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The use of molecular phylogenies to examine evolutionary questions has become commonplace with the automation of DNA sequencing and the availability of efficient computer programs to perform phylogenetic analyses. The application of computer simulation and likelihood ratio tests to evolutionary hypotheses represents a recent methodological development in this field. Likelihood ratio tests have enabled biologists to address many questions in evolutionary biology that have been difficult to resolve in the past, such as whether host-parasite systems are cospeciating and whether models of DNA substitution adequately explain observed sequences.
John P. Huelsenbeck* and Bruce Rannala
Evolutionary biology is founded on the concept that organisms share a common origin and have subsequently diverged through time. Phylogenies represent our attempts to reconstruct this evolutionary history, and there is probably more interest in phylogenetic reconstruction today than at any time in the past. For years phylogenetics played a relatively minor role in evolutionary biology, and it is only in the past decade that the importance of phylogeny in most branches of biology has been fully recognized (1, 2). Today it is not uncommon to see phylogenies applied in fields far removed from evolutionary biology. For example, they have found a practical use in tracing routes of infectious disease transmission and in identifying the relationship of pathogens, such as the New Mexico hantavirus (3).
With the realization that phylogeny can provide answers to many questions of interest in evolutionary biology, there has been an explosion in the number of statistical tests that take phylogeny into account. In part, this is because an essentially infinite number of possible tests can be applied to any biological question. A hypothesis test involves calculating a test statistic from the data and then determining the probability of the observed statistic if the hypothesis were true; the probability is obtained from the null distribution of the test statistic (that is, the distribution if the hypothesis is true). For hypothesis tests involving phylogeny, the null distribution is usually generated by either permuting data matrices or resampling from the original data. However, the statistical properties of many tests based on such procedures are known to be poor, and although permutation of data matrices is a common procedure, the null hypothesis for many such tests is often not...