Genomic Medicine 2017 Module 5 Lab

Module 5: Available Epigenomics Data and Resources

by Guillaume Bourque, PhD

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.

Open a web browser on your computer, and load the URL http://epigenomesportal.ca/ihec .
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:

Can you sort and re-organize the grid differently? Try sorting by Cell type category.
Explore the various filtering options on the right, is there a way to restrict this list to your tissue of interest?

Go back to selecting only the datasets coming from the CEEHRC consortium sorted by Cell type
Select the 3 H3K27ac ChIP-seq datasets in B cells - Other
- Notice the importance of ontologies…
Select the 3 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.
(Optional) If the browser is slow, notice that in the address bar you have something like:
- http://ucscbrowser.genap.ca/cgi-bin/hgTracks?hubClear=http://epigenomesportal.ca/cgi-bin/hub.cgi?session=3113&db=hg19
- The second portion of the address is actually a track hub that you can load in any UCSC Genome Browser
- Go to the main UCSC genome browser: http://genome.ucsc.edu/cgi-bin/hgGateway
- Click on MyData -> Track Hubs, then click on My Hubs
- Copy the URL, e.g. http://epigenomesportal.ca/cgi-bin/hub.cgi?session=3113&db=hg19
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?

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 a outlier/bad dataset?
- Try correlating the 8 amygdala - Other with the 5 B cell - Blood H3K27ac datasets

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

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. http://epigenomesportal.ca/ihec/IHECDP00000092) 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?

Go to https://www.encodeproject.org/
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?

Go to https://www.gtexportal.org
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?

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