Not so different after all: a comparison of methods for detecting amino acid sites under selection.

By Sergei L. Kosakovsky Pond, Simon D. W. Frost. Molecular biology and evolution, 2005

2,181 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/84e721146de70540a6629554b0f254ac2017d15c

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Citations in the corpus

Datamonkey: rapid detection of selective pressure on individual sites of codon alignments (2005, methodology): “Random effects likelihood (REL) is an improved variant of the Nielsen– Yang approach, which uses flexible but not overly parameter-rich rate distributions (Kosakovsky Pond and Frost, 2005a) and allows both dS and dN to vary across sites independently.”
Fast hierarchical Bayesian analysis of population structure (2018, background): “Con-founding population structure must also be considered in tests for natural selection as well as genetic association studies (1–3).”
HyPhy 2.5 - a customizable platform for evolutionary hypothesis testing using phylogenies. (2019, methodology): “Key analyses in this class include methods for characterizing the action of natural selection on genes (Murrell et al. 2015), specific sites (Pond and Frost 2005a; Murrell et al. 2012, 2013) in genes, and branches of phylogenetic trees (Smith et al. 2015), comparing selective regimes between sites…”
Emergence and rapid spread of a new severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) lineage with multiple spike mutations in South Africa (2020, positive): “This pipeline examines the entire global SARS-CoV-2 nucleotide sequence dataset for evidence of: (i) polymorphisms having arisen in multiple epidemiologically unlinked lineages that have statistical support for non-neutral evolution (Mixed Effects Model of Evolution, MEME) 25 , (ii) sites where thes”
Selecton 2007: advanced models for detecting positive and purifying selection using a Bayesian inference approach (2007, background): “However, it was previously shown that the detection of positive selection is in general robust to tree topology inaccuracies (6,38,39).”
MEGA12: Molecular Evolutionary Genetic Analysis Version 12 for Adaptive and Green Computing (2024, positive): “The ML tree and MSAs for each protein-coding gene were obtained from Shen et al. (2017).”