Using Avida to test the effects of natural selection on phylogenetic reconstruction methods
Abstract
Phylogenetic trees group organisms by their ancestral relationships. There are a number of distinct algorithms used to reconstruct these trees from molecular sequence data, but different methods sometimes give conflicting results. Since there are few precisely known phylogenies, simulations are typically used to test the quality of reconstruction algorithms. These simulations randomly evolve strings of symbols to produce a tree, and then the algorithms are run with the tree leaves as inputs. Here we use Avida to test two widely used reconstruction methods, which gives us the chance to observe the effect of natural selection on tree reconstruction. We find that if the organisms undergo natural selection between branch points, the methods will be successful even on very large time scales. However, these algorithms often falter when selection is absent.
Additional Information
© 2004 Massachusetts Institute of Technology. Posted Online March 11, 2006. We thank C. Adami, D. A. Drummond, R.E. Lenski, D. Wagenaar, and C. O. Wilke for discussions. This work was supported in part by the National Science Foundation's Biocomplexity Program under Contract No. DEB-9981397. All data was obtained on a cluster of 160 processors at Michigan State University, supported by the NSF under the aforementioned contract. GIH acknowledges a Caltech SURF fellowship.Attached Files
Published - HAGal04.pdf
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Additional details
- Eprint ID
- 13452
- Resolver ID
- CaltechAUTHORS:HAGal04
- DEB-9981397
- NSF
- Caltech Summer Undergraduate Research Fellowship (SURF)
- Created
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2009-07-10Created from EPrint's datestamp field
- Updated
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2021-11-08Created from EPrint's last_modified field