Terrace Aware Data Structure for Phylogenomic Inference from Supermatrices

By Olga Chernomor, A. von Haeseler, Bui Quang Minh. Systematic Biology, 2016

1,872 citations recorded by the source corpus.

In phylogenomics the analysis of concatenated gene alignments, the so-called supermatrix, is commonly accompanied by the assumption of partition models. Under such models each gene, or more generally partition, is allowed to evolve under its own evolutionary model. Although partition models provide a more comprehensive analysis of supermatrices, missing data may hamper the tree search algorithms due to the existence of phylogenetic (partial) terraces. Here, we introduce the phylogenetic terrace aware (PTA) data structure for the efficient analysis under partition models. In the presence of missing data PTA exploits (partial) terraces and induced partition trees to save computation time. We show that an implementation of PTA in IQ-TREE leads to a substantial speedup of up to 4.5 and 8 times compared with the standard IQ-TREE and RAxML implementations, respectively. PTA is generally applicable to all types of partition models and common topological rearrangements thus can be employed by all phylogenomic inference software.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/7f719586024dffd0d5eb8c21cf8caaa9f5586765

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Citations in the corpus

Evaluating Fast Maximum Likelihood-Based Phylogenetic Programs Using Empirical Phylogenomic Data Sets (2017, methodology): “In these studies, RAxML and PhyML showed largely similar performance in identifying trees of higher likelihood scores (Guindon et al. 2010; Money and Whelan 2012), whereas IQ-TREE exhibited improved efficiency compared with both RAxML and PhyML (Nguyen et al. 2015; Chernomor et al. 2016).”
UFBoot2: Improving the Ultrafast Bootstrap Approximation (2017, methodology): “Figure 2 shows the ML tree inferred with IQTREE under edge-unlinked partition model (Chernomor et al. 2016), which allows separate sets of branch lengths across partitions.”
IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era (2019, methodology): “Moreover, IQ-TREE 2 offers a number of advanced models for phylogenomic data including partitioned models (Lanfear et al. 2012; Chernomor et al. 2016), mixture models (Le et al.”