Statistics for Bioinformatics

USJ, Nov 29, 2013

  1. Slides: microarray analysis
  2. Data tables and MeV analysis file
  3. Figures
  4. Expression matrix, selected probesets
  5. MeV analysis file

Lectures

  1. Course ASG1 2012
  2. Slides
  3. Suggested reading
  4. Links

Practicals

  1. Introduction

Settings

  1. Configuration
  2. R librairies

Statistical analysis with R

  1. Basic operations
  2. The normal distribution
  3. Sampling distributions
  4. Student conformity test

Motif occurrences

  1. Word probabilities
  2. Testing mulptile words
  3. Applying alternative distributions
  4. Fitting a distribution

Microarray data analysis

  1. Introduction
  2. Fitting
  3. Standardization
  4. Single-chip significance testing
  5. Standardizing many chips
  6. Student multi-tests
  7. Clustering with R
  8. Supervised classification
  9. Case study: Berry et al. (2010)

ASG1 - 2012

  1. Intro to Unix (slides)
  2. TD: Handling genome coordinates
  3. TD: GO statistics
  4. Affymetrix normalization (slides)
  5. TD: A quick tutorial to the R langage
  6. TD: Handling and normalizing affymetrix data with bioconductor
  7. TD: Selecting differentially expressed genes with R or TmeV
  8. Sampling distributions
  9. Multiple testing corrections
  10. Supervised classification
  11. RNA-seq Introduction
  12. RNA-seq practical session

Course material

  1. R files
  2. Datasets

Contact

Jacques van Helden
jacques.van-helden@univ-amu.fr

Aug 2002 - Oct 2008