Simulate Omics-Scale Data with Dependency
Draw random samples from the given random structure
Compute structure of dependency from a given data
Compute what spiked SD values will give you the desired top eigenvalue...
Compute means of each singular value and the mean Jacobian, see sample...
Remove all dependence in a random structure
Efficiently sample the singular values corresponding to a random Wisha...
Efficiently sample the singular values corresponding to a random Wisha...
Using a Gaussian copula approach, this package generates simulated data mimicking a target real dataset. It supports normal, Poisson, empirical, and 'DESeq2' (negative binomial with size factors) marginal distributions. It uses an low-rank plus diagonal covariance matrix to efficiently generate omics-scale data. Methods are described in: Yang, Grant, and Brooks (2025) <doi:10.1101/2025.01.31.634335>.