Schedule - Omics integration and systems biology - 2024

Before the course

Prepare Pre-course materials. In order to be able to access the lab notebooks for this course you need to have access to SciLifeLab Serve. For lunching practicals please follow the instructions here.

Course schedule

- lecture

- hands-on workshop

- invited seminar

- break

Day 1

09.00 - 09.15 Introduction and contextualization (Rasool)

Resources

• Slides

09.15 - 09.55 Machine Learning view of Omics integration (Nikolay)

Resources

• Slides

09.55 - 10.05 Break

10.05 - 10.55 Feature Selection and Supervised Omics integration (Nikolay)

Resources

• Slides

10.55 - 11.00 Break

11.00 - 12.00 Feature Selection and Supervised Omics integration (Nikolay)

Resources

• Launch Lab feature selection on Scilifelab Serve, use Rstudio app.
• Feature Selection lab Notebook
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_ml_feature_selection_amd_v.h24.9879876


• Launch Lab supervised omics integration on Scilifelab Serve, use Rstudio app.
• Supervised Integration lab Notebook
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_ml_supervised_omics_integration_amd_v.h24.38310b0

12.00 - 13.00 Lunch

13.00 - 13.10 Lab recap (Nikolay)

13.10 - 14.00 Unsupervised Omics integration (Nikolay)

Resources

• Slides

14.00 - 14.05 Break

14.05 - 15.20 Unsupervised Omics integration (Nikolay)

Resources

• Launch Lab unsupervised omics integration on Scilifelab Serve, use Rstudio app.
• Unsupervised Integration lab Notebook
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_ml_unsupervised_omics_integration_amd_v.h24.6d635ce

15.20 - 15.30 Lab recap (Nikolay)

15.30 - 17.00 Assisted exercises

🌟 18:00 Course Dinner at Valvet Steakhouse 🌟

Day 2

09.00 - 09.20 Review (Nikolay)

09.20 - 09.50 Single Cell Omics integration (Nikolay)

Resources

• Slides

09.50 - 10.00 Break

10.00 - 11.00 Daniel Muthas - “Deriving actionable insight from omics data – an industry perspective”

11.00 - 11.15 Break

11.15 - 12.00 Single cell omics integration (Nikolay)

Resources

• Launch Lab single cell on Scilifelab Serve, use Rstudio app.
• Single cell omics integration lab notebook
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_ml_single_cell_amd_v.h24.7054451


• Launch Lab UMAP on Scilifelab Serve, use Jupyter app.
• UMAP lab notebook
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_ml_umap_data_integration_amd_v.h24.6d635ce

12.00 - 13.00 Lunch

13.00 - 13.45 Single cell omics integration (Nikolay)

Resources

• Launch Lab single cell on Scilifelab Serve, use Rstudio app.
• Single cell omics integration lab notebook
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_ml_single_cell_amd_v.h24.7054451


• Launch Lab UMAP on Scilifelab Serve, use Jupyter app.
• UMAP lab notebook
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_ml_umap_data_integration_amd_v.h24.6d635ce

13.45 - 13.55 Lab recap (Nikolay)

13.55 - 14.05 Break

14.05 - 14.45 Deep Learning for Omics integration (Nikolay)

Resources

• Slides

14.45 - 15.00 Break

15.00 - 16.15 Deep Learning for Omics integration (Nikolay)

Resources

• Launch Lab deep learning integration on Scilifelab Serve, use Jupyter app.
• Deep Learning for data integration lab html
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_ml_deep_learning_integration_amd_v.h24.6d635ce

16.15 - 16.30 Lab recap (Nikolay)

16.30 - 17.00 Assisted exercises

Day 3

09.00 - 10.00 Introduction to biological network analysis (Sergiu)

Resources

• Introduction
• Network inference
• Community analysis

10.00 - 10.15 Break

10.15 - 11.00 Introduction to biological network analysis (Sergiu)

Resources

• Launch Lab topology on Scilifelab Serve, use Jupyter app.
• Topology lab Notebook part 1
• Topology lab Notebook part 2
• Topology lab Notebook part 3
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_topology_amd_v.h24.a2b336c

11.00 - 11.30 Review (Sergiu)

12.00 - 13.00 Lunch

13.00 - 14.00 Introduction to biological network analysis (continued) (Sergiu)

Resources

• Launch Lab topology on Scilifelab Serve, use Jupyter app.
• Topology lab Notebook part 1
• Topology lab Notebook part 2
• Topology lab Notebook part 3
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_topology_amd_v.h24.a2b336c

14.00 - 14.15 Break

14.15 - 16.15 Machine learning on Graphs (Sergiu)

Resources

• Graph neural networks (html)
• Graph neural networks (notebook file)
• Graph neural networks lab (html)
• Graph neural networks lab (notebook file)

16.15 - 16.30 Lab recap (Sergiu)

Resources

• Data engineering tutorial

16.30 - 17.00 Assisted exercises

Day 4

09.00 - 10.00 Genome-scale metabolic models for integration (Rasool)

Resources

• Introduction – Constraint-based modeling concepts

10.00 - 10.15 Break

10.15 - 11.30 Genome-scale metabolic models for integration (Rasool)

Resources

• Launch Lab GEMs on Scilifelab Serve, use Jupyter app.
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_gems_amd_v.h24.a2b336c

11.30 - 11.45 Lab recap (Rasool)

12.00 - 13.00 Lunch

13.00 - 14.00 Johan Gustafsson - “Generation of context-specific genome-scale metabolic models using single-cell RNA-Seq data”

14.00 - 14.15 Break

14.15 - 14.45 Non-negative matrix factorization (Sergiu)

Resources

• Non-negative Matrix Factorization

14.45 - 15.15 Non-negative matrix factorization (Sergiu)

Resources

• Launch Lab NMF & SNF on Scilifelab Serve, use Jupyter app.
• NMF lab Notebook
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_nmf_amd_v.h24.1b36f11

15.15 - 15.30 Break

15.30 - 16.00 Similarity network fusion (Sergiu)

Resources

• Similarity network fusion

16.00 - 16.30 Similarity network fusion (Sergiu)

Resources

• Launch Lab NMF & SNF on Scilifelab Serve, use Jupyter app.
• SNF lab Notebook
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_nmf_amd_v.h24.1b36f11

16.30 - 16.45 Lab recap (Sergiu)

Day 5

09.00 - 09.45 Gene set analysis and reporter features (Rasool)

Resources

• Gene set analysis via GEMs

09.55 - 10.00 Break

10.00 - 11.00 Mats Nilsson - “Targeted in situ sequencing for characterization of the genetic, molecular and cellular diversity of healthy and disease tissues”

11.00 - 11.45 Gene set analysis and reporter features (Rasool)

Resources

• Launch Lab GEM GSA on Scilifelab Serve, use Jupyter app.
• Gene set analysis lab Notebook
• Docker image: docker pull rasoolsnbis/omicsint_h24:session_gsa_amd_v.h24.a1ae0fc

11.45 - 12.00 Lab recap (Rasool)

12.00 - 13.10 Lunch

13.00 - 14.00 Discussions and course end (Rasool)

Resources

• Closing remarks!
• Course Evaluation

Teachers: - Nikolay Oskolkov - Rasool Saghaleyni - Sergiu Netotea

Teaching assistants: - Yuan Li - Jennifer Fransson - Stefan Ebmeyer

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