Abstract
Motivation: Horizontal gene transfer (HGT) is believed to be ubiquitous among bacteria, and plays a major role in their genome diversification as well as their ability to develop resistance to antibiotics. In light of its evolutionary significance and implications for human health, developing accurate and efficient methods for detecting and reconstructing HGT is imperative. Results: In this article we provide a new HGT-oriented likelihood framework for many problems that involve phylogeny-based HGT detection and reconstruction. Beside the formulation of various likelihood criteria, we show that most of these problems are NP-hard, and offer heuristics for efficient and accurate reconstruction of HGT under these criteria. We implemented our heuristics and used them to analyze biological as well as synthetic data. In both cases, our criteria and heuristics exhibited very good performance with respect to identifying the correct number of HGT events as well as inferring their correct location on the species tree.
| Original language | English |
|---|---|
| Pages (from-to) | 2604-2611 |
| Number of pages | 8 |
| Journal | Bioinformatics |
| Volume | 22 |
| Issue number | 21 |
| DOIs | |
| State | Published - 1 Nov 2006 |
| Externally published | Yes |
Bibliographical note
Funding Information:The authors would like to thank Derek Ruths and Satish Rao for helpful discussions and data, and the anonymous reviewers for their helpful comments. Experiments were run on the Rice Terascale Cluster, funded by NSF under grant EIA-0216467, Intel, and HP. L.N. was supported in part by DOE grant DE-FG02-06ER25734 and NSF grant CCF-0622037. S.S. was supported in part by NSF grant CCR-0105533.
ASJC Scopus subject areas
- Statistics and Probability
- Biochemistry
- Molecular Biology
- Computer Science Applications
- Computational Theory and Mathematics
- Computational Mathematics