PAQ: Partition Analysis of Quasispecies.
BACKGROUND
The complexities of genetic data may not be accurately described by any single analytical tool. Phylogenetic analysis is often used to study the genetic relationship among different sequences. Evolutionary models and assumptions are invoked to reconstruct trees that describe the phylogenetic relationship among sequences. Genetic databases are rapidly accumulating large amounts of sequences. Newly acquired sequences, which have not yet been characterized, may require preliminary genetic exploration in order to build models describing the evolutionary relationship among sequences. There are clustering techniques that rely less on models of evolution, and thus may provide nice exploratory tools for identifying genetic similarities. Some of the more commonly used clustering methods perform better when data can be grouped into mutually exclusive groups. Genetic data from viral quasispecies, which consist of closely related variants that differ by small changes, however, may best be partitioned by overlapping groups.


RESULTS
We have developed an intuitive exploratory program, Partition Analysis of Quasispecies (PAQ), which utilizes a non-hierarchical technique to partition sequences that are genetically similar. PAQ was used to analyze a data set of human immunodeficiency virus type 1 (HIV-1) envelope sequences isolated from different regions of the brain and another data set consisting of the equine infectious anemia virus (EIAV) regulatory gene rev. Analysis of the HIV-1 data set by PAQ was consistent with phylogenetic analysis of the same data, and the EIAV rev variants were partitioned into two overlapping groups. PAQ provides an additional tool which can be used to glean information from genetic data and can be used in conjunction with other tools to study genetic similarities and genetic evolution of viral quasispecies.
Department of Mathematics, Iowa State University, Ames, IA 50011, USA. pbaccam@lanl.gov
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Baccam
R J
RJ
Thompson
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Fedrigo
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Carpenter
J L
JL
Cornette
D000465:Algorithms; D000818:Animals; D016000:Cluster Analysis; D019295:Computational Biology; D016208:Databases, Factual; D019143:Evolution, Molecular; D005814:Genes, Viral; D005821:Genetic Techniques; D015497:HIV-1 / Q000235:genetics; D006736:Horses; D006801:Humans; D004860:Infectious Anemia Virus, Equine / Q000235:genetics; D010802:Phylogeny; D012984:Software; D013045:Species Specificity