Given a Tree of Blobs and qcCF information, resolve all multifurcations to cycles. Resolution is performed by finding a least-squares best-fit of an empirical distance to an expected distance related to the cycle, as described in ABRW24;textualMSCquartets.
resolveLevel1(
ToB,
pTable,
test = "T3",
alpha,
beta,
distance = "NANUQ",
hdegree = 10,
plot = 2,
delta = 10^-6,
fullResMax = 10
)
a list of resolutions and squared residuals:
[[1]] is a list of Newick
resolutions of entire network, with all edge lengths 1 (NULL if one cannot be produced or fullResMax
is exceeded),
[[2]]-[[n]] are individual resolutions of each multifurcation on ToB
,
each given as a list as output from resolveCycle
.
an unrooted tree of blobs (phylo object) as determined by TINNIK or another method
a table of qcCFs, with columns p_star and p_test
either "T3" or "cut", indicating test to use for determining what qcCFs indicate hybridization
test level for p_test
test level value for p_star
cycle resolution distance to be used ("NANUQ" or "modNANUQ")
resolve a multifurcation of this degree or larger by a heuristic method; must be at least 5
if 0, no plots; if 1, plot only possible root locations on ToB and full resolution; if 2, include plots of each individual blob resolution, if 3 include histograms of measure of fit for all hybrid/orders considered in choosing best
cutoff for relative difference in squared residuals and smallest, (RSS-minRSS)/minRSS, for determining near ties as "best" fit resolutions
maximum number of full resolutions (all multifurcations at once)
to form; if the product of the number of resolutions of individual multifurcations
exceeds this, no full resolutions are produced, although combineCycleResolutions
can be applied to produce them.
Possible distances to use are the NANUQ distance and a modified NANUQ distance that weights quartet trees differently, but from which the cycle structure is still identifiable.
For multifucations of degree less than a designated cutoff, all possible circular orders and choices of hybrid nodes are considered in choosing the best. Above that cutoff, a heuristic method is used to obtain a small number of orders likely to be good fits, with the least-squares fitting applied only to those.
ABRW24MSCquartets
TINNIK
, labelIntNodes
, resolveCycle
,
combineCycleResolutions
data(pTableYeastRokas)
out=TINNIK(pTableYeastRokas, alpha=.01, beta=.05)
ToB=labelIntNodes(out$ToB)
resolveLevel1(ToB, pTable=out$pTable, alpha=.01, beta=.05, distance="NANUQ")
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