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Welcome to Shortest Triplet Clustering
Introduction:
We propose a new distance-based clustering method,
triplet clustering algorithm (STC), to reconstruct phylogenies. The main idea is the introduction
of a natural definition of so-called k-representative sets.
Based on k-representative sets, shortest triplets are reconstructed
and serve as building blocks for the STC algorithm to
agglomerate sequences for tree reconstruction in O(n^2) time for
n sequences.
Simulations with 500, 1000 and 5000 sequences data sets show that STC gives better topological
accuracy than other methods tested.
Reference:
The method is described in detail in the following article:
- Le Sy Vinh and Arndt von Haeseler,
Shortest Triplet Clustering: Reconstructing Large Phylogenies, BMC-Bioinformatics.6:92. 2005.
Download:
Data:
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