Genomic Medicine 2018 Module 5 Lab

Module 5: Available Epigenomics Data and Resources

by Guillaume Bourque, PhD


Description of the lab

In this module’s lab, we will explore some of the tools that were covered in the lecture.

  • First, we will learn how to use the IHEC Data Portal’s tools to fetch datasets of interest.
  • Second, we will explore the ENCODE Data Portal.
  • Third, we will explore the GTEx Data Portal.

Local software that we will use

  • A web browser


1- IHEC Data Portal

Exploring available datasets

  • Open a web browser on your computer, and load the URL .

  • In the Overview page, click on the “View all” button.

  • You will get a grid with all available datasets for IHEC Core Assays.
    • You can filter visible datasets in the grid using the filtering options on the right side of the grid.
  • Select only the datasets coming from the CEEHRC consortium, you should see something like this:


  • Explore the various filtering options on the right, is there a way to restrict this list to your tissue of interest?

  • Can you search and find your favorite cell type? What type of datasets are available?

Visualizing the tracks

  • Go back to selecting only the datasets coming from the CEEHRC consortium

  • Select the 8 H3K27ac ChIP-seq datasets in B cells - Other

  • Select the 4 mRNA-seq datasets in the same cell type

  • Click on the button Visualize in Genome Browser just below the grid
    • You can see that the datasets are being displayed at a mirror of the UCSC Genome Browser. These are all peaks and signal for the chosen H3K27ac ChIP-Seq and RNA-seq datasets.
  • Now, type in the name of the gene CD79A (a gene expressed in B cells)

  • In the Genome Browser, expand the ChIP-seq tracks and RNA-seq tracks by changing visibility from “pack” to “full” and clicking the “Refresh” button.

  • Zoom out 10X, do you see the potential regulatory regions around this genes?

  • You should get something like this: Solution

  • Can you find another gene expressed in B cells?

Tracks correlation

You can get a whole genome overview of the similarity of a group of tracks by using the Portal’s correlation tool.

  • Select 3 RNA-seq datasets in Adipocyte of omentum tissue

  • Select 3 RNA-seq datasets in induced pluripotent stem cells

  • Click on the button Correlate datasets just below the grid, you should see something like:


  • Can you find an outlier/bad dataset?
    • Under Blood cell-type, try correlating the 8 B-cell with the 4 T-cell H3K27ac datasets

Download tracks or metadata

You can also download these tracks locally for visualization or further analysis, or view the metadata.

  • Go back to the IHEC Data Portal tab.
  • Click on the Download tracks button at the bottom of the grid.
  • Use the download links to download a few of the tracks.
  • What about the raw data?
  • Go back to the IHEC Data Portal tab.
  • Click on the Get metadata button at the bottom of the grid.

Permanent session

Finally, you can create a permanent session corresponding to your current selection of datasets

  • Go back to the IHEC Data Portal tab.
  • Make a selection of datasets and click on the Save session button at the bottom of the grid.
  • You now have a nicer and permanent view of the data that you have selected
    • You can use this ID and associated web address (e.g. and share it with your collaborators or in a publication
  • A permanent session also has links to all the raw datasets
  • Is is as easy that access that data? Why?

2- ENCODE Data Portal

  • Go to
  • So much data! Can you find which human cell type has the most ChIP-seq datasets?
  • Explore the different ways you can dynamically filter the data
  • Can you also find RNA-seq data in B cells?

3- GTEx Data Portal

  • Go to
  • How many datasets are available?
  • Look for the gene CD79A, it’s expressed in how many tissues? Solution
  • How many isoforms are expressed?
  • Can you find a genetic variant that is associated with CD79A expression levels?
  • Can you find a gene that’s diffentially expressed based on gender? Try a famous gene on the X chromsome…
  • What about a gene with the reverse pattern?

Congrats, you’re done!


Part of this module was developped by David Bujold, who also developped the IHEC Data Portal.