Skip to contents

Robust universal tree balance index

Source: R/RUtreebalance.R
J1Index.Rd

Calculate tree balance index J1 (when nonRootDominance = FALSE) or J1c (when nonRootDominance = TRUE) from Lemant J, Le Sueur C, Manojlović V, Noble R (2022). “Robust, Universal Tree Balance Indices.” Systematic Biology, 71(5), 1210–1224. doi:10.1093/sysbio/syac027 . .

Usage

J1Index(tree, q = 1, nonRootDominance = FALSE)

JQIndex(tree, q = 1, nonRootDominance = FALSE)

Arguments

tree

Either an object of class 'phylo', or a dataframe with column names Parent, Identity and (optionally) Population. The latter is similar to tree$edge, where tree is an object of class 'phylo'; the differences are in class (data.frame versus matrix) and column names. The dataframe may (but isn't required to) include a row for the root node. If population sizes are omitted then internal nodes will be assigned population size zero and leaves will be assigned population size one.

q

Numeric between zero and one specifying sensitivity to type frequencies. If q < 1, the Jq index - based on generalized entropy - will be returned; see Lemant et al. (2022) , page 1223.

nonRootDominance

Logical specifying whether to use non-root dominance factor.

Details

If population sizes are not provided, then the function assigns size 0 to internal nodes, and size 1 to leaves.

References

Lemant J, Le Sueur C, Manojlović V, Noble R (2022). “Robust, Universal Tree Balance Indices.” Systematic Biology, 71(5), 1210–1224. doi:10.1093/sysbio/syac027 .

See also

Other tree characterization functions: CladisticInfo(), Consensus(), Stemwardness, TotalCopheneticIndex()

Author

Rob Noble, adapted by Martin R. Smith

Examples

# Using phylo object as input:
phylo_tree <- read.tree(text="((a:0.1)A:0.5,(b1:0.2,b2:0.1)B:0.2);")
J1Index(phylo_tree)
#> [1] 0.7924813
phylo_tree2 <- read.tree(text='((A, B), ((C, D), (E, F)));')
J1Index(phylo_tree2)
#> [1] 0.9693609

# Using edges lists as input:
tree1 <- data.frame(Parent = c(1, 1, 1, 1, 2, 3, 4),
                    Identity = 1:7,
                    Population = c(1, rep(5, 6)))
J1Index(tree1)
#> [1] 0.6666667
tree2 <- data.frame(Parent = c(1, 1, 1, 1, 2, 3, 4),
                    Identity = 1:7,
                    Population = c(rep(0, 4), rep(1, 3)))
J1Index(tree2)
#> [1] 0.5
tree3 <- data.frame(Parent = c(1, 1, 1, 1, 2, 3, 4),
                    Identity = 1:7,
                    Population = c(0, rep(1, 3), rep(0, 3)))
J1Index(tree3)
#> [1] 1
cat_tree <- data.frame(Parent = c(1, 1:14, 1:15, 15),
                       Identity = 1:31,
                       Population = c(rep(0, 15), rep(1, 16)))
J1Index(cat_tree)
#> [1] 0.4740741

# If population sizes are omitted then internal nodes are assigned population
# size zero and leaves are assigned population size one:
sym_tree1 <- data.frame(Parent = c(1, rep(1:15, each = 2)),
                       Identity = 1:31,
                       Population = c(rep(0, 15), rep(1, 16)))
# Equivalently:                        
sym_tree2 <- data.frame(Parent = c(1, rep(1:15, each = 2)),
                       Identity = 1:31)
J1Index(sym_tree1)
#> [1] 1
J1Index(sym_tree2)
#> [1] 1