Interrogating spatial transcriptomics: hands-on spatial domain, neighborhood & density analysis with DOMINO, hooscanR and scider
Abstract
Spatial transcriptomics (ST) data offer molecule position with quantitative gene expression in situ. Downstream analysis of ST data can be tailored to answer different biological questions, from identifying spatial domains, detecting spatial neighborhoods at single-cell level to quantifying cell-type-specific density landscapes. In this workshop, we introduce three complementary Python and R/Bioconductor tools to tackle these questions. Through a guided workflow, participants will learn how to preprocess ST data, including performing quality control, data normalization and cell type annotation, configure parameters for each method, visualise results and interpret outputs in biological contexts such as tumor domains detection, cell neighborhood heterogeneity comparison and tumor density characterization. By the end of the workshop, attendees will be equipped to integrate these methods into their own projects, allowing for reproducible, data-driven insights about complex tissue architectures.
Organiser(s)
- Dr. Ning Liu (contact person)
- Dr. Nora Liu
- Miss. Monika Mohenska
- Prof. Jose Polo
Schedule
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Date: Friday, 28 November 2025
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Time: 1:30 PM - 3:00 PM (AEDT)