We’ve been doing training and workshops on the UCSC Genome Browser for 10 years now. It’s a tremendous tool that has to be a foundational item in your toolkit in genomics. But–there may be times when you want to examine some of the data that you can find there in another way, with a different focus or emphasis. It might be possible to craft some clever Table Browser queries that get you what you want. Sometimes, though, someone else has created a way for you to query the underlying data for a topic that could be useful too. And today’s tip of the week is exactly this kind of tool. A web interface to query the ENCODE data that resides in the UCSC Genome Browser, with a focus on finding transcription factors with enriched binding in a region that you might be interested in exploring. Today’s video tip is for the ENCODE ChIP-Seq Significance Tool.
There’s a ton of great data that flowed into the UCSC Genome Browser as part of the ENCODE project. It’s going to provide years of mining for biologists. What would be great is for biomedical researchers who have interest in specific genes–or sets of genes–to take a look at the ENCODE data to see if they can unearth some useful insights about the regulation of these genes or lists of genes. You can use the ChIP-Seq Significance tool to sift through the data.
The video that the Butte lab team did is very nice. Very specific guidance on how to use their tool–what to choose for the menu options, what the choices are, and what to expect from the results. Here’s their video:
Of course you should read their paper about this tool for the background you need (linked below), and the references that will also help you to understand what this tool offers. You should also read up on the associated ENCODE data. The supplement with the paper is also nicely written in clear language to help you to understand the features.
One of the things I was curious about was whether this might be extended to the mouse data too. One thing that people grouse to me about is that ENCODE is cell line data, and tissue data would really be great. But I saw discussion at Stephen Turner’s blog (read the comments) about the focus on human for now. There was also discussion of the CScan tool, though, which does cover the mouse data. So if this is a tool you are interested in, you might want to explore CScan too.
Hat tip to Stephen Turner for the awareness:
— Stephen Turner (@genetics_blog) June 7, 2013
ENCODE ChIP-Seq Significance Tool: http://encodeqt.stanford.edu/
Auerbach, R., Chen, B., & Butte, A. (2013). Relating Genes to Function: Identifying Enriched Transcription Factors using the ENCODE ChIP-Seq Significance Tool Bioinformatics DOI: 10.1093/bioinformatics/btt316