code that uses ggplot and some cell-level summaries on XenSPEP/XenSCE

ggplot_seg.R

library(plotly)
library(ggplot2)
library(XenSCE)
if (!exists("gbm")) load("gbm.rda")

print.xen_ggprep = function(x, ...) {
  cat(sprintf("xen_ggprep instance for %d cells with %d cell boundary vertices.\n", ncol(x$sampd), nrow(x$bounds)))
}

ggprep_seg = function(xsce, xlim=c(5800,6200), ylim=c(6300, 6700), show_tx=TRUE) {
  bounds = getCellBoundaries(xsce)
  bounds = bounds[bounds$vertex_x > xlim[1] &
      bounds$vertex_x < xlim[2] & bounds$vertex_y > ylim[1] & bounds$vertex_y < ylim[2],]
  c4 <- as.data.frame(bounds)
  #ggplot(c4, aes(x=vertex_x, y=vertex_y, group=cell_id)) + geom_path() -> pas
  tx = getTranscripts(xsce)
#  tx[which(as.character(tx$cell_id) %in% unique(c4$cell_id)),] -> myt
  myt = tx[tx$x_location > xlim[1] & tx$x_location < xlim[2] &
                  tx$y_location > ylim[1] & tx$y_location < ylim[2], ]
  sampd = as.data.frame(SummarizedExperiment::colData(xsce[, unique(c4$cell_id)]))
  sizq = cut(sampd$cell_area, c(0, quantile(sampd$cell_area, c(.2,.4,.6,.8)), max(sampd$cell_area)+.01))
  sampd$sizq = sizq
  bounds = dplyr::left_join(c4, sampd, by="cell_id")
  ans = list(bounds=bounds, txdata=myt)
  class(ans) = c("xen_ggprep", "list")
  ans
#  ggplot(c4, aes(x=vertex_x, y=vertex_y, group=cell_id)) + 
#     geom_path() + 
#     geom_point(data=myt, aes(x=x_location, y=y_location, 
#            text=as.character(feature_name)), size=.05, colour="grey", alpha=.2) 
}


ss = ggprep_seg(gbm)

plot.xen_ggprep = function(x, y, ...) {
  ggplot(x$bounds, aes(x=vertex_x, y=vertex_y, group=cell_id, colour=sizq, fill=sizq)) +
      geom_polygon() + geom_path(colour="black")
}