Editing Neighbor joining (section)

== Advantages and disadvantages ==

The main virtue of NJ is that it is fast{{r|Kuhner1994|page1=466}} as compared to [[Computational phylogenetics#Fitch-Margoliash method|least squares]], [[maximum parsimony]] and [[Computational phylogenetics#Maximum likelihood|maximum likelihood]] methods.<ref name="Kuhner1994">{{Cite journal|last1=Kuhner|first1=M. K.|last2=Felsenstein|first2=J.|date=1994-05-01|title=A simulation comparison of phylogeny algorithms under equal and unequal evolutionary rates.|journal=Molecular Biology and Evolution|language=en|volume=11|issue=3|pages=459–468|issn=0737-4038|pmid=8015439|doi=10.1093/oxfordjournals.molbev.a040126|doi-access=free}}</ref>
This makes it practical for analyzing large data sets (hundreds or thousands of taxa) and for [[bootstrapping (statistics)|bootstrapping]], for which purposes other means of analysis (e.g. [[maximum parsimony]], [[maximum likelihood]]) may be [[computation]]ally prohibitive.

Neighbor joining has the property that if the input distance matrix is correct, then the output tree will be correct.
Furthermore, the correctness of the output tree topology is guaranteed as long as the distance matrix is 'nearly additive', specifically if each entry in the distance matrix differs from the true distance by less than half of the shortest branch length in the tree.<ref>Atteson K (1997). "The performance of neighbor-joining algorithms of phylogeny reconstruction", pp.&nbsp;101&ndash;110. ''In'' Jiang, T., and Lee, D., eds., ''Lecture Notes in Computer Science, 1276'', Springer-Verlag, Berlin. COCOON '97.</ref>
In practice the distance matrix rarely satisfies this condition, but neighbor joining often constructs the correct tree topology anyway.<ref name="levy">{{cite journal |author=Mihaescu R, Levy D, [[Lior Pachter|Pachter L]] |title=Why neighbor-joining works |journal=Algorithmica |volume=54 |issue=1| pages=1–24 |year=2009 | doi=10.1007/s00453-007-9116-4|arxiv=cs/0602041 |s2cid=2462145 }}</ref> The correctness of neighbor joining for nearly additive distance matrices implies that it is [[statistical consistency|statistically consistent]] under many models of evolution; given data of sufficient length, neighbor joining will reconstruct the true tree with high probability.
Compared with [[UPGMA]] and [[WPGMA]], neighbor joining has the advantage that it does not assume all lineages evolve at the same rate ([[molecular clock hypothesis]]). 
 
Nevertheless, neighbor joining has been largely superseded by phylogenetic methods that do not rely on distance measures and offer superior accuracy under most conditions.{{citation needed|date=November 2012}} Neighbor joining has the undesirable feature that it often assigns negative lengths to some of the branches.