Github repository 18 March - 22 April 2022 Online    Schedule Start here FAQs

The aim of this workshop is to provide a brief overview of some of the approaches and applications of data integration in life sciences. We focus on the utilization of high throughput and multi dimensional biological data for characterization of health and disease states, their comparison, and mechanistic characterization. Among other techniques, we will briefly discuss the application of Machine Learning / Deep Learning, network- and pathway-based approaches including genome-scale metabolic modeling, in supervised and unsupervised omics integration. This workshop is a shorter version of our regular Omics Integration and Systems Biology workshop. 

Each seminar will follow a 3 step structure: a conceptual explanation of the main techniques, caveats in their application and example uses in research. Each session will include a ~1 hour seminar followed by a discussion about the topics that may include an overview or demo of a computational notebook, where the participants will be able to ask questions about the seminar or notebook. At the end of each day, the participants will retain the notebooks and instructions on how to reproduce the presented code in their own systems. Bonus reading and preparatory materials are given in parallel, but will not be compulsory in order to be able to conceptually follow the presentations. 

 

Calendar

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Note the time changes in CET:

• Before the lectures (optional): Start here
• 18th March (1 - 2:30 PM EST, 6 - 7:30 PM CET): Rui Benfeitas "Application of integrated network analyses in disease characterization."
• 25th March (1 - 2:30 PM EST, 6 - 7:30 PM CET): Rui Benfeitas "Genome-scale metabolic modeling for data integration and simulation."
• 1st April (1 - 2:30 PM EST, 7 - 8:30 PM CET): Nikolay Oskolkov "Machine learning view of integration and supervised integration."
• 8th April (1 - 2:30 PM EST, 7 - 8:30 PM CET): Nikolay Oskolkov "Unsupervised and Deep Learning integration."
• 22nd April (1 - 2:30 PM EST, 7 - 8:30 PM CET): Ashfaq Ali "Meta analyses, Reporter features and gene set analyses."

 

Target audience

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The workshop is aimed at biologists and clinicians with experience in frequentist statistics, but will also provide resources for computational biologists or those interested in exploring the presented techniques in greater depth. Importantly, we will discuss the conceptual rationale behind each of the techniques, but will not detail their mathematical foundations or line-by-line code explanations.

 

Learning objectives

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At the end of the workshop you will be able to: 

• Identify key methods for analysis and integration of omics data based on a given dataset;
• Understand strengths and pitfalls of key machine learning techniques in multi-omic analysis;
• Explain the strength and need for supervised integration vs unsupervised integration techniques;
• Explain the differences between various network-based approaches in integration and simulation;
• Enumerate different techniques for variable selection and identification of key disease markers;
• Describe the applicability of network approaches in meta-analyses;
• Recall potential confounding factors and sources of bias.

 

Pre-requisites

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All sessions will be recorded. Materials will be kept open source in Github and FAIR. This website will contain all slides, notebooks, bonus materials, and installation instructions, and participants will be able to ask questions on HackMD asynchronously.

Required:

• Familiarity with frequentist statistics
• Experience in generating and/or analysis of omics data (e.g. transcriptomic, metabolomic, proteomic, epigenomic)
• A computer with Zoom and internet browser

Desirable (for computational researchers aiming to reproduce the analyses):

• Experience with R or Python programming;
• Ability to install and run docker images

 

Course staff

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• Rui Benfeitas, PhD Scilifelab / National Bioinformatics Infrastructure Sweden
• Nikolay Oskolkov, PhD Scilifelab / National Bioinformatics Infrastructure Sweden
• Ashfaq Ali, PhD Scilifelab / National Bioinformatics Infrastructure Sweden
• Mihail Anton (moderator), Scilifelab / National Bioinformatics Infrastructure Sweden

 

 

Contact

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Technical and other questions: edu.omics-integration <at> nbis.se

NBIS Training: education <at> nbis.se

 

 

 

 

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