As I mentioned last week, I am watching a lot of farmers on twitter talk about this year’s North American growing season. To get a taste of that yourself, have a look at #Plant16 + wheat as a search. This is where the rubber of tractor tires and plant genomics hits the…well…rows. And just coincidentally I saw a story about this new plant genomics research tool–actually in the farming media.
— C. S. Prakash (@AgBioWorld) April 27, 2016
It’s kind of nice to see plant bioinformatics get some recognition beyond the bioinformatics nerd community. The piece “New online tool helps predict gene expression in food crops” did a pretty good job of talking about the features of the expVIP tool, and I was eager to have a look.
expVIP stands for expression Visualization and Integration Platform. Although the emphasis here is plant data, it can be used for any species. A good summary of their project is taken from their paper (linked below):
expVIP takes an input of RNA-seq reads (from single or multiple studies), quantifies expression per gene using the fast pseudoaligner kallisto (Bray et al., 2015) and creates a database containing the expression and sample information.
And it can handle polyploid species–try that on some of the tools aimed at human genomics! They illustrate this with some wheat samples from a number of different studies. And then they use the metadata about the studies, such as tissues and treatment conditions, to show how it works with some great sorting and filtering options. They created a version of this for you to interact with on the web: Wheat Expression Browser. But you can create your own data collections with their tools, aimed at your species or topics of interest.
This week’s Video Tip of the Week is their sample of how this Wheat Expression Browser works. Although you see the wheat data here, it’s just an example of how it can work with any species you’d like to examine.
I followed along and tried what they were showing in the video, and I found it to be a really slick and impressive way to explore the data. The dynamic filtering and sorting was really nice. You can customise the filtering/sorting/etc for the visualizations with the metadata that’s useful to your research. So you could set the tissue types, or treatment conditions, or whatever you want–and filter around to look at the expression with those. They go on to show that their strategies to compare genes in different situations seemed to reflect known biology in disease and abiotic stress conditions.
So their pipeline for gene matching, as well as the tools to explore and visualize RNA-Seq data, offer a great way to look at data that you might generate yourself or you could mine from existing submitted data–but that might not be well organized and available in a handy database just yet.
Wheat expression browser: www.wheat-expression.com
expVIP at GitHub: https://github.com/homonecloco/expvip-web
Philippa Borrill, Ricardo Ramirez-Gonzalez, & Cristobal Uauy (2016). expVIP: a customisable RNA-seq data analysis and visualisation platform Plant Physiology, 170, 2172-2186 : 10.1104/pp.15.01667