Merge pull request #237 from KlausVigo/main

remove phangorn dependency and add upgma

DESCRIPTION

@@ -46,7 +46,6 @@ Imports:
     utils,
     vegan,
     ggplot2,
-    phangorn,
     ape (>= 3.1-1),
     igraph (>= 1.0.0),
     methods,

NAMESPACE

@@ -99,6 +99,7 @@ export(rrmlg)
 export(samp.ia)
 export(shufflepop)
 export(test_replen)
+export(upgma)
 export(visible)
 export(win.ia)
 exportClasses(MLG)
@@ -123,6 +124,8 @@ importFrom(ade4,is.euclid)
 importFrom(ade4,lingoes)
 importFrom(ade4,quasieuclid)
 importFrom(ape,add.scale.bar)
+importFrom(ape,as.phylo)
+importFrom(ape,as.phylo.hclust)
 importFrom(ape,axisPhylo)
 importFrom(ape,boot.phylo)
 importFrom(ape,is.ultrametric)
@@ -172,8 +175,6 @@ importFrom(igraph,print.igraph)
 importFrom(magrittr,"%>%")
 importFrom(pegas,as.loci)
 importFrom(pegas,loci2genind)
-importFrom(phangorn,midpoint)
-importFrom(phangorn,upgma)
 importFrom(polysat,Genotypes)
 importFrom(polysat,Missing)
 importFrom(polysat,Ploidies)
@@ -185,6 +186,7 @@ importFrom(stats,as.formula)
 importFrom(stats,dbinom)
 importFrom(stats,df)
 importFrom(stats,dist)
+importFrom(stats,hclust)
 importFrom(stats,median)
 importFrom(stats,printCoefmat)
 importFrom(stats,quantile)

R/bruvo.r

@@ -297,7 +297,7 @@ bruvo.between <- function(query, ref, replen = 1, add = TRUE, loss = TRUE, by_lo
 #'   desired.
 #'   
 #' @param tree any function that can generate a tree from a distance matrix.
-#'   Default is \code{\link[phangorn]{upgma}}.
+#'   Default is \code{\link{upgma}}.
 #'   
 #' @param showtree \code{logical} if \code{TRUE}, a tree will be plotted with 
 #'   nodelabels.
@@ -331,7 +331,7 @@ bruvo.between <- function(query, ref, replen = 1, add = TRUE, loss = TRUE, by_lo
 #'   replacement, recalculate the tree, and tally up the bootstrap support
 #'   (measured in percent success). While this function can take any tree
 #'   function, it has native support for two algorithms: \code{\link[ape]{nj}}
-#'   and \code{\link[phangorn]{upgma}}. If you want to use any other functions,
+#'   and \code{\link{upgma}}. If you want to use any other functions,
 #'   you must load the package before you use them (see examples).
 #' 
 #' @note \strong{Please refer to the documentation for bruvo.dist for details on
@@ -383,7 +383,6 @@ bruvo.between <- function(query, ref, replen = 1, add = TRUE, loss = TRUE, by_lo
 #' }
 #' 
 #==============================================================================#
-#' @importFrom phangorn upgma midpoint
 #' @importFrom ape nodelabels nj boot.phylo plot.phylo axisPhylo ladderize 
 #' @importFrom ape add.scale.bar nodelabels tiplabels is.ultrametric
 #   /     \

R/upgma.R

@@ -0,0 +1,22 @@
+#' UPGMA
+#'
+#' UPGMA clustering. Just a wrapper function around \code{\link[stats]{hclust}}.
+#'
+#' @param d A distance matrix.
+#' @return A phylogenetic tree of class \code{phylo}.
+#' @author Klaus Schliep \email{klaus.schliep@@gmail.com}
+#' @seealso \code{\link{hclust}}, \code{\link{as.phylo}}
+#' @importFrom ape as.phylo.hclust as.phylo
+#' @importFrom stats hclust as.dist
+#' @keywords cluster
+#' @examples
+#'
+#' library(ape)
+#' data(woodmouse)
+#' dm <- dist.dna(woodmouse)
+#' tree <- upgma(dm)
+#' plot(tree)
+#'
+#' @rdname upgma
+#' @export
+"upgma" <- function(d) as.phylo(hclust(as.dist(d), method = "average"))

vignettes/mlg.Rmd

@@ -197,7 +197,6 @@ them as different. If we calculate the pairwise euclidean distances between
 samples, we see that "new", "mut" and, "C" are very similar to each other:
 
 ```{r, fig.width = 5, fig.height = 5}
-library("phangorn")
 library("ape")
 raw_dist <- function(x){
   dist(genind2df(x, usepop = FALSE))