Techniques for analysis of large data sets.

WENZEL JOHN W.; SIDDALL MARK E.; WHEELER, WARD C.; GOLOBOFF, PABLO AUGUSTO

: Techniques in Molecular Systematics and Evolution.

Birkhäuser

Año: 2002; p. 70 - 79

Parsimony problems of medium or large numbers of taxa can be analyzed onlyby means of trial-and-error or "heuristic" methods. Traditional strategies forfinding most parsimonious trees have long been in use, implemented in theprograms Hennig86 [1], PAUP [2], and NONA [3]. Although successful for smalland medium-sized data sets, these techniques normally fail for analyzing verylarge data sets, i. e., data sets with 200 or more taxa. This is because rather thansimply requiring more of the same kind of work used to analyze smaller datasets, very large data sets require the use of qualitatively different techniques.The techniques described here have so far been used only for prealignedsequences, but they could be adapted for other methods of analysis, like thedirect optimization method of Wheeler [4].