Uses of Interface
pal.substmodel.SubstitutionModel
Packages that use SubstitutionModel
Package
Description
Classes for reading and generating distance matrices, including computation
of pairwise distances for sequence data (maximum-likelihood and observed
distances).
Classes for evaluating evolutionary hypothesis (chi-square and likelihood
criteria) and estimating model parameters.
Classes with useful for statistics (normal distribution,
Gamma distribution, chi-square distribution, exponential distribution,
likelihood-ratio test, chi-square test, descriptive statistics, bootstrap estimators etc.)
Classes describing substitution models, i.e.
Classes for providing the data structure of
trees, for constructing and modifying trees, and for parameterizing
trees (e.g., clock constraint).
-
Uses of SubstitutionModel in pal.distance
Methods in pal.distance with parameters of type SubstitutionModelModifier and TypeMethodDescriptionstatic final DistanceMatrixDistanceTool.constructEvolutionaryDistances(Alignment a, SubstitutionModel sm) Construct a distance matrix object such that the distance between sequence A, and sequence B, is the evolutionary distance by a given substitution model.static DistanceMatrixAccessDistanceMatrixAccess.Utils.createEvolutionary(Alignment a, SubstitutionModel sm) static DistanceMatrixGeneratorDistanceMatrixGenerator.Utils.createEvolutionary(Alignment a, SubstitutionModel sm) static DistanceMatrixGeneratorDistanceMatrixGenerator.Utils.createParametric(Tree baseTree, SubstitutionModel sm, int numberOfSites) Silly idea stuffvoidAlignmentDistanceMatrix.recompute(SitePattern sp, SubstitutionModel model) recompute maximum-likelihood distances under new site patternvoidAlignmentDistanceMatrix.recompute(SitePattern sp, SubstitutionModel model, AlgorithmCallback callback) recompute maximum-likelihood distances under new site patternvoidPairwiseDistance.updateModel(SubstitutionModel m) update model of substitutionvoidSequencePairLikelihood.updateModel(SubstitutionModel m) update model of substitutionConstructors in pal.distance with parameters of type SubstitutionModelModifierConstructorDescriptioncompute maximum-likelihood distancesAlignmentDistanceMatrix(SitePattern sp, SubstitutionModel m, AlgorithmCallback callback) compute maximum-likelihood distancesConstructor 2 (uses evolutionary model)initialisation -
Uses of SubstitutionModel in pal.eval
Methods in pal.eval that return SubstitutionModelModifier and TypeMethodDescriptionLikelihoodValue.getModel()Returns the model of this likelihood value.SiteDetails.getRelatedModel()Methods in pal.eval with parameters of type SubstitutionModelModifier and TypeMethodDescriptionprotected abstract voidLHCalculator.AbstractExternal.calculateCategoryPatternProbabilities(double distance, SubstitutionModel model, PatternInfo centerPattern, ConditionalProbabilityStore leftFlatConditionalProbabilities, ConditionalProbabilityStore rightFlatConditionalProbabilities, ConditionalProbabilityStore tempStore, double[][] categoryPatternLogLikelihoodStore) protected abstract voidLHCalculator.AbstractExternal.calculateCategoryPatternProbabilities(SubstitutionModel model, PatternInfo centerPattern, ConditionalProbabilityStore leftConditionalProbabilities, ConditionalProbabilityStore rightConditionalProbabilities, double[][] categoryPatternLikelihoodStore) voidLHCalculator.External.calculateExtended(double distance, SubstitutionModel model, PatternInfo centerPattern, ConditionalProbabilityStore leftConditionalProbabilities, ConditionalProbabilityStore rightConditionalProbabilities, ConditionalProbabilityStore resultStore) LHCalculator.Internal.calculateExtended(double distance, SubstitutionModel model, PatternInfo centerPattern, ConditionalProbabilityStore leftConditionalProbabilities, ConditionalProbabilityStore rightConditionalProbabilities, boolean modelChangedSinceLastCall) doubleLHCalculator.External.calculateLogLikelihood(double distance, SubstitutionModel model, PatternInfo centerPattern, ConditionalProbabilityStore leftFlatConditionalProbabilities, ConditionalProbabilityStore rightFlatConditionalProbabilities, ConditionalProbabilityStore tempStore) Calculate the likelihood given two sub trees (left, right) and their flat (unextend) likeihood probabilitiesdoubleLHCalculator.External.calculateLogLikelihood(SubstitutionModel model, PatternInfo centerPattern, ConditionalProbabilityStore leftConditionalProbabilities, ConditionalProbabilityStore rightConditionalProbabilities) Calculate the likelihood given two sub trees (left, right) and their extended likeihood probabilitiesstatic final doubleLikelihoodTool.calculateLogLikelihood(Tree tree, Alignment alignment, SubstitutionModel model) Calculate the log likelihood of a particular set of phylogenetic datadoubleLHCalculator.External.calculateLogLikelihoodSingle(SubstitutionModel model, int[] patternWeights, int numberOfPatterns, ConditionalProbabilityStore conditionalProbabilityStore) Calculate the likelihood given the conditional probabilites at the rootLHCalculator.Internal.calculatePostExtendedFlat(double distance, SubstitutionModel model, PatternInfo centerPattern, ConditionalProbabilityStore leftConditionalProbabilities, ConditionalProbabilityStore rightConditionalProbabilities, boolean modelChangedSinceLastCall) voidLHCalculator.External.calculateSingleExtendedDirect(double distance, SubstitutionModel model, int numberOfPatterns, ConditionalProbabilityStore conditionalProbabilities) Extend the conditionals back in time by some distance, with some modelvoidLHCalculator.External.calculateSingleExtendedIndirect(double distance, SubstitutionModel model, int numberOfPatterns, ConditionalProbabilityStore baseConditionalProbabilities, ConditionalProbabilityStore resultConditionalProbabilities) Extend the conditionals back in time by some distance, with some modelfinal SiteDetailsLHCalculator.AbstractExternal.calculateSiteDetailsRooted(SubstitutionModel model, PatternInfo centerPattern, ConditionalProbabilityStore leftConditionalProbabilitiesStore, ConditionalProbabilityStore rightConditionalProbabilitiesStore) LHCalculator.External.calculateSiteDetailsRooted(SubstitutionModel model, PatternInfo centerPattern, ConditionalProbabilityStore leftConditionalProbabilitiesStore, ConditionalProbabilityStore rightConditionalProbabilitiesStore) Calculate the conditional probabilities of each pattern for each categoryfinal SiteDetailsLHCalculator.AbstractExternal.calculateSiteDetailsUnrooted(double distance, SubstitutionModel model, PatternInfo centerPattern, ConditionalProbabilityStore leftFlatConditionalProbabilities, ConditionalProbabilityStore rightFlatConditionalProbabilities, ConditionalProbabilityStore tempStore) LHCalculator.External.calculateSiteDetailsUnrooted(double distance, SubstitutionModel model, PatternInfo centerPattern, ConditionalProbabilityStore leftConditionalProbabilitiesStore, ConditionalProbabilityStore rightConditionalProbabilitiesStore, ConditionalProbabilityStore tempStore) Calculate the conditional probabilities of each pattern for each categorystatic final SiteDetailsSiteDetails.Utils.create(double[][] categoryPatternConditionalProbabilities, boolean isLoggedConditionals, SubstitutionModel model, int numberOfPatterns, int[] sitePatternMatchup, int numberOfSites, double[] siteLikelihoods) Create a Postriors objectstatic final MolecularClockLikelihoodModel.InstanceSimpleMolecularClockLikelihoodModel.createInstance(LHCalculator.Factory baseFactory, SubstitutionModel model) static final MolecularClockLikelihoodModel.InstanceSimpleMolecularClockLikelihoodModel.createInstance(SubstitutionModel model) static final UnconstrainedLikelihoodModel.InstanceSimpleUnconstrainedLikelihoodModel.createInstance(LHCalculator.Factory base, SubstitutionModel model) Create a SimpleUnconstrainedLikelihoodModel instancestatic final UnconstrainedLikelihoodModel.InstanceSimpleUnconstrainedLikelihoodModel.createInstance(LHCalculator.Generator base, SubstitutionModel model) Create a SimpleUnconstrainedLikelihoodModel instanceLHCalculator.Leaf.getExtendedConditionalProbabilities(double distance, SubstitutionModel model, boolean modelChanged) SimpleLeafCalculator.getExtendedConditionalProbabilities(double distance, SubstitutionModel model, boolean modelChanged) static final AlignmentLikelihoodTool.getMatchingDataType(Alignment alignment, SubstitutionModel model) Creates a new alignment that has a compatible data type with a substution model (needed for likelihood stuff)static final doubleLikelihoodOptimiser.optimiseAlternate(ParameterizedTree tree, Alignment alignment, SubstitutionModel model, MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits) Optimise parameters to acheive maximum likelihood using an alternating stategy.static final doubleLikelihoodOptimiser.optimiseAlternate(ParameterizedTree tree, Alignment alignment, SubstitutionModel model, MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits, MinimiserMonitor monitor) Optimise parameters to acheive maximum likelihood using an alternating stategy.static final TreeLikelihoodTool.optimiseClockConstrained(Tree tree, Alignment alignment, SubstitutionModel model, boolean optimiseModel) Optimise the branches of a tree with regard to maximum likelihood, with a molecular clock assumption, that is, constrained such that all tips are contemporaneous, the tree is treated as rooted.static final doubleLikelihoodOptimiser.optimiseCombined(ParameterizedTree tree, Alignment alignment, SubstitutionModel model, MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits) Optimise parameters to acheive maximum likelihood using a combined stategy.static final doubleLikelihoodOptimiser.optimiseCombined(ParameterizedTree tree, Alignment alignment, SubstitutionModel model, MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits, MinimiserMonitor monitor) Optimise parameters to acheive maximum likelihood using a combined stategy.static final doubleLikelihoodOptimiser.optimiseModel(Tree tree, Alignment alignment, SubstitutionModel model, MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits, MinimiserMonitor monitor) Optimise model parameters only to acheive maximum likelihood using a combined stategy.static final TreeLikelihoodTool.optimiseMRDT(Tree tree, Alignment alignment, SubstitutionModel model, TimeOrderCharacterData tocd, boolean optimiseModel, double[] rateStore) Optimise the branches of a tree with regard to maximum likelihood, with under an assumption of a molecular clock with serially sampled data and multiple mutation rate parameters, mu - one for each sampling interval.static final TreeLikelihoodTool.optimiseMRDT(Tree tree, Alignment alignment, SubstitutionModel model, TimeOrderCharacterData tocd, boolean optimiseModel, double[] rateChangeTimes, double[] rateStore) Optimise the branches of a tree with regard to maximum likelihood, with under an assumption of a molecular clock with serially sampled data and multiple mutation rate parameters, mu, over general time intervals.static final TreeLikelihoodTool.optimiseSRDT(Tree tree, Alignment alignment, SubstitutionModel model, TimeOrderCharacterData tocd, boolean optimiseModel, double[] rateStore) Optimise the branches of a tree with regard to maximum likelihood, with under an assumption of a molecular clock with serially sampled data and a single mutation rate parameter.static final doubleLikelihoodOptimiser.optimiseTree(ParameterizedTree tree, Alignment alignment, SubstitutionModel model, MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits) Optimise tree branchlengths only to acheive maximum likelihood using a combined stategy.static final doubleLikelihoodOptimiser.optimiseTree(ParameterizedTree tree, Alignment alignment, SubstitutionModel model, MultivariateMinimum minimiser, int fxFracDigits, int xFracDigits, MinimiserMonitor monitor) Optimise tree branchlengths only to acheive maximum likelihood using a combined stategy.static final TreeLikelihoodTool.optimiseUnrooted(Tree tree, Alignment alignment, SubstitutionModel model, boolean optimiseModel) Optimise the branches of a tree with regard to maximum likelihood, with no constraints on the branchlengths (as for an unrooted tree).voidLikelihoodValue.setModel(SubstitutionModel m) define model (a site pattern must have been set before calling this method)final voidGeneralLikelihoodCalculator.setup(Tree t, SubstitutionModel model) Constructors in pal.eval with parameters of type SubstitutionModelModifierConstructorDescriptionGeneralLikelihoodCalculator(Alignment baseAlignment, Tree tree, SubstitutionModel model) Constructor taking site pattern, tree and a general substitution model.InternalImpl(LHCalculator.Internal base, SubstitutionModel model) LeafImpl(LHCalculator.Leaf base, SubstitutionModel model) LikelihoodOptimiser(Tree tree, Alignment alignment, SubstitutionModel model) Constructor -
Uses of SubstitutionModel in pal.statistics
Methods in pal.statistics with parameters of type SubstitutionModelModifier and TypeMethodDescriptionstatic final ReplicateLikelihoodEvaluatorReplicateLikelihoodEvaluator.Utils.createRELLEvaluator(SubstitutionModel model) Create a ReplicateLikelihoodEvaluator that based likelihood on original tree (does no optimisation)static final LikelihoodEvaluatorLikelihoodEvaluator.Utils.createSimpleEvaluator(SubstitutionModel model) Create a simple evaluator that uses UnrootedTreeSearch -
Uses of SubstitutionModel in pal.substmodel
Classes in pal.substmodel that implement SubstitutionModelModifier and TypeClassDescriptionclassclassstatic classA Substitution Model which can be used to implment the Neutral Model (with out continuous rate stuff) Codon model of [1] which uses the weighted sum of trwo base YangCodon models where omega=0, omega=1 repectively
[1] Nielsen, R., Yang Z., 1998 Likelihood Models for Detecting Positively Selected Amino Acid Sites and Applications to the HIV-1 Envelope Gene.static classA Substitution Model which can be used to implment the Postitive Selection (with out continuous rate stuff) Codon model of [1] which uses the weighted sum of a three base Codon model where omega=0, omega=1 and omega=free
[1] Nielsen, R., Yang Z., 1998 Likelihood Models for Detecting Positively Selected Amino Acid Sites and Applications to the HIV-1 Envelope Gene.Fields in pal.substmodel declared as SubstitutionModelMethods in pal.substmodel that return SubstitutionModelModifier and TypeMethodDescriptionstatic final SubstitutionModelSubstitutionTool.createF81Model(double[] baseFrequencies) Create an F81 model of substitutionstatic final SubstitutionModelSubstitutionTool.createF84Model(double expectedTsTv, double[] baseFrequencies) Create an F84 model of substitutionstatic final SubstitutionModelSubstitutionTool.createGTRModel(double a, double b, double c, double d, double e, double[] baseFrequencies) Create an GTR model of substitutionstatic final SubstitutionModelSubstitutionTool.createJC69Model()Create a Jukes-cantor model of substitutionstatic final SubstitutionModelSubstitutionTool.createM0YangCodonModel(double kappa, double omega, double[] baseFrequencies) Create an base Yang Codon model (M0) of substitutionstatic final SubstitutionModelSubstitutionTool.createM1YangCodonModel(double kappa, double p0, double[] baseFrequencies) Create an neutral Yang Codon model (M1) of substitutionstatic final SubstitutionModelSubstitutionTool.createM2YangCodonModel(double kappa, double p0, double p1, double omega, double[] baseFrequencies) Create an Positive Yang Codon model (M2) of substitutionstatic final SubstitutionModelSubstitutionModel.Utils.createSubstitutionModel(NeoRateMatrix rm, DataType dt, double[] equilibriumFrequencies) static final SubstitutionModelSubstitutionModel.Utils.createSubstitutionModel(RateMatrix rm) static final SubstitutionModelSubstitutionModel.Utils.createSubstitutionModel(RateMatrix rm, RateDistribution rd) static final SubstitutionModelSubstitutionModel.Utils.createSubstitutionModel(RateMatrix rm, RateDistribution rd, boolean parameteriseDistribution) static final SubstitutionModelSubstitutionTool.createTNModel(double kappa, double r, double[] baseFrequencies) Create an Tamura-Nei model of substitutionGeneralRateDistributionSubstitutionModel.getCopy()SingleClassSubstitutionModel.getCopy()YangCodonModel.SimpleNeutralSelection.getCopy()YangCodonModel.SimplePositiveSelection.getCopy()Methods in pal.substmodel with parameters of type SubstitutionModelModifier and TypeMethodDescriptionstatic final double[][][]SubstitutionModel.Utils.generateTransitionProbabilityTables(SubstitutionModel model) Constructors in pal.substmodel with parameters of type SubstitutionModelModifierConstructorDescriptionSequenceSimulator(SubstitutionModel model, int sequenceLength, boolean stochasticDistribution) A constructor (with no provided random number generator - a fresh one is created)SequenceSimulator(SubstitutionModel model, int sequenceLength, MersenneTwisterFast random, boolean stochasticDistribution) A constructor (with no provided random number generator - a fresh one is created) -
Uses of SubstitutionModel in pal.supgma
Methods in pal.supgma with parameters of type SubstitutionModelModifier and TypeMethodDescriptionSUPGMABase.PopulationParameters.inferCI(AlgorithmCallback callback, int numberOfReplicates, SimulatedAlignment.Factory alignmentFactory, SubstitutionModel evolutionaryModel, LMSSolver solver) -
Uses of SubstitutionModel in pal.tree
Constructors in pal.tree with parameters of type SubstitutionModelModifierConstructorDescriptionFactory(int sequenceLength, SubstitutionModel model) SimulatedAlignment(int sites, Tree t, SubstitutionModel m) Inititalisation -
Uses of SubstitutionModel in pal.treesearch
Methods in pal.treesearch with parameters of type SubstitutionModelModifier and TypeMethodDescriptionBranchAccess.attach(String newSequence, Alignment fullAlignment, SubstitutionModel model) Create a new Tree Searcher with a new sub tree attachedBranchAccess.attach(Node subTree, Alignment fullAlignment, SubstitutionModel model) Create a new Tree Searcher with a new sub tree attachedTreeSearchTool.basicUnrootedTreeMLSearch(Alignment a, SubstitutionModel sm, boolean optimiseModel) Do a basic tree search using maximum likelihood on an unrooted tree space, without a given starting treeTreeSearchTool.basicUnrootedTreeMLSearch(Alignment a, SubstitutionModel sm, boolean optimiseModel, AlgorithmCallback callback) Do a basic tree search using maximum likelihood on an unrooted tree space, without a given starting treeTreeSearchTool.basicUnrootedTreeMLSearch(Tree baseTree, Alignment a, SubstitutionModel sm, boolean optimiseModel) Do a basic tree search using maximum likelihood on an unrooted tree space, with a given starting treeTreeSearchTool.basicUnrootedTreeMLSearch(Tree baseTree, Alignment a, SubstitutionModel sm, boolean optimiseModel, AlgorithmCallback callback) Do a basic tree search using maximum likelihood on an unrooted tree space, with a given starting treestatic final doubleTreeSearchTool.calculateLogLikelihood(Tree tree, Alignment alignment, SubstitutionModel model) Calculate the log likelihood of a particular set of phylogenetic datastatic final AlignmentTreeSearchTool.getMatchingDataType(Alignment alignment, SubstitutionModel model) Creates a new alignment that has a compatible data type with a substution model (needed for likelihood stuff)static final TreeTreeSearchTool.optimiseClockConstrainedFixed(Tree tree, Alignment alignment, SubstitutionModel model, boolean optimiseModel, AlgorithmCallback callback) Optimise the branches of a tree with regard to maximum likelihood, with the contraints of a global molecular clock - that is, all the tips terminate at the same point.static final TreeTreeSearchTool.optimiseUnrootedFixed(Tree tree, Alignment alignment, SubstitutionModel model, boolean optimiseModel) Optimise the branches of a tree with regard to maximum likelihood, with no constraints on the branchlengths (as for an unrooted tree).static final TreeTreeSearchTool.optimiseUnrootedFixed(Tree tree, Alignment alignment, SubstitutionModel model, boolean optimiseModel, AlgorithmCallback callback) Optimise the branches of a tree with regard to maximum likelihood, with no constraints on the branchlengths (as for an unrooted tree).Constructors in pal.treesearch with parameters of type SubstitutionModelModifierConstructorDescriptionUnrootedMLSearcher(Alignment alignment, SubstitutionModel model) Build an unconstrained optimiser based on a randomly generated tree.UnrootedMLSearcher(Alignment alignment, SubstitutionModel model, LHCalculator.Factory calcFactory) UnrootedMLSearcher(Node root, Alignment alignment, SubstitutionModel model) UnrootedMLSearcher(Node root, Alignment alignment, SubstitutionModel model, LHCalculator.Factory calcFactory) UnrootedMLSearcher(Node root, SubstitutionModel model) Create a searcher based on a given tree, that has no alignment specified (useful as backbone tree for attaching new nodes)UnrootedMLSearcher(Tree t, Alignment alignment, SubstitutionModel model)