Apply the NANUQ algorithm of ABR19;textualMSCquartets to infer a hybridization network from a collection of gene trees, under the level-1 network multispecies coalescent (NMSC) model.
NANUQ(
genedata,
outfile = "NANUQdist",
omit = FALSE,
epsilon = 0,
alpha = 0.05,
beta = 0.95,
taxanames = NULL,
plot = TRUE
)a table $pTable of quartets and p-values for judging fit to the MSC on quartet
trees, and a distance table $dist, or list of distance tables, giving NANUQ distance (returned invisibly);
the table can be used as input to NANUQ or NANUQdist with new choices of alpha and beta, without re-tallying quartets on
gene trees; the distance table is to be used as input to NeighborNet.
gene tree data that may be supplied in any of 3 forms:
as a character string giving the name of a file containing Newick gene trees,
as a multiPhylo object containing the gene trees, or
as a table of quartets on the gene trees, as produced by a previous call to
NANUQ or quartetTableResolved, which has columns only for taxa, resolved quartet counts,
and possibly p_T3 and p_star
a character string giving an output file name stub for
saving a NANUQ distance matrix in nexus format; to the stub outfile
will be appended an alpha and beta value and ".nex";
if NULL then then no file is written
FALSE to treat unresolved quartets as 1/3 of each resolution;
TRUE to discard unresolved quartet data; ignored if gene tree data given as quartet table
minimum for branch lengths to be treated as non-zero; ignored if gene tree data given as quartet table
a value or vector of significance levels for judging p-values testing a null hypothesis of no hybridization vs. an alternative of hybridization, for each quartet; a smaller value applies a less conservative test for a tree (more trees), hence a stricter requirement for desciding in favor of hybridization (fewer reticulations)
a value or vector of significance levels for judging p-values testing
a null hypothesis of a star tree (polytomy) for each quartet vs. an alternative of anything else; a smaller value applies a less conservative
test for a star tree (more polytomies), hence a stricter requirement for deciding in favor of a resolved tree or network;
if vectors, alpha and beta must have the same length
if genedata is a file or a multiPhylo object, a vector of a subset
of the taxa names on the gene trees
to be analyzed, if NULL all taxa on the first gene tree are used; if genedata
is a quartet table, this argument is ignored and all taxa in the table are used
TRUE produces simplex plots of hypothesis test results, FALSE omits plots
This function
counts displayed quartets across gene trees to form quartet count concordance factors (qcCFs),
applies appropriate hypothesis tests to judge qcCFs as representing putative hybridization,
resolved trees, or unresolved (star) trees using alpha and beta as significance levels,
produces a simplex plot showing results of the hypothesis tests for all qcCFs
computes the appropriate NANUQ distance table, writing it to a file.
The distance table file
can then be opened in the external software SplitsTree SplitsTreeMSCquartets (recommended) or within R using the package phangorn to
obtain a circular split system under the Neighbor-Net algorithm, which is then depicted as a splits graph.
The splits graph should be interpreted via
the theory of ABR19;textualMSCquartets to infer the level-1 species network, or to conclude the data does
not arise from the NMSC on such a network.
If alpha and beta are vectors, they must have the same length k. Then the i-th entries are paired to
produce k plots and k output files. This is equivalent to k calls to NANUQ with scalar values of alpha and beta.
A call of NANUQ with genedata given as a table previously output from NANUQ is
equivalent to a call of NANUQdist. If genedata is a table previously output from quartetTableResolved
which lacks columns of p-values for hypothesis tests, these will be appended to the table output by NANUQ.
If plots are produced, each point represents an empirical quartet concordance factor, color-coded to represent test results.
In general, alpha should be chosen to be small and beta
to be large so that most quartets are interpreted as resolved trees.
Usually, an initial call to NANUQ will not give a good analysis, as values
of alpha and beta are likely to need some adjustment based on inspecting the data. Saving the returned
table from NANUQ will allow for the results of the time-consuming computation of qcCFs to be
saved, along with p-values,
for input to further calls of NANUQ with new choices of alpha and beta.
See the documentation for quartetNetworkDist for an explanation of a small, rarely noticeable,
stochastic element of the algorithm.
For data sets of many gene trees, user time may be reduced by using parallel code for
counting displayed quartets. See quartetTableParallel, where example commands are given.
ABR19MSCquartets
SplitsTreeMSCquartets
quartetTable, quartetTableParallel, quartetTableDominant, quartetTreeTestInd,
quartetStarTestInd, NANUQdist, quartetTestPlot, pvalHist,
quartetNetworkDist
data(pTableYeastRokas)
out=NANUQ(pTableYeastRokas, alpha=.05, beta=.95, outfile = NULL)
# Specifying an outfile would write the distance table to it for opening in SplitsTree.
# Alternately, to use the phangorn implementation of NeighborNet
# within R, enter the following additional lines:
nn=neighborNet(out$dist)
plot(nn,"2D")
Run the code above in your browser using DataLab