Spatial transcriptomics has revolutionized biomedical research by preserving crucial spatial context within high-throughput molecular profiles. However, translating subcellular resolution and panoramic spatial datasets into reproducible workflows and high-impact biological insights presents distinct computational bottlenecks—from precision cell boundary segmentation and multi-tool benchmark selection to complex microenvironment modeling.
To systematically address these hurdles, STOmics introduced the Stereo Data Analysis Solution(SDAS) Webinar Series delivers an end-to-end bioinformatics roadmap tailored for spatial omics, especially Stereo-seq data. Across 8 dedicated modules (6 live interactive sessions and 2 self-paced benchmarks), this series guides researchers through every critical stage of the analytical journey: upstream cell segmentation and mask integration, rigorous cell type annotation and co-expression benchmarking, dynamic cascade profiling (DEGs, pseudotime trajectory, and cell-cell communication), and high-order spatial tissue architecture characterization. The series culminates in translational multi-omics workflows decoding the tumor immune microenvironment (TIME) and deciphering complex neural architecture in neuroscience. Featuring algorithmic deep-dives, benchmark comparisons, and SDAS workflow demonstrations on benchmark public datasets, this series serves as an essential resource for researchers seeking to master advanced spatial transcriptomics.
Join the Ongoing Webinar Series!
The SDAS Advanced Analysis Webinar Series is currently underway. Register now to secure your spot for the upcoming live interactive sessions and access comprehensive spatial omics workflows.
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Agenda
| Topic | Abstract | Webinar / Blog |
FOUNDATION | Session 01 Getting Started with SDAS: Advanced Analysis for Stereo-seq Data | An architectural tour of the SDAS framework tailored for Stereo-seq data. This session unpacks how SDAS streamlines end-to-end spatial data processing, covering data input/output formats, case‑driven interpretive figure generation, and workflow execution across its 14 analytical modules. |  Webinar: Live: Sep 22
 Blog
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Session 02 Cell Segmentation Strategies for Stereo-seq: Models, Evaluation, and Multimodal Solutions | Precise segmentation is vital for spatial transcriptomics. This session benchmarks cutting-edge morphological (DAPI/membrane) and transcript-density segmentation algorithms on nanoscale Stereo-seq data, providing practical guidance on importing external masks and matrices into SDAS for downstream quality control. | Webinar: Live: Oct 13 |
SELF-PACED LEARNING | On-Demand Cell Annotation Methods: Benchmarking & Best Practices | Accurately resolving cell identities in high-resolution spatial data requires robust deconvolution and mapping strategies. This session evaluates popular algorithms (e.g., Cell2location, Seurat, RCTD) on Stereo-seq benchmarks, establishing best-practice guidelines for computational efficiency and annotation accuracy. |  Webinar
Blog |
On-Demand Co-expression Analysis: Benchmarking & Interpretation | Moving beyond single-marker analyses, spatial gene co-expression captures co-regulated gene modules embedded within complex tissue contexts. This session reviews spatial autocorrelation metrics, module clustering methods to separate biological signal from noise, and biological interpretation of spatial modules. |  Webinar
Blog |
ADVANCED ANALYSIS | Session 03 Cellular Dynamic Profiling: DEGs, Trajectories, and Spatial Crosstalk | Four core SDAS modules form an analytical cascade: identifying DEGs across spatial regions, interpreting pathway enrichment, tracing dynamic cell-state differentiation, and decoding intercellular signaling networks in situ. | Webinar: Live: Oct 20 |
Session 04 Spatial Architecture Profiling: Domains, Distances, and Neighborhoods | Tissues function through ordered multicellular microenvironments. This session demonstrates how to leverage spatial coordinates to uncover tissue niches, measure inter‑cell‑type spatial distances, identify spatial domains, and infer copy number variations (inferCNV) directly from spatial data. | Webinar: Live: Nov 03 |
APPLICATIONS | Session 05 Decoding the Tumor Immune Microenvironment: Insights from Single-Cell and Spatial Multi-Omics | The tumor immune microenvironment (TIME) governs tumor progression, metastasis, and immunotherapeutic response. This session presents practical spatial multi-omics workflows for dissecting tumor heterogeneity, mapping immune infiltration patterns, and resolving spatial structures like Tertiary Lymphoid Structures (TLS). | Webinar: Live: Nov 17 |
Session 06 Analytical Strategies for Brain Stereo-seq Data: Unraveling Architecture, Development, and Disease | Deciphering the brain's complex spatial architecture demands nanoscale resolution over panoramic tissue fields. This session highlights bioinformatics workflows tailored for Stereo-seq data in neuroscience, reviewing atlas mapping, developmental lineage modeling, and neuropathological profiling. | Webinar: Live: Dec 01 |
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