Analyzing algorithms by simulation: variance reduction techniques and simulation speedups
ACM Computing Surveys (CSUR)
A few logs suffice to build (almost) all trees (l): part I
Random Structures & Algorithms
SODA '00 Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms
Hybrid tree reconstruction methods
Journal of Experimental Algorithmics (JEA)
Inferring evolutionary trees with strong combinatorial evidence
Theoretical Computer Science - computing and combinatorics
Quartet Cleaning: Improved Algorithms and Simulations
ESA '99 Proceedings of the 7th Annual European Symposium on Algorithms
An experimental study of quartets MaxCut and other supertree methods
WABI'10 Proceedings of the 10th international conference on Algorithms in bioinformatics
Learning Latent Tree Graphical Models
The Journal of Machine Learning Research
Quartet-based phylogeny reconstruction from gene orders
COCOON'05 Proceedings of the 11th annual international conference on Computing and Combinatorics
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We present the results of a large-scale experimental study of quartet-based methods (quartet cleaning and puzzling) for phylogeny reconstruction. Our experiments include a broad range of problem sizes and evolutionary rates, and were carefully designed to yield statistically robust results despite the size of the sample space. We measure outcomes in terms of numbers of edges of the true tree correctly inferred by each method (true positives). Our results indicate that these quartet-based methods are much less accurate than the simple and efficient method of neighbor-joining, particularly for data composed of short to medium length sequences. We support our experimental findings by theoretical results that suggest that quartet-cleaning methods are unlikely to yield accurate trees with less than exponentially long sequences. We suggest that a proposed reconstruction method should first be compared to the neighbor-joining method and further studied only if it offers a demonstrable practical advantage.