Keywords
DNA sequencing, phylogenetic search
Abstract
DNA sequence alignment is a critical step in identifying homology between organisms. The most widely used alignment program, ClustalW, is known to suffer from the local minima problem, where suboptimal guide trees produce incorrect gap insertions. The optimization alignment approach, has been shown to be effective in combining alignment and phylogenetic search in order to avoid the problems associated with poor guide trees. The optimization alignment algorithm operates at a small grain size, aligning each tree found, wasting time producing multiple sequence alignments for suboptimal trees. This research develops and analyzes a large grain size algorithm for optimization alignment that iterates through steps of alignment and phylogeny search, thus improving the quality of guide trees used for computation of multiple sequence alignments and eliminating computation of multiple sequence alignments for sub-optimal guide trees. Local minima are avoided by the use of stochastic search methods. Large Grain Size Stochastic Optimization Alignment (LGA) exploits the relationship between phylogenies and multiple sequence alignments, and in so doing achieves improved alignment accuracy. LGA is licensed under the GNU General Public License. Source code and data sets are publicly available at http://csl.cs.byu.edu/lga/.
Original Publication Citation
Large Grain Size Stochastic Optimization Alignment, Perry Ridge, Hyrum Carroll, Dan Sneddon, Mark Clement, Quinn Snell, IEEE Symposium on BioInformatics and BioEngineering (BIBE), Arlington, Virginia, October 26, pp 127.
BYU ScholarsArchive Citation
Carroll, Hyrum; Clement, Mark J.; Ridge, Perry; Sneddon, Dan; and Snell, Quinn O., "Large Grain Size Stochastic Optimization Alignment" (2006). Faculty Publications. 291.
https://scholarsarchive.byu.edu/facpub/291
Document Type
Peer-Reviewed Article
Publication Date
2006-10-01
Permanent URL
http://hdl.lib.byu.edu/1877/2579
Publisher
IEEE
Language
English
College
Physical and Mathematical Sciences
Department
Computer Science
Copyright Status
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