Center for Research Informatics, University of Chicago
November 13, 2016
8:30am-12:00pm
Instructor: Kyle Hernandez, Ph.D.
In this 1-hour session, participants will learn about the basics of what ChIP-seq is, the kinds of questions, it can answer, and gain some hands-on experience with real ChIP-seq data. All of this will be done on Amazon's EC2 cloud environment.
Both the lectures and hands-on documentation were developed using Jupyter notebooks. The first two parts of this session will be in lecture format. The first section will provide you with a basic understanding of ChIP-seq experiments and experimental design suggestions. The second session will introduce you to the basic workflow of analyzing ChIP-seq data with a particular focus on detecting ChIP-seq peaks and quality control. After these lectures we will move on to our hands-on activity which uses a Jupyter notebook with R to annotate and visualize our data. Finally, we will combine the RNA-seq results with our ChIP-seq results.
Our example data comes from a published paper that explores PRDM11 and lymphomagenesis. We will use the data from the Ab1 and RNAPII factors as well as both control samples. You are welcome to explore the full dataset on GEO (GSE56065).
Fog et al., 2015, Loss of PRDM11 promotes MYC-driven lymphomagenesis, Blood 125:1272-1281
There are two main Jupyter notebooks for this session:
01.Run_ChIPseq.tutorial.ipynb02.Run_ChIPseq.hands_on.ipynb
If something goes wrong, the 02.Run_ChIPseq.hands_on.rendered.ipynb notebook can be used which has all the outputs rendered.
In addition, the workshop_extended directory contains notebooks with more information that you can browse on your own time.
These materials are licensed via LGPLv3 with a copy available in this repository.