Journal of Molecular Evolution

, Volume 54, Issue 2, pp 200–209

Bootstrap Confidence Levels for HIV-1 Recombination

  • Karin S.  Dorman
  • Andrew H.  Kaplan
  • Janet S.  Sinsheimer
Article

DOI: 10.1007/s00239-001-0002-4

Cite this article as:
Dorman, K., Kaplan, A. & Sinsheimer, J. J Mol Evol (2002) 54: 200. doi:10.1007/s00239-001-0002-4

Abstract

Recombination has been invoked to explain the disparate evolutionary relationships observed for different genes or sequence segments of a single HIV-1 genome. We present a new method of assessing confidence in HIV-1 recombination as an alternative to the segment-by-segment nonparametric bootstrap commonly applied to confirm HIV-1 recombinant data. Our new method uses the bias-corrected accelerated percentile interval (BCa) bootstrap method as applied to the ``problem of regions'' (Efron and Tibshirani 1998). It is an extension of the BCa method used in the inference of evolutionary relationships (Efron et al. 1996). This method has two advantages over the traditional bootstrap procedure: (1) it gives a single overall confidence measure rather than segment-by-segment results, and (2) it is more accurate. We test our method on 61 sequences, including 16 with ambiguous recombinant status.

Key words: Bootstrapping — Confidence — Topology — Recombination — p-values — Accelerated bias-corrected percentile 

Copyright information

© Springer-Verlag New York Inc. 2002

Authors and Affiliations

  • Karin S.  Dorman
    • 1
  • Andrew H.  Kaplan
    • 3
  • Janet S.  Sinsheimer
    • 1
  1. 1.Department of Biomathematics, University of California at Los Angeles, Los Angeles, CA 90095, USAUS
  2. 2.Departments of Statistics and Zoology/Genetics, Iowa State University, Ames, IA 50011, USAUS
  3. 3.Departments of Medicine and Microbiology and Immunology, Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27599, USAUS
  4. 4.Department of Human Genetics, University of California at Los Angeles, Los Angeles, CA 90095, USAUS
  5. 5.Department of Biostatistics, University of California at Los Angeles, Los Angeles, CA 90095, USAUS

Personalised recommendations