plot.mnem: Plot mnem result.

Description Usage Arguments Value Author(s) Examples

View source: R/mnems.r

Description

Plot mnem result.

Usage

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## 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

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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.