There are two lectures and four workshops associated with this course.
This lecture is contained in the lecture 1 powerpoint slides and gives a broad overview of the RNAseq protocol with some pointers to consider in experimental design and the breadth of application of the RNAseq protocol from transcript assembly and variant calling to differential expression
This lecture is contained in the lecture 2 powerpoint slides and gives an overview of the statistics of differential gene expression analysis. There is a refresher about using statistics to judge if there is a difference between two samples, there is an introduction to the shape of RNA-seq data and an introduction to some methods used for differential gene expression analysis.
This is contained in the workshop 1 html page it covers an introduction to using Rmarkdown with RStudio. It then introduces some of the core Bioconductor data classes that are used in NGS processing, including Biostrings, GenomicRanges and GenomicAlignments. There is also an introduction to visualising genetic data with the Gvis package.
This is contained in the workshop 2 html page, it covers using AnnotationHub for retrieving annotation data. It looks at some tools for quality checking of fastq files. It then introduces the Rsubread package for aligning fastq files and assigning reads to features using the featureCounts() function.
This is contained in the workshop 3 html page, it introduces EDASeq for exploratory analysis of data via principle component analysis plots and relative log expression plots. It looks at using pvclust for clusting samples by expression profile.
This is contained in the workshop 4 html page, it introduces the STRINGdb package for examining the relationships and functional annotations of genes called significant by differential expression. It also introduces the pathview package for visualising KEGG pathways