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To Solve Short Read Problem, Danes Launch Network for Data Analysis

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While next-generation sequencing technology continues to push the high-throughput envelope, handling the landslide of data remains a persistent problem. Resourceful researchers have no trouble developing tailor-made tools to deal with the data deluge, but the distribution of such applications to the wider research community is often marred by the fact that not all labs use the same sequencing platforms.

In order to address this challenge, the Danish Agency for Science Technology and Innovation recently announced a $3 million grant to support a collaborative network of Danish research institutions called Seqnet. The three-year initiative aims to support the development of a national, user-friendly graphical interface platform for the analysis of next-generation sequencing data. Seqnet will be a team effort among the University of Copenhagen, the Agricultural Sciences at Aarhus University, Aalborg University Hospital, and the University of Southern Denmark, with Danish bioinformatics vendor CLC bio.

"There is a need to make a unified, next-generation sequencing platform capable of analyzing sequences for many purposes, regardless of whatever platforms they are coming from because each has their own software tied to that particular sequencer," says Kare Lehmann Nielsen, leader of the Seqnet project and an associate professor at Aalborg University. "We are already in the process of writing small scripts, but lack the capability to develop them in a user-friendly manner and make them easily distributable between labs because they are complicated, command-line based, and very specialized."

The platform will be tested in various research projects, such as metagenome analysis of bacterial systems taken from waste water treatment facilities, cancer cell typing, and tag-based expression. "We realized very early on that you had to develop your own applications or else rely on the slow development of comprehensive tools. … There is not nearly good enough software analysis for gene expression profiling," says Nielsen, who works on tag-based gene expression. "It is really important to do the visualization of the data in a way that is interpretable to regular users." Seqnet aims to eventually deploy a bioinformatics package with a slew of algorithms ported to CLC's workbench platform.

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