Introduction to Affymetrix microarray analysis

Trainer Janick Mathys
BITS Courses TRAINING AT VIB

Goal

This training is an introduction to a series of trainings on the analysis of microarray data. It is intended for newbies to the field and will teach them all background knowledge required to successfully complete the advanced microarray analysis trainings. Since almost all microarray data in the VIB are generated using Affymetrix chips, we will focus on this platform during the training.

Topics handled in the training:

  • Principle of microarrays, the Affymetrix platform: sample preparation, chip design, quantitation
  • Microarray data: public repositories, data formats (CEL and CDF), identifiers
  • Quality control of microarray data using quality measures and plots (images, box plots, histograms, MA plots)
  • Normalization of microarray data: comparison of different algorithms, plots to check the results of the normalization
  • Applications: identification of differentially expressed genes, clustering, feature extraction

Summary

Following this training is a prerequisite to the training on the analysis of Affymetrix microarray data using free Affymetrix software. If you want to follow this training, you have to follow this introduction first.

If you want to follow the Genevestigator training or the training on the analysis of public microarray data sets and you have no experience with microarrays, you can also follow this introduction or consult the training material of this introduction.

Prerequisites

None

Schedule

See the TRAINING AT VIB website for a detailed schedule of this training.

Training material

Slides by Janick Mathys

Extra slides: overview and comparison of an elaborate list of normalization algorithms

Extra slides: detailed description of methodology used by Limma to find DE genes

R/Bioconductor code for analysis of microarrays

  • Tutorial - Getting started: installation of required R packages
  • Tutorial - Comparison of 2 groups of samples
  • R-code used in the Tutorial - Comparison of 2 groups of samples
  • R-code solutions of exercises in the Tutorial - Comparison of 2 groups of samples
  • Tutorial - Comparison of 3 groups of samples (+ extras: PCA and hierarchical clustering)
  • R-code used in the Tutorial - Comparison of 3 groups of samples
  • R-code solutions of exercises in the Tutorial - Comparison of 3 groups of samples

Links

None

Scientific topics Microarray data rendering, Gene expression
Target audience Life Science Researchers, PhD students, post-docs