No meaning – no gain: Interpretation is the key
In September this year, Genomics England introduced the “PanelApp” that helps experts to comb through the 100,000 genomes project’s data for rare diseases. This is a crowdsourcing project where the whole scientific community is invited to take part in interpretation and reviewing of the variants. The aim is to produce diagnostic quality gene panels. The PanelApp is a very ambitious project, I would say, but definitely the way to go, as no other formal interpretation systems yet exist anywhere.
There have been other attempts at collective interpretation, on various levels of expected contribution, and in many different formats. One project is the Cafe Variome -portal, brought into daylight in Gen2Phen -project some years back. Here the idea is to collect variants and phenotypic evidence from various contributing resources, with an easy API for submissions, and to make remote repositories available for discovery. It is a neat solution, and grows its community of collaborators, partnership networks, and other experts, to add more value to the content.
The LOVD -project provides local tools for locus-specific projects that allow the experts to choose, what information they want to expose outside the project, whilst keeping the data in-house. A hub connects these distributed LOVD instances, and allows discovery platforms (like Cafe Variome) to tap into the exposed data in the LOVDs. The toolbox also doubles as an internal information centre.
In both of these concepts the value is in the expert interpretation, not in data sharing itself. The caveat is that their use requires some effort (you need to install the tool, or you need to reformat your data to fit the communication layer), and this is a deterrent. We need things to be made very, very easy for us to use, unless we have the luxury of having an IT team at our command. The other deterrent is the ultimate sharing of data, unfortunately.
Crowdsourcing interpretation work at Genomics England is a wonderful idea. The data is already there, and people are invited to show their expertise. Giving your expert opinion is rather easy, and serves a large community of people, so the requirements for easiness, motivation, and working on ‘somebody else’s data’ exist. I believe PanelApp has the potential makings of a true discovery platform.
Still, the problems persist with isolated data collections, and there is no immediately easy solution for those. Maybe only these big, centralised efforts will have the chance to become truly meaningful, and to propel the medical advancements. Or maybe, someone somewhere, will come up with another kind of idea, and is able to connect the scattered dots into an interpretation app that tells us, what’s going on with the genes.
It is not necessary to own or control massive server pits and cellars of machinery to be at the top of the genomic data food chain. The possession of the information is one thing – getting value out of it is a completely different story. Companies like Congenia and Omicia (recent additions to the Genomics England -family) are increasingly more interesting for their ability to provide fast and automated services. But even they are dependent on the large scheme of building a genomic consensus out of the complex space of evidence and knowledge that’s still hidden in the experts’ hard drives.