Analysis of epigenomics data obtained by Chromatin Immunoprecipitation sequencing using Python - 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 session on "Analysis of epigenomics data obtained by Chromatin Immunoprecipitation sequencing using Python" was designed and will be delivered by Mariateresa Mazzetto, PhD from the Department of Genetics.

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 second 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 peak calling, and visualization of the data, using Python packages in the linux environment. In his lecture we will focus on the “Deeptools” package.

The workshops are designed for: biomedical researchers at every stage. Minimal experience of bash language is appreciated but not essential. Limited to 10 seats.

You will learn to:

- import the data in your cluster

- load and run the required packages

- convert BAM files to normalized Bigwig for further visualization with Deeptools

- create metagene plots with Deeptools.

- create profile plots with Deeptools.

Requirements:

- The lecture requires a computer and an HPC YCRC cluster account; in case you do not an account, Deeptools is also available on a web interface (https://usegalaxy.eu/) which I will show you in the lecture. You can also request an account here.

- if you do have access to a cluster, and have MobaXterm installed, instructions on how to load the softwares will be sent before the workshop, along with the sample dataset.

Attendance: in person