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Explores the genomic tree space and detect outlier genes and species based on multiple co-inertia analysis (MCOA), which efficiently captures and compares the similarities in the phylogenetic topologies produced by individual genes. Phylo-MCOA allows the rapid identification of outlier genes and species by extracting the similarities and discrepancies, in terms of the pairwise distances, between all the species in all the trees, simultaneously. This is achieved by using MCOA, which finds successive decomposition axes from individual ordinations (i.e., derived from distance matrices) that maximize a covariance function.
A congruence method that accommodates both very large numbers of genes and high degrees of incongruence. Conclustador uses clustering algorithms to identify subsets of genes based on similarity of phylogenetic signal. It involves only a single phylogenetic analysis per gene, and therefore, computation time scales nearly linearly with the number of genes in the data set. We show that our method performs very well with sets of sequence alignments simulated under a wide variety of conditions.
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