Supermatrix and supertree methods are two strategies advocated for phylogenetic analysis of sequence data from multiple gene loci, especially when some species are missing at some loci. The supermatrix method concatenates sequences from multiple genes into a data supermatrix for phylogenetic analysis, and ignores differences in evolutionary dynamics among the genes. The supertree method analyzes each gene separately and assembles the subtrees estimated from individual genes into a supertree for all species. Most algorithms suggested for supertree construction lack statistical justifications and ignore uncertainties in the subtrees. Instead of supermatrix or supertree, we advocate the use of likelihood function to combine data from multiple genes while accommodating their differences in the evolutionary process. This combines the strengths of the supermatrix and supertree methods while avoiding their drawbacks. We conduct computer simulation to evaluate the performance of the supermatrix, supertree, and maximum likelihood methods applied to two phylogenetic problems: molecular-clock dating of species divergences and reconstruction of species phylogenies. The results confirm the theoretical superiority of the likelihood method. Supertree or separate analyses of data of multiple genes may be useful in revealing the characteristics of the evolutionary process of multiple gene loci, and the information may be used to formulate realistic models for combined analysis of all genes by likelihood.
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