 
Patricia Buendia and
Giri Narasimhan. Sliding MinPD: Building evolutionary networks of serial samples via an automated recombination detection approach. In BIO, Vol. 23(22):2993-3000, 2007.
Keywords: from sequences, phylogenetic network, phylogeny, Program Sliding MinPD, recombination, recombination detection, serial evolutionary networks, software.
Note: http://dx.doi.org/10.1093/bioinformatics/btm413.
Toggle abstract
"Motivation: Traditional phylogenetic methods assume tree-like evolutionary models and are likely to perform poorly when provided with sequence data from fast-evolving, recombining viruses. Furthermore, these methods assume that all the sequence data are from contemporaneous taxa, which is not valid for serially-sampled data. A more general approach is proposed here, referred to as the Sliding MinPD method, that reconstructs evolutionary networks for serially-sampled sequences in the presence of recombination. Results: Sliding MinPD combines distance-based phylogenetic methods with automated recombination detection based on the best-known sliding window approaches to reconstruct serial evolutionary networks. Its performance was evaluated through comprehensive simulation studies and was also applied to a set of serially-sampled HIV sequences from a single patient. The resulting network organizations reveal unique patterns of viral evolution and may help explain the emergence of disease-associated mutants and drug-resistant strains with implications for patient prognosis and treatment strategies. © The Author 2007. Published by Oxford University Press. All rights reserved."
|
- forked on GitHub.