Topic outline

  • Statistical methods for big data in life sciences and health with R

    Lausanne, 4-7 June 2018

    University of Lausanne, room 2020 - Génopode  & room 321 - Amphipôle

    This page is addressed to registered participants. To access course description and application form, please click here.

    For any assistance, please contact training@sib.swiss.


  • Schedule

    Subject to changes

    Day 1.

    • Overview: big data case studies in health domain
    • Identify the general challenges behind big data analysis (model and overfitting)
    • Big data visualisation

    Day 2. Linear models

    Day 3.

    • Big data exploration and classifications
    • Machine learning and decisional algorithms – unsupervised learning

    Day 4. Introduction to: Decision Tree, Random forest, Neural Networks, Deep learning

    • Installation prior to course

      You are required to bring your own laptop, with a working Wifi connection, and the latest versions of R and RStudio installed.


      From the following URL, download the file ZIP file, unzip it, you should end up with a XPT file.

      If not yet done, please also install the following packages by executing in R studio the following commands:

      install.packages("epitools)
      install.packages("taRifx")
      install.packages("data.table")
      install.packages("reshape")
      install.packages("dplyr")
      install.packages("plyr")
      install.packages("utils")
      install.packages("microbenchmark")
      install.packages("RevoScaleR")


      install.packages("rpart")
      install.packages("rpart.plot")
      install.packages("randomForest")
      install.packages("ggplot2")

      install.packages("devtools")
      devtools::install_github("rstudio/keras")
      library(keras)
      install_keras()
      install.packages("ggfortify”)