https://ddl095.r-universe.devRecent package updates in ddl095R-universehttps://github.com/ddl095.pnghttps://ddl095.r-universe.devWed, 19 Aug 2026 04:12:16 GMTsealgod@qq.com (Shenhui Xu)GSEAlens provides an interactive exploration layer on top of standard Bioconductor RNA-seq workflows. It consumes fitted model objects from limma (MArrayLM) or DESeq2 (DESeqDataSet) as input and accepts expression matrices and sample metadata as SummarizedExperiment objects, ensuring interoperability with core Bioconductor data containers. For core computation, GSEAlens wraps clusterProfiler::GSEA() as its statistical engine (thereby inheriting the fgsea fast GSEA methodology) and draws on MSigDB gene set collections via the msigdbr package from CRAN; multi-contrast parallel computation is handled by future (future::multisession). Visualization output relies on Bioconductor graphics packages including enrichplot, ComplexHeatmap, and circlize, producing figures suitable for publication pipelines. The package also includes a built-in Shiny application for interactive exploration of enrichment results after DEG analysis, with the ability to export self-contained reproducible R scripts.https://github.com/r-universe/bioc/actions/runs/35325917248Wed, 19 Aug 2026 04:12:16 GMTGSEAlens0.99.35successhttps://bioc.r-universe.devhttps://github.com/bioc/GSEAlensGSEAlens.RmdGSEAlens.htmlGSEAlens: An Interactive Exploration Platform for Gene Set Enrichment Analysis2026-06-26 15:37:592026-08-19 04:12:16GSEAlens-preprocessing.RmdGSEAlens-preprocessing.htmlGSEAlens: Preparing Input Data from limma-voom and DESeq2 Workflows2026-06-26 15:37:592026-08-19 04:12:16GSEAlens-preprocessing-zh.RmdGSEAlens-preprocessing-zh.htmlGSEAlens：从 limma-voom 和 DESeq2 流程准备输入数据2026-06-26 15:37:592026-08-19 04:12:16GSEAlens-vignette-zh.RmdGSEAlens-vignette-zh.htmlGSEAlens：基因集富集分析的交互式探索平台2026-05-18 21:45:272026-08-19 04:12:16