vg
tools for working with variation graphs
|
#include "extract_containing_graph.hpp"
#include "../gbwt_extender.hpp"
#include "../snarl_seed_clusterer.hpp"
#include "../zip_code_tree.hpp"
#include "../handle.hpp"
#include "../explainer.hpp"
#include "../utility.hpp"
#include <bdsg/hash_graph.hpp>
Classes | |
class | vg::algorithms::Anchor |
class | vg::algorithms::TracedScore |
Namespaces | |
vg | |
vg::algorithms | |
std | |
Hash functor to hash NodeSide s using std::hash. | |
Typedefs | |
using | vg::algorithms::transition_iteratee = std::function< void(size_t from_anchor, size_t to_anchor, size_t read_distance, size_t graph_distance)> |
using | vg::algorithms::transition_iterator = std::function< void(const VectorView< Anchor > &to_chain, const SnarlDistanceIndex &distance_index, const HandleGraph &graph, size_t max_indel_bases, const transition_iteratee &callback)> |
Functions | |
ostream & | vg::algorithms::operator<< (ostream &out, const Anchor &anchor) |
Explain an Anchor to the given stream. More... | |
vg::algorithms::TracedScore | std::max (const vg::algorithms::TracedScore &a, const vg::algorithms::TracedScore &b) |
Allow maxing TracedScore. More... | |
ostream & | vg::algorithms::operator<< (ostream &out, const TracedScore &value) |
Print operator. More... | |
void | vg::algorithms::sort_anchor_indexes (const std::vector< Anchor > &items, std::vector< size_t > &indexes) |
transition_iterator | vg::algorithms::lookback_transition_iterator (size_t max_lookback_bases, size_t min_lookback_items, size_t lookback_item_hard_cap) |
transition_iterator | vg::algorithms::zip_tree_transition_iterator (const std::vector< SnarlDistanceIndexClusterer::Seed > &seeds, const ZipCodeTree &zip_code_tree, size_t max_lookback_bases) |
TracedScore | vg::algorithms::chain_items_dp (vector< TracedScore > &chain_scores, const VectorView< Anchor > &to_chain, const SnarlDistanceIndex &distance_index, const HandleGraph &graph, int gap_open, int gap_extension, const transition_iterator &for_each_transition, int item_bonus, double item_scale, double gap_scale, double points_per_possible_match, size_t max_indel_bases, bool show_work) |
vector< pair< vector< size_t >, int > > | vg::algorithms::chain_items_traceback (const vector< TracedScore > &chain_scores, const VectorView< Anchor > &to_chain, const TracedScore &best_past_ending_score_ever, int item_bonus, double item_scale, size_t max_tracebacks) |
vector< pair< int, vector< size_t > > > | vg::algorithms::find_best_chains (const VectorView< Anchor > &to_chain, const SnarlDistanceIndex &distance_index, const HandleGraph &graph, int gap_open, int gap_extension, size_t max_chains, const transition_iterator &for_each_transition, int item_bonus, double item_scale, double gap_scale, double points_per_possible_match, size_t max_indel_bases, bool show_work) |
pair< int, vector< size_t > > | vg::algorithms::find_best_chain (const VectorView< Anchor > &to_chain, const SnarlDistanceIndex &distance_index, const HandleGraph &graph, int gap_open, int gap_extension, const transition_iterator &for_each_transition, int item_bonus, double item_scale, double gap_scale, double points_per_possible_match, size_t max_indel_bases) |
int | vg::algorithms::score_best_chain (const VectorView< Anchor > &to_chain, const SnarlDistanceIndex &distance_index, const HandleGraph &graph, int gap_open, int gap_extension) |
int | vg::algorithms::score_chain_gap (size_t distance_difference, size_t base_seed_length) |
size_t | vg::algorithms::get_graph_distance (const Anchor &from, const Anchor &to, const SnarlDistanceIndex &distance_index, const HandleGraph &graph, size_t distance_limit=std::numeric_limits< size_t >::max()) |
Get distance in the graph, or std::numeric_limits<size_t>::max() if unreachable or beyond the limit. More... | |
size_t | vg::algorithms::get_read_distance (const Anchor &from, const Anchor &to) |
Get distance in the read, or std::numeric_limits<size_t>::max() if unreachable. More... | |
Algorithms for chaining subalignments into larger alignments.
To use these algorithms, decide on the type (Anchor) you want to chain up.
Then, make a dynamic programming table: vector<TracedScore>.
Then, call chain_items_dp() to fill in the dynamic programming table and get the score of the best chain.
You can use chain_items_traceback() to get a traceback of the chain's items in order.
Helper entry points are find_best_chain() and score_best_chain() which set up the DP for you and do the traceback if appropriate.