distance matrix data

[Icon] FITCH. Estimates phylogenies from distance matrix data under the "additive tree model" according to which the distances are expected to equal the sums of branch lengths between the species. Uses the Fitch-Margoliash criterion and some related least squares criteria, or the Minimum Evolution distance matrix method. Does not assume an evolutionary clock. This program will be useful with distances computed from molecular sequences, restriction sites or fragments distances, with DNA hybridization measurements, and with genetic distances computed from gene frequencies.

[Icon] KITSCH. Estimates phylogenies from distance matrix data under the "ultrametric" model which is the same as the additive tree model except that an evolutionary clock is assumed. The Fitch-Margoliash criterion and other least squares criteria, or the Minimum Evolution criterion are possible. This program will be useful with distances computed from molecular sequences, restriction sites or fragments distances, with distances from DNA hybridization measurements, and with genetic distances computed from gene frequencies.

[Icon] NEIGHBOR. An implementation by Mary Kuhner and John Yamato of Saitou and Nei's "Neighbor Joining Method," and of the UPGMA (Average Linkage clustering) method. Neighbor Joining is a distance matrix method producing an unrooted tree without the assumption of a clock. UPGMA does assume a clock. The branch lengths are not optimized by the least squares criterion but the methods are very fast and thus can handle much larger data sets.

[Icon] DNADIST. Computes four different distances between species from nucleic acid sequences. The distances can then be used in the distance matrix programs. The distances are the Jukes-Cantor formula, one based on Kimura's 2- parameter method, the F84 model used in DNAML, and the LogDet distance. The distances can also be corrected for gamma-distributed and gamma-plus-invariant-sites-distributed rates of change in different sites. Rates of evolution can vary among sites in a prespecified way, and also according to a Hidden Markov model. The program can also make a table of percentage similarity among sequences.

[Icon] PROTDIST. Computes a distance measure for protein sequences, using maximum likelihood estimates based on the Dayhoff PAM matrix, the JTT matrix model, the PBM model, Kimura's 1983 approximation to these, or a model based on the genetic code plus a constraint on changing to a different category of amino acid. The distances can also be corrected for gamma-distributed and gamma-plus-invariant-sites-distributed rates of change in different sites. Rates of evolution can vary among sites in a prespecified way, and also according to a Hidden Markov model. The program can also make a table of percentage similarity among sequences. The distances can be used in the distance matrix programs.

[Icon] GENDIST. Computes one of three different genetic distance formulas from gene frequency data. The formulas are Nei's genetic distance, the Cavalli-Sforza chord measure, and the genetic distance of Reynolds et. al. The former is appropriate for data in which new mutations occur in an infinite isoalleles neutral mutation model, the latter two for a model without mutation and with pure genetic drift. The distances are written to a file in a format appropriate for input to the distance matrix programs.

[Icon] RESTDIST. Distances calculated from restriction sites data or restriction fragments data. The restriction sites option is the one to use to also make distances for RAPDs or AFLPs.


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