bool Realigner::computeSWalignment(vector<CigarOp>& CigarData, vector<MDelement>& MD_data,
unsigned int& start_pos_update) {
string dummy_string;
//AlignmentCell *best_cell;
//best_cell = &DP_matrix[0][0];
// Compute boundaries for tubed alignment around previously found alignment
if (!ComputeTubedAlignmentBoundaries())
return false;
// Path ordering creates left aligned InDels
vector<int> insertion_path_ordering(3);
vector<int> deletion_path_ordering(3);
insertion_path_ordering[0] = FROM_I;
insertion_path_ordering[1] = FROM_MATCH;
insertion_path_ordering[2] = FROM_MISM;
deletion_path_ordering[0] = FROM_D;
deletion_path_ordering[1] = FROM_MATCH;
deletion_path_ordering[2] = FROM_MISM;
// --- Compute first row and column of the matrix
// First row: moving horizontally for insertions
if (!soft_clip_key_end_) {
DP_matrix[0][1].best_path_direction = FROM_I;
DP_matrix[0][1].best_score = kGapOpen;
DP_matrix[0][1].scores[FROM_I] = kGapOpen;
DP_matrix[0][1].scores[FROM_NOWHERE] = kNotApplicable;
for (unsigned int q_idx=2; q_idx<q_limit_plus_[0]; q_idx++) {
DP_matrix[0][q_idx].in_directions[FROM_I] = FROM_I;
DP_matrix[0][q_idx].scores[FROM_NOWHERE] = kNotApplicable;
DP_matrix[0][q_idx].scores[FROM_I] = DP_matrix[0][q_idx-1].best_score + kGapExtend;
DP_matrix[0][q_idx].best_path_direction = FROM_I;
DP_matrix[0][q_idx].best_score = DP_matrix[0][q_idx-1].best_score + kGapExtend;
}
}
if (!start_anywhere_in_ref_) {
// First column: moving vertically for deletions
DP_matrix[1][0].best_path_direction = FROM_D;
DP_matrix[1][0].best_score = kGapOpen;
DP_matrix[1][0].scores[FROM_D] = kGapOpen;
DP_matrix[1][0].scores[FROM_NOWHERE] = kNotApplicable;
unsigned int t = 2;
while (t < q_limit_minus_.size() and q_limit_minus_[t] == 0) {
DP_matrix[t][0].in_directions[FROM_D] = FROM_D;
DP_matrix[t][0].scores[FROM_NOWHERE] = kNotApplicable;
DP_matrix[t][0].scores[FROM_D] = DP_matrix[t-1][0].best_score + kGapExtend;
DP_matrix[t][0].best_path_direction = FROM_D;
DP_matrix[t][0].best_score = DP_matrix[t-1][0].best_score + kGapExtend;
t++;
}
}
// ------ Main alignment loop ------
vector<int> temp_scores(FROM_NOWHERE);
vector<int> highest_score_cell(2, 0);
for (unsigned int t_idx=1; t_idx<t_seq_.size()+1; t_idx++) {
for (unsigned int q_idx=q_limit_minus_[t_idx]; q_idx<q_limit_plus_[t_idx]; q_idx++) {
if (q_idx == 0)
continue;
// Scoring for Match; Mismatch / Insertion / Deletion;
DP_matrix[t_idx][q_idx].scores.assign(FROM_NOWHERE+1, kNotApplicable);
DP_matrix[t_idx][q_idx].in_directions.assign(FROM_NOWHERE, FROM_NOWHERE);
if (soft_clip_key_end_)
DP_matrix[t_idx][q_idx].scores[FROM_NOWHERE] = 0;
// 1) - Match / Mismatch Score
DP_matrix[t_idx][q_idx].is_match = isMatch(q_seq_[q_idx-1], t_seq_[t_idx-1]);
if (DP_matrix[t_idx][q_idx].is_match) {
DP_matrix[t_idx][q_idx].in_directions[FROM_MATCH] = DP_matrix[t_idx-1][q_idx-1].best_path_direction;
DP_matrix[t_idx][q_idx].scores[FROM_MATCH] = DP_matrix[t_idx-1][q_idx-1].best_score + kMatchScore;
} else {
DP_matrix[t_idx][q_idx].in_directions[FROM_MISM] = DP_matrix[t_idx-1][q_idx-1].best_path_direction;
DP_matrix[t_idx][q_idx].scores[FROM_MISM] = DP_matrix[t_idx-1][q_idx-1].best_score + kMismatchScore;
}
// 2) - Insertion Score
temp_scores.assign(FROM_NOWHERE, kNotApplicable);
temp_scores[FROM_MATCH] = DP_matrix[t_idx][q_idx-1].scores[FROM_MATCH] + kGapOpen;
temp_scores[FROM_I] = DP_matrix[t_idx][q_idx-1].scores[FROM_I] + kGapExtend;
temp_scores[FROM_MISM] = DP_matrix[t_idx][q_idx-1].scores[FROM_MISM] + kGapOpen;
DP_matrix[t_idx][q_idx].scores[FROM_I] = kNotApplicable;
DP_matrix[t_idx][q_idx].in_directions[FROM_I] = FROM_NOWHERE;
for (int i=0; i<(int)insertion_path_ordering.size(); i++) {
if (temp_scores[insertion_path_ordering[i]] > DP_matrix[t_idx][q_idx].scores[FROM_I]) {
DP_matrix[t_idx][q_idx].scores[FROM_I] = temp_scores[insertion_path_ordering[i]];
DP_matrix[t_idx][q_idx].in_directions[FROM_I] = insertion_path_ordering[i];
}
}
// 3) - Deletion Score
temp_scores.assign(FROM_NOWHERE, kNotApplicable);
temp_scores[FROM_MATCH] = DP_matrix[t_idx-1][q_idx].scores[FROM_MATCH] + kGapOpen;
temp_scores[FROM_D] = DP_matrix[t_idx-1][q_idx].scores[FROM_D] + kGapExtend;
temp_scores[FROM_MISM] = DP_matrix[t_idx-1][q_idx].scores[FROM_MISM] + kGapOpen;
DP_matrix[t_idx][q_idx].scores[FROM_D] = kNotApplicable;
DP_matrix[t_idx][q_idx].in_directions[FROM_D] = FROM_NOWHERE;
for (int i=0; i<(int)deletion_path_ordering.size(); i++) {
if (temp_scores[deletion_path_ordering[i]] > DP_matrix[t_idx][q_idx].scores[FROM_D]) {
DP_matrix[t_idx][q_idx].scores[FROM_D] = temp_scores[deletion_path_ordering[i]];
DP_matrix[t_idx][q_idx].in_directions[FROM_D] = deletion_path_ordering[i];
}
}
// Choose best move for this cell
DP_matrix[t_idx][q_idx].best_score = kNotApplicable-1;
DP_matrix[t_idx][q_idx].best_path_direction = FROM_NOWHERE;
unsigned int s_idx;
for (unsigned int i=0; i<DP_matrix[t_idx][q_idx].scores.size(); i++) {
// Reverse lookup for reverse strand so that InDels are placed at the beginning of HPs
if (isForwardStrandRead_)
s_idx = i;
else
s_idx = DP_matrix[t_idx][q_idx].scores.size()-1-i;
if (DP_matrix[t_idx][q_idx].scores[s_idx] > DP_matrix[t_idx][q_idx].best_score) {
DP_matrix[t_idx][q_idx].best_score = DP_matrix[t_idx][q_idx].scores[s_idx];
DP_matrix[t_idx][q_idx].best_path_direction = s_idx;
}
}
bool investigate_highscore = false;
if (soft_clip_bead_end_ or (stop_anywhere_in_ref_ and q_idx == q_seq_.size()))
investigate_highscore = true;
if (investigate_highscore and DP_matrix[t_idx][q_idx].best_score
> DP_matrix[highest_score_cell[0]][highest_score_cell[1]].best_score) {
highest_score_cell[0] = t_idx;
highest_score_cell[1] = q_idx;
}
}
}
// ------- end alignment matrix loop ------
if (!stop_anywhere_in_ref_ and !soft_clip_bead_end_) {
highest_score_cell[0] = t_seq_.size();
highest_score_cell[1] = q_seq_.size();
}
// Backtrack alignment in dynamic programming matrix, generate cigar string / MD tag
backtrackAlignment(highest_score_cell[0], highest_score_cell[1], CigarData, MD_data, start_pos_update);
return true;
}
bool Realigner::computeSWalignment(vector<CigarOp>& CigarData, vector<MDelement>& MD_data,
unsigned int& start_pos_update) {
string dummy_string;
// Compute boundaries for tubed alignment around previously found alignment
if (!ComputeTubedAlignmentBoundaries())
return false;
// Path ordering creates left aligned InDels
vector<int> insertion_path_ordering(3);
vector<int> deletion_path_ordering(3);
insertion_path_ordering[0] = FROM_I;
insertion_path_ordering[1] = FROM_MATCH;
insertion_path_ordering[2] = FROM_MISM;
deletion_path_ordering[0] = FROM_D;
deletion_path_ordering[1] = FROM_MATCH;
deletion_path_ordering[2] = FROM_MISM;
// --- Compute first row and column of the matrix
// First row: moving horizontally for insertions
if (!soft_clip_left_) {
DP_matrix[0][1].best_path_direction = FROM_I;
DP_matrix[0][1].best_score = kGapOpen;
DP_matrix[0][1].scores[FROM_I] = kGapOpen;
DP_matrix[0][1].scores[FROM_NOWHERE] = kNotApplicable;
for (unsigned int q_idx=2; q_idx<q_limit_plus_[0]; q_idx++) {
DP_matrix[0][q_idx].in_directions[FROM_I] = FROM_I;
DP_matrix[0][q_idx].scores[FROM_NOWHERE] = kNotApplicable;
DP_matrix[0][q_idx].scores[FROM_I] = DP_matrix[0][q_idx-1].best_score + kGapExtend;
DP_matrix[0][q_idx].best_path_direction = FROM_I;
DP_matrix[0][q_idx].best_score = DP_matrix[0][q_idx-1].best_score + kGapExtend;
}
}
if (!start_anywhere_in_ref_) {
// First column: moving vertically for deletions
DP_matrix[1][0].best_path_direction = FROM_D;
DP_matrix[1][0].best_score = kGapOpen;
DP_matrix[1][0].scores[FROM_D] = kGapOpen;
DP_matrix[1][0].scores[FROM_NOWHERE] = kNotApplicable;
unsigned int t = 2;
while (t < q_limit_minus_.size() and q_limit_minus_[t] == 0) {
DP_matrix[t][0].in_directions[FROM_D] = FROM_D;
DP_matrix[t][0].scores[FROM_NOWHERE] = kNotApplicable;
DP_matrix[t][0].scores[FROM_D] = DP_matrix[t-1][0].best_score + kGapExtend;
DP_matrix[t][0].best_path_direction = FROM_D;
DP_matrix[t][0].best_score = DP_matrix[t-1][0].best_score + kGapExtend;
t++;
}
}
// ------ Main alignment loop ------
vector<int> temp_scores(FROM_NOWHERE);
vector<int> highest_score_cell(2, 0);
for (unsigned int t_idx=1; t_idx<t_seq_.size()+1; t_idx++) {
for (unsigned int q_idx=q_limit_minus_[t_idx]; q_idx<q_limit_plus_[t_idx]; q_idx++) {
if (q_idx == 0)
continue;
// Scoring for Match; Mismatch / Insertion / Deletion;
DP_matrix[t_idx][q_idx].scores.assign(FROM_NOWHERE+1, kNotApplicable);
DP_matrix[t_idx][q_idx].in_directions.assign(FROM_NOWHERE, FROM_NOWHERE);
if (soft_clip_left_)
DP_matrix[t_idx][q_idx].scores[FROM_NOWHERE] = 0;
// 1) - Match / Mismatch Score
DP_matrix[t_idx][q_idx].is_match = isMatch(q_seq_[q_idx-1], t_seq_[t_idx-1]);
if (DP_matrix[t_idx][q_idx].is_match) {
DP_matrix[t_idx][q_idx].in_directions[FROM_MATCH] = DP_matrix[t_idx-1][q_idx-1].best_path_direction;
DP_matrix[t_idx][q_idx].scores[FROM_MATCH] = DP_matrix[t_idx-1][q_idx-1].best_score + kMatchScore;
} else {
DP_matrix[t_idx][q_idx].in_directions[FROM_MISM] = DP_matrix[t_idx-1][q_idx-1].best_path_direction;
DP_matrix[t_idx][q_idx].scores[FROM_MISM] = DP_matrix[t_idx-1][q_idx-1].best_score + kMismatchScore;
}
// 2) - Insertion Score
temp_scores.assign(FROM_NOWHERE, kNotApplicable);
temp_scores[FROM_MATCH] = DP_matrix[t_idx][q_idx-1].scores[FROM_MATCH] + kGapOpen;
temp_scores[FROM_I] = DP_matrix[t_idx][q_idx-1].scores[FROM_I] + kGapExtend;
temp_scores[FROM_MISM] = DP_matrix[t_idx][q_idx-1].scores[FROM_MISM] + kGapOpen;
DP_matrix[t_idx][q_idx].scores[FROM_I] = kNotApplicable;
DP_matrix[t_idx][q_idx].in_directions[FROM_I] = FROM_NOWHERE;
for (int i=0; i<(int)insertion_path_ordering.size(); i++) {
if (temp_scores[insertion_path_ordering[i]] > DP_matrix[t_idx][q_idx].scores[FROM_I]) {
DP_matrix[t_idx][q_idx].scores[FROM_I] = temp_scores[insertion_path_ordering[i]];
DP_matrix[t_idx][q_idx].in_directions[FROM_I] = insertion_path_ordering[i];
}
}
// 3) - Deletion Score
temp_scores.assign(FROM_NOWHERE, kNotApplicable);
temp_scores[FROM_MATCH] = DP_matrix[t_idx-1][q_idx].scores[FROM_MATCH] + kGapOpen;
temp_scores[FROM_D] = DP_matrix[t_idx-1][q_idx].scores[FROM_D] + kGapExtend;
temp_scores[FROM_MISM] = DP_matrix[t_idx-1][q_idx].scores[FROM_MISM] + kGapOpen;
DP_matrix[t_idx][q_idx].scores[FROM_D] = kNotApplicable;
DP_matrix[t_idx][q_idx].in_directions[FROM_D] = FROM_NOWHERE;
for (int i=0; i<(int)deletion_path_ordering.size(); i++) {
if (temp_scores[deletion_path_ordering[i]] > DP_matrix[t_idx][q_idx].scores[FROM_D]) {
DP_matrix[t_idx][q_idx].scores[FROM_D] = temp_scores[deletion_path_ordering[i]];
DP_matrix[t_idx][q_idx].in_directions[FROM_D] = deletion_path_ordering[i];
}
}
// Choose best move for this cell
DP_matrix[t_idx][q_idx].best_score = kNotApplicable-1;
DP_matrix[t_idx][q_idx].best_path_direction = FROM_NOWHERE;
for (unsigned int iMove=0; iMove<DP_matrix[t_idx][q_idx].scores.size(); iMove++) {
if (DP_matrix[t_idx][q_idx].scores[iMove] > DP_matrix[t_idx][q_idx].best_score) {
DP_matrix[t_idx][q_idx].best_score = DP_matrix[t_idx][q_idx].scores[iMove];
DP_matrix[t_idx][q_idx].best_path_direction = iMove;
}
}
// Clipping settings determine where we search for the best scoring cell to stop aligning
bool valid_t_idx = stop_anywhere_in_ref_ or (t_idx == t_seq_.size());
bool valid_q_idx = soft_clip_right_ or (q_idx == q_seq_.size());
bool investigate_highscore = valid_t_idx and valid_q_idx;
if (investigate_highscore and DP_matrix[t_idx][q_idx].best_score
> DP_matrix[highest_score_cell[0]][highest_score_cell[1]].best_score) {
highest_score_cell[0] = t_idx;
highest_score_cell[1] = q_idx;
}
}
}
// ------- end alignment matrix loop ------
// Force full string alignment if desired, no matter what the score is.
if (!stop_anywhere_in_ref_ and !soft_clip_right_) {
highest_score_cell[0] = t_seq_.size();
highest_score_cell[1] = q_seq_.size();
}
// Backtrack alignment in dynamic programming matrix, generate cigar string / MD tag
backtrackAlignment(highest_score_cell[0], highest_score_cell[1], CigarData, MD_data, start_pos_update);
return true;
}
