91猫先生

Xenium 空間轉錄體分析工作坊：運用 SpatialX 探索腫瘤微環境

本 Workshop 將以 SpatialX&苍产蝉辫;分析&苍产蝉辫;Xenium 空間轉錄體資料，从资料匯入、品质检测、资料探索与视觉化开始，介绍细胞分群、细胞类型註解及&苍产蝉辫;BANKSY 空間分群等分析方法，并比较空间感知分群与传统分群的差异。进一步透过大肠直肠癌（颁搁颁）及肝转移的实际研究案例，探索肿瘤区域、基因与路径变化、细胞状态、肿瘤微环境及细胞间互动，带领大家从空间资料分析深入理解肿瘤微环境的生物学意义。

名??称： Xenium 空間轉錄體分析工作坊：運用 SpatialX 探索腫瘤微環境

时??间：&苍产蝉辫;2026年10月13日（二）上午09：30–11：30

讲??者： Hazel Pham, Product Specialist, BioTuring

演讲地点： 第一醫學大樓 十樓 會議室二
报名连结：
 

活动重点：
?Xenium 資料匯入、探索與視覺化
?细胞分群与细胞类型註解
?BANKSY 空間分群與傳統分群方法比較
?组织结构与肿瘤微环境分析
?大肠直肠癌及肝转移实际案例解析
?细胞空间分布、距离分析与细胞间互动
?Q&A 與專家交流 

主办单位： 長庚大學 贵重及共同仪器中心 基因体核酸分析平台

协办单位：&苍产蝉辫;世基生物医学股份有限公司

名额有限，额满為止
欢迎对&苍产蝉辫;Xenium 空間轉錄體、SpatialX、腫瘤微環境及空間生物學分析有兴趣的研究人员与师生踊跃报名参加！

Agenda

Event Information

Workshop Agenda — Xenium Spatial Data Analysis with SpatialX: From Clustering to Tumor Microenvironment Insights
Oct 13 | 9:30–11:30 AM | 91猫先生

Session 1 (9:30–10:15) — How to Work with Xenium Data on SpatialX

• Effortless Xenium data submission: local upload, S3, or command line, with multi-sample auto-population for large studies
• Automated QC, embedding & clustering the moment your data lands
• Visualize genes, proteins & cell types together - from whole slide to single transcript
• Annotate cell types using built-in references or your own single-cell data as a custom reference
• NEW — BANKSY spatial clustering: see spatially-aware vs. standard clustering compared side-by-side on real Xenium data
• Align your own H&E images onto Xenium morphology in a few clicks
• Advanced downstream spatial intelligence: move beyond basic clustering to map complex tissue architectures, deep-learning-driven region segmentation, precision microenvironment distance/proximity queries, and coordinate-mapped cell–cell communication (CCC)
• The Agentic AI & LLM-assisted SDK revolution: from manual programming to plain-language pipelines, use SpatialX SDK + AI Chat to automate end-to-end workflows (clustering to niches) and instantly generate trackable, publication-ready HTML reports with therapeutic annotations

Break (10:15–10:25)

Session 2 (10:25–11:10) — SpatialX for TME Analysis in Colorectal Cancer & Liver Metastasis

• Real case study: primary CRC vs. liver metastasis (published in Science, 2023)
• Detect tumor regions two ways, pathologist-style manual annotation or automated image segmentation
• Uncover the genes & pathways separating primary tumors from metastases (TNF-α, EMT, inflammation)
• Discover hidden cell states: CXCL13? CD8 T cells, SPP1? & OLFM4? cancer cells
• Profile the 100 ?m tumor microenvironment with distance query & cell–cell communication analysis
• Export publication-ready figures instantly with BioVinci

Q&A with BioTuring Experts (11:10–11:30)

Bring your Visium HD & Xenium analysis questions — leave with answers