MATH-474 / 5 credits

Teacher:

Language: English

Remark: Cours donné en alternance tous les deux ans (pas donné en 2021-22)


Summary

After a short introduction to basic molecular biology and genomic technologies, this course covers the most useful statistical concepts and methods for the analysis of genomic data.

Content

Keywords

statistics; statistical methods; data analysis; DNA; RNA; mRNA; genomics; genomic data; microarray; sequencing data; NGS; NGS technologies; machine learning; R statistical software; BioConductor

Learning Prerequisites

Important concepts to start the course

Elementary statistics

Previous experience with R is helpful (but not necessary)

 

Learning Outcomes

By the end of the course, the student must be able to:

  • Apply appropriate methods to analyze genomic data
  • Carry out targeted analyses of genomic data
  • Design genomic experiments

Transversal skills

  • Access and evaluate appropriate sources of information.
  • Write a scientific or technical report.

Teaching methods

Lectures and computer practical exercises

Expected student activities

Regular attendance in class, practical exercises, prepare a short report (max. 10 pages) on an analysis of genomic data using tools and methods from the course

Assessment methods

Evaluation is based on a written report of a genomic data analysis project.

Dans le cas de l’art. 3 al. 5 du Règlement de section, l’enseignant décide de la forme de l’examen qu’il communique aux étudiants concernés.

In the programs

  • Semester: Spring
  • Exam form: During the semester (summer session)
  • Subject examined: Statistics for genomic data analysis
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Semester: Spring
  • Exam form: During the semester (summer session)
  • Subject examined: Statistics for genomic data analysis
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Semester: Spring
  • Exam form: During the semester (summer session)
  • Subject examined: Statistics for genomic data analysis
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks

Reference week

 MoTuWeThFr
8-9     
9-10     
10-11     
11-12     
12-13     
13-14     
14-15     
15-16     
16-17     
17-18     
18-19     
19-20     
20-21     
21-22