Simulation of generalized dynamical system model.
SimulateDynamics.Rd
SimulateDynamics()
simulates any specified dynamical system of interconverting
RNA species. Its required input is similar to that of EstimateDynamics()
, i.e.,
an adjacency matrix describing the set of species and how they are related to
one another and a list of formula relating actually assayed species to the
modeled species. Currently, SimulateDynamics()
implements a naive heteroskedastic
replicate variability simulation and is not designed to simulate multiple experimental
conditions.
Usage
SimulateDynamics(
nfeatures,
graph,
metadf,
formula_list = NULL,
log_means,
log_sds,
unassigned_name = "__no_feature",
seqdepth = nfeatures * 2500,
dispersion = 100,
lfn_sd = 0.2,
...
)
Arguments
- nfeatures
Number of "features" to simulate data for. A "feature" in this case may contain a number of "sub-features". For example, you may want to simulate pre-RNA and mature RNA for a set of "genes", in which case the number of features is the number of genes.
- graph
An adjacency matrix describing the reaction diagram graph relating the various RNA species to one another.
- metadf
Data frame with two required columns (
sample
andtl
).sample
represents names given to each simulated sample.tl
represents the label time for that sample. Additional columns can specify other features of the sample, like what subcellular compartment the sample is taken from. NOTE: Not sure I am actually using these optional columns in any useful capacity anymore.- formula_list
A list of named lists. The names of each sub-list should be the same as the sample names as they are found in
metadf
. Each sub-list should be a list of formula relating feature names that will show up as columns of the simulated cB to species modeled in yourgraph
. This only needs to be specified if you want to simulate the scenario where some of the measured species are a sum of modeled species.- log_means
Vector of log-Normal logmeans from which the distribution of feature-specific parameters will be drawn from. Length of vector should be the same as max(entries in
graph
), i.e., the number of parameters in your specified model.- log_sds
Vector of log-Normal logsds from which the distribution of feature-specific parameters will be drawn from.
- unassigned_name
String to give to reads not assigned to a given feature.
- seqdepth
Total number of reads in each sample.
- dispersion
Negative binomial
size
parameter to use for simulating read counts- lfn_sd
Logit(fn) replicate variability.
- ...
Parameters passed to
SimulateOneRep()
.