Statistical Analyses of ¿omics Data

lstat2340  2020-2021  Louvain-la-Neuve

Statistical Analyses of ¿omics Data
Due to the COVID-19 crisis, the information below is subject to change, in particular that concerning the teaching mode (presential, distance or in a comodal or hybrid format).
4 credits
15.0 h
Bugli Céline; Govaerts Bernadette;
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

Due to the COVID-19 crisis, the information in this section is particularly likely to change.

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

Due to the COVID-19 crisis, the information in this section is particularly likely to change.

The evaluation is based on:
  • Small projects proposed after each course,
  • a final project and a linked oral presentation,
  • an oral exam (with open documentation).
Online resources
Moodle Site:
Faculty or entity

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