Simulate Omics-Scale Data with Dependency

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) .


Reference manual

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install.packages("dependentsimr")

1.0.0.0 by Thomas Brooks, a year ago


Browse source code at https://github.com/cran/dependentsimr


Authors: Thomas Brooks [aut, cre, cph] (ORCID:


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports rlang

Suggests DESeq2, S4Vectors, SummarizedExperiment, MASS, corpcor, testthat, Matrix, sparsesvd, knitr, rmarkdown, BiocManager, remotes, tidyverse


See at CRAN