Video Tip of the Week: ICGC portal for cancer genomics

A question at Biostar about cancer “gene sets” recently got me looking at one of my favorite data sources again–the ICGC, International Cancer Genome Consortium, and their data portal. Previous posts we’ve done were based on their legacy portal (which is still available on their site). They changed things up a bit with a release last fall, and I hadn’t covered those changes yet.

Conveniently, they have done a short video explaining how to access the data that they offer. They’ve continued to add new data, and to refine the software. You should check it out.

ICGC Data Portal Tutorial from ICGC on Vimeo.

In the past I found some really useful info to compare with a lung cancer cell line I had been examining. I saw the same mutation in actual tumor samples as had been found in this cell line years back. But there have also been publications recently that talk in more detail about the project and some interesting outcomes from data that’s been found there (linked below).

You really need to be mining these projects for data if they cover your research area. There’s a lot to learn that hasn’t been published yet–just be sure to read up on their usage policies before you deliver your great discoveries to the journals!

Quick link:

Data portal:

Project homepage:


Hudson (Chairperson) T.J., Anderson W., Aretz A., Barker A.D., Bell C., Bernabé R.R., Bhan M.K., Calvo F., Eerola I. & Gerhard D.S. & many others in a large consortium… (2010). International network of cancer genome projects, Nature, 464 (7291) 993-998. DOI:

Alexandrov L.B., Nik-Zainal S., Wedge D.C., Aparicio S.A.J.R., Behjati S., Biankin A.V., Bignell G.R., Bolli N., Borg A. & Børresen-Dale A.L. & many others in a large consortium…; (2013). Signatures of mutational processes in human cancer, Nature, 500 (7463) 415-421. DOI:

Gonzalez-Perez A., Mustonen V., Reva B., Ritchie G.R.S., Creixell P., Karchin R., Vazquez M., Fink J.L., Kassahn K.S. & Pearson J.V. & many others in a large consortium… (2013). Computational approaches to identify functional genetic variants in cancer genomes, Nature Methods, 10 (8) 723-729. DOI: