Package index

Tree distance measures

Functions for calculating distances between pairs of trees.

TreeDistance() SharedPhylogeneticInfo() DifferentPhylogeneticInfo() PhylogeneticInfoDistance() ClusteringInfoDistance() ExpectedVariation() MutualClusteringInfo() SharedPhylogeneticInfoSplits() MutualClusteringInfoSplits() MatchingSplitInfo() MatchingSplitInfoDistance() MatchingSplitInfoSplits()

Information-based generalized Robinson–Foulds distances

NyeSimilarity() NyeSplitSimilarity()

Nye et al. (2006) tree comparison

KendallColijn() KCVector() PathVector() SplitVector() KCDiameter()

Kendall–Colijn distance

MatchingSplitDistance() MatchingSplitDistanceSplits()

Matching Split Distance

JaccardRobinsonFoulds() JaccardSplitSimilarity()

Jaccard–Robinson–Foulds metric

MASTSize() MASTInfo()

Maximum Agreement Subtree size

NNIDist() NNIDiameter()

Approximate Nearest Neighbour Interchange distance

PathDist()

Path distance

InfoRobinsonFoulds() InfoRobinsonFouldsSplits() RobinsonFoulds() RobinsonFouldsMatching() RobinsonFouldsSplits()

Robinson–Foulds distances, with adjustments for phylogenetic information content

SPRDist()

Approximate the Subtree Prune and Regraft (SPR) distance.

CompareAll()

Distances between each pair of trees

VisualizeMatching()

Visualize a matching

Tree space

Functions for the construction, evaluation and exploration of tree space.

Islands()

Find islands from distance matrix

MSTSegments() StrainCol()

Add minimum spanning tree to plot, colouring by stress

MapTrees() Project()

Graphical user interface for mapping distances and analysing tree space

MappingQuality() ProjectionQuality()

Faithfulness of mapped distances

SpectralEigens() SpectralClustering()

Eigenvalues for spectral clustering

SumOfRanges() SumOfVariances() SumOfVars() MeanCentroidDistance() MeanCentDist() MeanCentroidDist() DistanceFromMedian() DistFromMed() MeanNN() MeanMSTEdge()

Cluster size statistics

median(<multiPhylo>)

Median of a set of trees

Plot3()

Pseudo-3D plotting

Cluster analysis

Functions for identifying and interrogating clusters of trees.

KMeansPP()

k-means++ clustering

SumOfRanges() SumOfVariances() SumOfVars() MeanCentroidDistance() MeanCentDist() MeanCentroidDist() DistanceFromMedian() DistFromMed() MeanNN() MeanMSTEdge()

Cluster size statistics

Information

Functions addressing the information content and entropy of splits.

AllSplitPairings()

Variation of information for all split pairings

Entropy() Ntropy()

Entropy in bits

MeilaVariationOfInformation() MeilaMutualInformation()

Use variation of clustering information to compare pairs of splits

SplitsCompatible()

Are splits compatible?

SplitEntropy()

Entropy of two splits

SplitSharedInformation() SplitDifferentInformation() TreesConsistentWithTwoSplits() LnTreesConsistentWithTwoSplits() Log2TreesConsistentWithTwoSplits()

Shared information content of two splits

SplitwiseInfo() ClusteringEntropy() ClusteringInfo() ConsensusInfo()

Information content of splits within a tree

Utility functions

Functions to facilitate interaction with the package.

CompareAll()

Distances between each pair of trees

LAPJV()

Solve linear assignment problem using LAPJV

Plot3()

Pseudo-3D plotting

ReduceTrees()

Collapse areas of agreement between two trees

StartParallel() SetParallel() GetParallel() StopParallel()

Calculate distances in parallel

VisualizeMatching()

Visualize a matching