#include<pthread.h>
#include "utils.h"
+#include "sampling.h"
#include "Read.h"
#include "SingleRead.h"
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
indices[i] = new ReadIndex(readFs[i]);
}
for (int i = 0; i < nThreads; i++) {
- readers[i] = new ReadReader<ReadType>(s, readFs);
+ readers[i] = new ReadReader<ReadType>(s, readFs, refs.hasPolyA(), mparams.seedLen); // allow calculation of calc_lq() function
readers[i]->setIndices(indices);
}
fprintf(fo, "%.15g%c", tau[i], (i < M ? '\t' : '\n'));
for (int i = 1; i <= M; i++) {
const Transcript& transcript = transcripts.getTranscriptAt(i);
- fprintf(fo, "%s%c", transcript.getLeft().c_str(), (i < M ? '\t' : '\n'));
+ fprintf(fo, "%s%c", transcript.getGeneID().c_str(), (i < M ? '\t' : '\n'));
}
fclose(fo);
}
inline bool doesUpdateModel(int ROUND) {
- //return false; // never update, for debugging only
- return ROUND <= 20 || ROUND % 100 == 0;
+ // return ROUND <= 20 || ROUND % 100 == 0;
+ return ROUND <= 10;
}
//Including initialize, algorithm and results saving
}
if (verbose) printf("ROUND = %d, SUM = %.15g, bChange = %f, totNum = %d\n", ROUND, sum, bChange, totNum);
- } while (ROUND < MIN_ROUND || totNum > 0 && ROUND < MAX_ROUND);
+ } while (ROUND < MIN_ROUND || (totNum > 0 && ROUND < MAX_ROUND));
//while (ROUND < MAX_ROUND);
if (totNum > 0) fprintf(stderr, "Warning: RSEM reaches %d iterations before meeting the convergence criteria.\n", MAX_ROUND);
//calculate expected weights and counts using learned parameters
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]));
if (rc != 0) { fprintf(stderr, "Cannot create thread %d when calculate expected weights! (numbered from 0)\n", i); exit(-1); }
writeResults<ModelType>(model, countvs[0]);
if (genBamF) {
- sprintf(outBamF, "%s.bam", outName);
- if (transcripts.getType() == 0) {
- sprintf(chr_list, "%s.chrlist", refName);
- pt_chr_list = (char*)(&chr_list);
+ sprintf(outBamF, "%s.transcript.bam", outName);
+
+ if (bamSampling) {
+ int local_N;
+ int fr, to, len, id;
+ vector<double> arr;
+ arr.clear();
+
+ if (verbose) printf("Begin to sample reads from their posteriors.\n");
+ for (int i = 0; i < nThreads; i++) {
+ local_N = hitvs[i]->getN();
+ for (int j = 0; j < local_N; j++) {
+ fr = hitvs[i]->getSAt(j);
+ to = hitvs[i]->getSAt(j + 1);
+ len = to - fr + 1;
+ arr.resize(len);
+ arr[0] = ncpvs[i][j];
+ for (int k = fr; k < to; k++) arr[k - fr + 1] = arr[k - fr] + hitvs[i]->getHitAt(k).getConPrb();
+ id = (arr[len - 1] < EPSILON ? -1 : sample(arr, len)); // if all entries in arr are 0, let id be -1
+ for (int k = fr; k < to; k++) hitvs[i]->getHitAt(k).setConPrb(k - fr + 1 == id ? 1.0 : 0.0);
+ }
+ }
+ if (verbose) printf("Sampling is finished.\n");
}
- BamWriter writer(inpSamType, inpSamF, pt_fn_list, outBamF, pt_chr_list);
+ BamWriter writer(inpSamType, inpSamF, pt_fn_list, outBamF, transcripts);
HitWrapper<HitType> wrapper(nThreads, hitvs);
- writer.work(wrapper, transcripts);
+ writer.work(wrapper);
}
release<ReadType, HitType, ModelType>(readers, hitvs, ncpvs, mhps);
bool quiet = false;
if (argc < 5) {
- printf("Usage : rsem-run-em refName read_type sampleName sampleToken [-p #Threads] [-b samInpType samInpF has_fn_list_? [fn_list]] [-q] [--gibbs-out]\n\n");
+ printf("Usage : rsem-run-em refName read_type sampleName sampleToken [-p #Threads] [-b samInpType samInpF has_fn_list_? [fn_list]] [-q] [--gibbs-out] [--sampling]\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(" -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 use by Gibbs sampler. (default: off)\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("// model parameters should be in imdName.mparams.\n");
exit(-1);
}
nThreads = 1;
genBamF = false;
+ bamSampling = false;
genGibbsOut = false;
pt_fn_list = pt_chr_list = NULL;
}
if (!strcmp(argv[i], "-q")) { quiet = true; }
if (!strcmp(argv[i], "--gibbs-out")) { genGibbsOut = true; }
+ if (!strcmp(argv[i], "--sampling")) { bamSampling = true; }
}
if (nThreads <= 0) { fprintf(stderr, "Number of threads should be bigger than 0!\n"); exit(-1); }
//assert(nThreads > 0);