plot.mnem {mnem} | R Documentation |
Plot mnem result.
## 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, ...)
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 |
visualization of mnem result with Rgraphviz
Martin Pirkl
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)