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EM.cpp
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EM.cpp
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#include<ctime>
#include<cmath>
#include<cstdio>
#include<cstdlib>
#include<cstring>
#include<cassert>
#include<string>
#include<vector>
#include<algorithm>
#include<fstream>
#include<iostream>
#include<pthread.h>
#include "utils.h"
#include "my_assert.h"
#include "sampling.h"
#include "Read.h"
#include "SingleRead.h"
#include "SingleReadQ.h"
#include "PairedEndRead.h"
#include "PairedEndReadQ.h"
#include "SingleHit.h"
#include "PairedEndHit.h"
#include "Model.h"
#include "SingleModel.h"
#include "SingleQModel.h"
#include "PairedEndModel.h"
#include "PairedEndQModel.h"
#include "Transcript.h"
#include "Transcripts.h"
#include "Refs.h"
#include "GroupInfo.h"
#include "HitContainer.h"
#include "ReadIndex.h"
#include "ReadReader.h"
#include "ModelParams.h"
#include "HitWrapper.h"
#include "BamWriter.h"
#include "WriteResults.h"
using namespace std;
bool verbose = true;
const double STOP_CRITERIA = 0.001;
const int MAX_ROUND = 10000;
const int MIN_ROUND = 20;
struct Params {
void *model;
void *reader, *hitv, *ncpv, *mhp, *countv;
};
int read_type;
int m, M; // m genes, M isoforms
READ_INT_TYPE N0, N1, N2, N_tot;
int nThreads;
bool genBamF; // If user wants to generate bam file, true; otherwise, false.
bool bamSampling; // true if sampling from read posterior distribution when bam file is generated
bool updateModel, calcExpectedWeights;
bool genGibbsOut; // generate file for Gibbs sampler
char refName[STRLEN], outName[STRLEN];
char imdName[STRLEN], statName[STRLEN];
char refF[STRLEN], cntF[STRLEN], tiF[STRLEN];
char mparamsF[STRLEN];
char modelF[STRLEN], thetaF[STRLEN];
char inpSamF[STRLEN], outBamF[STRLEN], *aux;
char out_for_gibbs_F[STRLEN];
vector<double> theta, eel; // eel : expected effective length
double *probv, **countvs;
Refs refs;
Transcripts transcripts;
ModelParams mparams;
bool hasSeed;
seedType seed;
bool appendNames;
template<class ReadType, class HitType, class ModelType>
void init(ReadReader<ReadType> **&readers, HitContainer<HitType> **&hitvs, double **&ncpvs, ModelType **&mhps) {
READ_INT_TYPE nReads;
HIT_INT_TYPE nHits;
int rt; // read type
READ_INT_TYPE nrLeft, curnr; // nrLeft : number of reads left, curnr: current number of reads
HIT_INT_TYPE nhT; // nhT : hit threshold per thread
char datF[STRLEN];
int s;
char readFs[2][STRLEN];
ReadIndex *indices[2];
ifstream fin;
readers = new ReadReader<ReadType>*[nThreads];
genReadFileNames(imdName, 1, read_type, s, readFs);
for (int i = 0; i < s; i++) {
indices[i] = new ReadIndex(readFs[i]);
}
for (int i = 0; i < nThreads; i++) {
readers[i] = new ReadReader<ReadType>(s, readFs, refs.hasPolyA(), mparams.seedLen); // allow calculation of calc_lq() function
readers[i]->setIndices(indices);
}
hitvs = new HitContainer<HitType>*[nThreads];
for (int i = 0; i < nThreads; i++) {
hitvs[i] = new HitContainer<HitType>();
}
sprintf(datF, "%s.dat", imdName);
fin.open(datF);
general_assert(fin.is_open(), "Cannot open " + cstrtos(datF) + "! It may not exist.");
fin>>nReads>>nHits>>rt;
general_assert(nReads == N1, "Number of alignable reads does not match!");
general_assert(rt == read_type, "Data file (.dat) does not have the right read type!");
//A just so so strategy for paralleling
nhT = nHits / nThreads;
nrLeft = N1;
curnr = 0;
ncpvs = new double*[nThreads];
for (int i = 0; i < nThreads; i++) {
HIT_INT_TYPE ntLeft = nThreads - i - 1; // # of threads left
general_assert(readers[i]->locate(curnr), "Read indices files do not match!");
while (nrLeft > ntLeft && (i == nThreads - 1 || hitvs[i]->getNHits() < nhT)) {
general_assert(hitvs[i]->read(fin), "Cannot read alignments from .dat file!");
--nrLeft;
if (verbose && nrLeft > 0 && nrLeft % 1000000 == 0) { cout<< "DAT "<< nrLeft << " reads left"<< endl; }
}
ncpvs[i] = new double[hitvs[i]->getN()];
memset(ncpvs[i], 0, sizeof(double) * hitvs[i]->getN());
curnr += hitvs[i]->getN();
if (verbose) { cout<<"Thread "<< i<< " : N = "<< hitvs[i]->getN()<< ", NHit = "<< hitvs[i]->getNHits()<< endl; }
}
fin.close();
mhps = new ModelType*[nThreads];
for (int i = 0; i < nThreads; i++) {
mhps[i] = new ModelType(mparams, false); // just model helper
}
probv = new double[M + 1];
countvs = new double*[nThreads];
for (int i = 0; i < nThreads; i++) {
countvs[i] = new double[M + 1];
}
if (verbose) { printf("EM_init finished!\n"); }
}
template<class ReadType, class HitType, class ModelType>
void* E_STEP(void* arg) {
Params *params = (Params*)arg;
ModelType *model = (ModelType*)(params->model);
ReadReader<ReadType> *reader = (ReadReader<ReadType>*)(params->reader);
HitContainer<HitType> *hitv = (HitContainer<HitType>*)(params->hitv);
double *ncpv = (double*)(params->ncpv);
ModelType *mhp = (ModelType*)(params->mhp);
double *countv = (double*)(params->countv);
bool needCalcConPrb = model->getNeedCalcConPrb();
ReadType read;
READ_INT_TYPE N = hitv->getN();
double sum;
vector<double> fracs; //to remove this, do calculation twice
HIT_INT_TYPE fr, to, id;
if (needCalcConPrb || updateModel) { reader->reset(); }
if (updateModel) { mhp->init(); }
memset(countv, 0, sizeof(double) * (M + 1));
for (READ_INT_TYPE i = 0; i < N; i++) {
if (needCalcConPrb || updateModel) {
general_assert(reader->next(read), "Can not load a read!");
}
fr = hitv->getSAt(i);
to = hitv->getSAt(i + 1);
fracs.resize(to - fr + 1);
sum = 0.0;
if (needCalcConPrb) { ncpv[i] = model->getNoiseConPrb(read); }
fracs[0] = probv[0] * ncpv[i];
if (fracs[0] < EPSILON) fracs[0] = 0.0;
sum += fracs[0];
for (HIT_INT_TYPE j = fr; j < to; j++) {
HitType &hit = hitv->getHitAt(j);
if (needCalcConPrb) { hit.setConPrb(model->getConPrb(read, hit)); }
id = j - fr + 1;
fracs[id] = probv[hit.getSid()] * hit.getConPrb();
if (fracs[id] < EPSILON) fracs[id] = 0.0;
sum += fracs[id];
}
if (sum >= EPSILON) {
fracs[0] /= sum;
countv[0] += fracs[0];
if (updateModel) { mhp->updateNoise(read, fracs[0]); }
if (calcExpectedWeights) { ncpv[i] = fracs[0]; }
for (HIT_INT_TYPE j = fr; j < to; j++) {
HitType &hit = hitv->getHitAt(j);
id = j - fr + 1;
fracs[id] /= sum;
countv[hit.getSid()] += fracs[id];
if (updateModel) { mhp->update(read, hit, fracs[id]); }
if (calcExpectedWeights) { hit.setConPrb(fracs[id]); }
}
}
else if (calcExpectedWeights) {
ncpv[i] = 0.0;
for (HIT_INT_TYPE j = fr; j < to; j++) {
HitType &hit = hitv->getHitAt(j);
hit.setConPrb(0.0);
}
}
}
return NULL;
}
template<class ReadType, class HitType, class ModelType>
void* calcConProbs(void* arg) {
Params *params = (Params*)arg;
ModelType *model = (ModelType*)(params->model);
ReadReader<ReadType> *reader = (ReadReader<ReadType>*)(params->reader);
HitContainer<HitType> *hitv = (HitContainer<HitType>*)(params->hitv);
double *ncpv = (double*)(params->ncpv);
ReadType read;
READ_INT_TYPE N = hitv->getN();
HIT_INT_TYPE fr, to;
assert(model->getNeedCalcConPrb());
reader->reset();
for (READ_INT_TYPE i = 0; i < N; i++) {
general_assert(reader->next(read), "Can not load a read!");
fr = hitv->getSAt(i);
to = hitv->getSAt(i + 1);
ncpv[i] = model->getNoiseConPrb(read);
for (HIT_INT_TYPE j = fr; j < to; j++) {
HitType &hit = hitv->getHitAt(j);
hit.setConPrb(model->getConPrb(read, hit));
}
}
return NULL;
}
template<class ModelType>
void writeResults(ModelType& model, double* counts) {
sprintf(modelF, "%s.model", statName);
model.write(modelF);
writeResultsEM(M, refName, imdName, transcripts, theta, eel, countvs[0], appendNames);
}
template<class ReadType, class HitType, class ModelType>
void release(ReadReader<ReadType> **readers, HitContainer<HitType> **hitvs, double **ncpvs, ModelType **mhps) {
delete[] probv;
for (int i = 0; i < nThreads; i++) {
delete[] countvs[i];
}
delete[] countvs;
for (int i = 0; i < nThreads; i++) {
delete readers[i];
delete hitvs[i];
delete[] ncpvs[i];
delete mhps[i];
}
delete[] readers;
delete[] hitvs;
delete[] ncpvs;
delete[] mhps;
}
inline bool doesUpdateModel(int ROUND) {
// return ROUND <= 20 || ROUND % 100 == 0;
return ROUND <= 10;
}
//Including initialize, algorithm and results saving
template<class ReadType, class HitType, class ModelType>
void EM() {
FILE *fo;
int ROUND;
double sum;
double bChange = 0.0, change = 0.0; // bChange : biggest change
int totNum = 0;
ModelType model(mparams); //master model
ReadReader<ReadType> **readers;
HitContainer<HitType> **hitvs;
double **ncpvs;
ModelType **mhps; //model helpers
Params fparams[nThreads];
pthread_t threads[nThreads];
pthread_attr_t attr;
int rc;
//initialize boolean variables
updateModel = calcExpectedWeights = false;
theta.clear();
theta.resize(M + 1, 0.0);
init<ReadType, HitType, ModelType>(readers, hitvs, ncpvs, mhps);
//set initial parameters
assert(N_tot > N2);
theta[0] = max(N0 * 1.0 / (N_tot - N2), 1e-8);
double val = (1.0 - theta[0]) / M;
for (int i = 1; i <= M; i++) theta[i] = val;
model.estimateFromReads(imdName);
for (int i = 0; i < nThreads; i++) {
fparams[i].model = (void*)(&model);
fparams[i].reader = (void*)readers[i];
fparams[i].hitv = (void*)hitvs[i];
fparams[i].ncpv = (void*)ncpvs[i];
fparams[i].mhp = (void*)mhps[i];
fparams[i].countv = (void*)countvs[i];
}
/* set thread attribute to be joinable */
pthread_attr_init(&attr);
pthread_attr_setdetachstate(&attr, PTHREAD_CREATE_JOINABLE);
ROUND = 0;
do {
++ROUND;
updateModel = doesUpdateModel(ROUND);
for (int i = 0; i <= M; i++) probv[i] = theta[i];
//E step
for (int i = 0; i < nThreads; i++) {
rc = pthread_create(&threads[i], &attr, E_STEP<ReadType, HitType, ModelType>, (void*)(&fparams[i]));
pthread_assert(rc, "pthread_create", "Cannot create thread " + itos(i) + " (numbered from 0) at ROUND " + itos(ROUND) + "!");
}
for (int i = 0; i < nThreads; i++) {
rc = pthread_join(threads[i], NULL);
pthread_assert(rc, "pthread_join", "Cannot join thread " + itos(i) + " (numbered from 0) at ROUND " + itos(ROUND) + "!");
}
model.setNeedCalcConPrb(false);
for (int i = 1; i < nThreads; i++) {
for (int j = 0; j <= M; j++) {
countvs[0][j] += countvs[i][j];
}
}
//add N0 noise reads
countvs[0][0] += N0;
//M step;
sum = 0.0;
for (int i = 0; i <= M; i++) sum += countvs[0][i];
assert(sum >= EPSILON);
for (int i = 0; i <= M; i++) theta[i] = countvs[0][i] / sum;
if (updateModel) {
model.init();
for (int i = 0; i < nThreads; i++) { model.collect(*mhps[i]); }
model.finish();
}
// Relative error
bChange = 0.0; totNum = 0;
for (int i = 0; i <= M; i++)
if (probv[i] >= 1e-7) {
change = fabs(theta[i] - probv[i]) / probv[i];
if (change >= STOP_CRITERIA) ++totNum;
if (bChange < change) bChange = change;
}
if (verbose) { cout<< "ROUND = "<< ROUND<< ", SUM = "<< setprecision(15)<< sum<< ", bChange = " << setprecision(6)<< bChange<< ", totNum = " << totNum<< endl; }
} while (ROUND < MIN_ROUND || (totNum > 0 && ROUND < MAX_ROUND));
// } while (ROUND < 1);
if (totNum > 0) fprintf(stderr, "Warning: RSEM reaches %d iterations before meeting the convergence criteria.\n", MAX_ROUND);
//generate output file used by Gibbs sampler
if (genGibbsOut) {
if (model.getNeedCalcConPrb()) {
for (int i = 0; i < nThreads; i++) {
rc = pthread_create(&threads[i], &attr, calcConProbs<ReadType, HitType, ModelType>, (void*)(&fparams[i]));
pthread_assert(rc, "pthread_create", "Cannot create thread " + itos(i) + " (numbered from 0) when generating files for Gibbs sampler!");
}
for (int i = 0; i < nThreads; i++) {
rc = pthread_join(threads[i], NULL);
pthread_assert(rc, "pthread_join", "Cannot join thread " + itos(i) + " (numbered from 0) when generating files for Gibbs sampler!");
}
}
model.setNeedCalcConPrb(false);
sprintf(out_for_gibbs_F, "%s.ofg", imdName);
ofstream fout(out_for_gibbs_F);
fout<< M<< " "<< N0<< endl;
for (int i = 0; i < nThreads; i++) {
READ_INT_TYPE numN = hitvs[i]->getN();
for (READ_INT_TYPE j = 0; j < numN; j++) {
HIT_INT_TYPE fr = hitvs[i]->getSAt(j);
HIT_INT_TYPE to = hitvs[i]->getSAt(j + 1);
HIT_INT_TYPE totNum = 0;
if (ncpvs[i][j] >= EPSILON) { ++totNum; fout<< "0 "<< setprecision(15)<< ncpvs[i][j]<< " "; }
for (HIT_INT_TYPE k = fr; k < to; k++) {
HitType &hit = hitvs[i]->getHitAt(k);
if (hit.getConPrb() >= EPSILON) {
++totNum;
fout<< hit.getSid()<< " "<< setprecision(15)<< hit.getConPrb()<< " ";
}
}
if (totNum > 0) { fout<< endl; }
}
}
fout.close();
}
//calculate expected weights and counts using learned parameters
//just use the raw theta learned from the data, do not correct for eel or mw
updateModel = false; calcExpectedWeights = true;
for (int i = 0; i <= M; i++) probv[i] = theta[i];
for (int i = 0; i < nThreads; i++) {
rc = pthread_create(&threads[i], &attr, E_STEP<ReadType, HitType, ModelType>, (void*)(&fparams[i]));
pthread_assert(rc, "pthread_create", "Cannot create thread " + itos(i) + " (numbered from 0) when calculating expected weights!");
}
for (int i = 0; i < nThreads; i++) {
rc = pthread_join(threads[i], NULL);
pthread_assert(rc, "pthread_join", "Cannot join thread " + itos(i) + " (numbered from 0) when calculating expected weights!");
}
model.setNeedCalcConPrb(false);
for (int i = 1; i < nThreads; i++) {
for (int j = 0; j <= M; j++) {
countvs[0][j] += countvs[i][j];
}
}
countvs[0][0] += N0;
/* destroy attribute */
pthread_attr_destroy(&attr);
sprintf(thetaF, "%s.theta", statName);
fo = fopen(thetaF, "w");
fprintf(fo, "%d\n", M + 1);
// output theta'
for (int i = 0; i < M; i++) fprintf(fo, "%.15g ", theta[i]);
fprintf(fo, "%.15g\n", theta[M]);
//calculate expected effective lengths for each isoform
calcExpectedEffectiveLengths<ModelType>(M, refs, model, eel);
polishTheta(M, theta, eel, model.getMW());
// output theta
for (int i = 0; i < M; i++) fprintf(fo, "%.15g ", theta[i]);
fprintf(fo, "%.15g\n", theta[M]);
fclose(fo);
writeResults<ModelType>(model, countvs[0]);
if (genBamF) {
sprintf(outBamF, "%s.transcript.bam", outName);
if (bamSampling) {
READ_INT_TYPE local_N;
HIT_INT_TYPE fr, to, len, id;
vector<double> arr;
engine_type engine(hasSeed ? seed : time(NULL));
uniform_01_dist uniform_01;
uniform_01_generator rg(engine, uniform_01);
if (verbose) cout<< "Begin to sample reads from their posteriors."<< endl;
for (int i = 0; i < nThreads; i++) {
local_N = hitvs[i]->getN();
for (READ_INT_TYPE j = 0; j < local_N; j++) {
fr = hitvs[i]->getSAt(j);
to = hitvs[i]->getSAt(j + 1);
len = to - fr + 1;
arr.assign(len, 0);
arr[0] = ncpvs[i][j];
for (HIT_INT_TYPE k = fr; k < to; k++) arr[k - fr + 1] = arr[k - fr] + hitvs[i]->getHitAt(k).getConPrb();
id = (arr[len - 1] < EPSILON ? -1 : sample(rg, arr, len)); // if all entries in arr are 0, let id be -1
for (HIT_INT_TYPE k = fr; k < to; k++) hitvs[i]->getHitAt(k).setConPrb(k - fr + 1 == id ? 1.0 : 0.0);
}
}
if (verbose) cout<< "Sampling is finished."<< endl;
}
BamWriter writer(inpSamF, aux, outBamF, transcripts, nThreads);
HitWrapper<HitType> wrapper(nThreads, hitvs);
writer.work(wrapper);
}
release<ReadType, HitType, ModelType>(readers, hitvs, ncpvs, mhps);
}
int main(int argc, char* argv[]) {
ifstream fin;
if (argc < 6) {
printf("Usage : rsem-run-em refName read_type sampleName imdName statName [-p #Threads] [-b samInpF has_fai? [fai_file]] [-q] [--gibbs-out] [--sampling] [--seed seed] [--append-names]\n\n");
printf(" refName: reference name\n");
printf(" read_type: 0 single read without quality score; 1 single read with quality score; 2 paired-end read without quality score; 3 paired-end read with quality score.\n");
printf(" sampleName: sample's name, including the path\n");
printf(" sampleToken: sampleName excludes the path\n");
printf(" -p: number of threads which user wants to use. (default: 1)\n");
printf(" -b: produce bam format output file. (default: off)\n");
printf(" -q: set it quiet\n");
printf(" --gibbs-out: generate output file used by Gibbs sampler. (default: off)\n");
printf(" --sampling: sample each read from its posterior distribution when BAM file is generated. (default: off)\n");
printf(" --seed uint32: the seed used for the BAM sampling. (default: off)\n");
printf(" --append-names: append transcript_name/gene_name when available. (default: off)\n");
printf("// model parameters should be in imdName.mparams.\n");
exit(-1);
}
time_t a = time(NULL);
strcpy(refName, argv[1]);
read_type = atoi(argv[2]);
strcpy(outName, argv[3]);
strcpy(imdName, argv[4]);
strcpy(statName, argv[5]);
nThreads = 1;
genBamF = false;
bamSampling = false;
genGibbsOut = false;
aux = NULL;
hasSeed = false;
appendNames = false;
for (int i = 6; i < argc; i++) {
if (!strcmp(argv[i], "-p")) { nThreads = atoi(argv[i + 1]); }
if (!strcmp(argv[i], "-b")) {
genBamF = true;
strcpy(inpSamF, argv[i + 1]);
if (atoi(argv[i + 2]) == 1) aux = argv[i + 3];
}
if (!strcmp(argv[i], "-q")) { verbose = false; }
if (!strcmp(argv[i], "--gibbs-out")) { genGibbsOut = true; }
if (!strcmp(argv[i], "--sampling")) { bamSampling = true; }
if (!strcmp(argv[i], "--seed")) {
hasSeed = true;
int len = strlen(argv[i + 1]);
seed = 0;
for (int k = 0; k < len; k++) seed = seed * 10 + (argv[i + 1][k] - '0');
}
if (!strcmp(argv[i], "--append-names")) appendNames = true;
}
general_assert(nThreads > 0, "Number of threads should be bigger than 0!");
//basic info loading
sprintf(refF, "%s.seq", refName);
refs.loadRefs(refF);
M = refs.getM();
sprintf(tiF, "%s.ti", refName);
transcripts.readFrom(tiF);
sprintf(cntF, "%s.cnt", statName);
fin.open(cntF);
general_assert(fin.is_open(), "Cannot open " + cstrtos(cntF) + "! It may not exist.");
fin>>N0>>N1>>N2>>N_tot;
fin.close();
general_assert(N1 > 0, "There are no alignable reads!");
if ((READ_INT_TYPE)nThreads > N1) nThreads = N1;
//set model parameters
mparams.M = M;
mparams.N[0] = N0; mparams.N[1] = N1; mparams.N[2] = N2;
mparams.refs = &refs;
sprintf(mparamsF, "%s.mparams", imdName);
fin.open(mparamsF);
general_assert(fin.is_open(), "Cannot open " + cstrtos(mparamsF) + "It may not exist.");
fin>> mparams.minL>> mparams.maxL>> mparams.probF;
int val; // 0 or 1 , for estRSPD
fin>>val;
mparams.estRSPD = (val != 0);
fin>> mparams.B>> mparams.mate_minL>> mparams.mate_maxL>> mparams.mean>> mparams.sd;
fin>> mparams.seedLen;
fin.close();
//run EM
switch(read_type) {
case 0 : EM<SingleRead, SingleHit, SingleModel>(); break;
case 1 : EM<SingleReadQ, SingleHit, SingleQModel>(); break;
case 2 : EM<PairedEndRead, PairedEndHit, PairedEndModel>(); break;
case 3 : EM<PairedEndReadQ, PairedEndHit, PairedEndQModel>(); break;
default : fprintf(stderr, "Unknown Read Type!\n"); exit(-1);
}
time_t b = time(NULL);
printTimeUsed(a, b, "EM.cpp");
return 0;
}