Conditionally Symmetric Multidimensional Gaussian Mixture Model R package csmGmm version 0.5.0 Implements the conditionally symmetric multidimensional Gaussian mixture model (csmGmm) for large-scale testing of composite null hypotheses in genetic association applications such as mediation analysis, pleiotropy analysis, and replication analysis. In such analyses, we typically have J sets of K test statistics where K is a small number (e.g. 2 or 3) and J is large (e.g. 1 million). For each one of the J sets, we want to know if we can reject all K individual nulls. Please see the vignette for a quickstart guide. The paper describing these methods is "Testing a Large Number of Composite Null Hypotheses Using Conditionally Symmetric Multidimensional Gaussian Mixtures in Genome-Wide Studies" by Sun R, McCaw Z, & Lin X (Journal of the American Statistical Association 2025, <doi:10.1080/01621459.2024.2422124>). Software Depends: R (>= 4.1.0) Imports: dplyr, mvtnorm, curl, data.table, ggplot2, rlang, magrittr, stats, utils Suggests: knitr, rmarkdown, R.utils Ryan Sun <ryansun.work@gmail.com> Comprehensive R Archive Network (CRAN) Ryan Sun [aut, cre], Emily Kim [aut] GPL-3 2026-06-16 application/tgz https://CRAN.R-project.org/package=csmGmm doi:10.32614/CRAN.package.csmGmm