
Simulate a complete time course of metabolic labeling - nucleotide conversion RNA-seq data.
Source:R/readsimulator.R
SimulateTimeCourseNonConstant.Rd
This function takes a vector of true synthesis rates and RNA half-lives, and then simulates data for multiple time points and replicates. Both synthesis rate and RNA half-lives are assumed to be constant, but the system might not be in steady-state.
Usage
SimulateTimeCourseNonConstant(
condition,
gene.info,
s,
d,
dispersion,
num.reads = 1e+07,
t = 2,
replicates = 3,
beta.approx = FALSE,
conversion.reads = FALSE,
verbose = TRUE,
seed = NULL,
...
)
Arguments
- condition
A user-defined condition name (which is placed into the
Coldata
of the final grandR object)- gene.info
either a data frame containing gene annotation or a vector of gene names
- s
a vector of synthesis rates (see details)
- d
a vector of degradation rates (see details)
- dispersion
a vector of dispersion parameters (estimate from data using DESeq2, e.g. by the estimate.dispersion utility function)
- num.reads
a vector representing the number of reads for each sample
- t
a single number denoting the time
- replicates
a single number denoting the number of replicates
- beta.approx
should the beta approximation of the NTR posterior be computed?
- conversion.reads
also output the number of reads with conversion
- verbose
Print status updates
- seed
seed value for the random number generator (set to make it deterministic!)
- ...
provided to
SimulateReadsForSample
Value
a grandR object containing the simulated data in its data slots and the true parameters in the gene annotation table
Details
Both rates can be either (i) a single number (constant rate), (ii) a data frame with names "offset", "factor" and "exponent" (for linear functions, see ComputeNonConstantParam; only one row allowed) or (iii) a unary function time->rate. Functions