prior.c

hmmer源程序

       * Only activated if X-PR* annotation has been used, in which
       * priors are overridden and a single Dirichlet component is
       * specified for each column (using structural annotation).
       * If X-PR* annotation is not used, which is usually the case, 
       * the following code has no effect (observe how the real prior 
       * distributions are copied into tq, mq, iq).
       */
      if (hmm->tpri != NULL && hmm->tpri[k] >= 0)
	{
	  if (hmm->tpri[k] >= pri->tnum) Die("X-PRT annotation out of range");
	  FSet(tq, pri->tnum, 0.0);
	  tq[hmm->tpri[k]] = 1.0;
	}
      else 
	FCopy(tq, pri->tq, pri->tnum);
      if (hmm->mpri != NULL && hmm->mpri[k] >= 0)
	{
	  if (hmm->mpri[k] >= pri->mnum) Die("X-PRM annotation out of range");
	  FSet(mq, pri->mnum, 0.0);
	  mq[hmm->mpri[k]] = 1.0;
	}
      else 
	FCopy(mq, pri->mq, pri->mnum);
      if (hmm->ipri != NULL && hmm->ipri[k] >= 0)
	{
	  if (hmm->ipri[k] >= pri->inum) Die("X-PRI annotation out of range");
	  FSet(iq, pri->inum, 0.0);
	  iq[hmm->ipri[k]] = 1.0;
	}
      else 
	FCopy(iq, pri->iq, pri->inum);

      /* This is the main line of the code:
       */
      P7PriorifyTransitionVector(hmm->t[k], pri, tq);
      P7PriorifyEmissionVector(hmm->mat[k], pri, pri->mnum, mq, pri->m, NULL);
      P7PriorifyEmissionVector(hmm->ins[k], pri, pri->inum, iq, pri->i, NULL);
    }

  /* We repeat the above steps just for the final match state, M.
   */
  if (hmm->mpri != NULL && hmm->mpri[hmm->M] >= 0)
    {
      if (hmm->mpri[hmm->M] >= pri->mnum) Die("X-PRM annotation out of range");
      FSet(mq, pri->mnum, 0.0);
      mq[hmm->mpri[hmm->M]] = 1.0;
    }
  else 
    FCopy(mq, pri->mq, pri->mnum);

  P7PriorifyEmissionVector(hmm->mat[hmm->M], pri, pri->mnum, mq, pri->m, NULL);

  /* Now we're done. Convert the counts-based HMM to probabilities.
   */
  Plan7Renormalize(hmm);
}


/* Function: P7PriorifyEmissionVector()
 * 
 * Purpose:  Add prior pseudocounts to an observed 
 *           emission count vector and renormalize. 
 *
 *           Can return the posterior mixture probabilities
 *           P(q | counts) if ret_mix[MAXDCHLET] is passed.
 *           Else, pass NULL.  
 * 
 * Args:     vec     - the 4 or 20-long vector of counts to modify
 *           pri     - prior data structure
 *           num     - pri->mnum or pri->inum; # of mixtures
 *           eq      - pri->mq or pri->iq; prior mixture probabilities
 *           e       - pri->i or pri->m; Dirichlet components          
 *           ret_mix - filled with posterior mixture probabilities, or NULL
 *                   
 * Return:   (void)
 *           The counts in vec are changed and normalized to probabilities.
 */                  
void
P7PriorifyEmissionVector(float *vec, struct p7prior_s *pri, 
		       int num, float eq[MAXDCHLET], float e[MAXDCHLET][MAXABET],
		       float *ret_mix)
{
  int   x;                      /* counter over vec                     */
  int   q;                      /* counter over mixtures                */
  float mix[MAXDCHLET];         /* posterior distribution over mixtures */
  float totc;                   /* total counts                         */
  float tota;                   /* total alpha terms                    */
  float xi;                     /* X_i term, Sjolander eq. 41           */

  /* Calculate mix[], which is the posterior probability
   * P(q | n) of mixture component q given the count vector n
   *
   * (side effect note: note that an insert vector in a PAM prior
   * is passed with num = 1, bypassing pam prior code; this means
   * that inserts cannot be mixture Dirichlets...)
   * [SRE, 12/24/00: the above comment is cryptic! what the hell does that
   *  mean, inserts can't be mixtures? doesn't seem to be true. it 
   *  may mean that in a PAM prior, you can't have a mixture for inserts,
   *  but I don't even understand that. The insert vectors aren't passed
   *  with num=1!!]
   */
  mix[0] = 1.0;
  if (pri->strategy == PRI_DCHLET && num > 1) 
    {
      for (q = 0; q < num; q++) 
	{
	  mix[q] =  eq[q] > 0.0 ? log(eq[q]) : -999.;
	  mix[q] += Logp_cvec(vec, Alphabet_size, e[q]);
	}
      LogNorm(mix, num);      /* now mix[q] is P(component_q | n) */
    }
  else if (pri->strategy == PRI_PAM && num > 1) 
    {		/* pam prior uses aa frequencies as `P(q|n)' */
      for (q = 0; q < Alphabet_size; q++) 
	mix[q] = vec[q];
      FNorm(mix, Alphabet_size);
    }

  /* Convert the counts to probabilities, following Sjolander (1996) 
   */
  totc = FSum(vec, Alphabet_size);
  for (x = 0; x < Alphabet_size; x++) {
    xi = 0.0;
    for (q = 0; q < num; q++) {
      tota = FSum(e[q], Alphabet_size);
      xi += mix[q] * (vec[x] + e[q][x]) / (totc + tota);
    }
    vec[x] = xi;
  }
  FNorm(vec, Alphabet_size);

  if (ret_mix != NULL)
    for (q = 0; q < num; q++)
      ret_mix[q] = mix[q];
}



/* Function: P7PriorifyTransitionVector()
 * 
 * Purpose:  Add prior pseudocounts to transition vector,
 *           which contains three different probability vectors
 *           for m, d, and i. 
 *           
 * Args:     t     - state transitions, counts: 3 for M, 2 for I, 2 for D.   
 *           prior - Dirichlet prior information
 *           tq    - prior distribution over Dirichlet components.
 *                   (overrides prior->iq[]; used for alternative
 *                   methods of conditioning prior on structural data)  
 *           
 * Return:   (void)
 *           t is changed, and renormalized -- comes back as
 *           probability vectors.
 */          
void
P7PriorifyTransitionVector(float *t, struct p7prior_s *prior, 
			   float tq[MAXDCHLET])
{
  int   ts;
  int   q;
  float mix[MAXDCHLET];
  float totm, totd, toti;       /* total counts in three transition vecs */
  float xi;                     /* Sjolander's X_i term */

  mix[0] = 1.0;			/* default is simple one component */
  if ((prior->strategy == PRI_DCHLET || prior->strategy == PRI_PAM) && prior->mnum > 1)
    {
      for (q = 0; q < prior->tnum; q++)
        {
          mix[q] =  tq[q] > 0.0 ? log(tq[q]) : -999.;
          mix[q] += Logp_cvec(t,   3, prior->t[q]);   /* 3 match  */
          mix[q] += Logp_cvec(t+3, 2, prior->t[q]+3); /* 2 insert */
	  mix[q] += Logp_cvec(t+5, 2, prior->t[q]+5); /* 2 delete */
        }
      LogNorm(mix, prior->tnum); /* mix[q] is now P(q | counts) */
    }
				/* precalc some denominators */
  totm = FSum(t,3);		
  toti = t[TIM] + t[TII];
  totd = t[TDM] + t[TDD];

  for (ts = 0; ts < 7; ts++)  
    {
      xi = 0.0;
      for (q = 0; q < prior->tnum; q++)
        {
	  switch (ts) {
	  case TMM: case TMI: case TMD: 
	    xi += mix[q] * (t[ts] + prior->t[q][ts]) / 
	      (totm + FSum(prior->t[q], 3)); 
	    break;
	  case TIM: case TII: 
	    xi += mix[q] * (t[ts] + prior->t[q][ts]) / 
	      (toti + prior->t[q][TIM] + prior->t[q][TII]);
	    break;
	  case TDM: case TDD: 
	    xi += mix[q] * (t[ts] + prior->t[q][ts]) / 
	      (totd + prior->t[q][TDM] + prior->t[q][TDD]);
	    break;
	  }
        }
      t[ts] = xi;
    }
  FNorm(t,   3);		/* match  */
  FNorm(t+3, 2);		/* insert */
  FNorm(t+5, 2);		/* delete */
}


/* Function: default_amino_prior()
 * 
 * Purpose:  Set the default protein prior.
 */
static struct p7prior_s *
default_amino_prior(void)
{
  struct p7prior_s *pri;
  int q, x;
				/* default match mixture coefficients */
  static float defmq[9] = {
    0.178091, 0.056591, 0.0960191, 0.0781233, 0.0834977, 
    0.0904123, 0.114468, 0.0682132, 0.234585 };

				/* default match mixture Dirichlet components */
  static float defm[9][20] = {
    { 0.270671, 0.039848, 0.017576, 0.016415, 0.014268, 
      0.131916, 0.012391, 0.022599, 0.020358, 0.030727, 
      0.015315, 0.048298, 0.053803, 0.020662, 0.023612,
      0.216147, 0.147226, 0.065438, 0.003758, 0.009621 },
    { 0.021465, 0.010300, 0.011741, 0.010883, 0.385651, 
      0.016416, 0.076196, 0.035329, 0.013921, 0.093517, 
      0.022034, 0.028593, 0.013086, 0.023011, 0.018866, 
      0.029156, 0.018153, 0.036100, 0.071770, 0.419641 },
    { 0.561459, 0.045448, 0.438366, 0.764167, 0.087364,
      0.259114, 0.214940, 0.145928, 0.762204, 0.247320,
      0.118662, 0.441564, 0.174822, 0.530840, 0.465529, 
      0.583402, 0.445586, 0.227050, 0.029510, 0.121090 },
    { 0.070143, 0.011140, 0.019479, 0.094657, 0.013162, 
      0.048038, 0.077000, 0.032939, 0.576639, 0.072293, 
      0.028240, 0.080372, 0.037661, 0.185037, 0.506783, 
      0.073732, 0.071587, 0.042532, 0.011254, 0.028723 },
    { 0.041103, 0.014794, 0.005610, 0.010216, 0.153602, 
      0.007797, 0.007175, 0.299635, 0.010849, 0.999446, 
      0.210189, 0.006127, 0.013021, 0.019798, 0.014509, 
      0.012049, 0.035799, 0.180085, 0.012744, 0.026466 },
    { 0.115607, 0.037381, 0.012414, 0.018179, 0.051778, 
      0.017255, 0.004911, 0.796882, 0.017074, 0.285858, 
      0.075811, 0.014548, 0.015092, 0.011382, 0.012696, 
      0.027535, 0.088333, 0.944340, 0.004373, 0.016741 },
    { 0.093461, 0.004737, 0.387252, 0.347841, 0.010822, 
      0.105877, 0.049776, 0.014963, 0.094276, 0.027761, 
      0.010040, 0.187869, 0.050018, 0.110039, 0.038668, 
      0.119471, 0.065802, 0.025430, 0.003215, 0.018742 },
    { 0.452171, 0.114613, 0.062460, 0.115702, 0.284246,
      0.140204, 0.100358, 0.550230, 0.143995, 0.700649, 
      0.276580, 0.118569, 0.097470, 0.126673, 0.143634, 
      0.278983, 0.358482, 0.661750, 0.061533, 0.199373 },
    { 0.005193, 0.004039, 0.006722, 0.006121, 0.003468, 
      0.016931, 0.003647, 0.002184, 0.005019, 0.005990, 
      0.001473, 0.004158, 0.009055, 0.003630, 0.006583, 
      0.003172, 0.003690, 0.002967, 0.002772, 0.002686 },
  };

  pri = P7AllocPrior();
  pri->strategy = PRI_DCHLET;

  /* Transition priors are subjective, but borrowed from GJM's estimations
   * on Pfam
   */
  pri->tnum     = 1;
  pri->tq[0]    = 1.0;
  pri->t[0][TMM]   = 0.7939;
  pri->t[0][TMI]   = 0.0278;
  pri->t[0][TMD]   = 0.0135;
  pri->t[0][TIM]   = 0.1551;
  pri->t[0][TII]   = 0.1331;
  pri->t[0][TDM]   = 0.9002;
  pri->t[0][TDD]   = 0.5630;
  
  /* Match emission priors are a mixture Dirichlet,
   * from Kimmen Sjolander (Blocks9)
   */
  pri->mnum  = 9;
  for (q = 0; q < pri->mnum; q++) 
    {
      pri->mq[q] = defmq[q];
      for (x = 0; x < 20; x++)
	pri->m[q][x] = defm[q][x];
    }

  /* These insert emission priors are subjective. Observed frequencies
   * were obtained from PFAM 1.0, 10 Nov 96; 
   *      see ~/projects/plan7/InsertStatistics.
   * Inserts are slightly biased towards polar residues and away from
   * hydrophobic residues.
   */
  pri->inum  = 1;
  pri->iq[0] = 1.;
  pri->i[0][0]  = 681.;         /* A */
  pri->i[0][1]  = 120.;         /* C */
  pri->i[0][2]  = 623.;         /* D */
  pri->i[0][3]  = 651.;         /* E */
  pri->i[0][4]  = 313.;         /* F */
  pri->i[0][5]  = 902.;         /* G */
  pri->i[0][6]  = 241.;         /* H */
  pri->i[0][7]  = 371.;         /* I */
  pri->i[0][8]  = 687.;         /* K */
  pri->i[0][9]  = 676.;         /* L */
  pri->i[0][10] = 143.;         /* M */
  pri->i[0][11] = 548.;         /* N */
  pri->i[0][12] = 647.;         /* P */
  pri->i[0][13] = 415.;         /* Q */
  pri->i[0][14] = 551.;         /* R */
  pri->i[0][15] = 926.;         /* S */
  pri->i[0][16] = 623.;         /* T */
  pri->i[0][17] = 505.;         /* V */
  pri->i[0][18] = 102.;         /* W */
  pri->i[0][19] = 269.;         /* Y */

  return pri;
}


/* Function: default_nucleic_prior()
 * 
 * Purpose:  Set the default DNA prior. (for now, almost a Laplace)
 */
static struct p7prior_s *
default_nucleic_prior(void)
{
  struct p7prior_s *pri;

  pri = P7AllocPrior();
  pri->strategy = PRI_DCHLET;

  /* The use of the Pfam-trained amino acid transition priors
   * here is TOTALLY bogus. But it works better than a straight
   * Laplace, esp. for Maxmodelmaker(). For example, a Laplace 
   * prior builds M=1 models for a single sequence GAATTC (at
   * one time an open "bug").
   */
  pri->tnum        = 1;
  pri->tq[0]       = 1.;
  pri->t[0][TMM]   = 0.7939;
  pri->t[0][TMI]   = 0.0278;
  pri->t[0][TMD]   = 0.0135;
  pri->t[0][TIM]   = 0.1551;
  pri->t[0][TII]   = 0.1331;
  pri->t[0][TDM]   = 0.9002;
  pri->t[0][TDD]   = 0.5630;
  
  pri->mnum  = 1;
  pri->mq[0] = 1.;
  FSet(pri->m[0], Alphabet_size, 1.);

  pri->inum  = 1;
  pri->iq[0] = 1.;
  FSet(pri->i[0], Alphabet_size, 1.);

  return pri;
}