When we go out and do workshops, we get a lot of requests from researchers who would like some guidance on cancer genomics tools. Our particular mission has been to aim more broadly at tools that are of wide interest and not to focus on a particular disease or condition area. But certainly the cancer genomics arena is going to be one of the ones that’s got so much opportunity for great bioinformatics-based outcomes in the near term. So I keep an eye out for tools researchers may want to explore.
When the “genomics” twitter column in my Tweetdeck dropped this new mini-review of cancer genomics tools on my desktop, I went to look right away: Data mining The Cancer Genome Atlas in the era of precision cancer medicine. TCGA is the focus of the data source they are talking about, but the tools included may have more data sets and wider utility, of course. Most of the tools described were familiar to me (cBioPortal, GDAC Firehose, UCSC Cancer Genomics Browser, canEvolve), but a couple of them were new. I had never explored the ProGeneV2 tools before. And the UZH Cancer Browser was also new to me.
One thing that’s very helpful to me is the kind of table they provided as Table 2. It’s a comparison of the main tools they are discussing, with different features of each compared. That’s handy for choosing the tool to spend time on, depending on your own research needs.
But they also referred to another tool that was new to me, Xena. “The UCSC cancer browser will be updated in the future, with the new Xena platform for visualisation and integration with Galaxy“. I can never resist new genomics visualization tools, and as a giant fan of Galaxy, I certainly need to know more about this.
So I went to look around for some information on it, and their introductory video is this week’s Tip of the Week.
So Xena is designed to let you combine your own data with large public resource collection data, without leaving your firewall or without being too onerous to pull down all the public data and manage it locally. You can explore functional genomics data and related phenotype and clinical data. It uses the “hubs” strategy that is becoming increasingly adopted as a way to integrate across data collections. We were just talking about hubs in another recent tip if these are new to you. It supports a wide range of data types to examine and visualize. If you want to go deeper, there’s a lot more information over at the Xena homepage. They have documentation, presentation slides, and a step-by-step demo available from a recent workshop.
— UCSC Xena (@UCSCXena) September 14, 2015
Certainly one of the key features appears to be that you can integrate your own research data–which might be subject to strict privacy regulations–on your own computer with all the other key information from public data providers. Increasingly researchers I talk to at workshops need this aspect very much.
So try out Xena, and explore the other tools in the cancer genomics space, to see what’s right for your research.
Hat tip to Oscar:
— oscar b (@DNA_oscar) September 18, 2015
And you can follow Xena on twitter for news and updates: https://twitter.com/UCSCXena
Cline, M., Craft, B., Swatloski, T., Goldman, M., Ma, S., Haussler, D., & Zhu, J. (2013). Exploring TCGA Pan-Cancer Data at the UCSC Cancer Genomics Browser Scientific Reports, 3 DOI: 10.1038/srep02652
Cheng PF, Dummer R, & Levesque MP (2015). Data mining The Cancer Genome Atlas in the era of precision cancer medicine. Swiss Med Wkly. (145) : 10.4414/smw.2015.14183