Statistical tests and statistical learning for omics data
This advanced statistics course will include feature selection in statistical tests, clustering and statistical learning methods.
Successful completion will be awarded with 1 ECTS.
Learning objectives:
- 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
Requirements
- 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.
Tuesday (29.11.2022)
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 |
Wednesday (30.11.2022)
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 |
Instructors
Enrico Glaab with Armin Rauschenberger and Veronica Codoni
Registration
Registration is closed.
Adress
The workshop will be held at Roudeneck building (BTL) on 4th floor, meeting room E04.020.
University of Luxembourg, Belval campus
1, Boulevard du Jazz
Esch-sur-Alzette