Analysis of epigenomics data obtained by Chromatin Immunoprecipitation sequencing (ChIP-seq) in the R/RStudio environment - P2P Teaching, Season 3

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Welcome to the third season of our Peer-to-Peer Teaching sessions. These are taught by our own community members to fill knowledge gaps and keep up with the accelerated pace at which bioinformatics grows. This season we are pleased to announce sessions covering * Image analysis methodologies (imageJ and QuPath) * Omics analysis in R and/or Python * Biomedical Data analysis using the clusters * Statistical analysis software (Prism) *Science communication (Illustrator).

This first session of two dedicated to the analysis of epigenomics data is entitled "Analysis of epigenomics data obtained by Chromatin Immunoprecipitation sequencing (ChIP-seq) in the R/RStudio environment" and was designed and will be delivered by Mariateresa Mazzetto, PhD from the Department of Genetics. The second workshop will be delivered in December. Keep an eye out for it!

ChIP-seq is a high-throughput technique used for the detection of enriched loci within a genome. The technique uses an antibody for a specific DNA-binding protein or a histone modification and needs a systematic downstream analysis to discover how the epigenomic landscape contributes to cell development and specification, as well as disease.

In this lecture (the first of a series of three concerning the analysis of ChIP-seq data on different platforms) we will learn the basics of epigenomic data downstream analysis, in particular differential binding profiles, annotation, and visualization of the data, using the R/RStudio environment. Rstudio is a free and open-source software that provides a user-friendly environment for your analysis; in his lecture, we will focus on the “DiffBind” package.

The workshops are designed for: biomedical researchers at every stage. Minimal experience of R programming is appreciated but not essential. Limited to 20 seats.

You will learn to:

- import your data into the R environment

- load and run the required packages

- perform differential binding analysis with DiffBind

- perform basic data visualization (PCA, heatmap, dotplots).

Requirements:

- Bring a laptop with R and RStudio installed and running (instructions and example dataset will be sent before the workshop).

- install the packages beforehand.