Watch Workshop "Spatial transcriptomics data analysis in Python" - 2.2 (cell2location) Video Tutorial


Tutorial Details & Info

Tutorial Title: Workshop "Spatial transcriptomics data analysis in Python" - 2.2 (cell2location)
Instructor / Channel: Single Cell Omics Germany
Lesson Runtime: 06:31 Minutes
Publish Date: May 25, 2022
Total Students / Views: 4,199 views

Follow step-by-step with Workshop "Spatial transcriptomics data analysis in Python" - 2.2 (cell2location) created by Single Cell Omics Germany. This full video course has a total duration of 06:31 minutes providing step-by-step visual instructions. Access this full online lesson on any desktop PC, Mac, tablet, or smartphone.

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Course Description & Lesson Notes

Official Video Description:

Speakers in this part of the workshop: Vitalii Kleshchevnikov (Wellcome Sanger Institute, UK), Johanna Klughammer (LMU, Germany) and Fabian Theis (Helmholtz Munich, Germany). The workshop was held by Giovanni Palla (Helmholtz Munich, Germany), David Fischer (Helmholtz Munich, Germany), Anna Schaar (TUM, Germany), Alma Andersson (KTH, Sweden), Vitalii Kleshchevnikov (Wellcome Sanger Institute, UK), Johanna Klughammer (LMU, Germany) and Fabian Theis (Helmholtz Munich, Germany). It covered the analysis of spatial transcriptomics data in Python, with tools like squidpy, node-centric expression models (ncem) as well as deconvolution (cell2location) and registration methods (eggplant). The workshop introduced the participants to both theoretical concepts as well as hands-on tutorials for the analysis of spatial transcriptomics data. Publicly available data was available for this purpose, but users were welcome to analyze their own data in the context of the workshop. Basic python and scanpy knowledge required. 0:00 cell2location Introduction & Tutorial (Vitalii Kleschchevnikov, Wellcome Sanger Institute, UK) 01:30:45 Keynote Lecture (Johanna Klughammer, LMU, Munich)

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🎓 Lesson Overview & Learning Outcomes:

Welcome to the step-by-step video guide for Workshop "Spatial transcriptomics data analysis in Python" - 2.2 (cell2location) taught by Single Cell Omics Germany. This tutorial provides a comprehensive walkthrough designed to take you from foundational principles to practical implementation.

💡 Key Topics Covered in This Course:

  • Core Fundamentals & Setup: Understanding the workspace, essential tools, and initial setup for Workshop "Spatial transcriptomics data analysis in Python" - 2.2 (cell2location).
  • Step-by-Step Practical Demonstration: Hands-on implementation guided by Single Cell Omics Germany with real-world examples.
  • Best Practices & Key Shortcuts: Time-saving workflows, keyboard shortcuts, and industry-standard recommendations.
  • Troubleshooting & Common Pitfalls: How to avoid common beginner errors and optimize your workflow for peak efficiency.

📋 Recommended Prerequisites & Study Notes:

No prior advanced experience is required. Follow along with the video player above on any desktop computer, tablet, or mobile device. Pause and rewind at key steps to practice along with the instructor.

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