plot.mnem: Plot mnem result.

In mnem: Mixture Nested Effects Models

Description

Plot mnem result.

Usage

## S3 method for class 'mnem'
plot(
  x,
  oma = c(3, 1, 1, 3),
  main = "M&NEM",
  anno = TRUE,
  cexAnno = 1,
  scale = NULL,
  global = TRUE,
  egenes = TRUE,
  sep = FALSE,
  tsne = FALSE,
  affinity = 0,
  logtype = 2,
  cells = TRUE,
  pch = ".",
  legend = FALSE,
  showdata = FALSE,
  bestCell = TRUE,
  showprobs = FALSE,
  shownull = TRUE,
  ratio = TRUE,
  method = "llr",
  showweights = TRUE,
  ...
)

Arguments

x	mnem object
oma	outer margin
main	main text
anno	annotate cells by their perturbed gene
cexAnno	text size of the cell annotations
scale	scale cells to show relative and not absolute distances
global	if TRUE clusters all cells, if FALSE clusters cells within a component
egenes	show egene attachments, i.e. number of E-genes assigned to each S-gene
sep	seperate clusters and not put them on top of each other for better visualization
tsne	if TRUE use tsne instead of pca
affinity	use hard clustering if TRUE
logtype	logarithm type of the data (e.g. 2 for log2 data or exp(1) for natural)
cells	show cell attachments, .i.e how many cells are assigned to each S-gene
pch	cell symbol
legend	show legend
showdata	show data if TRUE
bestCell	show probability of best fitting cell for each S-gene
showprobs	if TRUE, shows responsibilities for all cells and components
shownull	if TRUE, shows the null node
ratio	use log ratios (TRUE) or foldchanges (FALSE)
method	"llr" for ratios
showweights	if TRUE, shows mixture weights for all components
...	additional parameters

Value

visualization of mnem result with Rgraphviz

Author(s)

Martin Pirkl

Examples

sim <- simData(Sgenes = 3, Egenes = 2, Nems = 2, mw = c(0.4,0.6))
data <- (sim$data - 0.5)/0.5
data <- data + rnorm(length(data), 0, 1)
result <- mnem(data, k = 2, starts = 1)
plot(result)

mnem documentation built on Nov. 18, 2020, 2 a.m.