Package Introduction | Integration with Bioconductor Workflows | Installation | Quick Start | GSEAlens Processing | Creating GSEA Pathway Object | Assembling Computation Object | Running Processing | Interactive Analysis and Viewing | Interactive Exploration with the Shiny Application | Launching the App | Application Layout | Sidebar -- Data Preprocessing | Tab 1 -- Main Workspace | Tab 2 -- Holographic Quadruple Linkage | Tab 3 -- Pathway Relationship Exploration | Tab 4 -- HubGene Network | Tab 5 -- AI Interpretation | Tab 6 -- Joint GSEA Canvas | Interpreting Outputs | Reproducible Code Export | Package Intermediate Object Descriptions | GseaEnv Object | GseaRes Object | GseaTask Object | Session Info | References
Package: GSEAlens 0.99.35
Shenhui Xu
GSEAlens: Gene Set Enrichment Analysis Interactive Explorer
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.
Authors:
GSEAlens_0.99.35.tar.gz
GSEAlens_0.99.35.zip(r-4.7-any)GSEAlens_0.99.35.zip(r-4.6-any)GSEAlens_0.99.35.zip(r-4.5-any)
GSEAlens_0.99.35.tgz(r-4.6-any)GSEAlens_0.99.35.tgz(r-4.5-any)
GSEAlens_0.99.35.tar.gz(r-4.7-any)GSEAlens_0.99.35.tar.gz(r-4.6-any)
GSEAlens_0.99.35.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
GSEAlens/json (API)
| # Install 'GSEAlens' in R: |
| install.packages('GSEAlens', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/ddl095/gsealens/issues
Datasets:
- gsea_pathwaysets_toy - Toy MSigDB pathway collection
- gsea_pathwaysets_toy_hallmark - Toy MSigDB pathway collection
- precomputed_gseares - Pre-computed GSEA results from the airway dataset
- preprocessed_dds - Pre-computed DESeq2 DESeqDataSet from the airway dataset
- preprocessed_dds_se - Pre-computed DESeqDataSet
- preprocessed_limma - Pre-computed limma-voom fit and DGEList from the airway dataset
On BioConductor:GSEAlens-0.99.35(bioc 3.24)
genesetenrichmentvisualizationshinyappssoftwaregsea
Last updated from:d1807abe23. Checks:1 WARNING, 9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
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| bioc-checks | WARNING | 257 | ||
| linux-devel | OK | 786 | ||
| source / vignettes | OK | 431 | ||
| linux-release | OK | 766 | ||
| macos-release | OK | 521 | ||
| macos-oldrel | OK | 452 | ||
| windows-devel | OK | 561 | ||
| windows-release | OK | 534 | ||
| windows-oldrel | OK | 560 | ||
| wasm-release | OK | 221 |
Exports:batch_calc_gseabuild_edge_list_safelybuild_gsea_pathwaysbuild_hubgene_networkcalculate_overlap_ratiocolor_by_directioncreat_addition_data_rdsfilecreate_addition_templatecreate_gsea_envcreate_gsea_rescreate_gsea_taskextract_gsea_taskextract_hub_genesgenerate_boxplot_data_codegenerate_boxplot_image_codegenerate_combined_plot_codegenerate_de_volcano_codegenerate_dotplot_codegenerate_gsea_html_reportgenerate_hubgene_codegenerate_hubgene_hover_textgenerate_joint_canvas_codegenerate_network_codegenerate_pathway_plot_codegenerate_volcano_codeget_contrast_registryget_core_genes_for_pathwayget_core_genes_listget_de_tableget_expr_matrixget_geneset_infoget_hubgene_legendget_sample_metaget_term_genesimport_gsea_capsuleinspect_gsea_envinspect_gsea_reslaunch_gsea_appplot_directional_gseaplot_gsea_memoryprepare_hubgene_nodesread_addition_datasetup_gsea_envvalidate_param
Dependencies:abindaisdkAnnotationDbiapeaplotaskpassassertthatbabelgenebase64encBHBiobaseBiocBaseUtilsBiocGenericsBiocParallelBiostringsbitbit64blobbslibcachemcallrcirclizeclicliprclueclusterclusterProfilercodetoolscolorspacecommonmarkComplexHeatmapcpp11crayoncrosstalkcurldata.tableDBIDelayedArrayDESeq2digestdoParallelDOSEdplyrDTedgeRenrichitenrichplotevaluatefarverfastmapfontawesomefontBitstreamVerafontLiberationfontquiverforeachformatRfsfutile.loggerfutile.optionsfuturefuture.applygdtoolsgenericsGenomicRangesGetoptLongggforceggfunggiraphggnewscaleggplot2ggplotifyggrepelggtangleggtreeGlobalOptionsglobalsglueGO.dbGOSemSimgridGraphicsgsongtablehighrhtmltoolshtmlwidgetshttpuvhttrhttr2igraphIRangesisobanditeratorsjquerylibjsonliteKEGGRESTknitrlabelinglambda.rlaterlatticelazyevallifecyclelimmalistenvlocfitmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemimemsigdbrnlmeopensslotelparallellypatchworkpillarpkgconfigplotlyplyrpngpolyclipprocessxprogressrpromisespspurrrqvalueR6rappdirsRColorBrewerRcppRcppArmadilloRcppEigenreshape2rjsonrlangrmarkdownRSQLiteS4ArraysS4VectorsS7sassscalesscatterpieSeqinfoshapeshinyshinycssloadersshinyjssnowsourcetoolsSparseArraystatmodstringistringrSummarizedExperimentsyssystemfontstibbletidydrtidyrtidyselecttidytreetinytextreeiotweenrutf8vctrsviridisLitevisNetworkwithrxfunxtableXVectoryamlyulab.utils
GSEAlens: An Interactive Exploration Platform for Gene Set Enrichment Analysis
Last update: 2026-08-19
Started: 2026-06-26
GSEAlens: Preparing Input Data from limma-voom and DESeq2 Workflows
Installation | Introduction | Example Data | limma-voom Workflow | DESeq2 Workflow (SummarizedExperiment Input) | DESeq2 Workflow (Count Matrix Input) | Next Step
Last update: 2026-08-19
Started: 2026-06-26
GSEAlens：从 limma-voom 和 DESeq2 流程准备输入数据
安装 | 简介 | 示例数据 | limma-voom 流程 | DESeq2 流程（SummarizedExperiment 输入） | DESeq2 流程（Count Matrix 输入） | 下一步
Last update: 2026-08-19
Started: 2026-06-26
GSEAlens：基因集富集分析的交互式探索平台
包简介 | 与 Bioconductor 工作流的整合 | 安装 | 快速开始 | GSEAlens处理 | 创建GSEA基因集对象 | 组装运算对象 | 运行处理 | 交互式分析与查看 | 使用 Shiny 应用进行交互式探索 | 启动应用 | 应用布局 | 侧边栏 -- 数据预处理 | Tab 1 -- 主工作区（Main Workspace） | Tab 2 -- 全息四象限联动（Holographic Quadruple Linkage） | Tab 3 -- 通路关系探索（Pathway Relationship Exploration） | Tab 4 -- HubGene 网络（HubGene Network） | Tab 5 -- AI 解读（AI Interpretation） | Tab 6 -- 联合 GSEA 画布（Joint GSEA Canvas） | 输出解读指南 | 可重现代码导出 | R包中间对象说明 | GseaEnv 对象 | GseaRes 对象 | GseaTask 对象 | Session info | References
Last update: 2026-08-19
Started: 2026-05-18
