Esempio n. 1
0
void R_scantwo_imp(int *n_ind, int *same_chr, int *n_pos1, int *n_pos2, 
		   int *n_gen1, int *n_gen2, int *n_draws, int *draws1, 
		   int *draws2, double *addcov, int *n_addcov, 
		   double *intcov, int *n_intcov, double *pheno, int *nphe, 
		   double *weights, double *result, int *n_col2drop,
		   int *col2drop)
{
  int ***Draws1, ***Draws2;
  double **Addcov, **Intcov;

  /* reorganize draws */
  reorg_draws(*n_ind, *n_pos1, *n_draws, draws1, &Draws1);
  if(!(*same_chr)) reorg_draws(*n_ind, *n_pos2, *n_draws, draws2, &Draws2);

  /* reorganize addcov and intcov (if they are not empty) */
  /* currently reorg_geno function is used to reorganized the data */
  if(*n_addcov != 0) reorg_errlod(*n_ind, *n_addcov, addcov, &Addcov);
  if(*n_intcov != 0) reorg_errlod(*n_ind, *n_intcov, intcov, &Intcov);

  /* call the engine function scantwo_imp */
  scantwo_imp(*n_ind, *same_chr, *n_pos1, *n_pos2, *n_gen1, *n_gen2, 
	      *n_draws, Draws1, Draws2, Addcov, *n_addcov, 
	      Intcov, *n_intcov, pheno, *nphe, weights, result,
	      *n_col2drop, col2drop);
}
Esempio n. 2
0
void R_fitqtl_imp(int *n_ind, int *n_qtl, int *n_gen, int *n_draws,
                  int *draws, int *n_cov, double *cov, int *model,
                  int *n_int, double *pheno, int *get_ests,
                  /* return variables */
                  double *lod, int *df, double *ests, double *ests_covar,
                  double *design_mat, int *matrix_rank, double *residuals)
{
    int ***Draws;
    double **Cov=0;

    /* reorganize draws */
    reorg_draws(*n_ind, *n_qtl, *n_draws, draws, &Draws);

    /* reorganize cov (if they are not empty) */
    /* currently reorg_errlod function is used to reorganize the data */
    if(*n_cov != 0) reorg_errlod(*n_ind, *n_cov, cov, &Cov);

    fitqtl_imp(*n_ind, *n_qtl, n_gen, *n_draws, Draws,
               Cov, *n_cov, model, *n_int, pheno, *get_ests, lod, df,
               ests, ests_covar, design_mat, matrix_rank, residuals);
}
Esempio n. 3
0
void R_scanone_imp(int *n_ind, int *n_pos, int *n_gen, int *n_draws, 
		   int *draws, double *addcov, int *n_addcov, 
		   double *intcov, int *n_intcov, double *pheno, 
		   int *nphe, double *weights,
		   double *result, int *ind_noqtl)
{
  /* reorganize draws */
  int ***Draws;
  double **Addcov, **Intcov, **Result;
  
  reorg_draws(*n_ind, *n_pos, *n_draws, draws, &Draws);
  reorg_errlod(*n_pos, *nphe, result, &Result); 

  /* reorganize addcov and intcov (if they are not empty) */
  /* currently reorg_errlod function is used to reorganize the data */
  if(*n_addcov != 0) reorg_errlod(*n_ind, *n_addcov, addcov, &Addcov);
  if(*n_intcov != 0) reorg_errlod(*n_ind, *n_intcov, intcov, &Intcov);
      
  scanone_imp(*n_ind, *n_pos, *n_gen, *n_draws, Draws, 
	      Addcov, *n_addcov, Intcov, *n_intcov, pheno, *nphe, weights,
	      Result, ind_noqtl);
}
Esempio n. 4
0
void sim_geno(int n_ind, int n_pos, int n_gen, int n_draws,
              int *geno, double *rf, double *rf2,
              double error_prob, int *draws,
              double initf(int, int *),
              double emitf(int, int, double, int *),
              double stepf(int, int, double, double, int *))
{
    int i, k, j, v, v2;
    double s, **beta, *probs;
    int **Geno, ***Draws, curstate;
    int cross_scheme[2];

    /* cross scheme hidden in draws argument; used by hmm_bcsft */
    cross_scheme[0] = draws[0];
    cross_scheme[1] = draws[1];
    draws[0] = 0;
    draws[1] = 0;

    /* allocate space for beta and
       reorganize geno and draws */
    /* Geno indexed as Geno[pos][ind] */
    /* Draws indexed as Draws[rep][pos][ind] */
    reorg_geno(n_ind, n_pos, geno, &Geno);
    reorg_draws(n_ind, n_pos, n_draws, draws, &Draws);
    allocate_alpha(n_pos, n_gen, &beta);
    allocate_double(n_gen, &probs);

    /* Read R's random seed */
    GetRNGstate();

    for(i=0; i<n_ind; i++) { /* i = individual */

        R_CheckUserInterrupt(); /* check for ^C */

        /* do backward equations */
        /* initialize beta */
        for(v=0; v<n_gen; v++) beta[v][n_pos-1] = 0.0;

        /* backward equations */
        for(j=n_pos-2; j>=0; j--) {

            for(v=0; v<n_gen; v++) {
                beta[v][j] = beta[0][j+1] + stepf(v+1,1,rf[j], rf2[j], cross_scheme) +
                    emitf(Geno[j+1][i],1,error_prob, cross_scheme);

                for(v2=1; v2<n_gen; v2++)
                    beta[v][j] = addlog(beta[v][j], beta[v2][j+1] +
                                        stepf(v+1,v2+1,rf[j],rf2[j], cross_scheme) +
                                        emitf(Geno[j+1][i],v2+1,error_prob, cross_scheme));
            }
        }

        for(k=0; k<n_draws; k++) { /* k = simulation replicate */

            /* first draw */
            /* calculate probs */
            s = (probs[0] = initf(1, cross_scheme)+emitf(Geno[0][i],1,error_prob, cross_scheme)+beta[0][0]);
            for(v=1; v<n_gen; v++) {
                probs[v] = initf(v+1, cross_scheme) + emitf(Geno[0][i], v+1, error_prob, cross_scheme) +
                    beta[v][0];
                s = addlog(s, probs[v]);
            }
            for(v=0; v<n_gen; v++) probs[v] = exp(probs[v] - s);

            /* make draw: returns a value from {1, 2, ..., n_gen} */
            curstate = Draws[k][0][i] = sample_int(n_gen, probs);

            /* move along chromosome */
            for(j=1; j<n_pos; j++) {
                /* calculate probs */
                for(v=0; v<n_gen; v++)
                    probs[v] = exp(stepf(curstate,v+1,rf[j-1],rf2[j-1], cross_scheme) +
                                   emitf(Geno[j][i],v+1,error_prob, cross_scheme) +
                                   beta[v][j] - beta[curstate-1][j-1]);
                /* make draw */
                curstate = Draws[k][j][i] = sample_int(n_gen, probs);
            }

        } /* loop over replicates */

    } /* loop over individuals */

    /* write R's random seed */
    PutRNGstate();

}