New Tools Helping To Make Genomic Analysis More Accessible
User-friendly analytical tools could be set to help make genomic analysis much more widespread.
Genomic data is growing in volume at an exciting pace. This is giving bioinformaticians plenty to play with, as the pool of data deepens. But the algorithms that mine these databases often produce an intimidating output.
Without a background in statistics, trying to translate outputs into useable information can be difficult. This is something that will have to be addressed, as more and more researchers choose to exploit genomic databases. Familiarity with database tools can be developed over time. It may be as simple as having a colleague talk you through the interface and walk you through an analysis. This is a good starting point, but can be time consuming for both parties involved. It also causes problems when an unexpected result is presented.
This knowledge gap is something that the team behind StratomeX are keen to address. The team comes together from Harvard Medical School, Harvard School of Engineering and Applied Sciences, Johannes Kepler University of Linz, and Graz University of Technology. They have built StratomeX as a complimentary tool to what is already out in the public domain. Users upload their database analysis results onto the platform, where it then helps to guide them through the data.
Tools like StratomeX will likely have a significant impact in making genomic analysis much more widespread and accessibly. Not only does it allow researchers to interpret their results with much great clarity, but it also offers the opportunity to probe a little deeper. Education is a bottleneck right now. We are constantly told that physicians need to have a greater understanding of genomics. And we are told that researchers need to develop computational skills and have a greater understanding of statistics. Both are true. Developing user-friendly interfaces provides the perfect training wheels to give people the confidence to really start making the most of the wealth of genomic data that is being generated.