Join Us at Bio-IT World for a Personalized Demo and Chance to Win an iPad Mini!

Next week kicks off the annual Bio-IT World Conference & Expo, one of the best conferences dedicated to bioinformaticians and computational biologists. We look forward to it every year for the opportunity to rub elbows with die-hard developers, IT powerhouses, and the truly remarkable scientists who are just as comfortable working with lines of code as others are with lines of cells. Last year the meeting had more than 2,500 attendees from all over the world; it’s a can’t-miss venue for people who work hard to make sure the computational side of biology functions properly.

In that spirit, we hope to meet many of you at our booth (#311) for a personalized demo of the new DNAnexus, our cloud-based genomics platform. For the bioinformatics professional, the new DNAnexus eliminates up-front commitment to expensive hardware and maintenance. And since DNAnexus leverages Amazon Web Services for scalable and cost-effective data storage and computing, a research lab can access these resources, as there is need. The new DNAnexus is now in beta and you can request access for a free account today.IPad Mini Giveaway

To sweeten your personalized test drive of the new DNAnexus platform at Bio-IT World, we are giving away an iPad Mini! Here’s how to enter:

1. Sign up for a beta account
2. Upload your data so you can test-drive our system
3. Visit DNAnexus in booth #311 for a chance to win

DNAnexus scientists will be on hand to offer a custom data analysis and answer any questions you may have. This is a perfect opportunity to see how our new platform will perform in your lab! Even if you don’t have time to upload your data ahead of time, please stop by to learn more about the new platform and shoot the bioinformatics breeze.

Plus, join us in our booth for daily 10-minute mini-sessions during meeting breaks. We’ll be spotlighting a few new DNAnexus features, including compliance, collaboration and app building.

Wednesday – April 10th

10:00 am Instant Collaboration:
Compliance Meets Collaboration: Together at Last
Vince Ramey, Ph.D., Scientist, DNAnexus
3:30 pm App Building:
Build an App & Share With Your Team in 10 Minutes
Andrey Kislyuk, Ph.D., Sr. Engineer, DNAnexus

Thursday – April 11th

10:30 am App Building:
Build an App & Share With Your Team in 10 Minutes
Andrey Kislyuk, Ph.D., Sr. Engineer, DNAnexus
1:30 pm Instant Collaboration:
Compliance Meets Collaboration: Together at Last
Vince Ramey, Ph.D., Scientist, DNAnexus

Meet the new DNAnexus and its Configurable Cloud Infrastructure

dnanexus betaIt’s been a busy first week since we launched the beta of the new DNAnexus, our cloud-based DNA analysis platform designed for bioinformaticians. We’ve been blown away by the number of people who have signed up for the program and provided a lot of very positive and constructive feedback. We encourage all of our beta users to continue to comment on their experience. Request access today and see for yourself what it is all about.

 

configurable cloud infrastructureThis week we’d like to highlight one of the core capabilities of the new DNAnexus platform, the configurable cloud infrastructure, which lets you take full advantage of Amazon’s scalable and cost-effective Web Services. It not only allows you to scale your computational and data storage needs to any level, it is also fully scriptable and allows you to create an analysis solution that fits your specific needs. The benefit is eliminating capacity planning since you can now store and process any data on demand and only pay for what you use.

 

At DNAnexus we have always used the pay-as-you-go model for computational and storage services; this will continue with the new DNAnexus. The benefit of a pay-as-you-go approach is that you can cost-effectively address your needs today and scale up or down as those needs change. Whether you are familiar with or new to sequence data analysis, you can immediately get started with your data analysis projects without any setup costs or capacity planning risks — regardless of how many samples you might have. This is because the new platform, with its configurable infrastructure, processes samples in parallel, resolving resource contention issues among different teams.

 

When we set out to build the new platform, one of the most common requests we heard was for a fully configurable solution — allowing bioinformaticians and computational analysts the ability to run custom programs, tune compute performance through parallelization, and more. All of this is now possible with the new platform, through well-documented APIs and SDK, as these allow rich scripting for any data management, analysis, visualization, or reporting desires.

 

configurable genomics platform

Another advantage of this new infrastructure is that you can now manage and manipulate your data not only via the web interface, but also through the command-line, which is compatible with Linux and Mac OS X. The open and flexible new DNAnexus platform, with its SDK language support, allows you to run any tool in any language and perform platform operations through API bindings in Python, C++, Java, and the Bash Shell. This allows you to fully automate entire workflows from sequencing data upload to analysis and report generation. You may also create best practices workflows that can be easily shared with non-bioinformaticians within or across institutions.

 

In the weeks to come, we’ll explore the many additional capabilities of the new DNAnexus (e.g., the “Extensible Genomics Toolbox”, “Instant Collaboration”, and “Security and Compliance”). In the meantime, please take advantage of our beta program and sign up for your own account and explore firsthand what the new DNAnexus has to offer.

 

On the Scene at AMIA: Clinical Promise and Informatics Opportunities for Whole-Genome Sequencing

I recently got to attend the American Medical Informatics Association’s (AMIA) Joint Summits on Translational Science, held in nearby San Francisco. The event had tracks for both translational bioinformatics as well as clinical research informatics and served as a unique opportunity to hear about the informatics challenges that are being faced in the clinical realm right now.

Here are a few highlights from the talks I found particularly interesting:

Howard Jacob, director of the Human and Molecular Genetics Center at the Medical College of Wisconsin, gave a very charismatic talk on genome sequencing in the clinic. He told attendees the most compelling reason to use genome sequence with patients is that it’s family history with data. Jacob described an ongoing pilot whole-genome sequencing program at the college, noting that for a patient to be considered for the program, two physicians must nominate him or her and show that the sequencing would be actionable and “end a diagnostic odyssey.” Accepted patients must determine at the outset how much information they want to receive when returning results; some choose to know just the minimum, while others want to know about genetic variations for which we don’t yet understand the disease implications. Enrolled patients receive six to 10 hours of genetic counseling as part of the process.

Jacob said that with an 20% patient acceptance rate (16 out of 80) for the pilot program, clinicians are now eager to eliminate the approval process altogether to get their patients sequenced. To my surprise, four of the 10 cases submitted for insurance approval have gone through. Jacob added that as the cost continues to drop, it will be hard for clinicians not to use this approach for patients, especially for rare diseases and for pharmacogenomics decisions. (He noted that one lesson learned already is that clinical sequencing is not ready for common diseases, with the exception of cancer.) Jacob said the challenges in scaling up sequencing operations in the clinic will be: delivering adequate genetic counseling; selecting the most appropriate analytical tools for clinical sequencing; and determining who can order whole genome sequencing tests.

In another talk, Peter Tonalleto, a professor at the Center for Biomedical Informatics at Harvard Medical School, highlighted the medical opportunities associated with a patient’s genomic variation landscape. His research group is working on analysis pipelines for DNA sequencing, RNA-seq, microRNAs, and methylation. Those pipelines, coupled with preclinical and clinical variant annotation, yield application in areas such as risk prediction, tumor classification, and pathway analysis for alternative treatment approaches. He also noted a cost comparison his team did for a breast cancer project, in which standard practice cost about $19K and next-gen sequencing practice cost about $25K. With these costs finally being on par, Tonalleto told the audience that more clinicians at Harvard Medical School are eager to adopt whole genome sequencing for breast cancer patients.

In all, the conference offered valuable insight into how next-gen sequencing is being adopted in the clinic. It was clear from the talks I saw that clinicians are eager to embrace this new technology, despite the number of hurdles — including insurance reimbursement, approval processes, and technology learning curve — standing in the way. While there are a number of challenges to consider, I walked away from this conference feeling optimistic about the uptake of whole-genome sequencing in healthcare already.