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Bioinformatics Startup Scale Genomics Touts Flexibility as Key Differentiator of Cloud Platform

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By Uduak Grace Thomas

Bioinformatics startup Scale Genomics is prepping to roll out later this month a new cloud-based storage and analysis system for next-generation sequencing data.

The platform is targeted at customers who have some bioinformatics expertise but who do not have access to the compute resources needed to run their analysis, Dmitri Petrov, co-founder of the company and professor of biology at Stanford, told BioInform.

When it launches its private cloud platform later this month, Scale Genomics will compete indirectly with another Stanford bioinformatics spin-out, DNAnexus, in the sense that both companies offer a cloud-based infrastructure for analyzing next-gen sequence data.

However, the DNAnexus offering is aimed at a slightly different clientele because it caters to customers that are looking for prepackaged solutions that solve specific bioinformatics analysis needs, Petrov said.

"What they don’t provide is the ability to run their own pipelines and play with it," he said. "They don’t give the flexibility that [bioinformaticians] need to ... work."

With DNAnexus, users aren't in control of how the data is analyzed and what scripts are run to produce the results, he continued, which does not work for users who want to "play with the models” and tweak software settings.

The Scale Genomics platform, meantime, allows users to run existing pipelines as well as internal pipelines as virtual images on the company’s infrastructure. It also can accommodate third-party software and scripts, the company said.

Scale Genomics is currently beta-testing its platform ahead of a full launch. The company isn't divulging who its beta testers are but they include researchers at Stanford University, Petrov told BioInform.

The Scale Genomics cloud platform also offers storage infrastructure developed by the digital photo and video sharing web service Fotki. It includes a layer of software that lets customers manage their data and run virtual machines, Petrov said.

The initial offering will provide access to the company's Genomics Image application, which includes more than 50 open source software tools and scripts stored as virtual machines.

These include alignment tools such as ClustalW, HMMer, and fasta; de novo assembly tools such as SOAP, Velvet, and Phrap; as well as RNA-seq assembly tools like TopHat and Cufflinks. It also includes tools for population genomics, motif discovery, and copy number variation analysis among others.

Additionally, the company is currently working to implement the Galaxy framework so that users will be able to run pipelines from that system on their data, Petrov said.

The company also plans to make several public datasets from repositories like Ensembl available for analysis on its platform, he said.

Customers can sign up for a free trial that provides access to one core, one gigabyte of random access memory, and one terabyte of storage.

Subscriptions start at $99 per month for eight cores, 12 GB of RAM, and 4TB of storage and go up to $3,999 per month for 56 cores, 288 GB of RAM, and 80 TB of storage.

Customers set up accounts on the platform by creating virtual laboratories. Once the labs have been approved, customers can choose their subscription plans. Furthermore, customers can add collaborators to their labs and give them access to datasets and pipelines, Petrov said.

Currently, Scale Genomics has two employees but it plans to hire additional staff once it launches officially, Petrov said.


Have topics you'd like to see covered in BioInform? Contact the editor at uthomas [at] genomeweb [.] com.

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