ArticleGenetics2004
Accuracy and power of statistical methods for detecting adaptive evolution in protein coding sequences and for identifying positively selected sites.
Article in Genetics, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 323 papers.
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323 citing papers in PubMed.
- Reconstructing mammalian lifespan evolution reveals strong phylogenetic effects and lifespan-associated genes.BMC biology · 2026Article
- Screen for signatures of positive selection in the core genome ofMicrobial genomics · 2026Article
- Gene loss and positively selected genes in chloroplast genomes reveal adaptive evolution in Styracaceae.BMC plant biology · 2026Article
- Myxozoan parasite genomes assembled from contaminated host data reveal extensive gene order conservation and rapid sequence evolution.G3 (Bethesda, Md.) · 2025Article
- Detecting Interspecific Positive Selection Using Convolutional Neural Networks.Molecular biology and evolution · 2025Article
- Comparative Chloroplast Genomics Reveals Intrageneric Divergence inInternational journal of molecular sciences · 2025Article
- Phylogenetic analysis and detection of positive selection in the SIRT gene family across vertebrates.Scientific reports · 2025Article
- Evolutionary analysis of ZAP and its cofactors identifies intrinsically disordered regions as central elements in host-pathogen interactions.Computational and structural biotechnology journal · 2024Article
- Molecular evolution and genetic diversity of defective chorion 1 in Anastrepha fraterculus and Anastrepha obliqua (Diptera, Tephritidae).Development genes and evolution · 2024Article
- Bank vole genomics links determinate and indeterminate growth of teeth.BMC genomics · 2024Article
- CAM evolution is associated with gene family expansion in an explosive bromeliad radiation.The Plant cell · 2024Article
- Relaxed selection in evolution of genes regulating limb development gives clue to variation in forelimb morphology of cetaceans and other mammals.Proceedings. Biological sciences · 2024Article
- Evolution of Virus-like Features and Intrinsically Disordered Regions in Retrotransposon-derived Mammalian Genes.Molecular biology and evolution · 2024Article
- Vole genomics links determinate and indeterminate growth of teeth.bioRxiv : the preprint server for biology · 2024Article
- Phylogenomic resolution of Imparidentia (Mollusca: Bivalvia) diversification through mitochondrial genomes.Marine life science & technology · 2023Article
- Sex-Biased Expression Is Associated With Chromatin State in Drosophila melanogaster and Drosophila simulans.Molecular biology and evolution · 2023Article
- Selection in coral mitogenomes, with insights into adaptations in the deep sea.Scientific reports · 2023Article
- Beginner's Guide on the Use of PAML to Detect Positive Selection.Molecular biology and evolution · 2023Article
- Genes and sites under adaptation at the phylogenetic scale also exhibit adaptation at the population-genetic scale.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Genome-wide identification, expression profile and evolutionary relationships of TPS genes in the neotropical fruit tree species Psidium cattleyanum.Scientific reports · 2023Article
263 more citing papers are in PubMed but not listed here.
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4 authors.
Funding
Abstract
The parsimony method of Suzuki and Gojobori (1999) and the maximum likelihood method developed from the work of Nielsen and Yang (1998) are two widely used methods for detecting positive selection in homologous protein coding sequences. Both methods consider an excess of nonsynonymous (replacement) substitutions as evidence for positive selection. Previously published simulation studies comparing the performance of the two methods show contradictory results. Here we conduct a more thorough simulation study to cover and extend the parameter space used in previous studies. We also reanalyzed an HLA data set that was previously proposed to cause problems when analyzed using the maximum likelihood method. Our new simulations and a reanalysis of the HLA data demonstrate that the maximum likelihood method has good power and accuracy in detecting positive selection over a wide range of parameter values. Previous studies reporting poor performance of the method appear to be due to numerical problems in the optimization algorithms and did not reflect the true performance of the method. The parsimony method has a very low rate of false positives but very little power for detecting positive selection or identifying positively selected sites.
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