• L1. Introduction to R
  • L2. Distributions and Sampling
  • L3. Tests
  • L4. Linear models
  • L5. Clustering and classification
  • L6. Advanced Topics

  • Short reference card
  • Final Task!!!
  • Tasks L1
  • Tasks L2
  • Tasks L3
  • Tasks L4
  • Tasks L5
  • Tasks L6

  • Colored Scripts in PDF
  • scripts_L1
  • scripts_L2
  • scripts_L3
  • scripts_L4
  • scripts_L5
  • scripts_L6

  • scripts_L1.r
  • scripts_L2.r
  • scripts_L3.r
  • scripts_L4.r
  • scripts_L5.r
  • scripts_L6.r
  • solutions.zip (to be updated)

  • DATA

  • Official R Webpage
  • One more R Reference Card (by T.Short)
  • Quick-R course
  • Several free books

  • Leaded by Petr NAZAROV

    Dates: 15, 16, 17 December 2014

    Time: 9:00-18:00 with 1 hour lunch break

    Place: BS 0.11, Batiment des Sciences, Campus Limpertsberg, University

    Workload: 30 hours: 3 full days + report writing

    Number of Credit Points: 1 ECTS

    Course Objective: This course is devoted to practical aspects of statistical data analysis and oriented at PhD students working with biological data. Participants will learn how to import, visualize and analyse their data using R scripting.

    Learning Outcomes: We shall start with basic R programing, see how to load and transform biological data in R. Next we shall make a short revise of basic statistical methods (descriptive statistics, tests, ANOVA) and learn how to implement this methods in R. Finally advanced topics will be touched in the last 2 sessions including gene expression (microarray and RNASeq) Finally advanced topics will be touched in the last 2 sessions: gene expression (microarray and RNASeq) data analysis, functional enrichment and survival data analysis.

    Session 1: Introduction to programming in R
    Session 2: Basic statistics (descriptive, tests about means, etc)
    Session 3: Linear models (ANOVA, regression)
    Session 4: PCA, clustering, prediction and classification
    Session 5: Expression data analysis (microarrays and RNASeq)
    Session 6: Enrichment analysis. Survival analysis.

    Participants are welcome to bring their laptops with R/Bioconductor installed. RStudio may be a useful tool for participants as well.

    Examination: Report

    Responsible Person: Petr Nazarov (petr.nazarov[at]crp-sante.lu)

    In the case of mistakes or possible copyright violations, please, contact the webmaster. Last update 2-12-2013