We need to figure out a number of heuristics to reconstruct the full traversal trajectory of a particular haplotype for the greedy algorithms. The greedy algorithms that we have implemented so far leave a lot of nodes unmatched. These nodes are often intermediate and are subsumed into the edges connecting the tree sequence nodes.
I already implemented a simple heuristic that works in a limited number of cases (e.g. skipped parents). The code is in the .complete_paths() method of MatchingAligner class.
Heuristic (1): If a pedigree node is sandwiched between 2 matched nodes, and there's an edge between those 2 nodes in the tree sequence, then assign the pedigree node to that edge.
I also added the ped_node_to_ts_edge mappings to our evaluation metrics.
We need to figure out a number of heuristics to reconstruct the full traversal trajectory of a particular haplotype for the greedy algorithms. The greedy algorithms that we have implemented so far leave a lot of nodes unmatched. These nodes are often intermediate and are subsumed into the edges connecting the tree sequence nodes.
I already implemented a simple heuristic that works in a limited number of cases (e.g. skipped parents). The code is in the
.complete_paths()method ofMatchingAlignerclass.Heuristic (1): If a pedigree node is sandwiched between 2 matched nodes, and there's an edge between those 2 nodes in the tree sequence, then assign the pedigree node to that edge.
I also added the ped_node_to_ts_edge mappings to our evaluation metrics.
Feel free to contribute ideas or implementations.