sbphylo {scaleboot} | R Documentation |
Tables for phylogenetic inference
Description
Creating tables of p-values and tree/edge associaitons for phylogenetic inference. Trees and edges are sorted by the likelihood value.
Usage
sbphylo(relltest,ass,trees,edges,edge2tree,
treename=NULL,edgename=NULL,taxaname=NULL,mt=NULL,sort=TRUE)
## S3 method for class 'sbphylo'
summary(object, k = 2,...)
## S3 method for class 'sbphylo'
print(x,...)
## S3 method for class 'summary.sbphylo'
print(x,...)
Arguments
relltest |
|
ass |
|
trees |
|
edges |
|
edge2tree |
|
treename |
character vector for tree descriptions. |
edgename |
character vector for edge descriptions. |
taxaname |
character vector for taxa names. |
mt |
|
sort |
sorting trees and edges by likelhiood when TRUE. |
object |
output of |
k |
integer of |
x |
sbphylo or summary.sbphylo objects. |
... |
further arguments passed to and from other methods. |
Details
First, apply sbphylo
to consel results, and summary
will make tables.
Output tables are suitable for publication.
For the input of sbphylo
, you should specify either of (relltest
, ass
) or
(trees
, edges
, edge2tree
).
Value
sbphylo
returns a list of several information of multiscale bootstrap.
It does not do actual computation, but only sort trees and edges in decreasing order of likelihood values. The compied information is then passed to
summary
method, which returns a list containing character tables and its numerical values of p-values.
Author(s)
Hidetoshi Shimodaira
See Also
Examples
## working with CONSEL outputs
data(mam15)
mam15.trees <- mam15.relltest[attr(mam15.ass,"trees")] # 15 trees
mam15.edges <- mam15.relltest[attr(mam15.ass,"edges")] # 10 edges
mam15.edge2tree <- mam15.ass[attr(mam15.ass,"edges")] # 10 edges
mam15 <- sbphylo(trees=mam15.trees,edges=mam15.edges,
edge2tree=mam15.edge2tree) # sort trees and edges by likelihood
mam15 # print method for sbphylo
tab <- summary(mam15) # summary method for sbphylo
tab # prints character table
## plot (beta0,beta1)
a1 <- attr(summary(mam15$trees,k=2),"table")
a2 <- attr(summary(mam15$edges,k=2),"table")
beta <- rbind(a1$value,a2$value)[,c("beta0","beta1")]
sbplotbeta(beta) # for diagnostics of p-values