/* Function: p7_GNull2_ByTrace()
* Synopsis: Assign null2 scores to an envelope by the sampling method.
* Incept: SRE, Thu May 1 10:00:43 2008 [Janelia]
*
* Purpose: Given a traceback <tr> for an alignment of model <gm> to
* some target sequence; calculate null2 odds ratios $\frac{f'{x}}{f{x}}$
* as the state-usage-weighted emission probabilities,
* with state usages calculated by counting emissions used
* at positions <zstart..zend> in the trace.
*
* Because we only need to collect state usages from the
* trace <tr>, the target sequence is irrelevant. Because
* we are only averaging emission odds ratios from model
* <gm>, the configuration of <gm> is irrelevant (uni
* vs. multihit, or length config).
*
* Args: gm - model, in any configuration; only emission odds are used
* tr - traceback for any region (or all) of a target sequence
* zstart - first elem in <tr> to collect from; use 0 for complete
* zend - last elem in <tr> to collect from; use tr->N-1 for complete
* wrk - DP matrix w/ at least one row, for workspace
* null2 - RESULT: odds ratios f'(x)/f(x) for all Kp residues
*
* Returns: <eslOK> on success, and the <ddef->n2sc> scores are set
* for region <i..j>.
*
* Throws: <eslEMEM> on allocation error.
*/
int
p7_GNull2_ByTrace(const P7_PROFILE *gm, const P7_TRACE *tr, int zstart, int zend, P7_GMX *wrk, float *null2)
{
float **dp = wrk->dp; /* so that {MDI}MX() macros work */
float *xmx = wrk->xmx; /* so that XMX() macro works */
int Ld = 0;
int M = gm->M;
int k; /* index over model position */
int x; /* index over residues */
int z; /* index over trace position */
float xfactor;
/* We'll use the i=0 row in wrk for working space: dp[0][] and xmx[0..4]. */
esl_vec_FSet(wrk->dp[0], (M+1)*p7G_NSCELLS, 0.0);
esl_vec_FSet(wrk->xmx, p7G_NXCELLS, 0.0);
/* Calculate emitting state usage in this particular trace segment: */
for (z = zstart; z <= zend; z++)
{
switch (tr->st[z]) {
case p7T_M: Ld++; MMX(0,tr->k[z]) += 1.0; break;
case p7T_I: Ld++; IMX(0,tr->k[z]) += 1.0; break;
case p7T_N: if (tr->st[z-1] == p7T_N) { Ld++; XMX(0,p7G_N) += 1.0; } break;
case p7T_C: if (tr->st[z-1] == p7T_C) { Ld++; XMX(0,p7G_C) += 1.0; } break;
case p7T_J: if (tr->st[z-1] == p7T_J) { Ld++; XMX(0,p7G_J) += 1.0; } break;
}
}
esl_vec_FScale(wrk->dp[0], (M+1)*p7G_NSCELLS, (1.0 / (float) Ld));
esl_vec_FScale(wrk->xmx, p7G_NXCELLS, (1.0 / (float) Ld));
/* Calculate null2's odds ratio emission probabilities, by taking
* posterior weighted sum over all emission vectors used in paths
* explaining the domain.
*/
esl_vec_FSet(null2, gm->abc->K, 0.0);
xfactor = XMX(0,p7G_N) + XMX(0,p7G_C) + XMX(0,p7G_J);
for (x = 0; x < gm->abc->K; x++)
{
for (k = 1; k < M; k++)
{
null2[x] += MMX(0,k) * expf(p7P_MSC(gm, k, x));
null2[x] += IMX(0,k) * expf(p7P_ISC(gm, k, x));
}
null2[x] += MMX(0,M) * expf(p7P_MSC(gm, M, x));
null2[x] += xfactor;
}
/* now null2[x] = \frac{f_d(x)}{f_0(x)} odds ratios for all x in alphabet,
* 0..K-1, where f_d(x) are the ad hoc "null2" residue frequencies
* for this envelope.
*/
/* make valid scores for all degeneracies, by averaging the odds ratios. */
esl_abc_FAvgScVec(gm->abc, null2);
null2[gm->abc->K] = 1.0; /* gap character */
null2[gm->abc->Kp-2] = 1.0; /* nonresidue "*" */
null2[gm->abc->Kp-1] = 1.0; /* missing data "~" */
return eslOK;
}
/* Function: p7_masstrace_Zero()
* Synopsis: Initialize cumulative endpoint distributions to zeros.
*
* Purpose: Zero the cumulative distributions in <mt>, preparing to
* collect masstrace endpoint data for a sequence of length
* <L> and a profile of length <M>.
*
* Args: mt - mass trace object to collect endpoint data in
* M - profile length
* L - sequence length
*
* Returns: <eslOK> on success.
*/
int
p7_masstrace_Zero(P7_MASSTRACE *mt, int M, int L)
{
/* contract checks / argument validation */
ESL_DASSERT1( (mt->imass == NULL || L+2 <= mt->ialloc ) );
ESL_DASSERT1( (M+2 <= mt->kalloc) );
if (mt->imass) esl_vec_FSet(mt->imass, L+2, 0.0f);
esl_vec_FSet(mt->kmass, M+2, 0.0f);
mt->L = L;
mt->M = M;
return eslOK;
}
/* The MSV score can be validated against Viterbi (provided we trust
* Viterbi), by creating a multihit local profile in which:
* 1. All t_MM scores = 0
* 2. All other core transitions = -inf
* 3. All t_BMk entries uniformly log 2/(M(M+1))
*/
static void
utest_msv(ESL_GETOPTS *go, ESL_RANDOMNESS *r, ESL_ALPHABET *abc, P7_BG *bg, P7_PROFILE *gm, int nseq, int L)
{
P7_PROFILE *g2 = NULL;
ESL_DSQ *dsq = NULL;
P7_GMX *gx = NULL;
float sc1, sc2;
int k, idx;
if ((dsq = malloc(sizeof(ESL_DSQ) *(L+2))) == NULL) esl_fatal("malloc failed");
if ((gx = p7_gmx_Create(gm->M, L)) == NULL) esl_fatal("matrix creation failed");
if ((g2 = p7_profile_Clone(gm)) == NULL) esl_fatal("profile clone failed");
/* Make g2's scores appropriate for simulating the MSV algorithm in Viterbi */
esl_vec_FSet(g2->tsc, p7P_NTRANS * g2->M, -eslINFINITY);
for (k = 1; k < g2->M; k++) p7P_TSC(g2, k, p7P_MM) = 0.0f;
for (k = 0; k < g2->M; k++) p7P_TSC(g2, k, p7P_BM) = log(2.0f / ((float) g2->M * (float) (g2->M+1)));
for (idx = 0; idx < nseq; idx++)
{
if (esl_rsq_xfIID(r, bg->f, abc->K, L, dsq) != eslOK) esl_fatal("seq generation failed");
if (p7_GMSV (dsq, L, gm, gx, 2.0, &sc1) != eslOK) esl_fatal("MSV failed");
if (p7_GViterbi(dsq, L, g2, gx, &sc2) != eslOK) esl_fatal("viterbi failed");
if (fabs(sc1-sc2) > 0.0001) esl_fatal("MSV score not equal to Viterbi score");
}
p7_gmx_Destroy(gx);
p7_profile_Destroy(g2);
free(dsq);
return;
}
/* Function: p7_bg_Create()
* Incept: SRE, Fri Jan 12 13:32:51 2007 [Janelia]
*
* Purpose: Allocate a <P7_BG> object for digital alphabet <abc>,
* initializes it to appropriate default values, and
* returns a pointer to it.
*
* For protein models, default iid background frequencies
* are set (by <p7_AminoFrequencies()>) to average
* SwissProt residue composition. For DNA, RNA and other
* alphabets, default frequencies are set to a uniform
* distribution.
*
* The model composition <bg->mcomp[]> is not initialized
* here; neither is the filter null model <bg->fhmm>. To
* use the filter null model, caller will want to
* initialize these fields by calling
* <p7_bg_SetFilterByHMM()>.
*
* Throws: <NULL> on allocation failure.
*
* Xref: STL11/125.
*/
P7_BG *
p7_bg_Create(const ESL_ALPHABET *abc)
{
P7_BG *bg = NULL;
int status;
ESL_ALLOC(bg, sizeof(P7_BG));
bg->f = NULL;
bg->fhmm = NULL;
ESL_ALLOC(bg->f, sizeof(float) * abc->K);
if ((bg->fhmm = esl_hmm_Create(abc, 2)) == NULL) goto ERROR;
if (abc->type == eslAMINO)
{
if (p7_AminoFrequencies(bg->f) != eslOK) goto ERROR;
}
else
esl_vec_FSet(bg->f, abc->K, 1. / (float) abc->K);
bg->p1 = 350./351.;
bg->omega = 1./256.;
bg->abc = abc;
return bg;
ERROR:
p7_bg_Destroy(bg);
return NULL;
}
static void
utest_ReadWrite(ESL_RANDOMNESS *rng)
{
char msg[] = "bg Read/Write unit test failed";
char tmpfile[32] = "esltmpXXXXXX";
FILE *fp = NULL;
ESL_ALPHABET *abc = NULL; /* random alphabet choice eslRNA..eslDICE */
float *fq = NULL;
P7_BG *bg = NULL;
if ((abc = esl_alphabet_Create(esl_rnd_Roll(rng, 5) + 1)) == NULL) esl_fatal(msg);
if (( bg = p7_bg_Create(abc)) == NULL) esl_fatal(msg);
if (( fq = malloc(sizeof(float) * abc->K)) == NULL) esl_fatal(msg);
do {
if (esl_dirichlet_FSampleUniform(rng, abc->K, fq) != eslOK) esl_fatal(msg);
} while (esl_vec_FMin(fq, abc->K) < 0.001); /* small p's will get rounded off and fail FCompare() */
esl_vec_FCopy(fq, abc->K, bg->f);
if (esl_tmpfile_named(tmpfile, &fp) != eslOK) esl_fatal(msg);
if ( p7_bg_Write(fp, bg) != eslOK) esl_fatal(msg);
fclose(fp);
esl_vec_FSet(bg->f, bg->abc->K, 0.0);
if ( p7_bg_Read(tmpfile, bg, NULL) != eslOK) esl_fatal(msg);
if ( esl_vec_FCompare(fq, bg->f, bg->abc->K, 0.01) != eslOK) esl_fatal(msg);
p7_bg_Destroy(bg);
esl_alphabet_Destroy(abc);
free(fq);
remove(tmpfile);
}
/* Function: p7_ParameterEstimation()
* Incept: SRE, Sat Mar 24 10:15:37 2007 [Janelia]
*
* Purpose: Given an <hmm> containing collected, weighted counts;
* and given a mixture Dirichlet prior <pri>;
* calculate mean posterior parameter estimates for
* all model parameters, converting the
* HMM to a parameterized probabilistic model.
*
* Returns: <eslOK> on success.
*/
int
p7_ParameterEstimation(P7_HMM *hmm, const P7_PRIOR *pri)
{
int k;
double c[p7_MAXABET];
double p[p7_MAXABET];
double mix[p7_MAXDCHLET];
/* Match transitions 0,1..M: 0 is the B state
* TMD at node M is 0.
*/
for (k = 0; k <= hmm->M; k++) {
esl_vec_F2D(hmm->t[k], 3, c);
esl_mixdchlet_MPParameters(c, 3, pri->tm, mix, p);
esl_vec_D2F(p, 3, hmm->t[k]);
}
hmm->t[hmm->M][p7H_MD] = 0.0;
esl_vec_FNorm(hmm->t[hmm->M], 3);
/* Insert transitions, 0..M
*/
for (k = 0; k <= hmm->M; k++) {
esl_vec_F2D(hmm->t[k]+3, 2, c);
esl_mixdchlet_MPParameters(c, 2, pri->ti, mix, p);
esl_vec_D2F(p, 2, hmm->t[k]+3);
}
/* Delete transitions, 1..M-1
* For k=0, which is unused; convention sets TMM=1.0, TMD=0.0
* For k=M, TMM = 1.0 (to the E state) and TMD=0.0 (no next D; must go to E).
*/
for (k = 1; k < hmm->M; k++) {
esl_vec_F2D(hmm->t[k]+5, 2, c);
esl_mixdchlet_MPParameters(c, 2, pri->td, mix, p);
esl_vec_D2F(p, 2, hmm->t[k]+5);
}
hmm->t[0][p7H_DM] = hmm->t[hmm->M][p7H_DM] = 1.0;
hmm->t[0][p7H_DD] = hmm->t[hmm->M][p7H_DD] = 0.0;
/* Match emissions, 1..M
* Convention sets mat[0] to a valid pvector: first elem 1, the rest 0.
*/
for (k = 1; k <= hmm->M; k++) {
esl_vec_F2D(hmm->mat[k], hmm->abc->K, c);
esl_mixdchlet_MPParameters(c, hmm->abc->K, pri->em, mix, p);
esl_vec_D2F(p, hmm->abc->K, hmm->mat[k]);
}
esl_vec_FSet(hmm->mat[0], hmm->abc->K, 0.);
hmm->mat[0][0] = 1.0;
/* Insert emissions 0..M
*/
for (k = 0; k <= hmm->M; k++) {
esl_vec_F2D(hmm->ins[k], hmm->abc->K, c);
esl_mixdchlet_MPParameters(c, hmm->abc->K, pri->ei, mix, p);
esl_vec_D2F(p, hmm->abc->K, hmm->ins[k]);
}
return eslOK;
}
/* Function: ZeroCPlan9()
*
* Purpose: Zeros the counts/probabilities fields in a model.
* Leaves null model untouched.
*/
void
ZeroCPlan9(CP9_t *hmm)
{
int k;
esl_vec_FSet(hmm->ins[0], hmm->abc->K, 0.);
esl_vec_FSet(hmm->t[0], cp9_NTRANS, 0.);
for (k = 1; k <= hmm->M; k++)
{
esl_vec_FSet(hmm->t[k], cp9_NTRANS, 0.);
esl_vec_FSet(hmm->mat[k], hmm->abc->K, 0.);
esl_vec_FSet(hmm->ins[k], hmm->abc->K, 0.);
}
esl_vec_FSet(hmm->begin+1, hmm->M, 0.);
esl_vec_FSet(hmm->end+1, hmm->M, 0.);
/* initialize the el_* data structures, these
* depend on the CM guide tree and will be set
* when the CP9 is constructed from the CM.
*/
for (k = 0; k <= (hmm->M); k++)
{
hmm->has_el[k] = FALSE;
hmm->el_from_ct[k] = 0;
hmm->el_from_idx[k] = NULL;
hmm->el_from_cmnd[k] = NULL;
}
/* special case hmm->M+1 corresponds to the E state here */
hmm->el_from_ct[(hmm->M+1)] = 0;
hmm->el_from_idx[(hmm->M+1)] = NULL;
hmm->el_from_cmnd[(hmm->M+1)] = NULL;
hmm->flags &= ~CPLAN9_HASBITS; /* invalidates scores */
hmm->flags &= ~CPLAN9_HASPROB; /* invalidates probabilities */
hmm->el_self = 0.; /* EL self transition probability */
}
/* Function: CPlan9SWConfig()
* EPN 05.30.06
* based on SRE's Plan7SWConfig() from HMMER's plan7.c
*
* Purpose: Set the alignment independent parameters of
* a CM Plan 9 model to hmmsw (Smith/Waterman) configuration.
*
* Notes: The desideratum for begin/end probs is that all fragments ij
* (starting at match i, ending at match j) are
* equiprobable -- there is no information in the choice of
* entry/exit. There are M(M+1)/2 possible choices of ij, so
* each must get a probability of 2/M(M+1). This prob is the
* product of a begin, an end, and all the not-end probs in
* the path between i,j.
*
* Thus: entry/exit is asymmetric because of the left/right
* nature of the HMM/profile. Entry probability is distributed
* simply by assigning p_x = pentry / (M-1) to M-1
* internal match states. However, the same approach doesn't
* lead to a flat distribution over exit points. Exit p's
* must be corrected for the probability of a previous exit
* from the model. Requiring a flat distribution over exit
* points leads to an easily solved piece of algebra, giving:
* p_1 = pexit / (M-1)
* p_x = p_1 / (1 - (x-1) p_1)
*
* Modified EPN, Thu Feb 7 15:54:16 2008, as follows:
* To better match a locally configured CM, if <do_match_local_cm>
* we disallow insertions before the first (emitting) match state,
* (from I_0), and after the final (emitting) match state,
* (from I_M). I_0 maps to ROOT_IL and I_M maps to ROOT_IR
* which can never be entered in a locally configured CM
* (b/c the ROOT_S state MUST jump into a local begin state, which
* are always match states>). Also we disallow a M_0->D_1 transition
* because these would be impossible in a locally configured CM.
*
* <do_match_local_cm> is usually TRUE, unless we're configuring
* the CP9 specifically for eventual sub CM alignment, where
* the goal is simply find the most likely start/end point
* of the alignment with this CP9 (in that case we want
* I_0 and I_M reachable).
*
* Args: hmm - the CM Plan 9 model w/ data-dep prob's valid
* pentry - probability of an internal entry somewhere;
* will be evenly distributed over M-1 match states
* pexit - probability of an internal exit somewhere;
* will be distributed over M-1 match states.
* do_match_local_cm - TRUE to make I_0, D_1 and I_M unreachable
* to better match a locally configured CM.
* first_cm_ndtype - only used if do_match_local_cm is TRUE
* if it's MATL or MATP then D_1 should be unreachable (it is in the CM)
* if it's MATR or MATP then D_M should be unreachable (it is in the CM)
*
* Return: (void)
* HMM probabilities are modified.
*/
void
CPlan9SWConfig(CP9_t *hmm, float pentry, float pexit, int do_match_local_cm, int first_cm_ndtype)
{
float basep; /* p1 for exits: the base p */
int k; /* counter over states */
float d;
/* No special (*x* states in Plan 7) states in CM Plan 9 */
/*for (k = 1; k <= hmm->M; k++) printf("before anything: end[%d]: %f\n", k, hmm->end[k]);*/
/* Configure entry.
*/
if(do_match_local_cm) {
hmm->t[0][CTMI] = 0.;
hmm->t[0][CTMM] = 0.; /* already was 0.0, transition from M_0 to M_1 is begin[1] */
hmm->t[0][CTMEL] = 0.; /* already was 0.0, can never do a local end from M_0 */
if((first_cm_ndtype == MATL_nd) || (first_cm_ndtype == MATP_nd)) { /* CM can't possibly reach the CM delete state that maps to D_1, make D_1 unreachable too */
hmm->t[0][CTMD] = 0.;
}
hmm->t[hmm->M][CTMI] = 0.;
hmm->t[hmm->M][CTDI] = 0.;
if((first_cm_ndtype == MATR_nd) || (first_cm_ndtype == MATP_nd)) { /* CM can't possibly reach the CM delete state that maps to D_M, make D_M unreachable too */
hmm->t[hmm->M][CTMD] = 0.;
}
/* renormalize transitions out of M_M */
d = esl_vec_FSum(hmm->t[hmm->M], cp9_TRANS_NMATCH) + hmm->end[hmm->M];
esl_vec_FScale(hmm->t[hmm->M], cp9_TRANS_NMATCH, 1./d);
hmm->end[hmm->M] /= d;
/* renormalize transitions out of D_M */
esl_vec_FNorm(hmm->t[hmm->M] + cp9_TRANS_DELETE_OFFSET, cp9_TRANS_NDELETE); /* delete */
}
hmm->begin[1] = (1. - pentry) * (1. - (hmm->t[0][CTMI] + hmm->t[0][CTMD] + hmm->t[0][CTMEL]));
esl_vec_FSet(hmm->begin+2, hmm->M-1, (pentry * (1.- (hmm->t[0][CTMI] + hmm->t[0][CTMD] + hmm->t[0][CTMEL]))) / (float)(hmm->M-1));
/* note: hmm->t[0][CTMEL] == 0. (can't locally end from begin)
* and if do_match_local_cm, hmm->t[0][CTMI] and hmm->t[0][CTMD] were just set to 0.
*/
/* Configure exit.
* Don't touch hmm->end[hmm->M]
*/
basep = pexit / (float) (hmm->M-1);
for (k = 1; k < hmm->M; k++)
hmm->end[k] = basep / (1. - basep * (float) (k-1));
CPlan9RenormalizeExits(hmm, 1);
/*for (k = 1; k <= hmm->M; k++) printf("after renormalizing: end[%d]: %f\n", k, hmm->end[k]);*/
hmm->flags &= ~CPLAN9_HASBITS; /* reconfig invalidates log-odds scores */
hmm->flags |= CPLAN9_LOCAL_BEGIN; /* local begins now on */
hmm->flags |= CPLAN9_LOCAL_END; /* local ends now on */
CP9Logoddsify(hmm);
}
/* Function: CPlan9Renormalize()
*
* Purpose: Take an HMM in counts form, and renormalize
* all of its probability vectors. Also enforces
* CM Plan9 restrictions on nonexistent transitions.
*
* Args: hmm - the model to renormalize.
*
* Return: (void)
* hmm is changed.
*/
void
CPlan9Renormalize(CP9_t *hmm)
{
int k; /* counter for model position */
float d; /* denominator */
/* match emissions */
esl_vec_FSet(hmm->mat[0], hmm->abc->K, 0.); /*M_0 is B state, non-emitter*/
for (k = 1; k <= hmm->M; k++)
esl_vec_FNorm(hmm->mat[k], hmm->abc->K);
/* insert emissions */
for (k = 0; k <= hmm->M; k++)
esl_vec_FNorm(hmm->ins[k], hmm->abc->K);
/* begin transitions */
d = esl_vec_FSum(hmm->begin+1, hmm->M) + hmm->t[0][CTMI] + hmm->t[0][CTMD] + hmm->t[0][CTMEL];
/* hmm->t[0][CTMEL] should always be 0., can't local end from the M_0 == B state */
esl_vec_FScale(hmm->begin+1, hmm->M, 1./d);
hmm->t[0][CTMI] /= d;
hmm->t[0][CTMD] /= d;
hmm->t[0][CTMEL] /= d;
esl_vec_FNorm(hmm->t[0] + cp9_TRANS_INSERT_OFFSET, cp9_TRANS_NINSERT); /* transitions out of insert for node 0 (state N)*/
esl_vec_FSet (hmm->t[0] + cp9_TRANS_DELETE_OFFSET, cp9_TRANS_NDELETE, 0.);
/* main model transitions */
for (k = 1; k <= hmm->M; k++) /* safe for node M too, hmm->t[hmm->M][CTMM] should be 0.*/
{
d = esl_vec_FSum(hmm->t[k], cp9_TRANS_NMATCH) + hmm->end[k];
esl_vec_FScale(hmm->t[k], cp9_TRANS_NMATCH, 1./d);
hmm->end[k] /= d;
esl_vec_FNorm(hmm->t[k] + cp9_TRANS_INSERT_OFFSET, cp9_TRANS_NINSERT); /* insert */
esl_vec_FNorm(hmm->t[k] + cp9_TRANS_DELETE_OFFSET, cp9_TRANS_NDELETE); /* delete */
}
/* null model emissions */
esl_vec_FNorm(hmm->null, hmm->abc->K);
hmm->flags &= ~CPLAN9_HASBITS; /* clear the log-odds ready flag */
hmm->flags |= CPLAN9_HASPROB; /* set the probabilities OK flag */
}
/* Function: p7_profile_SameAsMF()
* Synopsis: Set a generic profile's scores to give MSV scores.
* Incept: MSF Tue Nov 3, 2009 [Janelia]
*
* Purpose: Set a generic profile's scores so that the normal <dp_generic> DP
* algorithms will give the same score as <p7_MSVFilter()>:
* all t_MM scores = 0; all other core transitions = -inf;
* multihit local mode; all <t_BMk> entries uniformly <log 2/(M(M+1))>;
* <tCC, tNN, tJJ> scores 0; total approximated later as -3;
* rounded in the same way as the 8-bit limited precision.
*
* Returns: <eslOK> on success.
*/
int
p7_profile_SameAsMF(const P7_OPROFILE *om, P7_PROFILE *gm)
{
int k;
float tbm = log(2.0f / ((float) gm->M * (float) (gm->M+1)));
/* Transitions */
esl_vec_FSet(gm->tsc, p7P_NTRANS * gm->M, -eslINFINITY);
for (k = 1; k < gm->M; k++) p7P_TSC(gm, k, p7P_MM) = 0.0f;
for (k = 0; k < gm->M; k++) p7P_TSC(gm, k, p7P_BM) = tbm;
return eslOK;
}
/* Function: CPlan9CMLocalBeginConfig()
* Incept: EPN, Thu Jun 21 15:43:29 2007
* based on SRE's Plan7SWConfig() from HMMER's plan7.c
*
* Purpose: Set up a CM Plan 9 HMM to mimic CM local begins as closely
* as it can. We can't enforce that a begin/end point are chosen
* the same way a CM's are, as the choice of a CM local begin
* (in non-truncated CYK mode) defines both a start and end point,
* and some start/end combinations are impossible. For the CP9
* we allow all possible start/end combos.
*
* Args: cm - the CM, must have valid cm->cp9, we'll use
* the CM local begin probs to set the cm->cp9s
* begin/end probs.
*
* Return: (void)
* HMM probabilities are modified.
*/
void
CPlan9CMLocalBeginConfig(CM_t *cm)
{
CMEmitMap_t *emap; /* consensus emit map for the CM */
int nd;
/* Contract checks */
if(cm->cp9 == NULL)
cm_Fail("ERROR in CPlan9CMLocalBeginConfig, cm->cp9 is NULL.\n");
if(cm->cp9map == NULL)
cm_Fail("ERROR in CPlan9CMLocalBeginConfig, cm->cp9map is NULL.\n");
if(!(cm->flags & CMH_CP9))
cm_Fail("ERROR in CPlan9CMLocalBeginConfig, CMH_CP9 flag is down.");
if(!(cm->flags & CMH_LOCAL_BEGIN))
cm_Fail("ERROR in CPlan9CMLocalBeginConfig, CMH_LOCAL_BEGIN flag is down.");
if(!(cm->flags & CMH_LOCAL_END))
cm_Fail("ERROR in CPlan9CMLocalBeginConfig, CP9_LOCAL_BEGIN flag is already up.");
if(cm->cp9->flags & CPLAN9_LOCAL_END)
cm_Fail("ERROR in CPlan9CMLocalBeginConfig, CP9_LOCAL_END flag is already up.");
/* Configure entry.
* To match CM, we enforce the only way out of the B state (M_0)
* is through a local begin into a match state
*/
esl_vec_FSet(cm->cp9->begin, cm->cp9->M, 0.);
emap = CreateEmitMap(cm);
for (nd = 1; nd < cm->nodes; nd++) {
if(NOT_IMPOSSIBLE(cm->begin[cm->nodemap[nd]])) {
cm->cp9->begin[emap->lpos[nd]] += cm->begin[cm->nodemap[nd]]; /* we do += b/c for lpos of BIFs, there's > 1 way to enter there, the BIF and the first MATP or MATL of the left child of the BIF */
}
}
cm->cp9->flags &= ~CPLAN9_HASBITS; /* reconfig invalidates log-odds scores */
cm->cp9->flags |= CPLAN9_LOCAL_BEGIN; /* local begins now on */
cm->cp9->flags |= CPLAN9_LOCAL_END; /* local ends now on */
CP9Logoddsify(cm->cp9);
}
/* Function: p7_bg_CreateUniform()
* Synopsis: Creates background model with uniform freqs.
* Incept: SRE, Sat Jun 30 10:25:27 2007 [Janelia]
*
* Purpose: Creates a background model for alphabet <abc>
* with uniform residue frequencies.
*/
P7_BG *
p7_bg_CreateUniform(const ESL_ALPHABET *abc)
{
P7_BG *bg = NULL;
int status;
ESL_ALLOC(bg, sizeof(P7_BG));
bg->f = NULL;
bg->fhmm = NULL;
ESL_ALLOC(bg->f, sizeof(float) * abc->K);
if ((bg->fhmm = esl_hmm_Create(abc, 2)) == NULL) goto ERROR;
esl_vec_FSet(bg->f, abc->K, 1. / (float) abc->K);
bg->p1 = 350./351.;
bg->omega = 1./256.;
bg->abc = (ESL_ALPHABET *) abc; /* safe: we're just keeping a reference */
return bg;
ERROR:
p7_bg_Destroy(bg);
return NULL;
}
/* Function: p7_bg_Create()
* Synopsis: Create a <P7_BG> null model object.
*
* Purpose: Allocate a <P7_BG> object for digital alphabet <abc>,
* initializes it to appropriate default values, and
* returns a pointer to it.
*
* For protein models, default iid background frequencies
* are set (by <p7_AminoFrequencies()>) to average
* Swiss-Prot residue composition. For DNA, RNA and other
* alphabets, default frequencies are set to a uniform
* distribution.
*
* The model composition <bg->mcomp[]> is not initialized
* here; neither is the filter null model <bg->fhmm>. To
* use the filter null model, caller will want to
* initialize these fields by calling
* <p7_bg_SetFilter()>.
*
* Throws: <NULL> on allocation failure.
*
* Xref: STL11/125.
*/
P7_BG *
p7_bg_Create(const ESL_ALPHABET *abc)
{
P7_BG *bg = NULL;
int status;
ESL_ALLOC(bg, sizeof(P7_BG));
bg->f = NULL;
bg->fhmm = NULL;
// this is not hard-coded for alphabet size...
ESL_ALLOC(bg->f, sizeof(float) * abc->K);
if ((bg->fhmm = esl_hmm_Create(abc, 2)) == NULL) goto ERROR;
if (abc->type == eslAMINO)
{
if (p7_AminoFrequencies(bg->f) != eslOK) goto ERROR;
}
// adding in background probabilities for music intervals
else if (abc->type == eslMUSIC)
{
if (p7_MusicFrequencies(bg->f) != eslOK) goto ERROR;
}
else
esl_vec_FSet(bg->f, abc->K, 1. / (float) abc->K);
bg->p1 = 350./351.;
bg->omega = 1./256.;
bg->abc = abc;
return bg;
ERROR:
p7_bg_Destroy(bg);
return NULL;
}
/* Function: p7_null3_score()
*
* Purpose: Calculate a correction (in log_2 odds) to be applied
* to a sequence, using a null model based on the
* composition of the target sequence.
* The null model is constructed /post hoc/ as the
* distribution of the target sequence; if the target
* sequence is 40% A, 5% C, 5% G, 40% T, then the null
* model is (0.4, 0.05, 0.05, 0.4). This function is
* based heavily on Infernal's ScoreCorrectionNull3(),
* with two important changes:
* - it leaves the log2 conversion from NATS to BITS
* for the calling function.
* - it doesn't include the omega score modifier
* (based on prior probability of using the null3
* model), again leaving this to the calling function.
*
* Args: abc - alphabet for hit (only used to get alphabet size)
* dsq - the sequence the hit resides in
* tr - trace of the alignment, used to find the match states
* (non-match chars are ignored in computing freq, not used if NULL)
* start - start position of hit in dsq
* stop - end position of hit in dsq
* bg - background, used for the default null model's emission freq
* ret_sc - RETURN: the correction to the score (in NATS);
* caller subtracts this from hit score to get
* corrected score.
* Return: void, ret_sc: the log-odds score correction (in NATS).
*/
void
p7_null3_score(const ESL_ALPHABET *abc, const ESL_DSQ *dsq, P7_TRACE *tr, int start, int stop, P7_BG *bg, float *ret_sc)
{
float score = 0.;
int status;
int i;
float *freq;
int dir;
int tr_pos;
ESL_ALLOC(freq, sizeof(float) * abc->K);
esl_vec_FSet(freq, abc->K, 0.0);
/* contract check */
if(abc == NULL) esl_exception(eslEINVAL, FALSE, __FILE__, __LINE__, "p7_null3_score() alphabet is NULL.%s\n", "");
if(dsq == NULL) esl_exception(eslEINVAL, FALSE, __FILE__, __LINE__, "p7_null3_score() dsq alphabet is NULL.%s\n", "");
if(abc->type != eslRNA && abc->type != eslDNA) esl_exception(eslEINVAL, FALSE, __FILE__, __LINE__, "p7_null3_score() expects alphabet of RNA or DNA.%s\n", "");
dir = start < stop ? 1 : -1;
if (tr != NULL) {
/* skip the parts of the trace that precede the first match state */
tr_pos = 2;
i = start;
while (tr->st[tr_pos] != p7T_M) {
if (tr->st[tr_pos] == p7T_N)
i += dir;
tr_pos++;
}
/* tally frequencies from characters hitting match state*/
while (tr->st[tr_pos] != p7T_E) {
if (tr->st[tr_pos] == p7T_M) {
if(esl_abc_XIsGap(abc, dsq[i])) esl_exception(eslEINVAL, FALSE, __FILE__, __LINE__, "in p7_null3_score(), res %d is a gap!%s\n", "");
esl_abc_FCount(abc, freq, dsq[i], 1.);
}
if (tr->st[tr_pos] != p7T_D )
i += dir;
tr_pos++;
}
} else {
/* tally frequencies from the full envelope */
for (i=ESL_MIN(start,stop); i <= ESL_MAX(start,stop); i++)
{
if(esl_abc_XIsGap(abc, dsq[i])) esl_exception(eslEINVAL, FALSE, __FILE__, __LINE__, "in p7_null3_score(), res %d is a gap!%s\n", "");
esl_abc_FCount(abc, freq, dsq[i], 1.);
}
}
esl_vec_FNorm(freq, abc->K);
/* now compute score modifier (nats) - note: even with tr!=NULL, this includes the unmatched characters*/
for (i = 0; i < abc->K; i++)
score += freq[i]==0 ? 0.0 : esl_logf( freq[i]/bg->f[i] ) * freq[i] * ( (stop-start)*dir +1) ;
/* Return the correction to the bit score. */
score = p7_FLogsum(0., score);
*ret_sc = score;
return;
ERROR:
esl_exception(eslEINVAL, FALSE, __FILE__, __LINE__, "p7_null3_score() memory allocation error.%s\n", "");
return; /* never reached */
}
/* Function: cm_tr_penalties_Create()
* Date: EPN, Sat Jan 21 12:03:52 2012
*
* Purpose: Allocate and initialize a CM_TR_PENALTIES object.
* A CM and its emit map are required to determine
* truncation penalty scores. This is annoyingly
* complex, see verbose notes within code below.
*
* Some of the code in this function, specifically
* that which calculates the probability of a fragment
* aligning at a given node, is checkable, but only
* if we disallow truncated begins into insert states.
* However, we want to allow truncated begins in reality.
* I've left in a flag for ignoring inserts (<ignore_inserts>)
* I used in testing this function. Set it to TRUE to
* perform the test.
*
* Returns: Newly allocated CM_TR_PENALTIES object. NULL if out
* of memory.
*/
CM_TR_PENALTIES *
cm_tr_penalties_Create(CM_t *cm, int ignore_inserts, char *errbuf)
{
int status;
int v, nd, m, i1, i2;
int lpos, rpos;
int i;
/* variables used for determining ratio of inserts to match at each consensus position */
float *mexpocc = NULL; /* [0..c..clen] probability match state is used to emit at cons posn c */
float *iexpocc = NULL; /* [0..c..clen] probability insert state is used to emit after cons posn c */
double *psi = NULL; /* [0..v..M-1] expected occupancy of state v */
float m_psi, i1_psi, i2_psi; /* temp psi values */
float summed_psi;
CM_TR_PENALTIES *trp = NULL;
/* variables used for calculating global truncation penalties */
float g_5and3; /* fragment probability if 5' and 3' truncation are allowed */
float g_5or3; /* fragment probability if 5' or 3' truncation are allowed */
/* variables used for calculating local truncation penalties */
float *begin = NULL; /* local begin probabilities 0..v..M-1 */
int subtree_clen; /* consensus length of subtree under this node */
float prv53, prv5, prv3; /* previous node's fragment probability, 5'&3', 5' only, 3'only */
float cur53, cur5, cur3; /* current node's fragment probability, 5'&3', 5' only, 3'only */
int nfrag53, nfrag5, nfrag3; /* number of fragments, 5'&3', 5' only, 3'only */
if(cm == NULL || cm->emap == NULL) goto ERROR;
ESL_ALLOC(trp, sizeof(CM_TR_PENALTIES));
trp->M = cm->M;
trp->ignored_inserts = ignore_inserts;
/* Define truncation penalties for each state v. This will be
* the score for doing a truncated begin into state v.
*
* Important note: For this discussion we assume that sequences can
* only be truncated at consensus positions, which means we don't
* have to worry about truncated begins into inserts. This is an
* approximation (also made by Diana and Sean in the 2009 trCYK
* paper) that greatly simplifies the explanation of the calculation
* of the truncation penalties. The examples in my ELN3 notebook
* also use this simplification. However, I need to be able to do
* truncated begins into insert states in some cases (some pass/mode
* combinations see ELN bottom of p.47). I explain first the
* rationale for calculating truncation penalties ignoring inserts
* and then I describe how I adapt those penalties to allow
* for inserts.
*
* This is a lengthy comment. I've divided it into 3 sections:
* Section 1. Global mode truncation penalties, ignoring inserts.
* Section 2. Local mode truncation penalties, ignoring inserts.
* Section 3. Adapting truncation penalties to allow for inserts.
*
**************************************************************
* Section 1. Global mode truncation penalties, ignoring inserts.
*
* We want the truncation penalty to be the log of the probability
* that the particular fragment we're aligning was generated from
* the following generative process. The generative process differs
* between global and local mode.
*
* In global mode:
* o Sample global parsetree which spans consensus positions 1..clen.
* o Randomly choose g and h in range 1..clen, where h >= g and
* truncate sequence from g..h. The first residue will either be
* an insert before position g, or a match at position g of the
* model. The final residue will either be an insert after position
* h or a match at position h of the model.
*
* All g,h fragments are equiprobable, so the probability of any
* particular fragment is 2 / (clen * (clen+1)). So log_2 of this
* value is the truncation penalty for all truncated alignments in
* global mode where both 5' and 3' truncation are allowed.
*
* We store this penalty, per-state in the
* g_ptyAA[TRPENALTY_5P_AND_3P][0..v..M-1]. The penalty is
* identical for all emitting states. The penalty value for
* non-emitters is IMPOSSIBLE because truncated begins are
* not allowed into non-emitters.
*
* If only 5' OR 3' truncation is allowed, we only truncate at g or
* h, which menas there's 1/clen possible fragments and log_2
* (1/clen) is our global truncation penalty.
*
* However, if 5' truncation is allowed we can only do a truncated
* begin into states that with a consensus subtree that spans
* position clen (since we don't allow a truncation at the 3' end).
* Thus any state whose subtree that doesn't span clen gets
* an IMPOSSIBLE value for its truncation score in:
* g_ptyAA[TRPENALTY_5P_ONLY][0..v..M-1].
*
* Likewise, if 3' truncation is allowed we can only do a truncated
* begin into states that with a consensus subtree that spans
* position 1 (since we don't allow a truncation at the 5' end).
*
* There's an example of computing all three types of penalties for
* a simple CM in ELN 3 p43.
*
************************************************************
* Section 2. Local mode truncation penalties, ignoring inserts.
*
* Generative process that generates fragments in local mode:
* o Sample local begin state b with consensus subtree from i..j from
* local begin state distribution.
* o Randomly choose g and h in range i..j, where h >= g and
* truncate sequence from g..h. The first residue will either be
* an insert before position g, or a match at position g of the
* model. The final residue will either be an insert after position
* h or a match at position h of the model.
*
* Unlike in global mode, in local mode all fragments are not
* equiprobable since the local begin state distribution can be
* anything, and each b allows different sets of fragments to be
* generated (because they can only span from i to j).
*
* The truncation penalty should be the log of the probability of
* aligning the current fragment to the model. So we need to know
* the probability of generating each possible fragment.
* We could calculate probability of any fragment g,h with the
* following inefficient algorithm:
*
* For each start fragment point g,
* For each start fragment point h,
* For each state v,
* If lpos[v] <= g && rpos[v] >= h, then
* prob[g][h] += begin[v] * 2. / (st_clen[v] * (st_clen[v]+1));
*
* Where lpos[v]/rpos[v] are the left/right consensus positions in
* consensus subtree rooted at state v. And st_clen[v] is rpos[v] -
* lpos[v] + 1, the consensus length of that subtree.
*
* This gives us prob[g][h], the probability of generating fragment
* g,h. But we want to apply the penalty to a state, not to a
* fragment, to avoid needing to know the fragment boundaries g,h
* during the DP recursion when applying the penalty.
*
* To facilitate this, we need to find state t, the state with
* smallest subtree that contains g,h. State t is relevant because
* it is the state which will root the alignment of the fragment g,h
* by using a truncated begin transition into t. This gives a new
* algorithm:
*
* For each start fragment point g,
* For each start fragment point h,
* Identify state t, the max valued state for which
* lpos[v] <= g && rpos[v] >= h, then {
* prob[t] += prob[g][h]
* fcount[t]++;
* }
*
* prob[t] will be the probability of observing an alignment that
* uses a truncated begin into t to align any fragment. Then we take
* average over all fragments: prob[t] / fcount[t] (since we'll only
* be aligning one of those fragments) and use the log of that
* probability as the penalty for observing a truncated alignment
* rooted at state t. Conveniently, it turns out that all fragments
* that share t are equiprobable (have equal prob[g][h] values), so
* the average probability is the actual probability for each
* fragment, and thus the correct penalty to apply.
*
* Fortunately, we can compute the correct penalty much more
* efficiently than the two algorithms shown above. The
* efficient way is implemented below. A test that the penalties
* are correctly computed is in cm_tr_penalties_Validate().
*
* This discussion assumes we're truncating 5' and 3', but if we're
* only truncating 5' or 3' The situation is a little different.
*
* There's an example of computing all three types of penalties for
* a simple CM in ELN3 p44-45.
*
************************************************************
* Section 3. Adapting truncation penalties to allow for inserts.
*
* We need to be able to do truncated begins into insert states
* because we enforce that the first/final residue of a sequence be
* included in 5'/3' truncated alignments and we want to be able
* to properly align those residues if they're probably emitted
* by insert states.
*
* The methods/logic explained in sections 1 and 2 above I believe
* is correct IF we ignore inserts (assume truncated begins into
* them are impossible). But we need to allow inserts, so I modify
* the truncation penalties as described above to allow for inserts
* as follows. We can calculate the appropriate truncated begin
* penalty for all MATP_MP, MATL_ML, MATR_MR, BIF_B states as with
* the methods described above by ignoring inserts. This gives us a
* probability p of using that state as the root of the truncated
* alignment, i.e. the truncated begin state. (The log_2 of this
* probability is the penalty.) We then partition p amongst the
* MATP_MP, MATL_ML, MATR_MR, BIF_B states and any parent insert
* states, i.e. any insert state that can transition into the
* match/bif state. For each match/bif state there's 0, 1 or 2
* parent inserts. We then partition p based on the relative
* expected occupancy of these inserts versus the match/bif state.
*
* This is certainly 'incorrect' in that it doesn't reflect the
* true probability of a fragment being aligned to each of the
* states, but it should be a close approximation. I think doing
* it correctly is basically impossible in the context of a single
* state-specific penalty (i.e. the penalty would have to be per-fragment
* which would be hard to deal with in the DP functions).
*/
/* allocate and initialize the penalty arrays */
ESL_ALLOC(trp->g_ptyAA, sizeof(float *) * NTRPENALTY);
ESL_ALLOC(trp->l_ptyAA, sizeof(float *) * NTRPENALTY);
ESL_ALLOC(trp->ig_ptyAA, sizeof(int *) * NTRPENALTY);
ESL_ALLOC(trp->il_ptyAA, sizeof(int *) * NTRPENALTY);
for(i = 0; i < NTRPENALTY; i++) {
trp->g_ptyAA[i] = NULL;
trp->l_ptyAA[i] = NULL;
trp->il_ptyAA[i] = NULL;
trp->ig_ptyAA[i] = NULL;
ESL_ALLOC(trp->g_ptyAA[i], sizeof(float) * cm->M);
ESL_ALLOC(trp->l_ptyAA[i], sizeof(float) * cm->M);
ESL_ALLOC(trp->ig_ptyAA[i], sizeof(int) * cm->M);
ESL_ALLOC(trp->il_ptyAA[i], sizeof(int) * cm->M);
esl_vec_FSet(trp->g_ptyAA[i], cm->M, IMPOSSIBLE);
esl_vec_FSet(trp->l_ptyAA[i], cm->M, IMPOSSIBLE);
esl_vec_ISet(trp->ig_ptyAA[i], cm->M, -INFTY);
esl_vec_ISet(trp->il_ptyAA[i], cm->M, -INFTY);
}
/* DumpEmitMap(stdout, cm->emap, cm); */
/* Calculate local begin probabilities and expected occupancy */
ESL_ALLOC(begin, sizeof(float) * cm->M);
cm_CalculateLocalBeginProbs(cm, cm->pbegin, cm->t, begin);
if((status = cm_ExpectedPositionOccupancy(cm, &mexpocc, &iexpocc, &psi, NULL, NULL, NULL)) != eslOK) goto ERROR;
/* Fill global and local truncation penalties in a single loop. We
* step through all nodes and set the truncation penalties for the
* MATP_MP, MATL_ML, MATR_MR, and BIF_B states and any parent
* inserts (i1, i2) of those states.
*/
g_5and3 = 2. / (cm->clen * (cm->clen+1)); /* for global mode: probability of all fragments if we're truncating 5' and 3' */
g_5or3 = 1. / cm->clen; /* for global mode: probability of all fragments if we're only truncating 5' or 3' */
prv5 = prv3 = prv53 = 0.; /* initialize 'previous' probability values used for calc'ing local truncation penalties */
for(nd = 0; nd < cm->nodes; nd++) {
lpos = (cm->ndtype[nd] == MATP_nd || cm->ndtype[nd] == MATL_nd) ? cm->emap->lpos[nd] : cm->emap->lpos[nd] + 1;
rpos = (cm->ndtype[nd] == MATP_nd || cm->ndtype[nd] == MATR_nd) ? cm->emap->rpos[nd] : cm->emap->rpos[nd] - 1;
/* now set penalties for match and insert states m, i1 and maybe i2 (if we're a MATP_MP or BIF_B) */
if(cm->ndtype[nd] == END_nd) {
prv5 = prv3 = prv53 = 0.;
}
else if(cm->ndtype[nd] == BEGL_nd || cm->ndtype[nd] == BEGR_nd) {
prv5 = (cm->ndtype[nd] == BEGL_nd) ? 0. : trp->l_ptyAA[TRPENALTY_5P_ONLY][cm->plast[cm->nodemap[nd]]]; /* parent BIF_B's probability */;
prv3 = (cm->ndtype[nd] == BEGR_nd) ? 0. : trp->l_ptyAA[TRPENALTY_3P_ONLY][cm->plast[cm->nodemap[nd]]]; /* parent BIF_B's probability */;
prv53 = trp->l_ptyAA[TRPENALTY_5P_AND_3P][cm->plast[cm->nodemap[nd]]]; /* parent BIF_B's probability */
}
else if(cm->ndtype[nd] == MATP_nd || cm->ndtype[nd] == MATL_nd || cm->ndtype[nd] == MATR_nd || cm->ndtype[nd] == BIF_nd) {
/* determine match states and insert states that pertain to this node */
m = cm->nodemap[nd]; /* MATP_MP, MATL_ML, MATR_MR, or BIF_B */
InsertsGivenNodeIndex(cm, nd-1, &i1, &i2);
m_psi = psi[m];
if(cm->ndtype[nd] == MATP_MP) { m_psi += (psi[m+1] + psi[m+2]); } /* include MATP_ML and MATP_MR psi */
i1_psi = (i1 == -1) ? 0. : psi[i1];
i2_psi = (i2 == -1) ? 0. : psi[i2];
summed_psi = m_psi + i1_psi + i2_psi;
if(ignore_inserts) {
i1_psi = i2_psi = 0.;
summed_psi = m_psi;
}
/* Global penalties */
/* sanity check, we should only set truncation penalty once per state */
if(NOT_IMPOSSIBLE(trp->g_ptyAA[TRPENALTY_5P_AND_3P][m])) goto ERROR;
if((i1 != -1) && NOT_IMPOSSIBLE(trp->g_ptyAA[TRPENALTY_5P_AND_3P][i1])) goto ERROR;
if((i2 != -1) && NOT_IMPOSSIBLE(trp->g_ptyAA[TRPENALTY_5P_AND_3P][i2])) goto ERROR;
/* divide up the probability g_5and3 amongst relevant states m, i1, i2, weighted by psi */
trp->g_ptyAA[TRPENALTY_5P_AND_3P][m] = (m_psi / summed_psi) * g_5and3;
if(i1 != -1) trp->g_ptyAA[TRPENALTY_5P_AND_3P][i1] = (i1_psi / summed_psi) * g_5and3;
if(i2 != -1) trp->g_ptyAA[TRPENALTY_5P_AND_3P][i2] = (i2_psi / summed_psi) * g_5and3;
/* same thing, for 5P only and 3P only */
if(rpos == cm->clen) { /* else it will remain IMPOSSIBLE */
trp->g_ptyAA[TRPENALTY_5P_ONLY][m] = (m_psi / summed_psi) * g_5or3;
if(i1 != -1) trp->g_ptyAA[TRPENALTY_5P_ONLY][i1] = (i1_psi / summed_psi) * g_5or3;
if(i2 != -1) trp->g_ptyAA[TRPENALTY_5P_ONLY][i2] = (i2_psi / summed_psi) * g_5or3;
}
if(lpos == 1) { /* else it will remain IMPOSSIBLE */
trp->g_ptyAA[TRPENALTY_3P_ONLY][m] = (m_psi / summed_psi) * g_5or3;
if(i1 != -1) trp->g_ptyAA[TRPENALTY_3P_ONLY][i1] = (i1_psi / summed_psi) * g_5or3;
if(i2 != -1) trp->g_ptyAA[TRPENALTY_3P_ONLY][i2] = (i2_psi / summed_psi) * g_5or3;
}
/* Local penalties */
subtree_clen = rpos - lpos + 1;
nfrag5 = subtree_clen;
nfrag3 = subtree_clen;
nfrag53 = (subtree_clen * (subtree_clen+1)) / 2;
/* determine probability of observing a fragment aligned at
* state m (here, m is what I call t above and in notes) and
* partition that probability between m and i1 and/or i2 by
* relative occupancy of match versus inserts
*/
cur5 = begin[m] / (float) nfrag5 + prv5;
cur3 = begin[m] / (float) nfrag3 + prv3;
cur53 = begin[m] / (float) nfrag53 + prv53;
/* sanity check, we should only set truncation penalty once per state */
if(NOT_IMPOSSIBLE(trp->l_ptyAA[TRPENALTY_5P_AND_3P][m])) goto ERROR;
if((i1 != -1) && NOT_IMPOSSIBLE(trp->l_ptyAA[TRPENALTY_5P_AND_3P][i1])) goto ERROR;
if((i2 != -1) && NOT_IMPOSSIBLE(trp->l_ptyAA[TRPENALTY_5P_AND_3P][i2])) goto ERROR;
trp->l_ptyAA[TRPENALTY_5P_AND_3P][m] = (m_psi / summed_psi) * cur53;
if(i1 != -1) trp->l_ptyAA[TRPENALTY_5P_AND_3P][i1] = (i1_psi / summed_psi) * cur53;
if(i2 != -1) trp->l_ptyAA[TRPENALTY_5P_AND_3P][i2] = (i2_psi / summed_psi) * cur53;
trp->l_ptyAA[TRPENALTY_5P_ONLY][m] = (m_psi / summed_psi) * cur5;
if(i1 != -1) trp->l_ptyAA[TRPENALTY_5P_ONLY][i1] = (i1_psi / summed_psi) * cur5;
if(i2 != -1) trp->l_ptyAA[TRPENALTY_5P_ONLY][i2] = (i2_psi / summed_psi) * cur5;
trp->l_ptyAA[TRPENALTY_3P_ONLY][m] = (m_psi / summed_psi) * cur3;
if(i1 != -1) trp->l_ptyAA[TRPENALTY_3P_ONLY][i1] = (i1_psi / summed_psi) * cur3;
if(i2 != -1) trp->l_ptyAA[TRPENALTY_3P_ONLY][i2] = (i2_psi / summed_psi) * cur3;
prv5 = (cm->ndtype[nd] == MATL_nd) ? cur5 : 0.;
prv3 = (cm->ndtype[nd] == MATR_nd) ? cur3 : 0.;
prv53 = cur53;
}
}
/* all penalties are currently probabilities, convert them to log
* probs and set integer penalties (careful, we have to check if
* IMPOSSIBLE first)
*/
for(v = 0; v < cm->M; v++)
{
if((cm->stid[v] == MATP_MP || cm->stid[v] == MATL_ML || cm->stid[v] == MATR_MR || cm->stid[v] == BIF_B) ||
((cm->sttype[v] == IL_st || cm->sttype[v] == IR_st) && (! StateIsDetached(cm, v))))
{
/* Check for rare special case: if we're a MATP_IL and next
* two states are MATP_IR and END_E, then we won't have set
* a trunction penalty. This state will keep an impossible
* truncated begin score, if we did a truncated begin into
* it we'd just emit from the MATP_IL and then go to the
* END_E anyway (the MATP_IR will be detached.
*/
if(cm->stid[v] == MATP_IL && cm->ndtype[cm->ndidx[v]+1] == END_nd) continue;
/* glocal 5P AND 3P: all of these should have been set to a non-IMPOSSIBLE value */
if(! NOT_IMPOSSIBLE(trp->g_ptyAA[TRPENALTY_5P_AND_3P][v])) goto ERROR;
trp->ig_ptyAA[TRPENALTY_5P_AND_3P][v] = Prob2Score(trp->g_ptyAA[TRPENALTY_5P_AND_3P][v], 1.0);
trp->g_ptyAA[TRPENALTY_5P_AND_3P][v] = sreLOG2(trp->g_ptyAA[TRPENALTY_5P_AND_3P][v]);
/* glocal 5P only: some may be IMPOSSIBLE */
if(NOT_IMPOSSIBLE(trp->g_ptyAA[TRPENALTY_5P_ONLY][v])) {
trp->ig_ptyAA[TRPENALTY_5P_ONLY][v] = Prob2Score(trp->g_ptyAA[TRPENALTY_5P_ONLY][v], 1.0);
trp->g_ptyAA[TRPENALTY_5P_ONLY][v] = sreLOG2(trp->g_ptyAA[TRPENALTY_5P_ONLY][v]);
}
/* glocal 5P only: some may be IMPOSSIBLE */
if(NOT_IMPOSSIBLE(trp->g_ptyAA[TRPENALTY_3P_ONLY][v])) {
trp->ig_ptyAA[TRPENALTY_3P_ONLY][v] = Prob2Score(trp->g_ptyAA[TRPENALTY_3P_ONLY][v], 1.0);
trp->g_ptyAA[TRPENALTY_3P_ONLY][v] = sreLOG2(trp->g_ptyAA[TRPENALTY_3P_ONLY][v]);
}
/* local penalties all of these should have been set to a non-IMPOSSIBLE value */
if(! NOT_IMPOSSIBLE(trp->il_ptyAA[TRPENALTY_5P_AND_3P][v])) goto ERROR;
if(! NOT_IMPOSSIBLE(trp->il_ptyAA[TRPENALTY_5P_ONLY][v])) goto ERROR;
if(! NOT_IMPOSSIBLE(trp->il_ptyAA[TRPENALTY_3P_ONLY][v])) goto ERROR;
trp->il_ptyAA[TRPENALTY_5P_AND_3P][v] = Prob2Score(trp->l_ptyAA[TRPENALTY_5P_AND_3P][v], 1.0);
trp->il_ptyAA[TRPENALTY_5P_ONLY][v] = Prob2Score(trp->l_ptyAA[TRPENALTY_5P_ONLY][v], 1.0);
trp->il_ptyAA[TRPENALTY_3P_ONLY][v] = Prob2Score(trp->l_ptyAA[TRPENALTY_3P_ONLY][v], 1.0);
trp->l_ptyAA[TRPENALTY_5P_AND_3P][v] = sreLOG2(trp->l_ptyAA[TRPENALTY_5P_AND_3P][v]);
trp->l_ptyAA[TRPENALTY_5P_ONLY][v] = sreLOG2(trp->l_ptyAA[TRPENALTY_5P_ONLY][v]);
trp->l_ptyAA[TRPENALTY_3P_ONLY][v] = sreLOG2(trp->l_ptyAA[TRPENALTY_3P_ONLY][v]);
}
}
if(ignore_inserts) {
if((status = cm_tr_penalties_Validate(trp, cm, 0.0001, errbuf)) != eslOK) { printf("%s", errbuf); goto ERROR; }
}
/* cm_tr_penalties_Dump(stdout, cm, trp); */
if(mexpocc != NULL) free(mexpocc);
if(iexpocc != NULL) free(iexpocc);
if(psi != NULL) free(psi);
if(begin != NULL) free(begin);
return trp;
ERROR:
if(mexpocc != NULL) free(mexpocc);
if(iexpocc != NULL) free(iexpocc);
if(psi != NULL) free(psi);
if(begin != NULL) free(begin);
if(trp != NULL) cm_tr_penalties_Destroy(trp);
return NULL;
}
/**
* int main(int argc, char **argv)
* Main driver
*/
int
main(int argc, char **argv)
{
ESL_GETOPTS *go = NULL; /* command line processing */
ESL_ALPHABET *abc = NULL;
char *hmmfile = NULL;
char *outhmmfile = NULL;
P7_HMMFILE *hfp = NULL;
FILE *outhmmfp; /* HMM output file handle */
P7_HMM *hmm = NULL;
P7_BG *bg = NULL;
int nhmm;
double x;
float KL;
int status;
char errbuf[eslERRBUFSIZE];
float average_internal_transitions[ p7H_NTRANSITIONS ];
int k;
char errmsg[eslERRBUFSIZE];
/* Process the command line options.
*/
go = esl_getopts_Create(options);
if (esl_opt_ProcessCmdline(go, argc, argv) != eslOK ||
esl_opt_VerifyConfig(go) != eslOK)
{
printf("Failed to parse command line: %s\n", go->errbuf);
esl_usage(stdout, argv[0], usage);
printf("\nTo see more help on available options, do %s -h\n\n", argv[0]);
exit(1);
}
if (esl_opt_GetBoolean(go, "-h") == TRUE)
{
profillic_p7_banner(stdout, argv[0], banner);
esl_usage(stdout, argv[0], usage);
puts("\nOptions:");
esl_opt_DisplayHelp(stdout, go, 0, 2, 80); /* 0=docgroup, 2 = indentation; 80=textwidth*/
exit(0);
}
if (esl_opt_ArgNumber(go) != 2)
{
puts("Incorrect number of command line arguments.");
esl_usage(stdout, argv[0], usage);
printf("\nTo see more help on available options, do %s -h\n\n", argv[0]);
exit(1);
}
if ((hmmfile = esl_opt_GetArg(go, 1)) == NULL)
{
puts("Failed to read <input hmmfile> argument from command line.");
esl_usage(stdout, argv[0], usage);
printf("\nTo see more help on available options, do %s -h\n\n", argv[0]);
exit(1);
}
if ((outhmmfile = esl_opt_GetArg(go, 2)) == NULL)
{
puts("Failed to read <output hmmfile> argument from command line.");
esl_usage(stdout, argv[0], usage);
printf("\nTo see more help on available options, do %s -h\n\n", argv[0]);
exit(1);
}
profillic_p7_banner(stdout, argv[0], banner);
/* Initializations: open the input HMM file for reading
*/
status = p7_hmmfile_OpenE(hmmfile, NULL, &hfp, errbuf);
if (status == eslENOTFOUND) p7_Fail("File existence/permissions problem in trying to open HMM file %s.\n%s\n", hmmfile, errbuf);
else if (status == eslEFORMAT) p7_Fail("File format problem in trying to open HMM file %s.\n%s\n", hmmfile, errbuf);
else if (status != eslOK) p7_Fail("Unexpected error %d in opening HMM file %s.\n%s\n", status, hmmfile, errbuf);
/* Initializations: open the output HMM file for writing
*/
if ((outhmmfp = fopen(outhmmfile, "w")) == NULL) ESL_FAIL(status, errmsg, "Failed to open HMM file %s for writing", outhmmfile);
/* Main body: read HMMs one at a time, print one line of stats
*/
printf("#\n");
printf("# %-4s %-20s %-12s %8s %8s %6s %6s %6s %6s %6s\n", "idx", "name", "accession", "nseq", "eff_nseq", "M", "relent", "info", "p relE", "compKL");
printf("# %-4s %-20s %-12s %8s %8s %6s %6s %6s %6s %6s\n", "----", "--------------------", "------------", "--------", "--------", "------", "------", "------", "------", "------");
nhmm = 0;
while ((status = p7_hmmfile_Read(hfp, &abc, &hmm)) != eslEOF)
{
if (status == eslEOD) esl_fatal("read failed, HMM file %s may be truncated?", hmmfile);
else if (status == eslEFORMAT) esl_fatal("bad file format in HMM file %s", hmmfile);
else if (status == eslEINCOMPAT) esl_fatal("HMM file %s contains different alphabets", hmmfile);
else if (status != eslOK) esl_fatal("Unexpected error in reading HMMs from %s", hmmfile);
nhmm++;
if (bg == NULL) bg = p7_bg_Create(abc);
esl_vec_FSet(average_internal_transitions, p7H_NTRANSITIONS, 0.);
for( k = 1; k < hmm->M; k++ ) {
esl_vec_FAdd(average_internal_transitions, hmm->t[k], p7H_NTRANSITIONS);
}
// Match transitions
esl_vec_FNorm(average_internal_transitions, 3);
// Insert transitions
esl_vec_FNorm(average_internal_transitions + 3, 2);
// Delete transitions
esl_vec_FNorm(average_internal_transitions + 5, 2);
// Ok now set them.
for( k = 1; k < hmm->M; k++ ) {
esl_vec_FCopy( average_internal_transitions, p7H_NTRANSITIONS, hmm->t[k] );
}
if ((status = p7_hmm_Validate(hmm, errmsg, 0.0001)) != eslOK) return status;
if ((status = p7_hmmfile_WriteASCII(outhmmfp, -1, hmm)) != eslOK) ESL_FAIL(status, errmsg, "HMM save failed");
p7_MeanPositionRelativeEntropy(hmm, bg, &x);
p7_hmm_CompositionKLDist(hmm, bg, &KL, NULL);
printf("%-6d %-20s %-12s %8d %8.2f %6d %6.2f %6.2f %6.2f %6.2f\n",
nhmm,
hmm->name,
hmm->acc == NULL ? "-" : hmm->acc,
hmm->nseq,
hmm->eff_nseq,
hmm->M,
p7_MeanMatchRelativeEntropy(hmm, bg),
p7_MeanMatchInfo(hmm, bg),
x,
KL);
/* p7_MeanForwardScore(hmm, bg)); */
p7_hmm_Destroy(hmm);
}
p7_bg_Destroy(bg);
esl_alphabet_Destroy(abc);
p7_hmmfile_Close(hfp);
if (outhmmfp != NULL) fclose(outhmmfp);
esl_getopts_Destroy(go);
exit(0);
}
/* Function: p7_GNull2_ByExpectation()
* Synopsis: Calculate null2 model from posterior probabilities.
* Incept: SRE, Thu Feb 28 09:52:28 2008 [Janelia]
*
* Purpose: Calculate the "null2" model for the envelope encompassed
* by a posterior probability calculation <pp> for model
* <gm>. Return the null2 odds emission probabilities
* $\frac{f'{x}}{f{x}}$ in <null2>, which caller
* provides as space for at least <alphabet->Kp> residues.
*
* The expectation method is applied to envelopes in
* simple, well resolved regions (regions containing just a
* single envelope, where no stochastic traceback
* clustering was required).
*
* Make sure that the posterior probability matrix <pp> has
* been calculated by the caller for only the envelope; thus
* its rows are numbered <1..Ld>, for envelope <ienv..jenv>
* of length <Ld=jenv-ienv+1>.
*
* Args: gm - profile, in any mode, target length model set to <L>
* pp - posterior prob matrix, for <gm> against domain envelope <dsq+i-1> (offset)
* null2 - RETURN: null2 odds ratios per residue; <0..Kp-1>; caller allocated space
*
* Returns: <eslOK> on success; <null2> contains the null2 scores. The 0
* row of <pp> has been used as temp space, and happens to contain
* the expected frequency that each M,I,N,C,J state is used in this
* <pp> matrix to generate residues.
*
* Throws: (no abnormal error conditions)
*/
int
p7_GNull2_ByExpectation(const P7_PROFILE *gm, P7_GMX *pp, float *null2)
{
int M = gm->M;
int Ld = pp->L;
float **dp = pp->dp;
float *xmx = pp->xmx;
float xfactor;
int x; /* over symbols 0..K-1 */
int i; /* over offset envelope dsq positions 1..Ld */
int k; /* over model M states 1..M, I states 1..M-1 */
/* Calculate expected # of times that each emitting state was used
* in generating the Ld residues in this domain.
* The 0 row in <wrk> is used to hold these numbers.
*/
esl_vec_FCopy(pp->dp[1], (M+1)*p7G_NSCELLS, pp->dp[0]);
esl_vec_FCopy(pp->xmx+p7G_NXCELLS, p7G_NXCELLS, pp->xmx);
for (i = 2; i <= Ld; i++)
{
esl_vec_FAdd(pp->dp[0], pp->dp[i], (M+1)*p7G_NSCELLS);
esl_vec_FAdd(pp->xmx, pp->xmx+i*p7G_NXCELLS, p7G_NXCELLS);
}
/* Convert those expected #'s to log frequencies; these we'll use as
* the log posterior weights.
*/
esl_vec_FLog(pp->dp[0], (M+1)*p7G_NSCELLS);
esl_vec_FLog(pp->xmx, p7G_NXCELLS);
esl_vec_FIncrement(pp->dp[0], (M+1)*p7G_NSCELLS, -log((float)Ld));
esl_vec_FIncrement(pp->xmx, p7G_NXCELLS, -log((float)Ld));
/* Calculate null2's log odds emission probabilities, by taking
* posterior weighted sum over all emission vectors used in paths
* explaining the domain.
* This is dog-slow; a point for future optimization.
*/
xfactor = XMX(0,p7G_N);
xfactor = p7_FLogsum(xfactor, XMX(0,p7G_C));
xfactor = p7_FLogsum(xfactor, XMX(0,p7G_J));
esl_vec_FSet(null2, gm->abc->K, -eslINFINITY);
for (x = 0; x < gm->abc->K; x++)
{
for (k = 1; k < M; k++)
{
null2[x] = p7_FLogsum(null2[x], MMX(0,k) + p7P_MSC(gm, k, x));
null2[x] = p7_FLogsum(null2[x], IMX(0,k) + p7P_ISC(gm, k, x));
}
null2[x] = p7_FLogsum(null2[x], MMX(0,M) + p7P_MSC(gm, k, x));
null2[x] = p7_FLogsum(null2[x], xfactor);
}
esl_vec_FExp (null2, gm->abc->K);
/* now null2[x] = \frac{f_d(x)}{f_0(x)} for all x in alphabet,
* 0..K-1, where f_d(x) are the ad hoc "null2" residue frequencies
* for this envelope.
*/
/* make valid scores for all degeneracies, by averaging the odds ratios. */
esl_abc_FAvgScVec(gm->abc, null2); /* does not set gap, nonres, missing */
null2[gm->abc->K] = 1.0; /* gap character */
null2[gm->abc->Kp-2] = 1.0; /* nonresidue "*" */
null2[gm->abc->Kp-1] = 1.0; /* missing data "~" */
return eslOK;
}
/* Function: p7_bg_Read()
* Synopsis: Read background frequencies from a file.
*
* Purpose: Read new background frequencies from file <bgfile>,
* overwriting the frequencies previously in the
* <P7_BG> object <bg>.
*
* Note that <bg> is already created by the caller, not
* created here. Also note that <p7_bg_Read()> only reads
* residue background frequencies used for the "null
* model", whereas a <P7_BG> object contains additional
* information for the bias filter and for the biased
* composition correction.
*
* Args: bgfile - file to read.
* bg - existing <P7_BG> object provided by the caller.
* errbuf - OPTIONAL: space for an error message, upon parse errors; or NULL.
*
* Returns: <eslOK> on success, and background frequencies in <bg>
* are overwritten.
*
* <eslENOTFOUND> if <bgfile> can't be opened for reading.
* <eslEFORMAT> if parsing of <bgfile> fails for some
* reason. In both cases, <errbuf> contains a
* user-directed error message upon return, including (if
* relevant) the file name <bgfile> and the line number on
* which an error was detected. <bg> is unmodified.
*
* Throws: <eslEMEM> on allocation failure; <bg> is unmodified,
* and <errbuf> is empty.
*/
int
p7_bg_Read(char *bgfile, P7_BG *bg, char *errbuf)
{
ESL_FILEPARSER *efp = NULL;
float *fq = NULL;
int n = 0;
char *tok;
int toklen;
int alphatype;
ESL_DSQ x;
int status;
if (errbuf) errbuf[0] = '\0';
status = esl_fileparser_Open(bgfile, NULL, &efp);
if (status == eslENOTFOUND) ESL_XFAIL(eslENOTFOUND, errbuf, "couldn't open bg file %s for reading", bgfile);
else if (status != eslOK) goto ERROR;
esl_fileparser_SetCommentChar(efp, '#');
/* First token is alphabet type: amino | DNA | RNA */
status = esl_fileparser_GetToken(efp, &tok, &toklen);
if (status == eslEOF) ESL_XFAIL(eslEFORMAT, errbuf, "premature end of file [line %d of bgfile %s]", efp->linenumber, bgfile);
else if (status != eslOK) goto ERROR;
alphatype = esl_abc_EncodeType(tok);
if (alphatype == eslUNKNOWN) ESL_XFAIL(eslEFORMAT, errbuf, "expected alphabet type but saw \"%s\" [line %d of bgfile %s]", tok, efp->linenumber, bgfile);
else if (alphatype != bg->abc->type) ESL_XFAIL(eslEFORMAT, errbuf, "bg file's alphabet is %s; expected %s [line %d, %s]", tok, esl_abc_DecodeType(bg->abc->type), efp->linenumber, bgfile);
ESL_ALLOC(fq, sizeof(float) * bg->abc->K);
esl_vec_FSet(fq, bg->abc->K, -1.0);
while ((status = esl_fileparser_NextLine(efp)) == eslOK)
{
status = esl_fileparser_GetTokenOnLine(efp, &tok, &toklen);
if (status == eslEOL) ESL_XFAIL(eslEFORMAT, errbuf, "premature end of file [line %d of bgfile %s", efp->linenumber, bgfile);
else if (status != eslOK) goto ERROR;
if (toklen != 1 || ! esl_abc_CIsCanonical(bg->abc, *tok))
ESL_XFAIL(eslEFORMAT, errbuf, "expected to parse a residue letter; saw %s [line %d of bgfile %s]", tok, efp->linenumber, bgfile);
x = esl_abc_DigitizeSymbol(bg->abc, *tok);
if (fq[x] != -1.0) ESL_XFAIL(eslEFORMAT, errbuf, "already parsed probability of %c [line %d of bgfile %s]", bg->abc->sym[x], efp->linenumber, bgfile);
n++;
status = esl_fileparser_GetTokenOnLine(efp, &tok, &toklen);
if (status == eslEOL) ESL_XFAIL(eslEFORMAT, errbuf, "premature end of file, expected a probability [line %d of bgfile %s]", efp->linenumber, bgfile);
else if (status != eslOK) goto ERROR;
if (! esl_str_IsReal(tok)) ESL_XFAIL(eslEFORMAT, errbuf, "expected a probability, saw %s [line %d of bgfile %s]", tok, efp->linenumber, bgfile);
fq[x] = atof(tok);
status = esl_fileparser_GetTokenOnLine(efp, &tok, &toklen);
if (status == eslOK) ESL_XFAIL(eslEFORMAT, errbuf, "extra unexpected data found [line %d of bgfile %s]", efp->linenumber, bgfile);
else if (status != eslEOL) goto ERROR;
}
if (status != eslEOF) goto ERROR;
if ( n != bg->abc->K)
ESL_XFAIL(eslEFORMAT, errbuf, "expected %d residue frequencies, but found %d in bgfile %s", bg->abc->K, n, bgfile);
if ( esl_FCompare(esl_vec_FSum(fq, bg->abc->K), 1.0, 0.001) != eslOK)
ESL_XFAIL(eslEFORMAT, errbuf, "residue frequencies do not sum to 1.0 in bgfile %s", bgfile);
/* all checking complete. no more error cases. overwrite bg with the new frequencies */
esl_vec_FNorm(fq, bg->abc->K);
esl_vec_FCopy(fq, bg->abc->K, bg->f);
free(fq);
esl_fileparser_Close(efp);
return eslOK;
ERROR:
if (fq) free(fq);
if (efp) esl_fileparser_Close(efp);
return status;
}
/* Function: p7_profile_Create()
* Synopsis: Allocates a profile.
*
* Purpose: Allocates for a profile of up to <M> nodes, for digital
* alphabet <abc>.
*
* Because this function might be in the critical path (in
* hmmscan, for example), we leave much of the model
* uninitialized, including scores and length model
* probabilities. The <p7_profile_Config()> call is what
* sets these.
*
* The reference pointer <gm->abc> is set to <abc>.
*
* Returns: a pointer to the newly allocated profile.
*
* Throws: <NULL> on allocation error.
*/
P7_PROFILE *
p7_profile_Create(int allocM, const ESL_ALPHABET *abc)
{
P7_PROFILE *gm = NULL;
int x;
int status;
/* level 0 */
ESL_ALLOC(gm, sizeof(P7_PROFILE));
gm->tsc = NULL;
gm->rsc = NULL;
gm->name = NULL;
gm->acc = NULL;
gm->desc = NULL;
gm->rf = NULL;
gm->mm = NULL;
gm->cs = NULL;
gm->consensus = NULL;
/* level 1 */
ESL_ALLOC(gm->tsc, sizeof(float) * (allocM+1) * p7P_NTRANS); /* 0..M */
ESL_ALLOC(gm->rsc, sizeof(float *) * abc->Kp);
ESL_ALLOC(gm->rf, sizeof(char) * (allocM+2)); /* yes, +2: each is (0)1..M, +trailing \0 */
ESL_ALLOC(gm->mm, sizeof(char) * (allocM+2));
ESL_ALLOC(gm->cs, sizeof(char) * (allocM+2));
ESL_ALLOC(gm->consensus, sizeof(char) * (allocM+2));
gm->rsc[0] = NULL;
/* level 2 */
ESL_ALLOC(gm->rsc[0], sizeof(float) * abc->Kp * (allocM+1) * p7P_NR);
for (x = 1; x < abc->Kp; x++)
gm->rsc[x] = gm->rsc[0] + x * (allocM+1) * p7P_NR;
/* Initialization of tsc[0], including removal of I0. tsc[k-1,LM],tsc[k-1,GM] will be configured + overwritten later */
esl_vec_FSet(gm->tsc, p7P_NTRANS, -eslINFINITY);
/* tsc[M] initialized and Im removed when we know actual M : see modelconfig.c */
for (x = 0; x < abc->Kp; x++) {
P7P_MSC(gm, 0, x) = -eslINFINITY; /* no emissions from nonexistent M_0... */
P7P_ISC(gm, 0, x) = -eslINFINITY; /* nor I_0... */
/* I_M is initialized in profile config, when we know actual M, not just allocated max M */
}
x = esl_abc_XGetGap(abc); /* no emission can emit/score gap characters */
esl_vec_FSet(gm->rsc[x], (allocM+1)*p7P_NR, -eslINFINITY);
x = esl_abc_XGetMissing(abc); /* no emission can emit/score missing data characters */
esl_vec_FSet(gm->rsc[x], (allocM+1)*p7P_NR, -eslINFINITY);
/* Set remaining info */
gm->M = 0;
gm->allocM = allocM;
gm->L = -1; /* "unset" flag */
gm->nj = -1.0f; /* "unset" flag */
gm->pglocal = -1.0f; /* "unset" flag */
gm->roff = -1;
gm->eoff = -1;
gm->offs[p7_MOFFSET] = -1;
gm->offs[p7_FOFFSET] = -1;
gm->offs[p7_POFFSET] = -1;
gm->name = NULL;
gm->acc = NULL;
gm->desc = NULL;
gm->rf[0] = 0; /* RF line is optional annotation; this flags that it's not set yet */
gm->mm[0] = 0; /* likewise for MM annotation line */
gm->cs[0] = 0; /* likewise for CS annotation line */
gm->consensus[0] = 0;
for (x = 0; x < p7_NEVPARAM; x++) gm->evparam[x] = p7_EVPARAM_UNSET;
for (x = 0; x < p7_NCUTOFFS; x++) gm->cutoff[x] = p7_CUTOFF_UNSET;
for (x = 0; x < p7_MAXABET; x++) gm->compo[x] = p7_COMPO_UNSET;
gm->max_length = -1; /* "unset" */
gm->abc = abc;
return gm;
ERROR:
p7_profile_Destroy(gm);
return NULL;
}
/* glocal_region_trace_ensemble()
* EPN, Tue Oct 5 10:13:25 2010
*
* Based on p7_domaindef.c's region_trace_ensemble(). Modified so that
* generic matrices (which can be used for glocally configured models)
* can be used. An additional parameter <do_null2> has been added,
* so that null2-related calculations are only done if necessary.
* That is, they're skipped if null2 has been turned off in the pipeline.
*
* Notes from p7_domaindef.c::region_trace_ensemble():
*~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
* SRE, Fri Feb 8 11:49:44 2008 [Janelia]
*
* Here, we've decided that region <ireg>..<jreg> in sequence <dsq> might be
* composed of more than one domain, and we're going to use clustering
* of a posterior ensemble of stochastic tracebacks to sort it out.
*
* Caller provides a filled Forward matrix in <fwd> for the sequence
* region <dsq+ireg-1>, length <jreg-ireg+1>, for the model <om>
* configured in multihit mode with its target length distribution
* set to the total length of <dsq>: i.e., the same model
* configuration used to score the complete sequence (if it weren't
* multihit, we wouldn't be worried about multiple domains).
*
* Caller also provides a DP matrix in <wrk> containing at least one
* row, for use as temporary workspace. (This will typically be the
* caller's Backwards matrix, which we haven't yet used at this point
* in the processing pipeline.)
*
* Caller provides <ddef>, which defines heuristic parameters that
* control the clustering, and provides working space for the
* calculation and the answers. The <ddef->sp> object must have been
* reused (i.e., it needs to be fresh; we're going to use it here);
* the caller needs to Reuse() it specifically, because it can't just
* Reuse() the whole <ddef>, when it's in the process of analyzing
* regions.
*
* Upon return, <*ret_nc> contains the number of clusters that were
* defined.
*
* The caller can retrieve info on each cluster by calling
* <p7_spensemble_GetClusterCoords(ddef->sp...)> on the
* <P7_SPENSEMBLE> object in <ddef>.
*
* Other information on what's happened in working memory:
*
* <ddef->n2sc[ireg..jreg]> now contains log f'(x_i) / f(x_i) null2 scores
* for each residue.
*
* <ddef->sp> gets filled in, and upon return, it's holding the answers
* (the cluster definitions). When the caller is done retrieving those
* answers, it needs to <esl_spensemble_Reuse()> it before calling
* <region_trace_ensemble()> again.
*
* <ddef->tr> is used as working memory for sampled traces.
*
* <wrk> has had its zero row clobbered as working space for a null2 calculation.
*~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
*/
static int
glocal_region_trace_ensemble(P7_DOMAINDEF *ddef, const P7_PROFILE *gm, const ESL_DSQ *dsq, int ireg, int jreg,
const P7_GMX *fwd, P7_GMX *wrk, int do_null2, int *ret_nc)
{
int Lr = jreg-ireg+1;
int t, d, d2;
int nov, n;
int nc;
int pos;
float null2[p7_MAXCODE];
esl_vec_FSet(ddef->n2sc+ireg, Lr, 0.0); /* zero the null2 scores in region */
/* By default, we make results reproducible by forcing a reset of
* the RNG to its originally seeded state.
*/
if (ddef->do_reseeding)
esl_randomness_Init(ddef->r, esl_randomness_GetSeed(ddef->r));
/* Collect an ensemble of sampled traces; calculate null2 odds ratios from these if nec */
for (t = 0; t < ddef->nsamples; t++)
{
p7_GStochasticTrace(ddef->r, dsq+ireg-1, Lr, gm, fwd, ddef->tr);
p7_trace_Index(ddef->tr);
pos = 1;
for (d = 0; d < ddef->tr->ndom; d++)
{
p7_spensemble_Add(ddef->sp, t, ddef->tr->sqfrom[d]+ireg-1, ddef->tr->sqto[d]+ireg-1, ddef->tr->hmmfrom[d], ddef->tr->hmmto[d]);
if(do_null2) {
p7_GNull2_ByTrace(gm, ddef->tr, ddef->tr->tfrom[d], ddef->tr->tto[d], wrk, null2);
/* residues outside domains get bumped +1: because f'(x) = f(x), so f'(x)/f(x) = 1 in these segments */
for (; pos <= ddef->tr->sqfrom[d]; pos++) ddef->n2sc[ireg+pos-1] += 1.0;
/* Residues inside domains get bumped by their null2 ratio */
for (; pos <= ddef->tr->sqto[d]; pos++) ddef->n2sc[ireg+pos-1] += null2[dsq[ireg+pos-1]];
}
}
if(do_null2) {
/* the remaining residues in the region outside any domains get +1 */
for (; pos <= Lr; pos++) ddef->n2sc[ireg+pos-1] += 1.0;
}
p7_trace_Reuse(ddef->tr);
}
/* Convert the accumulated n2sc[] ratios in this region to log odds null2 scores on each residue. */
if(do_null2) {
for (pos = ireg; pos <= jreg; pos++)
ddef->n2sc[pos] = logf(ddef->n2sc[pos] / (float) ddef->nsamples);
}
/* Cluster the ensemble of traces to break region into envelopes. */
p7_spensemble_Cluster(ddef->sp, ddef->min_overlap, ddef->of_smaller, ddef->max_diagdiff, ddef->min_posterior, ddef->min_endpointp, &nc);
/* A little hacky now. Remove "dominated" domains relative to seq coords. */
for (d = 0; d < nc; d++)
ddef->sp->assignment[d] = 0; /* overload <assignment> to flag that a domain is dominated */
/* who dominates who? (by post prob) */
for (d = 0; d < nc; d++)
{
for (d2 = d+1; d2 < nc; d2++)
{
nov = ESL_MIN(ddef->sp->sigc[d].j, ddef->sp->sigc[d2].j) - ESL_MAX(ddef->sp->sigc[d].i, ddef->sp->sigc[d2].i) + 1;
if (nov == 0) break;
n = ESL_MIN(ddef->sp->sigc[d].j - ddef->sp->sigc[d].i + 1, ddef->sp->sigc[d2].j - ddef->sp->sigc[d2].i + 1);
if ((float) nov / (float) n >= 0.8) /* overlap */
{
if (ddef->sp->sigc[d].prob > ddef->sp->sigc[d2].prob) ddef->sp->assignment[d2] = 1;
else ddef->sp->assignment[d] = 1;
}
}
}
/* shrink the sigc list, removing dominated domains */
d = 0;
for (d2 = 0; d2 < nc; d2++)
{
if (ddef->sp->assignment[d2]) continue; /* skip domain d2, it's dominated. */
if (d != d2) memcpy(ddef->sp->sigc + d, ddef->sp->sigc + d2, sizeof(struct p7_spcoord_s));
d++;
}
ddef->sp->nc = d;
*ret_nc = d;
return eslOK;
}
/* Function: p7_domaindef_GlocalByPosteriorHeuristics()
* Synopsis: Define glocal domains in a sequence using posterior probs.
* Incept: EPN, Tue Oct 5 10:02:34 2010
* SRE, Sat Feb 23 08:17:44 2008 [Janelia] (p7_domaindef_ByPosteriorHeuristics())
*
* Purpose: Given a sequence <sq> and model <gm> for which we have
* already calculated a Forward and Backward parsing
* matrices <gxf> and <gxb>; use posterior probability
* heuristics to determine an annotated domain structure;
* and for each domain found, score it (with null2
* calculations) and obtain an optimal accuracy alignment,
* using <fwd> and <bck> matrices as workspace for the
* necessary full-matrix DP calculations. Caller provides a
* new or reused <ddef> object to hold these results.
*
* As a special case, if the profile is in unihit mode
* upon entering, we don't ever modify its configuration.
* This is especially important if this function is
* being used within a search/scan pipeline with a
* specially configured p7 profile in which N->N and/or
* C->C transitions have been set to IMPOSSIBLE. (If
* we were to call ReconfigLength() on such a profile
* we would make those transitions possible.)
*
* One case in which profile reconfiguration is necessary
* is when multiple domains are suspected. However, we
* guard against this if the profile enters in unihit mode
* by no allowing multiple domains (in fact, it should
* never happen because J states are unreachable in unihit
* profiles). If multiple domains are suspected in this case,
* we return eslEINCONCEIVABLE.
*
* Upon return, <ddef> contains the definitions of all the
* domains: their bounds, their null-corrected Forward
* scores, and their optimal posterior accuracy alignments.
*
* <do_null2> is TRUE if we'll eventually apply a null2
* penalty FALSE if not. If FALSE, we can save time by
* skipping Backward calls at some stages.
*
* Returns: <eslOK> on success.
*
* <eslERANGE> on numeric overflow in posterior
* decoding. This should not be possible for multihit
* models.
*
* <eslEINCONCEIVABLE> if profile enters as unihit but
* multiple domains are suspected.
*/
int
p7_domaindef_GlocalByPosteriorHeuristics(const ESL_SQ *sq, P7_PROFILE *gm,
P7_GMX *gxf, P7_GMX *gxb, P7_GMX *fwd, P7_GMX *bck,
P7_DOMAINDEF *ddef, int do_null2)
{
int i, j;
int triggered;
int d;
int i2,j2;
int last_j2;
int nc;
int saveL = gm->L; /* Save the length config of <om>; will restore upon return */
int save_mode = gm->mode; /* Likewise for the mode. */
int status;
int save_mode_is_unihit;
save_mode_is_unihit = (p7_IsMulti(save_mode)) ? FALSE : TRUE; /* if save_mode_is_unihit is TRUE, we never modify profile's configuration (length nor mode) */
if ((status = p7_domaindef_GrowTo(ddef, sq->n)) != eslOK) return status; /* ddef's btot,etot,mocc now ready for seq of length n */
/*printf("GDD P7 mode: %d\n", gm->mode);*/
if ((status = p7_GDomainDecoding(gm, gxf, gxb, ddef)) != eslOK) return status; /* ddef->{btot,etot,mocc} now made. */
/*printf("In p7_domaindef_GlocalByPosteriorHeuristics(): mode: %d rt1: %g rt2: %g rt3: %g nsamples: %d reseed: %d\n", save_mode, ddef->rt1, ddef->rt2, ddef->rt3, ddef->nsamples, ddef->do_reseeding);*/
esl_vec_FSet(ddef->n2sc, sq->n+1, 0.0); /* ddef->n2sc null2 scores are initialized */
ddef->nexpected = ddef->btot[sq->n]; /* posterior expectation for # of domains (same as etot[sq->n]) */
if(! save_mode_is_unihit) p7_ReconfigUnihit(gm, saveL); /* process each domain in unihit mode, regardless of gm->mode */
i = -1;
triggered = FALSE;
for (j = 1; j <= sq->n; j++)
{
/*printf("GDD j: %5d m: %.5f b: %8.3f e: %8.3f bhere: %8.3f ehere: %8.3f\n",
j,
ddef->mocc[j],
ddef->btot[j],
ddef->etot[j],
ddef->btot[j] - ddef->btot[j-1],
ddef->etot[j] - ddef->etot[j-1]);
*/
if (! triggered)
{ /* xref J2/101 for what the logic below is: */
if (ddef->mocc[j] - (ddef->btot[j] - ddef->btot[j-1]) < ddef->rt2) i = j;
else if (i == -1) i = j;
if (ddef->mocc[j] >= ddef->rt1) triggered = TRUE;
}
else if (ddef->mocc[j] - (ddef->etot[j] - ddef->etot[j-1]) < ddef->rt2)
{
/* We have a region i..j to evaluate. */
p7_gmx_GrowTo(fwd, gm->M, j-i+1);
p7_gmx_GrowTo(bck, gm->M, j-i+1);
ddef->nregions++;
if (is_multidomain_region(ddef, i, j))
{
if(save_mode_is_unihit) return eslEINCONCEIVABLE;
/* This region appears to contain more than one domain, so we have to
* resolve it by cluster analysis of posterior trace samples, to define
* one or more domain envelopes.
*/
ddef->nclustered++;
/* Resolve the region into domains by stochastic trace
* clustering; assign position-specific null2 model by
* stochastic trace clustering; there is redundancy
* here; we will consolidate later if null2 strategy
* works
*/
p7_ReconfigMultihit(gm, saveL);
p7_GForward(sq->dsq+i-1, j-i+1, gm, fwd, NULL);
glocal_region_trace_ensemble(ddef, gm, sq->dsq, i, j, fwd, bck, do_null2, &nc);
p7_ReconfigUnihit(gm, saveL);
/* ddef->n2sc is now set on i..j by the traceback-dependent method */
last_j2 = 0;
for (d = 0; d < nc; d++) {
p7_spensemble_GetClusterCoords(ddef->sp, d, &i2, &j2, NULL, NULL, NULL);
if (i2 <= last_j2) ddef->noverlaps++;
/* Note that k..m coords on model are available, but
* we're currently ignoring them. This leads to a
* rare clustering bug that we eventually need to fix
* properly [xref J3/32]: two different regions in one
* profile HMM might have hit same seq domain, and
* when we now go to calculate an OA trace, nothing
* constrains us to find the two different alignments
* to the HMM; in fact, because OA is optimal, we'll
* find one and the *same* alignment, leading to an
* apparent duplicate alignment in the output.
*
* Registered as #h74, Dec 2009, after EBI finds and
* reports it. #h74 is worked around in p7_tophits.c
* by hiding all but one envelope with an identical
* alignment, in the rare event that this
* happens. [xref J5/130].
*/
ddef->nenvelopes++;
if (glocal_rescore_isolated_domain(ddef, gm, sq, fwd, bck, i2, j2, TRUE, do_null2, FALSE) == eslOK)
last_j2 = j2;
}
p7_spensemble_Reuse(ddef->sp);
p7_trace_Reuse(ddef->tr);
}
else
{
/* The region looks simple, single domain; convert the region to an envelope. */
ddef->nenvelopes++;
glocal_rescore_isolated_domain(ddef, gm, sq, fwd, bck, i, j, FALSE, do_null2, FALSE);
}
i = -1;
triggered = FALSE;
}
}
/* If profile was unihit upon entrance, we didn't modify its configuration (length nor mode),
* else restore it to its original multihit mode, and to its original length model */
if (! save_mode_is_unihit) {
p7_ReconfigMultihit(gm, saveL);
}
return eslOK;
}
