test.one.species.tree: Tests the fit of a population tree to quartet concordance...

In phylolm: Phylogenetic Linear Regression

Tests the fit of a population tree to quartet concordance factor data

Description

From a set of quartet concordance factors obtained from genetic data (proportion of loci that truly have a given quartet), this function tests the adequacy of the coalescent process on a given population tree, where branch lengths indicate coalescent units.

Usage

test.one.species.tree(cf, guidetree, prep, edge.keep,
                      plot=TRUE, shape.correction = TRUE)

Arguments

cf	data frame containing one row for each 4-taxon set, with taxon names in columns 1-4 and concordance factors in columns 5-7.
guidetree	tree of class phylo on the same taxon set as those in cf, with branch lengths in coalescent units.
prep	result of test.tree.preparation(cf,guidetree). If the test is repeated multiple times on various resolutions of the guide tree (see edge.keep), it saves time to do this only once.
edge.keep	Indices of edges to keep in the guide tree. All other edges are collapsed to reflect ancestral panmixia. In the tested population tree, the collapsed edges have length set to 0.
plot	boolean. If TRUE, a number of plots are output.
shape.correction	boolean. If TRUE, the shapes of all Dirichlet distributions are corrected to be greater or equal to 1. This correction avoids Dirichlet densities going near 0 or 1. It applies when the \alpha parameter is estimated and when the outlier p-values are calculated.

Value

alpha	estimated \alpha parameter.
negPseudoLoglik	Negative pseudo log-likelihood of the population tree.
X2	Chi-square statistic, from comparing the counts of outlier p-values (in outlier.table) to the expected counts.
chisq.pval	p-value from the chi-square test, obtained from the comparing the X2 value to a chi-square distribution with 3 df.
chisq.conclusion	character string. If the chi-square test is significant, this statement says if there is an excess (or deficit) of outlier 4-taxon sets.
outlier.table	Table with 2 rows (observed and expected counts) and 4 columns: number of 4-taxon sets with p-values p\leq 0.01, 0.01<p\leq 0.05, 0.05<p\leq 0.10 or p>0.10.
outlier.pvalues	Vector of outlier p-values, with as many entries as there are rows in cf, one for each set of 4 taxa.
cf.exp	Matrix of concordance factors expected from the estimated population tree, with as many rows as in cf (one row for each 4-taxon set) and 3 columns (one for each of the 3 possible quartet trees).

Author(s)

Cécile Ané

References

Stenz, Noah W. M., Bret Larget, David A. Baum and Cécile Ané (2015). Exploring tree-like and non-tree-like patterns using genome sequences: An example using the inbreeding plant species Arabidopsis thaliana (L.) Heynh. Systematic Biology, 64(5):809-823.

See Also

stepwise.test.tree, test.tree.preparation.

Examples

data(quartetCF)
data(guidetree)
prelim <- test.tree.preparation(quartetCF,guidetree) # takes 5-10 seconds

# test of panmixia: all edges collapsed, none resolved.
panmixia <- test.one.species.tree(quartetCF,guidetree,prelim,edge.keep=NULL)
panmixia[1:6]

# test of full tree: all internal edges resolved, none collapsed.
Ntaxa = length(guidetree$tip.label)
# indices of internal edges:
internal.edges = which(guidetree$edge[,2] > Ntaxa)
fulltree <- test.one.species.tree(quartetCF,guidetree,prelim,edge.keep=internal.edges)
fulltree[1:6]

# test of a partial tree, some edges (but not all) collapsed
edges2keep <- c(1,2,4,6,7,8,11,14,20,21,23,24,31,34,35,36,38,39,44,47,53)
partialTree <- test.one.species.tree(quartetCF,guidetree,prelim,edge.keep=edges2keep)
partialTree[1:5]
partialTree$outlier.table
# identify taxa most responsible for the extra outlier quartets
outlier.4taxa <- which(partialTree$outlier.pvalues < 0.01)
length(outlier.4taxa) # 483 4-taxon sets with outlier p-value below 0.01
q01 = as.matrix(quartetCF[outlier.4taxa,1:4])
sort(table(as.vector(q01)),decreasing=TRUE)
# So: Cnt_1 and Vind_1 both appear in 239 of these 483 outlier 4-taxon sets.
sum(apply(q01,1,function(x){"Cnt_1" %in% x | "Vind_1" %in% x}))
# 266 outlier 4-taxon sets have either Cnt_1 or Vind_1
sum(apply(q01,1,function(x){"Cnt_1" %in% x & "Vind_1" %in% x}))
# 212 outlier 4-taxon sets have both Cnt_1 and Vind_1

phylolm documentation built on Oct. 1, 2024, 1:09 a.m.