Events

Statistical tests and statistical learning for omics data

14 - 15 September 2021 two days, Online Register here

This advanced statistics course will include feature selection in statistical tests, clustering and statistical learning methods.

Successful completion will be awarded with 1 ECTS.

Obtaining an overview of current computational systems biology approaches for omics data analysis
Understanding the principles behind data pre-processing, quality control and statistical analysis of large-scale biological datasets
Obtaining experience in higher-level omics analysis via pathway and network analyses
Learning the basics of machine learning analyses for omics sample clustering and classification

Registration is closed, as the maximum number of participants has been reached.

Basic working knowledge of R
Have a computer ready with a recent version of R (4.0 or later) and RStudio (1.2 or later) installed. Please have your computer set-up well before the start of the course.

Time	Topic
9.15	Coffee & virtual get together
9.45	Lecture
	Welcome & introduction
	Data pre-processing, filtering & quality control
	Feature selection and hypothesis tests
	Statistical meta-analysis of omics data
12.30	Lunch break
13.30	Practical tutorial
	Introduction to the example datasets used for the project
	Software installations on student laptops, retrieving public biomedical datasets
	Hands-on data pre-processing & differential abundance analysis
17.00	End

Time	Topic
9.15	Coffee & virtual get together
9.45	Lecture
	Cellular pathway & network analysis
	Unsupervised machine learning analysis (clustering)
	Supervised machine learning analysis (prediction)
12.30	Lunch break
13.30	Practical tutorial
	Hands-on pathway & network analysis
	Hands-on machine learning analyses
	Conclusion & final discussion
17.00	End

Enrico Glaab with Veronica Codoni.

The course will be held online. Access will be available for registered participants only.