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A Distance-Based Method for Detecting Horizontal Gene Transfer in Whole Genomes

  • Xintao Wei
  • Lenore Cowen
  • Carla Brodley
  • Arthur Brady
  • D. Sculley
  • Donna K. Slonim
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4983)

Abstract

As the number of sequenced genomes has grown, we have become increasingly aware of the impact of horizontal gene transfer on our understanding of genome evolution. Methods for detecting horizontal gene transfer from sequence abound. Among the most accurate are methods based on phylogenetic tree inference, but even these can perform poorly in some cases, such as when multiple trees fit the data equally well. In addition, they tend to be computationally intensive, making them poorly suited to genomic-scale applications. We introduce a new method for detecting horizontal transfer that incorporates the distances typically used by phylogeny-based methods, rather than the trees themselves. We demonstrate that the distance method is scalable and that it performs well precisely in cases where phylogenetic approaches struggle. We conclude that a distance-based approach may be a valuable addition to the set of tools currently available for identifying horizontal gene transfer.

Keywords

Horizontal Gene Transfer Distance Method Yersinia Pestis Xylella Fastidiosa Horizontal Gene Transfer Candidate 
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 2008

Authors and Affiliations

  • Xintao Wei
    • 1
  • Lenore Cowen
    • 1
  • Carla Brodley
    • 1
  • Arthur Brady
    • 1
  • D. Sculley
    • 1
  • Donna K. Slonim
    • 1
    • 2
  1. 1.Department of Computer ScienceTufts UniversityMedford 
  2. 2.Department of PathologyTufts University School of MedicineBoston

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