CodonTest: Modeling Amino Acid Substitution Preferences in Coding Sequences
Publication Date
August 19, 2010
Journal
PLOS Computational Biology
Authors
Wayne Delport, Konrad Scheffler, Gordon Botha, Mike B. Gravenor, et al
Volume
6
Issue
8
Pages
e1000885
DOI
http://doi.org/10.1371/journal.pcbi.1000885
Publisher URL
http://journals.plos.org/ploscompbiol/article?id=10.1371%2Fjournal.pcbi.1000885
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/20808876
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2924240
Europe PMC
http://europepmc.org/abstract/MED/20808876
Web of Science
000281389500017
Scopus
77955377373
Mendeley
http://www.mendeley.com/research/codontest-modeling-amino-acid-substitution-preferences-coding-sequences
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CiteULike | Further Information

Mendeley | Further Information

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CrossRef

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/415585", "https://ndownloader.figshare.com/files/415606", "https://ndownloader.figshare.com/files/415636"], "description"=>"<div><p>Codon models of evolution have facilitated the interpretation of selective forces operating on genomes. These models, however, assume a single rate of non-synonymous substitution irrespective of the nature of amino acids being exchanged. Recent developments have shown that models which allow for amino acid pairs to have independent rates of substitution offer improved fit over single rate models. However, these approaches have been limited by the necessity for large alignments in their estimation. An alternative approach is to assume that substitution rates between amino acid pairs can be subdivided into rate classes, dependent on the information content of the alignment. However, given the combinatorially large number of such models, an efficient model search strategy is needed. Here we develop a Genetic Algorithm (GA) method for the estimation of such models. A GA is used to assign amino acid substitution pairs to a series of rate classes, where is estimated from the alignment. Other parameters of the phylogenetic Markov model, including substitution rates, character frequencies and branch lengths are estimated using standard maximum likelihood optimization procedures. We apply the GA to empirical alignments and show improved model fit over existing models of codon evolution. Our results suggest that current models are poor approximations of protein evolution and thus gene and organism specific multi-rate models that incorporate amino acid substitution biases are preferred. We further anticipate that the clustering of amino acid substitution rates into classes will be biologically informative, such that genes with similar functions exhibit similar clustering, and hence this clustering will be useful for the evolutionary fingerprinting of genes.</p></div>", "links"=>[], "tags"=>["modeling", "amino", "substitution", "preferences", "coding", "sequences"], "article_id"=>142048, "categories"=>["Evolutionary Biology", "Cancer"], "users"=>["Wayne Delport", "Konrad Scheffler", "Gordon Botha", "Mike B. Gravenor", "Spencer V. Muse", "Sergei L. Kosakovsky Pond"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1000885.s001", "https://dx.doi.org/10.1371/journal.pcbi.1000885.s002", "https://dx.doi.org/10.1371/journal.pcbi.1000885.s003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/CodonTest_Modeling_Amino_Acid_Substitution_Preferences_in_Coding_Sequences/142048", "title"=>"CodonTest: Modeling Amino Acid Substitution Preferences in Coding Sequences", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2010-08-19 00:34:08"}
  • {"files"=>["https://ndownloader.figshare.com/files/834053"], "description"=>"<p>Each panel plots the difference in log likelihood () normalized by the logarithm of the sample size (number of characters), between best fitting GA models with and rates (), against the number of sites in the alignment. For simulations with a single rate class we plotted , top right. Figures for multiple rate simulations (2–5 rates) show as black dots (left column); and as blue dots (right column). Values to the right of row report simulated rates for each class. The left column is a reflection of power, whereas the right column – of the degree of over-fitting. For the case where a single rate was simulated, the degree of over-fitting is the rate of false positives. The desired behavior for is achieved when the model with rate classes is preferred to models with , and rate classes. For a modified BIC criterion with , the former happens if (more definitively with increasing sample size), and the latter if (regardless of sample size).</p>", "links"=>[], "tags"=>["studies"], "article_id"=>504418, "categories"=>["Evolutionary Biology", "Infectious Diseases"], "users"=>["Wayne Delport", "Konrad Scheffler", "Gordon Botha", "Mike B. Gravenor", "Spencer V. Muse", "Sergei L. Kosakovsky Pond"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1000885.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Simulation_studies_used_to_derive_the_appropriate_penalty_term_for_/504418", "title"=>"Simulation studies used to derive the appropriate penalty term for .", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-08-19 01:13:38"}
  • {"files"=>["https://ndownloader.figshare.com/files/834144"], "description"=>"<p>An example from HIV-1 polymerase gene alignment for which the inferred 7 non-synonymous rate classes. The idealized biological rate distribution (unobservable) is depicted by the dashed line. The goodness of fit, the complexity of the models, and the range of maximum likelihood parameter estimates are listed in the table.</p>", "links"=>[], "tags"=>["estimation"], "article_id"=>504518, "categories"=>["Evolutionary Biology", "Infectious Diseases"], "users"=>["Wayne Delport", "Konrad Scheffler", "Gordon Botha", "Mike B. Gravenor", "Spencer V. Muse", "Sergei L. Kosakovsky Pond"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1000885.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Evolutionary_rate_estimation_as_8220_curve_fitting_8221_/504518", "title"=>"Evolutionary rate estimation as “curve fitting.”", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-08-19 01:15:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/834217"], "description"=>"<p>Neighbor-joining <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000885#pcbi.1000885-Saitou1\" target=\"_blank\">[57]</a> trees built from matrices of pairwise substitution spectrum distances (<b>Eq. 2</b>) computed between different models fitted to the HIV-1 group M <i>pol</i> alignment, and between models inferred from different alignments.</p>", "links"=>[], "tags"=>["trees", "built", "matrices", "pairwise", "substitution", "distances", "computed", "models", "fitted", "hiv-1", "inferred"], "article_id"=>504572, "categories"=>["Evolutionary Biology", "Infectious Diseases"], "users"=>["Wayne Delport", "Konrad Scheffler", "Gordon Botha", "Mike B. Gravenor", "Spencer V. Muse", "Sergei L. Kosakovsky Pond"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1000885.g003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Neighbor_joining_57_trees_built_from_matrices_of_pairwise_substitution_spectrum_distances_Eq_2_computed_between_different_models_fitted_to_the_HIV_1_group_M_pol_alignment_and_between_models_inferred_from_different_alignments_/504572", "title"=>"Neighbor-joining [57] trees built from matrices of pairwise substitution spectrum distances (<b>Eq. 2</b>) computed between different models fitted to the HIV-1 group M <i>pol</i> alignment, and between models inferred from different alignments.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-08-19 01:16:12"}
  • {"files"=>["https://ndownloader.figshare.com/files/834282"], "description"=>"<p>Each cluster is labeled with the maximum likelihood estimate of its rate inferred under . The residues (nodes) are annotated by their biochemical properties and Stanfel class, and the rates (edges) are labeled with model-averaged () rate estimates. The style of an edge is determined by its cluster affinity, where high cluster affinities indicate that a large proportion of models in the credible set were consistent with the structured model.</p>", "links"=>[], "tags"=>["clusters", "structured", "ga", "models", "inferred", "hiv-1"], "article_id"=>504644, "categories"=>["Evolutionary Biology", "Infectious Diseases"], "users"=>["Wayne Delport", "Konrad Scheffler", "Gordon Botha", "Mike B. Gravenor", "Spencer V. Muse", "Sergei L. Kosakovsky Pond"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1000885.g004"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Evolutionary_rate_clusters_in_structured_GA_models_inferred_from_the_HIV_1_group_M_pol_alignment_/504644", "title"=>"Evolutionary rate clusters in structured GA models () inferred from the HIV-1 group M <i>pol</i> alignment.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-08-19 01:17:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/834375"], "description"=>"<p>Each cluster is labeled with the maximum likelihood estimate of its rate inferred under . The residues (nodes) are annotated by their biochemical properties and Stanfel class, and the rates (edges) are labeled with model-averaged () rate estimates. The style of an edge is determined by its cluster affinity, where high cluster affinities indicate that a large proportion of models in the credible set were consistent with the structured model.</p>", "links"=>[], "tags"=>["clusters", "structured", "ga", "models", "inferred", "vertebrate", "rhodopsin"], "article_id"=>504733, "categories"=>["Evolutionary Biology", "Infectious Diseases"], "users"=>["Wayne Delport", "Konrad Scheffler", "Gordon Botha", "Mike B. Gravenor", "Spencer V. Muse", "Sergei L. Kosakovsky Pond"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1000885.g005"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Evolutionary_rate_clusters_in_structured_GA_models_inferred_from_the_vertebrate_rhodopsin_protein_alignment_/504733", "title"=>"Evolutionary rate clusters in structured GA models () inferred from the vertebrate rhodopsin protein alignment.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-08-19 01:18:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/834482"], "description"=>"<p>Model-averaged rates were stratified by whether or not they involved a change in polarity, charge or Stanfel class, the medians of two rate distributions were compared using a one sided Wilcoxon rank-sum test. We further correlated the magnitude of substitution rates with one of five property-based distances between the corresponding residues (defined in <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000885#pcbi.1000885-Conant2\" target=\"_blank\">[18]</a>) using a one-sided (negative correlation) Pearson product-moment correlation test.</p>", "links"=>[], "tags"=>["substitution", "rates", "preservation", "hiv-1"], "article_id"=>504849, "categories"=>["Evolutionary Biology", "Infectious Diseases"], "users"=>["Wayne Delport", "Konrad Scheffler", "Gordon Botha", "Mike B. Gravenor", "Spencer V. Muse", "Sergei L. Kosakovsky Pond"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1000885.g006"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Correlations_of_lower_substitution_rates_and_property_preservation_in_the_HIV_1_group_M_pol_alignment_/504849", "title"=>"Correlations of lower substitution rates and property preservation in the HIV-1 group M <i>pol</i> alignment.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-08-19 01:20:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/834574"], "description"=>"<p>Model-averaged rates were stratified by whether or not they involved a change in polarity, charge or Stanfel class, the medians of two rate distributions were compared using a one sided Wilcoxon rank-sum test. We further correlated the magnitude of substitution rates with one of five property-based distances between the corresponding residues (defined in <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000885#pcbi.1000885-Conant2\" target=\"_blank\">[18]</a>) using a one-sided (negative correlation) Pearson product-moment correlation test.</p>", "links"=>[], "tags"=>["substitution", "rates", "preservation", "vertebrate", "rhodopsin"], "article_id"=>504939, "categories"=>["Evolutionary Biology", "Infectious Diseases"], "users"=>["Wayne Delport", "Konrad Scheffler", "Gordon Botha", "Mike B. Gravenor", "Spencer V. Muse", "Sergei L. Kosakovsky Pond"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1000885.g007"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Correlations_of_lower_substitution_rates_and_property_preservation_in_the_vertebrate_rhodopsin_alignment_/504939", "title"=>"Correlations of lower substitution rates and property preservation in the vertebrate rhodopsin alignment.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-08-19 01:22:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/834656"], "description"=>"<p> = number of model parameters estimated from the data. denotes rates that are estimated by maximum likelihood by the data and – those that are estimated in other ways.</p>", "links"=>[], "tags"=>["approaches", "estimating", "residue-dependent", "non-synonymous", "substitution"], "article_id"=>505012, "categories"=>["Evolutionary Biology", "Infectious Diseases"], "users"=>["Wayne Delport", "Konrad Scheffler", "Gordon Botha", "Mike B. Gravenor", "Spencer V. Muse", "Sergei L. Kosakovsky Pond"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1000885.t001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Various_approaches_to_estimating_residue_dependent_non_synonymous_substitution_rates_/505012", "title"=>"Various approaches to estimating residue-dependent non-synonymous substitution rates.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-08-19 01:23:32"}
  • {"files"=>["https://ndownloader.figshare.com/files/834698"], "description"=>"<p> measures the simulated pairwise sequence divergence (expected substitutions/nucleotide site); , standard deviation (averaged over replicates) of estimated rates from the generating values; , the proportion of simulations for which the correct number of rate classes are inferred; , the proportion of simulations which are under-fitted, , the proportion of simulations which are over-fitted, and , the mean Rand C-statistic <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000885#pcbi.1000885-Rand1\" target=\"_blank\">[35]</a> between rate clusters in the generating model and that in the inferred models.</p>", "links"=>[], "tags"=>["ga", "estimating", "classes", "simulated"], "article_id"=>505063, "categories"=>["Evolutionary Biology", "Infectious Diseases"], "users"=>["Wayne Delport", "Konrad Scheffler", "Gordon Botha", "Mike B. Gravenor", "Spencer V. Muse", "Sergei L. Kosakovsky Pond"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1000885.t002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_performance_of_GA_model_selection_with_in_estimating_the_number_and_membership_of_rate_classes_as_well_as_rate_values_from_simulated_data_/505063", "title"=>"The performance of GA model selection with in estimating the number and membership of rate classes as well as rate values from simulated data.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-08-19 01:24:23"}
  • {"files"=>["https://ndownloader.figshare.com/files/834726"], "description"=>"<p> is mean pairwise nucleotide divergence (substitutions/site, estimated under the single rate codon model), is the number of rates estimated in the GA, are the maximum likelihood estimates for the rates.</p><p>*Reference alignments for which GA models were estimated. All GA results presented are for the model with best .</p>†<p>ATP cone is comprised of highly divergent sequences, with only average pairwise amino-acid identity; synonymous rates appear to be saturated.</p>", "links"=>[], "tags"=>["computational biology/evolutionary modeling", "evolutionary biology/bioinformatics"], "article_id"=>505096, "categories"=>["Evolutionary Biology", "Infectious Diseases"], "users"=>["Wayne Delport", "Konrad Scheffler", "Gordon Botha", "Mike B. Gravenor", "Spencer V. Muse", "Sergei L. Kosakovsky Pond"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1000885.t003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Empirical_data_set_characteristics_/505096", "title"=>"Empirical data set characteristics.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-08-19 01:24:56"}
  • {"files"=>["https://ndownloader.figshare.com/files/834765"], "description"=>"<p>The best model (with smallest BIC) is shown in boldface and the rank of each model is provided in parentheses.</p><p>*Reference alignments from which GA models were estimated.</p>", "links"=>[], "tags"=>["empirical", "fits"], "article_id"=>505132, "categories"=>["Evolutionary Biology", "Infectious Diseases"], "users"=>["Wayne Delport", "Konrad Scheffler", "Gordon Botha", "Mike B. Gravenor", "Spencer V. Muse", "Sergei L. Kosakovsky Pond"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1000885.t004"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_empirical_model_fits_using_BIC_/505132", "title"=>"Comparison of empirical model fits using BIC.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-08-19 01:25:32"}
  • {"files"=>["https://ndownloader.figshare.com/files/834807"], "description"=>"<p>The entry for joint effect was obtained by running the general bivariate model fit using the model obtained under the assumption of constant site-to-site rates. df = degrees of freedom.</p>", "links"=>[], "tags"=>["modeling", "site-to-site", "non-synonymous", "rates", "vertebrate", "rhodopsin", "alignment", "mg"], "article_id"=>505166, "categories"=>["Evolutionary Biology", "Infectious Diseases"], "users"=>["Wayne Delport", "Konrad Scheffler", "Gordon Botha", "Mike B. Gravenor", "Spencer V. Muse", "Sergei L. Kosakovsky Pond"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1000885.t005"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_effects_of_modeling_site_to_site_rate_variation_and_multiple_non_synonymous_rates_in_the_vertebrate_rhodopsin_alignment_using_the_MG_frequency_parameterization_/505166", "title"=>"The effects of modeling site-to-site rate variation and multiple non-synonymous rates in the vertebrate rhodopsin alignment using the MG frequency parameterization.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-08-19 01:26:06"}
  • {"files"=>["https://ndownloader.figshare.com/files/834852"], "description"=>"<p>The entry for joint effect was obtained by augmenting the model with non-zero rates for substitutions requiring two or three nucleotide changes. df = degrees of freedom.</p>", "links"=>[], "tags"=>["modeling", "multi-nucleotide", "instantaneous", "substitutions", "non-synonymous", "rates", "vertebrate", "rhodopsin", "alignment", "f61"], "article_id"=>505204, "categories"=>["Evolutionary Biology", "Infectious Diseases"], "users"=>["Wayne Delport", "Konrad Scheffler", "Gordon Botha", "Mike B. Gravenor", "Spencer V. Muse", "Sergei L. Kosakovsky Pond"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1000885.t006"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_effects_of_modeling_multi_nucleotide_instantaneous_substitutions_and_multiple_non_synonymous_rates_in_the_vertebrate_rhodopsin_alignment_using_the_F61_frequency_parameterization_/505204", "title"=>"The effects of modeling multi-nucleotide instantaneous substitutions and multiple non-synonymous rates in the vertebrate rhodopsin alignment using the F61 frequency parameterization.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-08-19 01:26:44"}

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