This workshop will comprise hands-on sessions, lectures and seminars. All times indicated in CET (Stockholm time), check your time here.

- lecture; - hands-on workshop; - open seminar; - break; - extra materials

Questions? Check the FAQs or use HackMD

Before the course

Follow the pre-course materials and data pre-processing introduction notebook.

Wednesday 08/02/2023

09.00 - 09.20 - Introduction and contextualization (Nikolay Oskolkov)

09.20 - 10.00 - Machine Learning view of Omics integration part1 (Nikolay Oskolkov)

10.00 - 10.10 - Break

10.10 - 11.00 - Machine Learning view of Omics integration part2 (Nikolay Oskolkov)

11.00 - 11.10 - Break

11.10 - 12.00 - Feature selection and supervised Omics integration (Nikolay Oskolkov)

12.00 - 13.00 - Lunch

13.00 - 14.00 - Unsupervised Omics integration (Nikolay Oskolkov)

14.00 - 14.10 - Break

14.10 - 15.00 - Hands-on: Feature selection, supervised and unsupervised Omics integration

Notebook 1: Feature selection
Notebook 2: Supervised Omics integration
Notebook 3: Unsupervised Omics integration

Thursday 09/02/2023

09.00 - 10.00 - Application of integrated network analyses in disease characterization, part 1 (Rui Benfeitas)

10.00 - 10.10 - Break

10.10 - 10.50 - Application of integrated network analyses in disease characterization, part 2 (Rui Benfeitas)

10.50 - 11.00 - Break

11.00 - 12.00 - Dimension reduction and UMAP for Omics integration (Nikolay Oskolkov)

12.00 - 13.00 - Lunch

13.00 - 13.50 - Deep Learning for Omics integration (Nikolay Oskolkov)

13.50 - 14.00 - Break

14.00 - 15.00 - Hands-on: UMAP and Deep Learning for Omics integration

Notebook 1: Data pre-processing
Notebook 2: Network construction and analysis of a transcriptomic and metabolic dataset
Notebook 3: Introduction to metabolic modeling with cobrapy
Notebook 4: UMAP for data integration
Notebook 5: Deep Learning for Omics integration
Bonus: Understanding neural networks

Friday 10/02/20213

09.00 - 09.30 - Gene set analysis and reporter features (Ashfaq Ali)

09.30 - 10.00 - Network Meta-analysis (Ashfaq Ali)

Gene set analysis and reporter features: Ashaq's lecture for today (Ashfaq Ali)

10.00 - 10.10 - Break

10.10 - 10.50 - Hands-on: GSA, reporter features and network meta-analysis (Ashfaq Ali)

10.50 - 11.00 - Break

11.00 - 11.30 - Non-negative Matrix Factorization (Sergiu Netotea)

11.30 - 12.00 - Similarity Network Fusion (Sergiu Netotea)

12.00 - 13.00 - Lunch

13.00 - 13.40 - Hands-on: SNF and NMF (Sergiu Netotea)

Notebook 1: Non-negative Matrix Factorization

Notebook 2: Similarity Network Fusion

13.40 - 13.45 - Break

13.45 - 14.40 - Invited lecture: Single cell Omics integration (Paulo Czarnewski)

14.40 - 14.45 - Break

14.45 - 15.00 - Final words and course end

Additional materials

The following content is presented as stand-alone resources and not presented during the course.

Multi-omics data management in R

Visualization with Cytoscape in R

Circos & Hive visualization in R

Additional reading materials