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BioDatomics Launches New NGS Analysis Software, Announces Digicon Partnership


BioDatomics has launched a new commercial product for the next-generation sequence data analysis market — a software package called BioDT that the company claims is faster and much simpler to use than existing source software packages.

The Bethesda, Md.-based bioinformatics software developer launched BioDT last week during the American Society of Human Genetics meeting in Boston. It is based on technology that was first developed by BioDatomics CEO and founder Maxim Mikheev and colleagues at the Russian Academy of Sciences between 2002 and 2006.

Two years ago, the company released a version of that early platform, called BioUML, that provided data storage, transfer, visualization, and analysis capabilities (BI 11/11/2011). However, they decided to make changes to the platform that would enable it take advantage of the Hadoop architecture to offer much faster analyses for the NGS market, BioDatomics' representatives told BioInform this week.

"As NGS becomes more ubiquitous in research, it's just as important that processing power and analysis tools keep up with — and even anticipate the needs of — the researcher," Mikheev said in a statement. "With the support of our partners, we have created a next-generation bioinformatics analysis platform, with which we hope to accelerate insights, advance research, and reduce development costs."

BioDT brings together in a single product a combination of features that the firm believes scientists need to improve research productivity, ease of use, visualizations, and support for collaboration between researchers. The company believes that these features will help it compete favorably in what has become a very crowded data analysis market made up of more established firms like CLC Bio and DNANexus, and startups like Bina Technologies.

It also offers shorter analyses times, which should be attractive to potential customers. Alan Taffel, the company's chief marketing officer, told BioInform that the platform reduces data analysis times from weeks or days down to minutes using its proprietary execution engine and Hadoop-based architecture that enables some versions of the tool to analyze data up to 100 times faster than other platforms can by carrying out tasks in parallel — these figures are based on internal benchmarks, the results of which BioDatomics is not disclosing publicly.

Other benefits of using BioDT include its support for real-time collaboration between researchers, enabling them to share both data and workflows with others in the platform's community — much the same way people share information via Google docs, Taffel said.

BioDT offers over 400 optimized open-source tools to analyze data from mRNA, ChIP, whole-exome, and whole-genome sequencing experiments. The platform also offers improved visualization capabilities such as exploring data as graphs and charts, which provide much clearer pictures of research results than standard tables can.

The toolkit includes open-source tools, such as the Broad Institute's Genome Analysis Toolkit, Galaxy, the Burrows-Wheeler Aligner, Bowtie, and more. These tools reside in an open environment with a simple interface that allows users to create workflows from scratch and edit them using a drag and drop mechanism that does not require command line expertise. According to the company, this is one of the distinguishing features that set BioDT apart from more traditional commercial products, which either combine open-source tools into fixed pipelines and market them to researchers or provide proprietary closed-source applications for analysis use.

BioDatomics also has a slightly different business model from some of its competitors. It offers three versions of BioDT including a free downloadable community version that provides most of the same features that are included in the two priced versions of the software — such as the drag and drop interface and collaboration capabilities — with some exceptions. The paid versions of the tool also include software support and added security and file transfer features that aren't included in the free offering. Also, the paid versions of the tool provide 100x analysis speed-ups while the free version of the tool provides10x analysis acceleration.

Under the terms of the first priced option, BioDT Software-as-a-Service, customers are charged per compute hour with monthly usage fees expected to be between $50 and several hundred dollars per users. Under the terms of the second priced option, BioDT Pro, customers are charged per-seat licensing fees of $2,000 and or per-site licensing fees of $20,000 per 200 cores — both paid versions of the tool are essentially the same except BioDT Pro has more security features than BioDT SaaS.

BioDatomics is hoping to attract research customers in independent and government laboratories as well as academic institutions and pharmaceutical companies. One of the ways through which the company hopes to make inroads into the government sector is through its participation in a new program launched by Digicon, an information technology vendor that provides health science-related IT services to agencies such as the US National Institutes of Health.

A spokesperson for Digicon told BioInform in an email that under the terms of its agreement with BioDatomics, BioDT will be part of a newly launched Digicon service called BioGenLink that aims to combine tools, bioinformatics support services, as well as proven workflow and methodologies into "cost-effective and high-quality solutions and services."

Meanwhile, BioDatomics has caught the interest of researchers at the J. Craig Venter Institute who had the opportunity to test an earlier version of the tool before it was fully launched.

Indresh Singh, core informatics services lead at JCVI, whose team tested the software, highlighted its workflow capabilities including the drag and drop feature as well as cost-competitive price tags for the added software support, security, and maintenance as key factors in the BioDT's favor.

"It minimizes our internal resources because [we] don't need to maintain the workflow [or] the infrastructure, or upgrade the system," Singh told BioInform. It also reduced the time his team spent integrating open-source tools themselves, allowing them to "focus on the analysis and new tool development and not the basic infrastructure," he said.

Furthermore, because the platform is open source, identifying and fixing problems with the infrastructure is a much smoother process, Singh said. With proprietary packages, "you don't have visibility about what's going on [internally] and [also] you cannot integrate it well," he said.

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