Prospects for inferring very large phylogenies by using the neighbor-joining method

Current efforts to reconstruct the tree of life and histories of multigene families demand the inference of phylogenies consisting of thousands of gene sequences. However, for such large data sets even a moderate exploration of the tree space needed to identify the optimal tree is virtually impossible. For these cases the neighbor-joining (NJ) method is frequently used because of its demonstrated accuracy for smaller data sets and its computational speed. As data sets grow, however, the fraction of the tree space examined by the NJ algorithm becomes minuscule. Here, we report the results of our computer simulation for examining the accuracy of NJ trees for inferring very large phylogenies. First we present a…

• NS
  National Science Foundation
• AS
  Arizona State University
• NI
  National Institutes of Health
• SO
  School of Life Sciences, Arizona State University
• JS
  Japan Society for the Promotion of Science