Tuesday, October 6, 2009

From Blue Gene to Blue Genome? Big Blue Jumps In with DNA Transistors

Today, IBM announced that are getting into the DNA sequencing business and race for the $1,000 dollar genome by winning a research grant to explore new sequencing technology based on nanopore devices they call DNA transistors.

IBM news travels fast. Genome Web and The Daily Scan covered the high points and Genetic Future presented a skeptical analysis of the news. You can read the original news at the IBM site, and enjoy a couple of videos.

A NY Times article a listed a couple of facts that I thought were interesting: First, IBM becomes the 17th company to pursue the next next-gen (or third-generation) technology. Second, according to George Church, in the past five years the cost of collecting DNA sequence data has decreased by 10 fold annually and is expected to continue decreasing at a similar pace for the next few years.

But what does this all mean?

It is clear from this and other news that DNA sequencing is fast becoming a standard way to study genomes, gene expression, and measure genetic variation. It is also clear the while the cost of DNA sequencing is decreasing at a fast rate, the amount of data being produced is increasing at a similarly fast rate.

While some of the articles above discussed the technical hurdles nanopore sequencing must overcome, none discussed the real challenges researchers face today with using the data. The fact is, for most groups, the current next-gen sequencers are under utilized because the volumes of data combined with the complexity of data analysis has created a significant bioinformatics bottleneck.

Fortunately, Geospiza is clearing data analysis barriers by delivering access to systems that provide standard ways of working with the data and visualizing results. For many NGS applications, groups can upload their data to our servers, align reads to reference data sources, and compare the resulting output across multiple samples in efficient and cost effective processes.

And, because we are meeting the data analysis challenges for all of the current NGS platforms, we'll be ready for whatever comes next.

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