PARSIMONY JACKKNIFING OUTPERFORMS NEIGHBOR‐JOINING
1996/06/01 by James S. Farris, Victor A. Albert, Mari Källersjö +2 · 49 citations
Computer Science · #Evolutionary Algorithms and Applications #Software Engineering Research #Software System Performance and Reliability
paper · pdf · doi:10.1111/j.1096-0031.1996.tb00196.x
openalex publication_date 1996/06/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Abstract
Abstract- Because they are designed to produced just one tree, neighbor-joining programs can obscure ambiguities in data. Ambiguities can be uncovered by resampling, but existing neighbor-joining programs may give misleading bootstrap frequencies because they do not suppress zero-length branches and/or are sensitive to the order of terminals in the data. A new procedure, parsimony jackknifing, overcomes these problems while running hundreds of times faster than existing programs for neighbor-joining bootstrapping. For analysis of large matrices, parsimony jackknifing is hundreds of thousands of times faster than extensive branch-swapping, yet is better able to screen out poorly-supported groups.
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