https://tgbrooks.r-universe.devRecent package updates in tgbrooksR-universehttps://github.com/tgbrooks.pnghttps://tgbrooks.r-universe.devMon, 06 Oct 2025 18:06:45 GMTtgbrooks@gmail.com (Thomas Brooks)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>.https://github.com/r-universe/tgbrooks/actions/runs/28644698353Mon, 06 Oct 2025 18:06:45 GMTdependentsimr1.0.0.0successhttps://tgbrooks.r-universe.devhttps://github.com/tgbrooks/dependentsimrsimulate_data.Rmdsimulate_data.htmlSimulating data with dependentsimr2025-01-28 14:31:132025-07-11 17:25:47