We describe a computer-implemented method of determining at least one optimal alignment of at least part of a first map to at least part of a second map or a plurality of second maps, the method comprising: receiving first map data indicative of a first ordered list of distances between features of the first map; receiving second map data indicative of a second ordered list of distances between features of the second map or second maps; generating, from the second map data, seed data indicative of a plurality of seeds, each seed comprising at least one of the distances in the second ordered list; generating a plurality of candidate alignments from the seed data by searching at least part of the first ordered list to find at least approximate matches for respective seeds, and extending the approximate matches by dynamic programming; determining respective alignment scores for respective candidate alignments; and selecting one or more of the candidate alignments as an optimal alignment or optimal alignments, based on the alignment scores.

Bioinformatics Data Processing Systems

VERZOTTO D;
2016-01-01

Abstract

We describe a computer-implemented method of determining at least one optimal alignment of at least part of a first map to at least part of a second map or a plurality of second maps, the method comprising: receiving first map data indicative of a first ordered list of distances between features of the first map; receiving second map data indicative of a second ordered list of distances between features of the second map or second maps; generating, from the second map data, seed data indicative of a plurality of seeds, each seed comprising at least one of the distances in the second ordered list; generating a plurality of candidate alignments from the seed data by searching at least part of the first ordered list to find at least approximate matches for respective seeds, and extending the approximate matches by dynamic programming; determining respective alignment scores for respective candidate alignments; and selecting one or more of the candidate alignments as an optimal alignment or optimal alignments, based on the alignment scores.
2016
Optical mapping
Map-to-sequence alignment
Glocal and overlap alignment
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14252/1315
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