RIATA-HGT: A Fast and Accurate Heuristic for Reconstructing Horizontal Gene Transfer

  • Luay Nakhleh
  • Derek Ruths
  • Li-San Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3595)


Horizontal gene transfer (HGT) plays a major role in microbial genome diversification, and is claimed to be rampant among various groups of genes in bacteria. Further, HGT is a major confounding factor for any attempt to reconstruct bacterial phylogenies. As a result, detecting and reconstructing HGT events in groups of organisms has become a major endeavor in biology. The problem of detecting HGT events based on incongruence between a species tree and a gene tree is computationally very hard (NP-hard). Efficient algorithms exist for solving restricted cases of the problem.

We propose RIATA-HGT, the first polynomial-time heuristic to handle all HGT scenarios, without any restrictions. The method accurately infers HGT events based on analyzing incongruence among species and gene trees. Empirical performance of the method on synthetic and biological data is outstanding. Being a heuristic, RIATA-HGT may overestimate the optimal number of HGT events; empirical performance, however, shows that such overestimation is very mild.

We have implemented our method and run it on biological and synthetic data. The results we obtained demonstrate very high accuracy of the method. Current version of RIATA-HGT uses the PAUP tool, and we are in the process of implementing a stand-alone version, with a graphical user interface, which will be made public. The tool, in its current implementation, is available from the authors upon request.


Species Tree Gene Tree Horizontal Gene Transfer Lateral Gene Transfer Horizontal Gene Transfer Event 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Luay Nakhleh
    • 1
  • Derek Ruths
    • 1
  • Li-San Wang
    • 2
  1. 1.Department of Computer ScienceRice UniversityHoustonUSA
  2. 2.Department of BiologyUniversity of PennsylvaniaPhiladelphiaUSA

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