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Introduction to Spatial Transcriptomics Data Analysis

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Spatial transcriptomics in action: a case study from human reproductive development

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In this webinar, we will present a study published in December 2025, where spatial transcriptomics, single-cell RNA-seq, and chromatin accessibility data were combined to build a multi-omic, spatiotemporal atlas of the developing human reproductive tract. We will highlight how spatial methods (including in situ sequencing and Visium) were integrated with single-cell data to refine cell-type definitions, resolve tissue patterning and differentiation, and uncover developmental regulators that inform both basic biology and potential targets for reproductive health applications.  This event is part of a broader webinar series on spatial transcriptomics. For more information about the series and its webinars, please visit the following link: “Decoding spatial transcriptomics through sequences, pixels, and bioinformatics”.

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Training material of the computational part of the Course held at the CRG: [Decoding Transcriptomes: A Practical Course on RNA-seq](https://courses.crg.eu/events/decoding-transcriptomes-practical-course-rna-seq).
The material provides an introduction to the skills needed to design robust RNA-seq experiments and to apply reproducible analysis workflows following the FAIR practices. Both theoretical lectures on the state-of-the-art transcriptomics and bioinformatics and hands-on exercises are offered, so students can deepen into the topic.

# data[].attributes.target-audience[]
Biologists interested in learning about RNA-seq

# data[].attributes.prerequisites
Basic Linux skills
Basic knowledge of R is preferred

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ADER18F - Analysis of Differential Expression with RNAseq (first course in 2018)

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Analysis of Differential Expression with RNAseq (first course in 2018)

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The Gulbenkian Training Programme in Bioinformatics

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The Gulbenkian Training Programme in Bioinformatics

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ADER18S - Analysis of Differential Expression with RNAseq (Second course in 2018)

# data[].attributes.version
Analysis of Differential Expression with RNAseq (second course in 2018)

# data[].attributes.contributors[]
The Gulbenkian Training Programme in Bioinformatics

# data[].attributes.authors[]
The Gulbenkian Training Programme in Bioinformatics

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Interactive visualisation of spatial transcriptomics data

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This webinar introduces approaches for visualising spatial-transcriptomics data leveraging the SpatialData framework together with open-source software tools such as napari  and Vitessce. It will demonstrate multiple examples for each tool, including datasets from both sequencing-based and imaging-based spatial-transcriptomics technologies. The session will provide a practical overview of how to configure, customise, and interact with visualisations in napari and Vitessce, and conclude with an overview of how these visualisations can be integrated in different stages of the analysis workflow from exploratory analyses to publication.This event is part of a broader webinar series on spatial transcriptomics. For more information about the series and its webinars, please visit the following link: “Decoding spatial transcriptomics through sequences, pixels, and bioinformatics”.You can click here to access the GitHub repo containing the materials to follow and reproduce the demo in the webinar.

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In this webinar, we will outline a roadmap for using sequencing-based spatial transcriptomics (e.g. 10x Visium) to extract compositional, organisational, and functional features of tissues, enabling the study of tissue remodelling.  We will show how integrating single-cell transcriptomics with spatial data can increase the effective resolution of 10x Visium, using myocardial infarction as a case study. We will further illustrate how spatial patterns of gene expression can be translated into mechanistic hypotheses about dependencies between tissue structure and function.This event is part of a broader webinar series on spatial transcriptomics. For more information about the series and its webinars, please visit the following link: “Decoding spatial transcriptomics through sequences, pixels, and bioinformatics”.

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This crash course walks you through RNA-seq data analysis in R: From raw count matrices to functional interpretation of differentially expressed genes.

# meta.available-facets.licence[].value
Creative Commons Attribution 4.0 International

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Creative Commons Attribution Share Alike 4.0 International

# meta.available-facets.licence[].value
Creative Commons Attribution Non Commercial 4.0 International

# meta.available-facets.licence[].value
Creative Commons Attribution Non Commercial Share Alike 4.0 International

# meta.available-facets.target-audience[].value
Biologists interested in learning about RNA-seq

# meta.available-facets.authors[].value
Teaching materials at the Harvard Chan Bioinformatics Core

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UC Davis Bioinformatics Core Training Page

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NBIS - National Bioinformatics Infrastructure Sweden

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The Gulbenkian Training Programme in Bioinformatics

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Computational Biology and Bioinformatics at UCLouvain

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Institut Français de Bioinformatique (IFB)

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Laboratory of Genomics and Bioinformatics

# meta.available-facets.contributors[].value
The Gulbenkian Training Programme in Bioinformatics

# meta.available-facets.collections[].value
Single-cell Omics Community - collection of courses and materials