results_heatmap: Make a heatmap of sparse biclustering results
In jreisner/sparseBiclustering: Biclustering with Missing Data

Make a heatmap of sparse biclustering results

results_heatmap(
  x,
  reorder = FALSE,
  transform_colors = FALSE,
  c = 1/6,
  cell_alpha = 1/5,
  col_clusts = NULL,
  row_clusts = NULL,
  ...
)

`x`	A `biclustermd` object.
`reorder`	A logical. If TRUE, heatmap will be sorted according to the cell-average matrix, `A`.
`transform_colors`	If equals `TRUE` then the data is scaled by `c` and run through a standard normal cdf before plotting. If `FALSE` (default), raw data values are used in the heat map.
`c`	Value to scale the data by before running it through a standard normal CDF. Default is 1/6.
`cell_alpha`	A scalar defining the transparency of shading over a cell and by default this equals 1/5. The color corresponds to the cell mean.
`col_clusts`	A vector of column cluster indices to display. If NULL (default), all are displayed.
`row_clusts`	A vector of row cluster indices to display. If NULL (default), all are displayed.
`...`	Arguments to be passed to `geom_vline()` and `geom_hline()`.