SimulateTimeCourseNonConstant {grandR} | R Documentation |
Simulate a complete time course of metabolic labeling - nucleotide conversion RNA-seq data.
Description
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 |
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 |
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
Value
a grandR object containing the simulated data in its data slots and the true parameters in the gene annotation table