THE ACCURACY OF PHYLOGENETIC ESTIMATION USING THE NEIGHBOR-JOINING METHOD

We studied the factors affecting the accuracy of the neighbor-joining (NJ) method for estimating phylogenies by simulating character change under different evolutionary models applied to twenty different 8-OTU tree topologies that varied widely with respect to tree imbalance and stemminess. The models incorporated three evolutionary rates-constant, varying among lineages, varying among characters-and three evolutiona ry contexts concerning patterns of character change relative to specia tion events-phyletic, speciational, and punctuational. All combination s of the rate and context models were studied. In addition, three diff erent absolute rates of change were investigated. To measure the accur acy, the strict consensus index was computed between the estimated tre e and the tree topology along which the data had been generated. The r esults were analyzed by analysis of variance and compared to a previou s study that evaluated UPGMA clustering and maximum parsimony (MP) as phylogenetic estimation techniques. We found evolutionary context and tree imbalance to be the most important factors affecting the accuracy of the NJ method. NJ was more accurate than UPGMA or MP in terms of t he average strict consensus index over all treatments. However, no one method was more accurate than the other two for all combinations of t reatments. Higher absolute rate of change generally resulted in higher accuracy for all three methods.