Multiple sequence alignment using partial order graphs

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ID: 305154
2002
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Abstract
Abstract Motivation: Progressive Multiple Sequence Alignment (MSA) methods depend on reducing an MSA to a linear profile for each alignment step. However, this leads to loss of information needed for accurate alignment, and gap scoring artifacts. Results: We present a graph representation of an MSA that can itself be aligned directly by pairwise dynamic programming, eliminating the need to reduce the MSA to a profile. This enables our algorithm (Partial Order Alignment (POA)) to guarantee that the optimal alignment of each new sequence versus each sequence in the MSA will be considered. Moreover, this algorithm introduces a new edit operator, homologous recombination, important for multidomain sequences. The algorithm has improved speed (linear time complexity) over existing MSA algorithms, enabling construction of massive and complex alignments (e.g. an alignment of 5000 sequences in 4 h on a Pentium II). We demonstrate the utility of this algorithm on a family of multidomain SH2 proteins, and on EST assemblies containing alternative splicing and polymorphism. Availability: The partial order alignment program POA is available at http://www.bioinformatics.ucla.edu/poa. Contact: leec@mbi.ucla.edu * To whom correspondence should be addressed. 2 Current address: center for Applied Mathematics, 657 Rhodes Hall, Cornell University, Ithaca NY 14853, USA.
Reference Key
openalex_W2142113273 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Christopher Lee, Catherine S. Grasso, Mark Sharlow
Journal BMC Bioinformatics
Year 2002
DOI
10.1093/bioinformatics/18.3.452
URL
https://academic.oup.com/bioinformatics/article-pdf/18/3/452/648375/180452.pdf
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