Differential Gene Expression analysis with R (microarray and NGS data)

This hands-on workshop will introduce users of the R software environment to the specific skills and applications used in the analysis of microarray and next-generation sequencing (NGS) data.

Practical exercises will include quality control and normalisation of data for differential gene expression, and linking genomic information to external public datasets.

Learning Objectives

  • Import Affymetrix CEL files to R as data objects
  • Carry out standard QC tests on microarray and RNA-Seq datasets
  • Use the limma-voom R package to produce lists of differentially expressed genes between pairs of samples
  • Identify over-represented gene ontology categories in gene lists using the GOStats package


  • Pre-processing and quality control of microarray and RNA-Seq data
  • The use of R packages for the identification of differentially-expressed genes from expression data
  • Systems biology interpretation of gene lists using pathway analysis
  • Integration of expression and genome data with Ensembl databases

For more information contact training@qfab.org