Video Tip of the Week: gene.iobio for genome and variation browsing

Twitter erupted recently with some chatter about a new tool that people seemed to really like. The iobio team from the Marth lab had launched a new gene “app” on their iobio framework. Here was some of the response:

So of course I wanted to have a look. And I agree–it is a very slick tool, and fun to explore. If you want to get started, check out their gene.iobio announcement blog post for a bit of the goals and features in text form:

Gene.iobio is designed to help medical and clinical researchers hunt for disease-causing genetic variants through a combination of real-time genomic data analysis and intuitive visualization.

And they invite you to watch their intro video to get a sense of how it works. Their overview video is our tip this week:

They have other videos as well, on more specific use cases, via their YouTube channel. There is one publication I could find, too, which gives you some of the background on their goals and intentions for their software and app ecosystem (linked below). I like this summary of their goals from the paper, I think it helps you to understand these nifty and speedy tools:

We have developed and are continually expanding a web-based analysis system, iobio (, to empower all biological researchers to analyze—easily, interactively and in a visually driven manner—large biomedical data sets that are essential for their research, without onerous resource requirements.

On their blog they also talk about some of the other apps they already have–bam.iobio and vcf.iobio. They also note that they provide Docker containers to make it very easy for you to deploy your own installation if you’d like to have one. (If you are new to Docker, we’ve done tips on that too: intro, and a bioinformatics application example). And they note in their paper that they intend to have other folks use their libraries to create more apps that have similar features. So if people like this, and they seem to so far, you may see more of these tools coming along. Check ‘em out.

Quick links:

iobio main site:



Miller, C., Qiao, Y., DiSera, T., D’Astous, B., & Marth, G. (2014). bam.iobio: a web-based, real-time, sequence alignment file inspector Nature Methods, 11 (12), 1189-1189 DOI: 10.1038/nmeth.3174