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Of the distance methods, the neighbor-joining (NJ) method is most theoretically similar to PA in that it seeks to capture the phylogenetic signal by finding the cladogram with the shortest summed distances over all the branches (Saitou and Nei 1987).
In both methods, the Neighbor-Joining reconstruction algorithm was used.
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As a distance-based method, the Neighbor-Joining (NJ) method [ 62] was applied.
Phylogenetic analyses were conducted with the MEGA version 3.1 software (26 ) by using the distance method and the neighbor-joining algorithm with Kimura-2 parameters.
Phylogenetic trees were constructed by two methods, the neighbor joining procedure with 10,000 bootstrap replicates using with the MEGA program [ 56] and the Bayesian inference approach implemented in the MrBayes program [ 57] run with a GTR model assuming a gamma-distribution of substitution rates across sites for 1 million iterations (mcmc ngen = 1000000 in MrBayes).
Evolutionary distances were computed by using the Kimura 2-parameter method (32 ) and the neighbor-joining method (33, 34 ).
Kimura 2-parameters were used for the distance method, by using the neighbor-joining algorithm.
A distance-based method phylogenetic tree was inferred by the neighbor-joining method using the Poisson correction.
A phylogenetic tree was generated by the neighbor-joining method by the p-distance method (on 1000 bootstrapped datasets).
The derived distance matrix can be used to reconstruct a tree by the neighbor-joining method, and we refer to the resulting method as Profile Neighbor-Joining (PNJ).
a Phylogenetic trees were reconstructed by the neighbor-joining methods with the MEGA 5 program package.
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