using namespace std;
struct Params {
- int no, nsamples;
- FILE *fo;
- engine_type *engine;
- double *pme_c, *pve_c; //posterior mean and variance vectors on counts
+ int no, nsamples;
+ FILE *fo;
+ engine_type *engine;
+ double *pme_c, *pve_c; //posterior mean and variance vectors on counts
double *pme_tpm, *pme_fpkm;
+
+ double *pve_c_genes, *pve_c_trans;
};
-
struct Item {
int sid;
double conprb;
vector<double> pme_c, pve_c; //global posterior mean and variance vectors on counts
vector<double> pme_tpm, pme_fpkm;
-bool var_opt;
bool quiet;
Params *paramsArray;
bool hasSeed;
seedType seed;
+int m;
+char groupF[STRLEN];
+GroupInfo gi;
+
+bool alleleS;
+int m_trans;
+GroupInfo gt, ta;
+vector<double> pve_c_genes, pve_c_trans;
+
+void load_group_info(char* refName) {
+ // Load group info
+ sprintf(groupF, "%s.grp", refName);
+ gi.load(groupF);
+ m = gi.getm();
+
+ alleleS = isAlleleSpecific(refName, >, &ta); // if allele-specific
+ m_trans = (alleleS ? ta.getm() : 0);
+
+ if (verbose) { printf("Loading group information is finished!\n"); }
+}
+
void load_data(char* refName, char* statName, char* imdName) {
ifstream fin;
string line;
totc = N0 + N1 + (M + 1);
- if (verbose) { printf("Loading Data is finished!\n"); }
+ if (verbose) { printf("Loading data is finished!\n"); }
}
template<class ModelType>
memset(paramsArray[i].pme_tpm, 0, sizeof(double) * (M + 1));
paramsArray[i].pme_fpkm = new double[M + 1];
memset(paramsArray[i].pme_fpkm, 0, sizeof(double) * (M + 1));
+
+ paramsArray[i].pve_c_genes = new double[m];
+ memset(paramsArray[i].pve_c_genes, 0, sizeof(double) * m);
+
+ paramsArray[i].pve_c_trans = NULL;
+ if (alleleS) {
+ paramsArray[i].pve_c_trans = new double[m_trans];
+ memset(paramsArray[i].pve_c_trans, 0, sizeof(double) * m_trans);
+ }
}
engineFactory::finish();
calcExpressionValues(M, theta, eel, tpm, fpkm);
for (int i = 0; i <= M; i++) {
params->pme_c[i] += counts[i] - 1;
- params->pve_c[i] += (counts[i] - 1) * (counts[i] - 1);
+ params->pve_c[i] += double(counts[i] - 1) * (counts[i] - 1);
params->pme_tpm[i] += tpm[i];
params->pme_fpkm[i] += fpkm[i];
}
+
+ for (int i = 0; i < m; i++) {
+ int b = gi.spAt(i), e = gi.spAt(i + 1);
+ double count = 0.0;
+ for (int j = b; j < e; j++) count += counts[j] - 1;
+ params->pve_c_genes[i] += count * count;
+ }
+
+ if (alleleS)
+ for (int i = 0; i < m_trans; i++) {
+ int b = ta.spAt(i), e = ta.spAt(i + 1);
+ double count = 0.0;
+ for (int j = b; j < e; j++) count += counts[j] - 1;
+ params->pve_c_trans[i] += count * count;
+ }
}
}
pve_c.assign(M + 1, 0);
pme_tpm.assign(M + 1, 0);
pme_fpkm.assign(M + 1, 0);
+
+ pve_c_genes.assign(m, 0);
+ pve_c_trans.clear();
+ if (alleleS) pve_c_trans.assign(m_trans, 0);
+
for (int i = 0; i < nThreads; i++) {
fclose(paramsArray[i].fo);
delete paramsArray[i].engine;
pme_tpm[j] += paramsArray[i].pme_tpm[j];
pme_fpkm[j] += paramsArray[i].pme_fpkm[j];
}
+
+ for (int j = 0; j < m; j++)
+ pve_c_genes[j] += paramsArray[i].pve_c_genes[j];
+
+ if (alleleS)
+ for (int j = 0; j < m_trans; j++)
+ pve_c_trans[j] += paramsArray[i].pve_c_trans[j];
+
delete[] paramsArray[i].pme_c;
delete[] paramsArray[i].pve_c;
delete[] paramsArray[i].pme_tpm;
delete[] paramsArray[i].pme_fpkm;
+
+ delete[] paramsArray[i].pve_c_genes;
+ if (alleleS) delete[] paramsArray[i].pve_c_trans;
}
delete[] paramsArray;
-
for (int i = 0; i <= M; i++) {
pme_c[i] /= NSAMPLES;
- pve_c[i] = (pve_c[i] - NSAMPLES * pme_c[i] * pme_c[i]) / (NSAMPLES - 1);
+ pve_c[i] = (pve_c[i] - double(NSAMPLES) * pme_c[i] * pme_c[i]) / double(NSAMPLES - 1);
+ if (pve_c[i] < 0.0) pve_c[i] = 0.0;
pme_tpm[i] /= NSAMPLES;
pme_fpkm[i] /= NSAMPLES;
}
+
+ for (int i = 0; i < m; i++) {
+ int b = gi.spAt(i), e = gi.spAt(i + 1);
+ double pme_c_gene = 0.0;
+ for (int j = b; j < e; j++) pme_c_gene += pme_c[j];
+ pve_c_genes[i] = (pve_c_genes[i] - double(NSAMPLES) * pme_c_gene * pme_c_gene) / double(NSAMPLES - 1);
+ if (pve_c_genes[i] < 0.0) pve_c_genes[i] = 0.0;
+ }
+
+ if (alleleS)
+ for (int i = 0; i < m_trans; i++) {
+ int b = ta.spAt(i), e = ta.spAt(i + 1);
+ double pme_c_tran = 0.0;
+ for (int j = b; j < e; j++) pme_c_tran += pme_c[j];
+ pve_c_trans[i] = (pve_c_trans[i] - double(NSAMPLES) * pme_c_tran * pme_c_tran) / double(NSAMPLES - 1);
+ if (pve_c_trans[i] < 0.0) pve_c_trans[i] = 0.0;
+ }
}
int main(int argc, char* argv[]) {
if (argc < 7) {
- printf("Usage: rsem-run-gibbs reference_name imdName statName BURNIN NSAMPLES GAP [-p #Threads] [--var] [--seed seed] [-q]\n");
+ printf("Usage: rsem-run-gibbs reference_name imdName statName BURNIN NSAMPLES GAP [-p #Threads] [--seed seed] [-q]\n");
exit(-1);
}
GAP = atoi(argv[6]);
nThreads = 1;
- var_opt = false;
hasSeed = false;
quiet = false;
for (int i = 7; i < argc; i++) {
if (!strcmp(argv[i], "-p")) nThreads = atoi(argv[i + 1]);
- if (!strcmp(argv[i], "--var")) var_opt = true;
if (!strcmp(argv[i], "--seed")) {
hasSeed = true;
int len = strlen(argv[i + 1]);
printf("Warning: Number of samples is less than number of threads! Change the number of threads to %d!\n", nThreads);
}
+ load_group_info(refName);
load_data(refName, statName, imdName);
sprintf(modelF, "%s.model", statName);
if (verbose) printf("Gibbs finished!\n");
- writeResultsGibbs(M, refName, imdName, pme_c, pme_fpkm, pme_tpm);
-
- if (var_opt) {
- char varF[STRLEN];
-
- // Load group info
- int m;
- GroupInfo gi;
- char groupF[STRLEN];
- sprintf(groupF, "%s.grp", refName);
- gi.load(groupF);
- m = gi.getm();
-
- sprintf(varF, "%s.var", statName);
- FILE *fo = fopen(varF, "w");
- general_assert(fo != NULL, "Cannot open " + cstrtos(varF) + "!");
- for (int i = 0; i < m; i++) {
- int b = gi.spAt(i), e = gi.spAt(i + 1), number_of_isoforms = e - b;
- for (int j = b; j < e; j++) {
- fprintf(fo, "%s\t%d\t%.15g\t%.15g\n", refs.getRef(j).getName().c_str(), number_of_isoforms, pme_c[j], pve_c[j]);
- }
- }
- fclose(fo);
- }
-
+ writeResultsGibbs(M, m, m_trans, gi, gt, ta, alleleS, imdName, pme_c, pme_fpkm, pme_tpm, pve_c, pve_c_genes, pve_c_trans);
+
delete mw; // delete the copy
return 0;
projects / rsem.git / blobdiff