This story was originally posted on June 8.
Illumina is waiting for the first genome-wide association studies using its next-generation arrays to yield interesting results, with the hope that new findings will reinvigorate the GWAS market, according to its CEO.
Though the company has for several years been predicting a second round of association studies run on chips containing rare variant content, Jay Flatley said this week that the market is "at the very beginning" of this new phase, which Illumina refers to as "rich GWAS."
"Chips with rare variant content came into the market with the launch of our Omni2.5" BeadChip, Flatley said at the Goldman Sachs Global Healthcare Conference held in Rancho Palos Verdes, Calif.. Illumina launched the Omni2.5 last year (BAN 6/8/2010).
Flatley said in his presentation, which was webcast, that the first studies using the chips began in the third and fourth quarter of 2010. The company also plans to launch a 5-million-variant whole-genome genotyping array called the Omni5 next quarter, which will give users the "next increment" of rare variant content, he said. Altogether, the company is waiting to see what initial adopters find using the new arrays.
"We are optimistic that there will be some interesting discoveries here, but it is a wait-and-see situation for us," said Flatley.
Flatley cautioned that the discovery that very rare variants are linked to common human diseases may require even larger follow-up studies to validate. At the same time, he said the company would also benefit in such a scenario.
"For Illumina, the more complicated the biology turns out to be, the better it is for us," Flatley said at Goldman Sachs. "The only really bad scenario is that everybody throws up their hands and says, 'We're never going to figure this out,'" he said. "We don't think that's going to happen."
He also discounted the idea that next-generation sequencing will replace arrays as the platform of choice for those conducting association studies. "Ninety percent of GWAS is something that can't be replaced by sequencing," said Flatley. "You are not going to [take] a 4,000-person study in GWAS to be done in four months and move that to sequencing," he said.
More than cost and throughput issues, Flatley cited data reliability, saying that the accuracy of the data is, "frankly, much better on arrays" and that "arrays are the better technology" for GWAS.
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