R/plot_pls_varimax.R

In graeberlab-ucla/glab.library: Data Analysis Functions

#' Plot PLS
#'
#' Plots PLS from scores file (output of PLSR_from_file)
#'
#' @param file File containing scores matrix
#' @param info.name Vector of sample names
#' @param info.type Vector of sample types in the same order
#' @param title Title of the plot
#' @param labels default=T
#' @param PCx,PCy PCs to display
#' @param ellipse Construct confidence region based on groups in info.type, default = T
#' @param conf default = 0.95
#' @param fliph default = F
#' @param flipv default = F
#'
# @importFrom ggplot2 ggplot aes aes_string element_rect element_text geom_point geom_text labs margin theme theme_bw
#'
#' @export
#'
plot_pls_varimax = function(file, info.name, info.type, title = "", labels = TRUE, PCx="V1", PCy="V2", ellipse = F, conf = 0.95,
                    fliph = F, flipv = F){
  #Input: PLSR scores file to be ploted
  ##process PLS output and adds groupings
  require(ggplot2)
  require(vegan)

  table <- read.table(file, header = TRUE)
  table$type = info.type[match(table$Score, info.name)]

  if (fliph == T) {
    table[, PCx] = table[, PCx] * -1
  }
  if (flipv == T) {
    table[, PCy] = table[, PCy] * -1
  }

  ###exp_var = read.delim(paste0(gsub("scores.txt","",file),"pve.txt"), row.names = 1)
  ###exp_var$pve =  unlist(round(exp_var[,1] * 100, digits = 2))
  ###rownames(exp_var) = paste0("comp",seq(1,nrow(exp_var)))


  pcx.y <- ggplot(table, aes_string(x=PCx,y=PCy)) +geom_point(size = I(3), aes(color = factor(type))) +
    theme(legend.position="right",plot.title=element_text(size=30),legend.text=element_text(size=22),
          legend.title=element_text(size=20),axis.title=element_text(size=30),legend.background = element_rect(),
          axis.text.x = element_text(margin = margin(b=-2)),axis.text.y = element_text(margin = margin(l=-14)))+
    guides(color=guide_legend(title="Type"))+
    labs(title = title,
         #x = paste0(PCx," (", exp_var$pve[match(PCx, rownames(exp_var))], "%)"),
         #y = paste0(PCy," (", exp_var$pve[match(PCy, rownames(exp_var))], "%)"))+

         x = PCx,
         y = PCy)+
  
    theme_bw(base_size=18)+
    if(labels==TRUE){geom_text(data = table, mapping = aes(label = Score), check_overlap = TRUE, size = 3)}


  if(ellipse==TRUE){
    plot(table[,c(PCx, PCy)], main=title)
    ord = ordiellipse(table[,c(PCx, PCy)],table$type, kind = "sd", conf = conf)

    cov_ellipse<-function (cov, center = c(0, 0), scale = 1, npoints = 100)
    {
      theta <- (0:npoints) * 2 * pi/npoints
      Circle <- cbind(cos(theta), sin(theta))
      t(center + scale * t(Circle %*% chol(cov)))
    }

    df_ell <- data.frame(matrix(ncol = 0, nrow = 0))
    for(g in (droplevels(table$type))){
      df_ell <- rbind(df_ell, cbind(as.data.frame(with(table[table$type==g,],
                                                       cov_ellipse(ord[[g]]$cov,ord[[g]]$center,ord[[g]]$scale)))
                                    ,type=g))
    }

    pcx.y2 = pcx.y + geom_path(data=df_ell, aes(x=df_ell[,PCx], y=df_ell[,PCy], colour = type), size=1, linetype=1)
    pcx.y2
  } else{
    pcx.y
  }

}