RNA-Seq analysis using R
This hands-on workshop will introduce users of the R software environment to the specific skills and applications used in the analysis of RNA-Seq gene expression data.
Practical exercises will include quality control and normalisation of data for differential gene expression, and linking genomic information to external public datasets.
Biologists and bioinformaticians wishing to use R for RNA expression analysis. Prior expertise with R and the command line interface is required, to a level equivalent of that provided by the QFAB workshop “Introduction to R”.
- Reading and Parsing FastQ files
- Carry out standard QC tests on RNA-Seq datasets
- Use the limma-voom R package to produce lists of differentially expressed genes
- Use of Biomart to annotation of transcripts
- Use of GoStats to perform enrichment analysis
- Pre-processing and quality control of RNA-Seq data
- Mapping and quantification of read data
- Identification of differentially-expressed genes
- Annotation of transcripts
- Systems biology interpretation of gene lists using pathway enrichment analysis