Introduction to Bioconductor
How to create a digital EPIC course
The Bioconductor project provides open-source software based on the R programming language for statistical analysis and visualization of high-throughput genomic data. This course provides a broad introduction to the project, from navigating its large collection of packages to its core functionality for representation, manipulation, and visualization of genomic data. We will learn how to efficiently analyze genomic intervals and SNPs, how to manage experiments of one or more genomic data type with clinical and pathological data, and how to visualize genomic data. This workshop equips participants with essential background for a wide range of applications in statistical genomics and genetic epidemiology, such as GWAS, RNA-seq, DNA methylation, ChIP-seq, metagenomics, and multi'omic experiments.
Part 1: Bioconductor
Find, install, and learn how to use Bioconductor packages
Import and manipulate genomic files and Bioconductor data objects
Start an RNA-seq differential expression workflow
Part 2: Data structures for representing 'omics experiments
Use the ExpressionSet data structure to represent, manipulate, and analyze microarray data
Use the SummarizedExperiment data structure to represent, manipulate, and analyze RNA-seq data
Understand similarities and differences between the two data structures
Create both data structures from public data resource
Use the MultiAssayExperiment data structure to coordinate multi'omics experiments
Part 3: GenomicRanges
Understand how to apply the *Ranges infrastructure to solve common bioinformatic challenges in genomic research
Gain insight into the design principles of the infrastructure and how it is meant to be used
Learn basics of genomic region algebra and how to carry out intra- and inter-region operations
Part 4: Visualizing genomic data
Understand basic principles of the grammar of graphics used in R/Bioconductor
Learn how to display heatmaps for genomic data exploration
Learn how to display genomic data tracks in a genome browser view
This workshop is accessible for those with little or no experience using Bioconductor, although even more experienced users can benefit from the broad overview of Bioconductor paradigms. The workshop assumes elementary knowledge of R, which can be gained in advance or simultaneously from other courses such as the introductory course from DataCamp. A basic understanding of genome biology and statistical analysis is helpful, but specific prerequisites are not needed.
R and Bioconductor: www.bioconductor.org/install
R Studio: https://www.rstudio.com/products/rstudio/download3/