Approximate likelihood-ratio test for branches: A fast, accurate, and powerful alternative.

By Maria Anisimova, Olivier Gascuel. Systematic Biology, 2006

2,645 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/5b330809eeb9b8ae935399595ad111aa4b172b50

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Citations in the corpus

A tale of worldwide success: Behind the scenes of Carex (Cyperaceae) biogeography and diversification (2019, methodology): “Finally, the SH ‐ aLRT value (nonparametric Shimodaira ‐ Hasegawa implementation of the approximate likelihood ‐ ratio test; Anisimova & Gascuel, 2006; Anisimova et al., 2011) was used to evaluate query tree branch support with RAxML.”
FastTree 2 – Approximately Maximum-Likelihood Trees for Large Alignments (2010, methodology): “We defined ‘‘strongly supported’’ as having both SH-like local supports and approximate likelihood ratio test (aLRT) supports [21] of 95% or higher.”
FastTree: Computing Large Minimum Evolution Trees with Profiles instead of a Distance Matrix (2009, methodology): “To identify strongly supported splits, we used PhyML 3.0’s approximate likelihood ratio test (aLRT) with the minimum of SH-like and χ2 supports ( Anisimova and Gascuel, 2006 ).”
BMGE (Block Mapping and Gathering with Entropy): a new software for selection of phylogenetic informative regions from multiple sequence alignments (2010, methodology): “…phylogenetic trees, we have focused on two different approaches to estimate confidence values on the internal branches of a phylogenetic tree: the bootstrap-based support [62] with BioNJ trees, and the approximate likelihood ratio test (aLRT; [63]) as implemented by default in PhyML 3.0 [64].”
Survey of Branch Support Methods Demonstrates Accuracy, Power, and Robustness of Fast Likelihood-based Approximation Schemes (2011, methodology): “Such behavior of the aLRT under moderate model misspecifications is consistent with our earlier report (Anisimova and Gascuel 2006).”
New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. (2010, methodology): “0 implements a fast aLRT for branches (Anisimova and Gascuel 2006), which is a useful complement to the (time consuming) bootstrap D ow naded rom http/academ ic.”
Ultrafast Approximation for Phylogenetic Bootstrap (2013, methodology): “The approximate likelihood-ratio test (aLRT; Anisimova and Gascuel 2006) and its nonparametric variant (SH-aLRT; Guindon et al. 2010) differ slightly from the method used to calculate LBP by employing the SH test (Shimodaira and Hasegawa 1999) on these three NNI trees.”
IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era (2019, methodology): “IQ-TREE 2 provides fast and parallel implementations for several existing branch tests including the approximate likelihood ratio test (aLRT) (Anisimova and Gascuel 2006), the Shimodaira–Hasegawa-like aLRT (SH-aLRT) (Guindon et al. 2010), and the aBayes test (Anisimova et al. 2011).”
Genome Sequence of the Pea Aphid Acyrthosiphon pisum (2010, methodology): “Support for the different partitions was computed by approximate likelihood ratio test as implemented in PhymL (aLRT) [109].”
A comparative study of ancient environmental DNA to pollen and macrofossils from lake sediments reveals taxonomic overlap and additional plant taxa (2013, methodology): “The percentage in the brackets are posterior probability scores from the SAP, the point numbers are branch support values from the Approximate Likelihood Ratio tests given where this was used (Anisimova and Gascuel, 2006).”
Phylogenetic relatedness and plant invader success across two spatial scales (2009, methodology): “Using the aligned sequences and the estimated models of nucleotide substitution, we estimated a maximum likelihood phylogeny using the PHYML algorithm with a BIONJ starting tree (Guindon & Gascuel, 2003; Anisimova & Gascuel, 2006).”
Tracing the origin of a cryptic invader: phylogeography of the Euwallacea fornicatus (Coleoptera: Curculionidae: Scolytinae) species complex (2017, methodology): “Branch support was assessed using a nonparametric approximate likelihood-ratio test [aLTR (SH-Like)] (Anisimova & Gascuel, 2006; Guindon et al., 2010; Anisimova et al., 2011).”
A large phylogeny of turtles (Testudines) using molecular data (2012, methodology): “Maximum likelihood phylogenetic tree obtained using PhyML and the complete DNA dataset (-log(likelihood) = 286215.0).”
Estimating maximum likelihood phylogenies with PhyML. (2009, methodology): “Statistical supports for branches displayed by each of the two competing topologies were measured using 100 non-parametric bootstrap replicates (BP; (43)) and the approximate likelihood ratio test for branches (aLRT; (8)).”