i],d1[i],freq[i]);
}
ap.seqDepth = d0;
ap.nonMajor = err0;
ap.e1=err1;
ap.d1=d1;
ap.freq = freq;
ap.newllh =0;
mom= likeOldMom(d.cn.size()/9,d0,err0,freq,c,-1);
momJack = jackMom(&ap,nJack);
//print(tp.ap,"asdff2");
// exit(0);
val = kmin_brent(myfun,1e-6,0.5-1e-6,&tp,0.0001,&ML);
//fprintf(stderr,"\nML2:%f VAL:%f\n",ML,val);
// exit(0);
//FILE *fp = fopen("heyaa","w"); print(&ap,fp);fclose(fp);
//return;
mlJack= jackML(&ap,nThreads,NULL,nJack);
fprintf(stderr,"\nMethod2: old_llh Version: MoM:%f SE(MoM):%e ML:%f SE(ML):%e",mom,momJack,ML,mlJack);
ap.newllh =1;
mom=likeNewMom(d.cn.size()/9,d0,err0,freq,c,-1);
momJack= jackMom(&ap,nJack);
kmin_brent(myfun,1e-6,0.5-1e-6,&tp,0.0001,&ML);
mlJack= jackML(&ap,nThreads,NULL,nJack);
fprintf(stderr,"\nMethod2: new_llh Version: MoM:%f SE(MoM):%e ML:%f SE(ML):%e\n",mom,momJack,ML,mlJack);
delete [] rowSum;
delete [] rowMax;
delete [] rowMaxW;
delete [] error1;
delete [] error2;
delete [] err0;
delete [] err1;
delete [] d0;
delete [] d1;
delete [] freq;
}
