FastTree: Computing Large Minimum Evolution Trees with Profiles instead of a Distance Matrix
Lawrence Berkeley National Laboratory · University of California, Berkeley
Abstract
Gene families are growing rapidly, but standard methods for inferring phylogenies do not scale to alignments with over 10,000 sequences. We present FastTree, a method for constructing large phylogenies and for estimating their reliability. Instead of storing a distance matrix, FastTree stores sequence profiles of internal nodes in the tree. FastTree uses these profiles to implement Neighbor-Joining and uses heuristics to quickly identify candidate joins. FastTree then uses nearest neighbor interchanges to reduce the length of the tree. For an alignment with N sequences, L sites, and a different characters, a distance matrix requires O(N(2)) space and O(N(2)L) time, but FastTree requires just O(NLa + N ) memory…
Citation impact
- FWCI
- 26.69
- Percentile
- 100%
- References
- 43
Authors
3Topics & keywords
- Distance matrix
- Bootstrapping (finance)
- Tree (set theory)
- Speedup
- Distance matrices in phylogeny
- Joins
- Matrix (chemical analysis)
- Pairwise comparison