simData {mnem} | R Documentation |
This function simulates single cell data from a random mixture of networks.
simData( Sgenes = 5, Egenes = 1, Nems = 2, reps = NULL, mw = NULL, evolution = FALSE, nCells = 1000, uninform = 0, unitheta = FALSE, edgeprob = c(0, 1), multi = FALSE, subsample = 1, scalefree = FALSE, badCells = 0, exactProb = TRUE, ... )
Sgenes |
number of Sgenes |
Egenes |
number of Egenes |
Nems |
number of components |
reps |
number of replicates, if set (not realistic for cells) |
mw |
mixture weights (has to be vector of length Nems) |
evolution |
evolving and not purely random network, if set to TRUE |
nCells |
number of cells |
uninform |
number of uninformative Egenes |
unitheta |
uniform theta, if TRUE |
edgeprob |
edge probability, value between 0 and 1 for sparse or dense networks or a range c(l,u) with lower and upper bound |
multi |
a vector with the percentages of cell with multiple perturbations, e.g. c(0.2,0.1,0) for 20 no quadruple knock-downs |
subsample |
range to subsample data. 1 means the full simulated data is used |
scalefree |
if TRUE, graph is scale free |
badCells |
number of cells, which are just noise and not connected to the ground truth network |
exactProb |
logical; if TRUE generates random network with exact fraction of edges provided by edgeprob |
... |
additional parameters for the scale free network sampler (see 'nem' package) |
simulation object with meta information and data
Nem |
list of adjacency matrixes generatign the data |
theta |
E-gene attachaments |
data |
data matrix |
index |
index for which Nem generated which cell (data column) |
mw |
vector of input mixture weights |
Martin Pirkl
sim <- simData(Sgenes = 3, Egenes = 2, Nems = 2, mw = c(0.4,0.6))