plotPosterior: A function to visualize outputs of QIRP, QIHP, and QIPP...

Description Usage Arguments Value Author(s) References Examples

Description

A function to visualize outputs of QIRP, QIHP, and QIPP computed across a distribution of trees

Usage

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plotPosterior(final, plotType = "QIPs")

Arguments

final

output from su.bayes

plotType

type of plot, can be "QIPs" or "violin"

Value

Returns a graphical visulatization of values of either calculation densitys (plot='QIPS') or kernel denstities and quartiles (plot='violin')

Author(s)

A. Dornburg

References

Townsend, J. P., Su, Z., and Tekle, Y. I. “Phylogenetic Signal and Noise: Predicting the Power of a Data Set to Resolve Phylogeny” Systematic biology 61, no. 5 (2012): 835–849. Su, Z., Zhuo, S., Zheng, W., Francesc, L.-G., and Townsend, J. P. “The Impact of Incorporating Molecular Evolutionary Model into Predictions of Phylogenetic Signal and Noise” Frontiers in Ecology and Evolution 2, (2014): doi:10.3389/fevo.2014.00011, Available at http://dx.doi.org/10.3389/fevo.2014.00011 Su, Z. and Townsend, J. P. “Utility of Characters Evolving at Diverse Rates of Evolution to Resolve Quartet Trees with Unequal Branch Lengths: Analytical Predictions of Long-Branch Effects” BMC evolutionary biology 15, (2015): 86.

Examples

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library("ape")
read.tree(system.file("extdata","polypterus_trees.phy",package="PhyInformR"))->trees
trees<-trees[1:10]
as.matrix(rag1)->rates
quart<-c("Polypterus_congicus", "Polypterus_bichir", 
"Polypterus_ansorgii", "Polypterus_endlicheri")
a<-1
b<-1
c<-1
d<-1
e<-1
f<-1
Pi_T<-.25
Pi_C<-.25
Pi_A<-.25
Pi_G<-.25
##Not run
#su.bayes(a,b,c,d,e,f, Pi_T, Pi_C, Pi_A, Pi_G, rates, quart, trees)->final
#plotPosterior(final, plotType='violin')
##

PhyInformR documentation built on May 2, 2019, 2:49 p.m.