Looks like the customer is always right, at least in the gene expression analysis market.
The past week and a half saw both Affymetrix and Rosetta Inpharmatics take great pains to reassure end-users that all is well in the competitive world of gene expression analysis software.
At the recent Northwest Microarray Conference held August 15-17 in Seattle, Affymetrix responded to customer dissatisfaction with its existing data analysis methods by announcing plans to introduce an improved algorithm for analysis of its GeneChip arrays.
Then, within days of the conference, Rosetta assured customers that despite its recent acquisition by Merck, it would continue to support and upgrade the Resolver system as part of a plan to cordon off its biosoftware division into a separate unit that will move to a new building near its existing headquarters.
Speaking about his companys existing empirical algorithm at the Seattle microarray conference, Tarif Awad of Affymetrixs genomics collaborations group bluntly admitted, Users are not crazy about it.
Noting that the current algorithm has black boxes and is not based on a statistical approach, Awad added that the current method also generates negative values for some mostly absent probe sets and has unintuitive parameters.
Statisticians have publicly criticized the companys existing algorithm for its assumption that microarray gene expression data fits a normal distribution. Awad agreed that, probe pair data is not necessarily normally distributed, so it is not appropriate to use an algorithm that assumes normal distribution. By contrast, Awad said the new algorithm employs the Wilcoxon Rank-Sum test, a classic statistical test that does not require data to fit into a normal distribution curve.
The algorithm does not require that users throw out outliers in a dataset, a practice in Affymetrixs previous algorithm that statisticians had questioned due to its potential to skew the data toward more highly expressed genes.
Outside experts have also noted that Affymetrixs existing algorithm fails to include a published statistical error model for its experiments, which means that researchers have not known how much to adjust their data for variations in spot intensity, hybridization patterns, and intensity measurement sensitivity.
The new algorithm, which is to be incorporated in new versions of the microarray analysis software the company is planning to release in the fourth quarter, is designed to address these issues, Awad said.
The new approach is certainly a move in the right direction, and I am happy to see Affymetrix responding to the concerns that have been raised by their customers, said Michael Recce, director of the Center for Computational Biology and Bioengineering at the New Jersey Institute of Technology. Recce, who uses Affymetrix GeneChip systems and has sought to develop more useful alternatives to the companys existing approach, said he would look forward to having a more detailed look at their algorithm.
Statisticians attending the Seattle conference also indicated that Awads presentation looked interesting, but that they would have to see more statistical details in order to really evaluate the robustness of the algorithm.
Affymetrix is also building a huge database that offers a comparative view of the human genome, Awad said. The database is to be offered to customers through NetAffx, the online array information and ordering interface the company introduced in late July.
The House that Resolver Built
Days after Affys admission of a sub-par offering and its promise to make good in future products, Rosetta sought to reassure users of its Rosetta Resolver microarray data analysis software that its recent acquisition by Merck would not impede its support for the product.
In a demonstration of its plan to protect its current customers best interests, the company said it would formally split its operations into two units: a biosoftware division, which will move to its own building, and a research arm, which will continue to collaborate with Merck.
Rosetta Inpharmatics had two key business components, its scientific collaborations and high-throughput expression profiling business, and its software business, explained Doug Bassett, vice president and general manager of Rosettas biosoftware unit. In the context of the Merck acquisition, the [first] business makes sense to plug into the Merck research and development engine. But the commercial software product portion of the business flourishes by virtue of the fact that it has a large number of diverse customers, and a user base that is coming up with new requirements for the system.
To keep these Resolver customers, which include some of Mercks competitors in the pharmaceutical and biotechnology industries, Rosetta knew it had to assure them that their data would not get into the hands of the competition. The separation of the biosoftware division is designed to accomplish just this.
Its a separate IT infrastructure and a separate physical infrastructure, and to the extent that customers have confidentiality arrangements with us, Rosetta continues to exist as an independent corporate entity, said Bassett. Theres no risk of confidential information being communicated to Merck.
As Rosetta goes through this corporate mitosis, the biosoftware division will be looking to hire more software developers and marketing staff, Bassett said. It will also be expanding its efforts to develop and provide best of breed bioinformatics systems to customers.
The division is meanwhile planning to continue its schedule of releasing one major and two minor updates of Resolver per year.
Marian Moser Jones
Editor, BioArray News