Statistical tests and statistical learning for omics data

29 - 30 November 2022 two days, On-site Registration currently closed.

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)

TimeTopic
9.15Coffee & virtual get together
9.45Lecture
 Welcome & introduction
 Data pre-processing, filtering & quality control
 Feature selection and hypothesis tests
 Statistical meta-analysis of omics data
12.30Lunch break
13.30Practical 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
17.00End

Wednesday (30.11.2022)

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

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

Contact

Veronica Codoni Milena Zizovic