Statistical Analyses of ¿omics Data

lstat2340  2021-2022  Louvain-la-Neuve

Statistical Analyses of ¿omics Data
4 credits
15.0 h
Q2
Language
French
Content
After reviewing the basics of molecular biology, the course presents a series of -omics methods and especially related data processing methods:
  • Molecular biology basics.
  • Revision of multivariate methods useful in -omics methods (PCA, Clustering...) and application in R + RMarkdown.
  • Transcriptomic data acquisition method (micro-arrays, q-PCR...).
  • Pretreatment and analysis of transcriptomic data (background correction, normalization,.... + hypothesis tests with multiplicity correction).
  • Use of prediction and classification models from chemometry and machine learning for the analysis of omic data (PLS, O-PLS, trees...).
  • Acquisition and processing of proteomic data. 
  • Acquisition and processing of metabolomic data (including detailed pre-processing of 1H-NMR data). 
  • Processing of metagenomic data. 
Teaching methods
The course consists of a series of activities that lead the student to actively immerse himself in the world of -omics data.  It proposes:
  • presentations by specialists active in the field,
  • mini-projects of data processing to be carried out each week,
  • interactive computer work during the course, 
  • a laboratory visit,
  • a final project on data proposed by the various participants in the course or data repositories.
The modalities foreseen will evolve according to the health situation.
Evaluation methods
In this course, students are evaluated in two ways:
  • continuous assessment including:
    • mandatory assignments to be delivered during the quarter according to a schedule set at the beginning of the quarter (40% of the final grade)
    • and a final project to be presented during the last class (40% of the final grade)
  • an open-book oral exam  (20% of the final grade)
Online resources
Moodle Site: https://moodleucl.uclouvain.be/course/view.php?id=10846
Faculty or entity


Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Sigle
Credits
Prerequisites
Aims
Master [120] in Statistics: General

Master [120] in Agricultural Bioengineering

Master [120] in Statistics: Biostatistics

Certificat d'université : Statistique et sciences des données (15/30 crédits)

Master [120] in Data Science : Statistic