About

This course provides an introduction to the rapidly evolving field of spatial omics, with a focus on spatially resolved transcriptomics (SRT) and its applications in understanding tissue organization and cellular interactions. By preserving spatial information about gene expression, SRT technologies offer new opportunities to investigate tissue complexity and uncover biological insights that cannot be captured by conventional transcriptomic approaches alone.

Participants will explore both imaging-based and sequencing-based SRT technologies and learn how to analyze spatial transcriptomics data using a range of computational approaches. The course covers key steps in the analysis workflow, including data preprocessing, quality control (QC), normalization, spatial domain identification and characterization, integration with single-cell RNA sequencing data, and the statistical analysis of spatial patterns. Participants will also learn approaches for investigating cell–cell interactions in their spatial context.

The course combines lectures with hands-on practical sessions, providing both the theoretical background and practical skills needed to develop a comprehensive SRT data analysis workflow, from raw data processing to biological interpretation.

Audience

This 3.5-day course is intended for PhD students, postdocs, and researchers who are working (or will soon be working) on projects involving spatially resolved transcriptomics data and want to acquire the skills needed to get started with spatial data analysis.

Topics covered

• Imaging-based (Xenium In Situ) and sequencing-based (Visium HD) spatial data acquisition
• Data preprocessing: segmentation, QC, filtering, normalization, cell annotation
• Cell segmentation-based and segmentation-free analyses
• SRT and single-cell data integration
• Spatial statistics; domains and niches
• Cell–cell interactions

Learning outcomes

At the end of the course, participants will be able to:

• Identify and recall key concepts and terminology related to imaging- and sequencing-based SRT technologies.
• Assess the quality of SRT data.
• Perform standard SRT data analysis, including data cleaning, normalization, and QC.
• Examine and interpret spatial patterns and relationships within SRT data using statistical and machine learning approaches.
• Construct a comprehensive workflow for SRT data analysis, from raw data to meaningful biological insights.

Prerequisites and practical information

• Participants should be proficient in Python for basic data analysis (as covered, e.g., in https://www.elixir-czech.cz/events/python-basics-05-2026).
• Participants should be familiar with next-generation sequencing (NGS) technologies and have experience analyzing (single-cell) transcriptomic data.
• Participants should also have a basic understanding of working with command-line tools on Unix-based systems.
• Participants are encouraged to bring their own laptops. Software requirements will be communicated to all participants upon registration. If needed, desktop workstations will be provided.
• Coffee breaks will be provided during the workshop, featuring small snacks, fresh fruits, coffee, tea, and soft drinks. Please note that lunches are not included in the workshop. Participants are welcome to dine at the local canteen at their own expense.

Dates

December 14–17, 2026

Venue

Jágr’s Hall, Institute of Molecular Genetics of the Czech Academy of Sciences, Vídeňská 1083, Prague 4

Maximum capacity

25 participants

Registration

The course is provided by ELIXIR Czech Republic, no participant fee is collected.

Program

Day 1 – Monday, December 14

09:00 – 09:15    Welcome coffee

09:15 – 09:30    Course introduction
09:30 – 10:15    Lecture: Overview of SRT technologies

10:15 – 10:30    Break

10:30 – 11:15    Lecture: SRT data formats and cell segmentation
11:15 – 11:30    Introduction to practicals
11:30 – 12:15    Practical 1: SRT data formats

12:15 – 13:15    Break

13:15 – 15:00    Practical 2: Cell segmentation
15:00 – 16:30    (Optional) SRT laboratory visit

Day 2 – Tuesday, December 15

09:00 – 09:15    Welcome coffee

09:15 – 10:00    Lecture: Imaging-based SRT data analysis and QC
10:00 – 10:30    Practical 3: Imaging-based SRT data analysis and QC

10:30 – 10:45    Break

10:45 – 11:30    Practical 3 continued: Imaging-based SRT data analysis and QC
11:30 – 12:15    Lecture: Segmentation-free analysis of SRT data

12:15 – 13:15    Break

13:15 – 14:45    Practical 4: Segmentation-free analysis of SRT data
14:45 – 15:30    Lecture: Sequencing-based SRT data analysis and QC

15:30 – 15:45    Break

15:45 – 17:15    Practical 5: Sequencing-based SRT data analysis and QC

Day 3 – Wednesday, December 16

09:00 – 09:15    Welcome coffee

09:15 – 10:00    Lecture: SRT and single-cell data integration
10:00 – 10:30    Practical 6: SRT and single-cell data integration

10:30 – 10:45    Break

10:45 – 11:30    Practical 6 continued: SRT and single-cell data integration
11:30 – 12:15    Lecture: Spatial statistics

12:15 – 13:15    Break and group photo

13:15 – 14:00    Lecture: Spatially aware clustering
14:00 – 16:30    Practical 7: Domain identification and niche reconstruction

Day 4 – Thursday, December 17

09:00 – 09:15    Welcome coffee

09:15 – 10:00    Lecture: Cell–cell interactions

10:00 – 10:15    Break

10:15 – 11:45    Practical 8: Cell–cell interactions
11:45 – 12:00    Course wrap-up

Instructors (in alphabetical order)

• Michal Kolář (IMG)
• Jan Kubovčiak (IMG)
• Vojtěch Melichar (IMG)
• Jiří Netušil (IMG)
• Lucie Pfeiferová (IMG)
• Zuzana Ševčovičová (IMG)

Attribution

This course is largely based on courses developed by the Swiss Institute of Bioinformatics and NBIS/SciLifeLab in collaboration with the ELIXIR Single-Cell Omics community.