Differentially Expressed Heterogeneous Overdispersion Gene Test for Count Data R package DEHOGT version 0.99.0 Implements a generalized linear model approach for detecting differentially expressed genes across treatment groups in count data. The package supports both quasi-Poisson and negative binomial models to handle over-dispersion, ensuring robust identification of differential expression. It allows for the inclusion of treatment effects and gene-wise covariates, as well as normalization factors for accurate scaling across samples. Additionally, it incorporates statistical significance testing with options for p-value adjustment and log2 fold range thresholds, making it suitable for RNA-seq analysis as described in by Xu et al., (2024) <doi:10.1371/journal.pone.0300565>. Software Depends: R (>= 3.5.0) Imports: doParallel, foreach, MASS, Suggests: knitr, rmarkdown, BiocStyle Arlina Shen <ahshen24@berkeley.edu> Comprehensive R Archive Network (CRAN) Qi Xu [aut], Arlina Shen [cre] (ORCID: <https://orcid.org/0009-0008-5330-6659>), Yubai Yuan [ctb], Annie Qu [ctb] GPL-3 2024-09-13 application/tgz https://CRAN.R-project.org/package=DEHOGT doi:10.32614/CRAN.package.DEHOGT