R/pf.plot.R

In reptalex/phylofactor: phylofactor

#' Label and visualize phylofactors
#'
#' @export
#' @param PF PhyloFactor object
#' @param tree Phylogeny used in generating PhyloFactor object. Default will scan PF for a tree.
#' @param Data Data used to generate PhyloFactor object. If Null, default will plot the phylofactor prediction of the dataset.
#' @param bg Background color for node labels, default 'white'
#' @param cex Size of node labels, default 2.
#' @param factors factors of phylofactor object to be labelled on tree and used in prediction.
#' @param compare Whether or not to compare the Data with phylofactor prediction. If compare = TRUE, two phylo-heatmaps will be produced for direct comparison.
#' @param ... additional arguments for pf.heatmap
#' @return phylo.heatmap labelling the tree with phylofactors and optionally comparing data to phylofactor predictions.
#' @examples
#'  ### Create Data ###
#'  set.seed(1)
#' tree <- unroot(rtree(7))

#' X <- as.factor(c(rep(0,5),rep(1,5)))
#' sigClades <- phangorn::Descendants(tree,c(9,12),type='tips')
#' Data <- matrix(rlnorm(70,meanlog = 8,sdlog = .5),nrow=7)
#' rownames(Data) <- tree$tip.label
#' colnames(Data) <- X
#' Data[sigClades[[1]],X==0] <- Data[sigClades[[1]],X==0]*8
#' Data[sigClades[[2]],X==1] <- Data[sigClades[[2]],X==1]*9
#' Data <- t(clo(t(Data)))

#' PF <- PhyloFactor(Data,tree,X,nfactors=2)

#' pf.plot(PF,factors=1)
#' pf.plot(PF,factors=c(1,2),Data=PF$Data,compare=TRUE)


pf.plot <- function(PF,tree=NULL,Data=NULL,bg='white',cex=2,factors=1,compare=F,...){
  #returns phylo.heatmap highlighting our PFs.
  if(is.null(tree)){
    if(is.null(PF$tree)){stop('Input Phylofactor object does not contain tree - must input tree')}
    tree <- PF$tree
  }
  clr <- function(A) apply(A,MARGIN=2,FUN=function(a) log(a)-mean(log(a)))

  if (compare==F){
    #makes just one plot
    par(mfrow=c(1,1))
    if (is.null(Data)==T){
      if (is.null(names)){stop('must input rownames for PhyloPF predicted dataset')}
      row.names=tree$tip.label
      PData <- pf.predict(PF,factors)
      rownames(PData) <- row.names
      colnames(PData) <- colnames(PData)
      pf.heatmap(tree=tree,Data=clr(PData),...)
    } else {
      pf.heatmap(tree=tree,Data=clr(Data),...)
    }
    # ape::nodelabels(text = as.list(factors),node=PF$nodes[factors],bg = bg,cex=cex)
  } else {


    #makes two plots for comparison
    par(mfrow=c(2,1))
    if (is.null(Data)==T){
      stop('if compare==T, need to input Data for Comparison')
    }
    row.names=rownames(Data)
    PData <-  pf.predict(PF,factors)
    rownames(PData) <- row.names
    rownames(PData) <- tree$tip.label
    colnames(PData) <- colnames(Data)

    pf.heatmap(tree=tree,Data=clr(Data),...)
    # ape::nodelabels(text = as.list(factors),node=PF$nodes[factors],bg = bg,cex=cex)
    pf.heatmap(tree=tree,Data=clr(PData),...)
    # ape::nodelabels(text = as.list(factors),node=PF$nodes[factors],bg = bg,cex=cex)




  }
}