The group of Dr. Nadir Alvarez from the University of Lausanne, Switzerland was really excited: a novel method for extracting DNA from historical samples with little preserved DNA (such as museum specimens) seemed to work well in the lab! However, to ensure method’s practical validity, the team had to apply various bioinformatics analysis and test the data in-silico. And that posed a serious problem: none of the team members had enough of bioinformatics know-how to quickly develop a bioinformatics pipeline. Moreover, learning all the details around bioinformatics on their own would take the team months, if not years, of training and work. In addition, Nadir’s team only had access to their own single server, and running such massive data analysis would block the entire team from executing any, even simple, daily tasks for two months.
Nadir recalls: “It was really a pain, my team needed additional training to learn the complex bioinformatics analysis and ultimately it was taking too much of time to be effective in publishing our results quickly. We seriously feared being scooped, because we knew that other labs also work on a similar techniques.”
Nadir adds: “What is more painful for me as a lab leader, the management of our server was taking a lot of my own time. It was more than once that our only big server nearly died and we had to give it to the maintenance service and that took over a month of our precious time. We really did not know how to make the work of our lab easier with the existing computing solution”.
With a constant frustration from infrastructure management and need for ongoing training for all newcoming team members, Nadir quickly realized the costs of their own server outweigh its benefits, so he began searching for a better bioinformatics solution.
Nadir evaluated a number of options, for example switching their analysis to a self-managed cloud or going to other cloud bioinformatics providers, free or proprietary. However, all of them lacked a key feature - none provided dedicated bioinformatics consulting in addition to the infrastructure and bioinformatics pipeline management. Free tools, such as Galaxy or iPlantCollaborative, only offered 5Gb of storage space, which was absolutely limiting - the lab has already generated over 0.5Tb of data and analysis would take even more of disk space. So InsideDNA has emerged as a clear winner: it offered a managed cloud computing infrastructure, all the tool integration, it’s baseline prices are nearly equal to the default Cloud provider prices and bioinformatics support comes as part of the deal.
Nadir adds: “Thanks to InsideDNA dedicated bioinformatics support we could get all necessary learning and to quickly move our project. On average, analysis of this type takes 1 year of 1-2 PhD students work and here we managed to develop the pipeline, test it, write manuscript and submit the paper just within 3 months which is absolutely incredible!”
The results of the Nadir’s project and its collaboration with InsideDNA was a massive success. The paper is currently published and it took a bit less than half a year to see it live on the PLOSOne website. The HyRAD method was featured on different news websites including one of the most popular molecular biology blogs “Molecular ecologist”. The citations are picking up quickly and other labs are already developing modifications of the method/pipeline which proves practical and scientific value of HyRAD methodology. Currently Dr. Alvarez plan to use it for very analysis of old museum specimens stored in the Museum of History, Geneva and continues collaboration with the InsideDNA team.
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