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/* -*- mode: c; tab-width: 4; c-basic-offset: 4; indent-tabs-mode: nil -*- */
/*********************************************************************
* Clustal Omega - Multiple sequence alignment
*
* Copyright (C) 2010 University College Dublin
*
* Clustal-Omega 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 2 of the
* License, or (at your option) any later version.
*
* This file is part of Clustal-Omega.
*
********************************************************************/
/*
* RCS $Id: hhhit.h 243 2011-05-31 13:49:19Z fabian $
*/
// hhhit.h
//////////////////////////////////////////////////////////////////////////////
/* Describes an alignment of two profiles.
Used as list element in Hits : List<Hit> */
//////////////////////////////////////////////////////////////////////////////
class Hit
{
public:
char* longname; // Name of HMM
char* name; // One-word name of HMM
char* file; // Basename (with path, without extension) of alignment file that was used to construct the HMM
// (path from db-file is prepended to FILE record in HMM file!)
char fam[IDLEN]; // family ID (derived from name) (FAM field)
char sfam[IDLEN]; // superfamily ID (derived from name)
char fold[IDLEN]; // fold ID (derived from name)
char cl[IDLEN]; // class ID (derived from name)
int index; // index of HMM in order of reading in (first=0)
char* dbfile; // full database file name from which HMM was read
long ftellpos; // start position of HMM in database file
float score; // Score of alignment (i.e. of Viterbi path)
float score_sort; // score to sort hits in output list (negative means first/best!)
float score_aass; // first: just hit.score, then hit.logPval-SSSCORE2NATLOG*hit.score_ss;(negative means best!)
float score_ss; // Part of score due to secondary structure
float Pval; // P-value for whole protein based on score distribution of query
float Pvalt; // P-value for whole protein based on score distribution of template
float logPval; // natural logarithm of Pval
float logPvalt; // natural logarithm of Pvalt
float Eval; // E-value for whole protein
float Probab; // probability in % for a positive (depends only on score)
float weight; // weight of hit for P-value calculation (= 1/#HMMs-in-family/#families-in-superfamily)
double Pforward; // scaled total forward probability : Pforward * Product_{i=1}^{Lq+1}(scale[i])
/* float score_comp; // compositional similarity score */
/* float logPcomp; // natural logarithm of Pvalue for compositional similarity score */
/* float Prep; // P-value for single-repeat hit */
/* float Erep; // E-value for single-repeat hit */
/* float logPrep; // natural logarithm of P-value for single-repeat hit */
float E1val; // E-value for whole protein from transitive scoring
float logP1val; // natural logarithm of P1val, the transitive P-value
int L; // Number of match states in template
int irep; // Index of single-repeat hit (1: highest scoring repeat hit)
int nrep; // Number of single-repeat hits with one template
int n_display; // number of sequences stored for display of alignment
char** sname; // names of stored sequences
char** seq; // residues of stored sequences (first at pos 1)
int nss_dssp; // index of dssp secondary structure sequence in seq[]
int nsa_dssp; // index of of dssp solvent accessibility in seq[]
int nss_pred; // index of dssp secondary structure sequence in seq[]
int nss_conf; // index of dssp secondary structure sequence in seq[]
int nfirst; // index of query sequence in seq[]
int ncons; // index of consensus sequence
int nsteps; // index for last step in Viterbi path; (first=1)
int* i; // i[step] = query match state at step of Viterbi path
int* j; // j[step] = template match state at step of Viterbi path
char* states; // state at step of Viterbi path 0: Start 1: M(MM) 2: A(-D) 3: B(IM) 4: C(D-) 5 D(MI)
float* S; // S[step] = match-match score contribution at alignment step
float* S_ss; // S_ss[step] = secondary structure score contribution
float* P_posterior; // P_posterior[step] = posterior prob for MM states (otherwise zero)
char* Xcons; // consensus sequence for aligned states in internal representation (A=0 R=1 N=2 D=3 ...)
int i1; // First aligned residue in query
int i2; // Last aligned residue in query
int j1; // First aligned residue in template
int j2; // Last aligned residue in template
int matched_cols; // number of matched columns in alignment against query
int ssm1; // SS scoring AFTER alignment? 0:no 1:yes; t->dssp q->psipred 2:yes; q->dssp t->psipred
int ssm2; // SS scoring DURING alignment? 0:no 1:yes; t->dssp q->psipred 2:yes; q->dssp t->psipred
char self; // 0: align two different HMMs 1: align HMM with itself
int min_overlap; // Minimum overlap between query and template
float sum_of_probs; // sum of probabilities for Maximum ACcuracy alignment (if dssp states defined, only aligned pairs with defined dssp state contribute to sum)
float Neff_HMM; // Diversity of underlying alignment
// Constructor (only set pointers to NULL)
Hit();
~Hit(){};
// Free all allocated memory (to delete list of hits)
void Delete();
// Allocate/delete memory for dynamic programming matrix
void AllocateBacktraceMatrix(int Nq, int Nt);
void DeleteBacktraceMatrix(int Nq);
void AllocateForwardMatrix(int Nq, int Nt);
void DeleteForwardMatrix(int Nq);
void AllocateBackwardMatrix(int Nq, int Nt);
void DeleteBackwardMatrix(int Nq);
// Compare an HMM with overlapping subalignments
void Viterbi(HMM& q, HMM& t, float** Sstruc=NULL);
// Compare two HMMs with each other in lin space
int Forward(HMM& q, HMM& t, float** Pstruc=NULL);
// Compare two HMMs with each other in lin space
int Backward(HMM& q, HMM& t);
// Find maximum accuracy alignment (after running Forward and Backward algorithms)
void MACAlignment(HMM& q, HMM& t);
// Trace back alignment of two profiles based on matrices bXX[][]
void Backtrace(HMM& q, HMM& t);
// Trace back alignment of two profiles based on matrices bXX[][]
void StochasticBacktrace(HMM& q, HMM& t, char maximize=0);
// Trace back MAC alignment of two profiles based on matrix bMM[][]
void BacktraceMAC(HMM& q, HMM& t);
// Calculate secondary structure score between columns i and j of two HMMs (query and template)
inline float ScoreSS(HMM& q, HMM& t, int i, int j, int ssm);
// Calculate secondary structure score between columns i and j of two HMMs (query and template)
inline float ScoreSS(HMM& q, HMM& t, int i, int j);
// Calculate total score (including secondary structure score and compositional bias correction
inline float ScoreTot(HMM& q, HMM& t, int i, int j);
// Calculate score (excluding secondary structure score and compositional bias correction
inline float ScoreAA(HMM& q, HMM& t, int i, int j);
// Comparison (used to sort list of hits)
int operator<(const Hit& hit2) {return score_sort<hit2.score_sort;}
// Merge HMM with next aligned HMM
void MergeHMM(HMM& Q, HMM& t, float wk[]);
#ifdef CLUSTALO
void ClobberGlobal(void);
#endif
double** B_MM; // Backward matrices
private:
char state; // 0: Start/STOP state 1: MM state 2: GD state (-D) 3: IM state 4: DG state (D-) 5 MI state
char** bMM; // (backtracing) bMM[i][j] = STOP:start of alignment MM:prev was MM GD:prev was GD etc
char** bGD; // (backtracing) bMM[i][j] = STOP:start of alignment MM:prev was MM SAME:prev was GD
char** bDG; // (backtracing)
char** bIM; // (backtracing)
char** bMI; // (backtracing)
char** cell_off; // cell_off[i][j]=1 means this cell will get score -infinity
double** F_MM; // Forward matrices
double** F_GD; // F_XY[i][j] * Prod_1^i(scale[i])
double** F_DG; // = Sum_x1..xl{ P(HMMs aligned up to Xi||Yj co-emmitted x1..xl ) / (Prod_k=1^l f(x_k)) }
double** F_IM; // end gaps are not penalized!
double** F_MI; //
double* scale; //
double** B_GD; // B_XY[i][j] * Prod_i+1^(L+1) (scale[i])
double** B_DG; // = Sum_x2..xl{ P(HMMs aligned from Xi||Yj to end co-emmitted x2..xl ) / (Prod_k=2^l f(x_k)) }
double** B_IM; // end gaps are not penalized!
double** B_MI; //
void InitializeBacktrace(HMM& q, HMM& t);
void InitializeForAlignment(HMM& q, HMM& t);
};
double Pvalue(double x, double a[]);
double Pvalue(float x, float lamda, float mu);
double logPvalue(float x, float lamda, float mu);
double logPvalue(float x, double a[]);
double Probab(Hit& hit);
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