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huashu/
Yuanclaw

Name: Yuanclaw
Availability: InStock

differential-expression

kegg

gsea

mit

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YuanSeq

This repository hosts the code snapshot / repo card for YuanSeq on Hugging Face.
It is not a pretrained model checkpoint.

YuanSeq is a web-based R/Shiny platform for comprehensive bioinformatics analysis of RNA-seq and microarray data: differential expression (limma-voom / edgeR), functional enrichment (KEGG / GO / GSEA), transcription factor and pathway activity inference, and interactive visualization. Developed at Shanghai Jiao Tong University School of Pharmacy.

GitHub Repository: https://github.com/Passpoor/Yuanseq

开发者 Developer: 乔宇 Yu Qiao · 上海交通大学药学院药理学博士 | School of Pharmacy, Shanghai Jiao Tong University · PhD in Pharmacology

导师 Supervisors: 钱峰教授 Prof. Feng Qian、孙磊教授 Prof. Lei Sun

Hugging Face Repo Card

This Hugging Face repository mirrors the lightweight open-source YuanSeq project for easier discovery and sharing.

Type: code / application snapshot
Framework: R + Shiny
Scope: RNA-seq and microarray downstream analysis
Not included here: large binary assets such as local .rds resources and image assets were excluded from this Hub export

If you want the full development history and the main upstream repository, please use the GitHub repo above.

项目概述 | About

YuanSeq（源Seq）为模块化生物信息学分析平台，基于 Shiny 开发，提供从差异表达、富集分析到通路活性推断的完整流程，支持科幻主题 UI 与日夜模式切换。本项目集成 R/Bioconductor 社区开源包，饮水思源，在此致谢所有上游开发者。

功能特性 | Features

核心功能

差异表达分析: limma-voom、edgeR；支持 1v1 / nvn 比较
富集分析: KEGG（含本地/背景基因）、GO、GSEA（含 Leading Edge 与 GPSAdb 延伸提示）
通路活性推断: ULM/WMEAN/AUCell/GSVA（decoupleR），基于 KEGG 富集结果
转录因子活性: CollecTRI 网络与 decoupleR
韦恩图、火山图: 多组交集、多种差异结果格式

界面与扩展

科幻主题、玻璃拟态、响应式布局
GSEA 模块内提示可配合 GPSAdb fastGPSA 做延伸分析

安装与运行 | Install & Run

Note: the Hugging Face export may omit some local binary resources. For the complete runnable project, prefer the GitHub repository.

要求

R >= 4.0
需安装 Shiny、BiocManager 及以下依赖

1. 克隆仓库

bash

git clone https://github.com/Passpoor/Xseq0.1.git
cd Xseq0.1

2. 安装 R 包

在 R 中执行：

install.packages(c("shiny", "shinyjs", "bslib", "ggplot2", "dplyr", "DT",
  "pheatmap", "plotly", "colourpicker", "shinyWidgets", "rlang",
  "tibble", "tidyr", "ggrepel", "RColorBrewer", "VennDiagram", "grid", "gridExtra"))

if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager")
BiocManager::install(c("edgeR", "limma", "AnnotationDbi", "clusterProfiler",
  "org.Mm.eg.db", "org.Hs.eg.db", "GseaVis", "enrichplot", "decoupleR", "sva"))

# KEGG 本地富集（可选，推荐从 GitHub 安装）
remotes::install_github("Passpoor/biofree.qyKEGGtools", upgrade = "never")

3. 启动应用

shiny::runApp("app.R")

或使用项目内脚本：launch_app.R、run_app.bat / run_app.sh。

饮水思源 · 致谢 | Acknowledgments

YuanSeq 为集成平台，未重复造轮子，依赖并致谢以下 R/Bioconductor 开源包及社区。

类别	包名	用途
框架与 UI	shiny, shinyjs, bslib, DT, plotly, colourpicker, shinyWidgets	应用框架与交互界面
差异分析	edgeR, limma	RNA-seq / 芯片差异表达
注释与富集	AnnotationDbi, org.Mm.eg.db, org.Hs.eg.db, clusterProfiler, enrichplot, GseaVis	基因注释、GO/KEGG/GSEA 富集与可视化
KEGG 本地	biofree.qyKEGGtools	本地 KEGG 富集（可选）
通路与 TF	decoupleR	通路活性、转录因子活性推断
可视化	ggplot2, pheatmap, ggrepel, RColorBrewer, VennDiagram, grid, gridExtra	图表与排版
数据处理	dplyr, tibble, tidyr, rlang, later	数据整理与异步

芯片分析模块另用 reshape2、sva 等。

感谢 R、Bioconductor 及上述所有包的开发者与维护者。

项目结构 | Structure

├── app.R                 # 主入口
├── config/               # 配置
├── modules/              # Shiny 模块
│   ├── ui_theme.R        # 主题与布局
│   ├── data_input.R      # 数据上传与注释
│   ├── differential_analysis.R
│   ├── kegg_enrichment.R
│   ├── gsea_analysis.R
│   ├── pathway_activity.R # 通路活性推断
│   ├── tf_activity.R
│   └── venn_diagram.R
├── workflow/             # 工作流脚本
├── tests/                # 测试
└── docs/                 # 文档

许可证 | License

MIT License. See LICENSE for details.

huashu/Yuanclaw