Program

Monday – Classes from 09:30 to 17:30 - “The basics”

    Session 1: Motivation and introduction to the biological system_(morning)

We will start with an introductory lecture presenting several examples of integrative epigenomic data analyses from recent literature. We will then focus on the biological system that will be used throughout this 5-days course, where we will study dynamic chromatin changes induced by Lipopolysaccharide (LPS) stimulation of mouse bone marrow-derived macrophages.

    Session 2: Introduction to Linux and bash (morning)

In this session, we will provide a targeted introduction to Linux and bash scripting, with a focus on the tools required for the rest of the course. No previous exposure to scripting is strictly required. Also, we will not attempt to provide a catalogue of functions and command syntax. Rather, we will focus on the principles and logic of scripting.



    Session 3: R programming_(afternoon)

In the afternoon, we will cover the basics of R programming. This session will alternate short talks covering the basics with extensive hands-on tutorials to allow students without prior exposure to R to familiarize themselves with this language in the most natural way. This session aims at building a solid foundation of R programming, and will also cover good coding practices for reproducible research.

 


Tuesday – Classes from 09:30 to 17:30 -  “ChIP-seq data analysis”

    Session 4: ChIP-seq data analysis - theory (morning)

This module covers the building blocks of a ChIP-seq data analysis workflow. We will discuss quality control metrics and common pitfalls, and the theoretical foundations of commonly used aligners and peak callers.



    Session 5: ChIP-seq data analysis lab (afternoon)

In the afternoon, we will transition from theory to practice. We will run a complete ChIP-seq data analysis workflow. We will also learn how to generate and visualize tracks in formats widely adopted by genome browsers. During this hands-on session, we will randomly assign a topic for a lightning talk (3 minutes = 3 slides) on common pitfalls of ChIP-seq algorithms and/or results interpretation.

 


Wednesday – Classes from 09:30 to 17:30 - “RNA-seq data analysis”

    Session 6: Lightning talks_(morning)

In this session, the students will present their lightning talks on the topic assigned in Session 5. This will be followed by a 30’ round table open discussion.



    Session 7: RNA-seq data analysis - theory (morning)

We will then move on to RNA-seq data analysis. We will first cover the theoretical basis of commonly adopted algorithms for RNA-seq data processing. We will then discuss the statistical foundation of algorithms for differential expression analysis (with a particular focus on DESeq2)



    Session 8: RNA-seq data analysis lab (afternoon)

In the afternoon, we will run a complete RNA-seq data analysis workflow, from read alignment to differential gene expression. We will use subcellular RNA-seq data, which will allow us to go beyond quantification of stable mRNA levels. During this hands-on session, short talks will further cover the statistical aspects of differential gene expression analysis.



Thursday – Classes from 09:30 to 17:30  - “ATAC-seq/DNase-seq data analysis and the big picture”

    Session 9: ATAC-seq/DNase-seq data analysis - theory (morning)

In this session, we will introduce genomic methods for the analysis of chromatin accessibility and discuss commonly used workflows for data analysis. We will highlight similarities and differences with ChIP-seq data analysis pipelines.



    Session 10: ATAC-seq/DNase-seq data analysis lab (morning)

We will then run an ATAC-seq/DNase-seq analysis pipeline to infer putative regulatory elements in mouse macrophages.



    Session 11: the big picture (afternoon)

A successful epigenomic data analysis often requires the coherent integration of multiple data sets. We will then integrate the results of ChIP-seq, RNA-seq and ATAC-seq/DNase-seq data analysis from the previous sessions to identify the dynamic chromatin changes that characterize the LPS response. At the end of this session, we will distribute projects to be carried out by groups of 2-3 partecipants within the next 24 hours. These projects will address real life research questions and the groups will need to wisely organize their work to manage the limited amount of time.



Friday – Classes from 09:30 to 17:30 - “Group project and presentations“

    Session 12: group projects (morning)

Each group will work on the assigned project.  During this session, short Q&A sessions will be held to support each project.



    Session 13: group projects (afternoon)

This afternoon session is meant to ensure all groups can successfully complete their project.



    Session 14: group project presentations (afternoon)

In this session, each group will present the results of their work. Each member of the groups will present part(s) of the projects. This will be followed by a round table discussion of the group tasks and the course.