![[feed]](/style/images/feed-icon-14x14.png){kind=icon}
Tools
Tools
Preview |
PDF
- Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
448kB |
| Item Type: | Article |
|---|---|
| Title: | Evolutionary distances in the twilight zone-a rational kernel approach |
| Creators Name: | Schwarz, R.F., Fletcher, W., Foerster, F., Merget, B., Wolf, M., Schultz, J. and Markowetz, F. |
| Abstract: | Phylogenetic tree reconstruction is traditionally based on multiple sequence alignments (MSAs) and heavily depends on the validity of this information bottleneck. With increasing sequence divergence, the quality of MSAs decays quickly. Alignment-free methods, on the other hand, are based on abstract string comparisons and avoid potential alignment problems. However, in general they are not biologically motivated and ignore our knowledge about the evolution of sequences. Thus, it is still a major open question how to define an evolutionary distance metric between divergent sequences that makes use of indel information and known substitution models without the need for a multiple alignment. Here we propose a new evolutionary distance metric to close this gap. It uses finite-state transducers to create a biologically motivated similarity score which models substitutions and indels, and does not depend on a multiple sequence alignment. The sequence similarity score is defined in analogy to pairwise alignments and additionally has the positive semi-definite property. We describe its derivation and show in simulation studies and real-world examples that it is more accurate in reconstructing phylogenies than competing methods. The result is a new and accurate way of determining evolutionary distances in and beyond the twilight zone of sequence alignments that is suitable for large datasets. |
| Keywords: | Algorithms, Amino Acid Sequence, Chlorophyta, Computer Simulation, Intergenic DNA, Likelihood Functions, Markov Chains, Molecular Evolution, Molecular Sequence Data, Phylogeny, Probability, Secondary Protein Structure, Sequence Alignment, Statistical Models |
| Source: | PLoS ONE |
| ISSN: | 1932-6203 |
| Publisher: | Public Library of Science |
| Volume: | 5 |
| Number: | 12 |
| Page Range: | e15788 |
| Date: | 31 December 2010 |
| Official Publication: | https://doi.org/10.1371/journal.pone.0015788 |
| PubMed: | View item in PubMed |
Repository Staff Only: item control page
