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/*
Genome-wide Efficient Mixed Model Association (GEMMA)
Copyright (C) 2011-2017 Xiang Zhou
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef __BSLMM_H__
#define __BSLMM_H__
#include <vector>
#include <map>
#include <gsl/gsl_rng.h>
#include <gsl/gsl_randist.h>
#include "param.h"
using namespace std;
class BSLMM {
public:
// IO-related parameters.
int a_mode;
size_t d_pace;
string file_bfile;
string file_geno;
string file_out;
string path_out;
// LMM related parameters
double l_min;
double l_max;
size_t n_region;
double pve_null;
double pheno_mean;
// BSLMM MCMC related parameters
double h_min, h_max, h_scale; //priors for h
double rho_min, rho_max, rho_scale; //priors for rho
double logp_min, logp_max, logp_scale; //priors for log(pi)
size_t s_min, s_max; //minimum and maximum number of gammas
size_t w_step; //number of warm up/burn in iterations
size_t s_step; //number of sampling iterations
size_t r_pace; //record pace
size_t w_pace; //write pace
size_t n_accept; //number of acceptance
size_t n_mh; //number of MH steps within each iteration
double geo_mean; //mean of the geometric distribution
long int randseed;
double trace_G;
HYPBSLMM cHyp_initial;
// Summary statistics
size_t ni_total, ns_total; //number of total individuals and snps
size_t ni_test, ns_test; //number of individuals and snps used for analysis
size_t n_cvt; //number of covariates
double time_UtZ;
double time_Omega; //time spent on optimization iterations
double time_Proposal; //time spent on constructing the proposal distribution for gamma (i.e. lmm or lm analysis)
vector<int> indicator_idv; //indicator for individuals (phenotypes), 0 missing, 1 available for analysis
vector<int> indicator_snp; //sequence indicator for SNPs: 0 ignored because of (a) maf, (b) miss, (c) non-poly; 1 available for analysis
vector<SNPINFO> snpInfo; //record SNP information
// Not included in PARAM
gsl_rng *gsl_r;
gsl_ran_discrete_t *gsl_t;
map<size_t, size_t> mapRank2pos;
// Main Functions
void CopyFromParam (PARAM &cPar);
void CopyToParam (PARAM &cPar);
void RidgeR(const gsl_matrix *U, const gsl_matrix *UtX, const gsl_vector *Uty, const gsl_vector *eval, const double lambda);
void MCMC (const gsl_matrix *U, const gsl_matrix *UtX, const gsl_vector *Uty, const gsl_vector *K_eval, const gsl_vector *y);
void WriteLog ();
void WriteLR ();
void WriteBV (const gsl_vector *bv);
void WriteParam (vector<pair<double, double> > &beta_g, const gsl_vector *alpha, const size_t w);
void WriteParam (const gsl_vector *alpha);
void WriteResult (const int flag, const gsl_matrix *Result_hyp, const gsl_matrix *Result_gamma, const size_t w_col);
//Subfunctions inside MCMC
void CalcPgamma (double *p_gammar);
double CalcPveLM (const gsl_matrix *UtXgamma, const gsl_vector *Uty, const double sigma_a2);
void InitialMCMC (const gsl_matrix *UtX, const gsl_vector *Uty, vector<size_t> &rank_old, class HYPBSLMM &cHyp, vector<pair<size_t, double> > &pos_loglr);
double CalcPosterior (const gsl_vector *Uty, const gsl_vector *K_eval, gsl_vector *Utu, gsl_vector *alpha_prime, class HYPBSLMM &cHyp);
double CalcPosterior (const gsl_matrix *UtXgamma, const gsl_vector *Uty, const gsl_vector *K_eval, gsl_vector *UtXb, gsl_vector *Utu, gsl_vector *alpha_prime, gsl_vector *beta, class HYPBSLMM &cHyp);
void CalcCC_PVEnZ (const gsl_matrix *U, const gsl_vector *Utu, gsl_vector *z_hat, class HYPBSLMM &cHyp);
void CalcCC_PVEnZ (const gsl_matrix *U, const gsl_vector *UtXb, const gsl_vector *Utu, gsl_vector *z_hat, class HYPBSLMM &cHyp);
double CalcREMLE (const gsl_matrix *Utw, const gsl_vector *Uty, const gsl_vector *K_eval);
double CalcLR (const gsl_matrix *U, const gsl_matrix *UtX, const gsl_vector *Uty, const gsl_vector *K_eval, vector<pair<size_t, double> > &loglr_sort); //calculate the maximum marginal likelihood ratio for each analyzed SNPs with gemma, use it to rank SNPs
void SampleZ (const gsl_vector *y, const gsl_vector *z_hat, gsl_vector *z);
double ProposeHnRho (const class HYPBSLMM &cHyp_old, class HYPBSLMM &cHyp_new, const size_t &repeat);
double ProposePi (const class HYPBSLMM &cHyp_old, class HYPBSLMM &cHyp_new, const size_t &repeat);
double ProposeGamma (const vector<size_t> &rank_old, vector<size_t> &rank_new, const double *p_gamma, const class HYPBSLMM &cHyp_old, class HYPBSLMM &cHyp_new, const size_t &repeat);
void SetXgamma (gsl_matrix *Xgamma, const gsl_matrix *X, vector<size_t> &rank);
void CalcXtX (const gsl_matrix *X_new, const gsl_vector *y, const size_t s_size, gsl_matrix *XtX_new, gsl_vector *Xty_new);
void SetXgamma (const gsl_matrix *X, const gsl_matrix *X_old, const gsl_matrix *XtX_old, const gsl_vector *Xty_old, const gsl_vector *y, const vector<size_t> &rank_old, const vector<size_t> &rank_new, gsl_matrix *X_new, gsl_matrix *XtX_new, gsl_vector *Xty_new);
double CalcPosterior (const double yty, class HYPBSLMM &cHyp);
double CalcPosterior (const gsl_matrix *Xgamma, const gsl_matrix *XtX, const gsl_vector *Xty, const double yty, const size_t s_size, gsl_vector *Xb, gsl_vector *beta, class HYPBSLMM &cHyp);
void CalcCC_PVEnZ (gsl_vector *z_hat, class HYPBSLMM &cHyp);
void CalcCC_PVEnZ (const gsl_vector *Xb, gsl_vector *z_hat, class HYPBSLMM &cHyp);
void MCMC (const gsl_matrix *X, const gsl_vector *y);
//utility functions
// double vec_sum (gsl_vector *v);
// void vec_center (gsl_vector *v);
// double calc_var (gsl_vector *v);
// void calc_sigma (MCMC &cMcmc);
// bool comp_lr (pair<size_t, double> a, pair<size_t, double> b);
};
#endif
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