The U.S. Cancer Moonshot and a Culture of Collaboration

Yesterday, United States Vice President Joe Biden hosted the National Cancer Moonshot Summit. Scientists, oncologists, donors, and patients convened for a daylong conference intended to pick up the pace of research towards curing cancer. Rather than focusing on one specific type of cancer, the conference broadly discussed more than 100 types of cancer; emphasizing strategies for prevention, early detection, wide access to treatment, and encouraging collaboration among researchers. You can read a first-hand account from our CMO, David Shaywitz, here.

As part of the Moonshot effort, DNAnexus, in partnership with PatientCrossroads, has committed to develop the Integrated Data Engagement Analytics (IDEA) platform to facilitate the collection, analysis, and sharing of genetic, proteomic, and EMR/phenotypic data to accelerate disease research. PatientCrossroads and DNAnexus are currently engaging in a pioneering effort to help patients obtain the raw genetic files and medical records and then integrate these data along with patient reported outcomes data obtained by PatientCrossroads on a secure and compliant platform that allows authorized researcher access to this information and use it to develop novel insights — the IDEA platform. You can review the complete list of public and private sector Cancer Moonshot commitments announced in the White House press release.

Here at DNAnexus, we are particularly devoted to reducing the technical barriers to accessing and working with research datasets.  We believe that a culture of openness in genomic research will lead to greater medical breakthroughs. Most data sharing in cancer genomics research has been centralized through rich, yet controlled-access databases like The Cancer Genome Atlas (TCGA) or International Cancer Genome Consortium (ICGC) — both of which properly approved researchers can easily access on the DNAnexus Platform. Read more about some of the genomic community collaborative initiatives DNAnexus is a part of: precisionFDA, open access cancer genomics pilot, and ICGC.


Once in a Blue Moon Competition: precisionFDA Truth Challenge

The FDA, the Global Alliance for Genomics and Health (GA4GH)  and National Institute for Standards and Technology (NIST) recently teamed up to create a once-in-a-blue-moon challenge for genomic scientists! Dubbed the precisionFDA Truth Challenge, genomic innovators were invited to test their informatics pipelines on two datasets, the well-characterized Genome in a Bottle’s (GiaB) NA12878 (HG001) reference sample and a new reference sample HG002, of which the results were unknown.


PrecisionFDA is an online, cloud-based, virtual research space where members of the genomics community can experiment, share data and tools, collaborate, and define standards for evaluating analytical pipelines. Community members span academia, industry, healthcare organizations and government.  All of these organizations are working together to further innovation and develop regulatory science around NGS tests. So far, the community currently includes more than 1,500 users across 600 organizations, with more than 10 terabytes of genetic data stored.

This is the second challenge issued through precisionFDA, following the precisionFDA Consistency Challenge.   The Truth Challenge is about discovering the consistency and accuracy of informatics pipelines when analyzing a human sample whose truth data is unknown. NIST and GiaB released the truth data May 26, 2016, after the close of the challenge.

What makes this challenge so exciting?

NIST released NA12878 in 2014, the first gold standard whole human reference genome, in collaboration with GiaB and the FDA. Since then,  it has arguably become one of the most studied biospecimens. Researchers from around the world use NA12878 as training data for assessing pipeline performance.

Since many pipelines use some sort of machine learning algorithm when trying to determine whether a reported mutation is real or not,  the difficulty that arises is ensuring a pipeline doesn’t overfit the training data. Pipelines can ultimately be tuned, in order to maximize performance on the training dataset, and if the test data happens to be similar to the training data the pipeline’s performance would be abnormally consistent and accurate. A great resource in understanding why scientists split data into train and test roles in order to assess the accuracy, reliability, and credibility of their predictive models (the algorithm that goes into a pipeline) can be found here.

In order to test performance of pipelines in real-life, scientists needed a second reference sample and associated truth callset of which NGS pipelines have not been trained on. This is exactly what NIST and GiaB have provided in reference sample HG002.

Scientists can now evaluate algorithms using test data that is separate from the training data, an attribute  that is broadly accepted as fundamental to the evaluation methodology. Moreover, unlike NA12878, the new reference sample HG002 is male, which poses new challenges to algorithms since there is only one copy of the X chromosome, and brings new opportunity for evaluating NGS methods along this dimension.

The winners

As the clock struck midnight EST on May 25, 2016, the precisionFDA Truth Challenge closed with 36 entries across 21 teams, spanning 5 countries;  truly an international competition of epic proportions!

The winners of the Truth Challenge will be announced at the upcoming Festival of Genomics in Boston on June 29th at 8:45am EST by Elizabeth Mansfield, PhD, Deputy Director for Personalized Medicine in FDA’s Center for Devices and Radiological Health’s Office of In Vitro Diagnostics and Radiological Health. Registration is free. Want to learn more about precisionFDA?  Stop by the DNAnexus booth (# 240)  during the Festival to receive a demo of the precisionFDA platform from a member of the precisionFDA team.

Want to recreate the Truth Challenge for yourself? Join the precisionFDA community today and evaluate a pipeline of your choice against HG002. Happy testing!

Webinar Series: Enabling PacBio Long-Read Bioinformatics in the Cloud

We are excited to be hosting, in collaboration with our partner PacBio, an inaugural webinar series focused on best practices for analyzing SMRT® Sequencing data.

De novo genome assembly and structural variant calling are complex tasks, which can require massive computational resources to weave long-reads into a final, polished assembly or run a variety of SV detection methods across multiple data types. Reference genome assembly is done far less frequently than whole genome sequencing, just as the case with SV detection vs. SNP detection.  DNAnexus and PacBio are collaborating to make tools and resources easily accessible and enabling researchers to take long-read bioinformatics to new heights. Learn about today’s best practices for PacBio sequencing data.

Session 1: Rapid Reference-Quality Genome Assembly
May 4, 2016
8:00am PST, 11:00am EST, 5:00pm CET


Brett Hannigan, PhD, Director, Scientific Partnerships at DNAnexus, will present how running FALCON on the DNAnexus Platform can provide a fast, accurate, and cost-efficient solution for de novo genome assembly. In this webinar, we’ll examine the challenges around assembling the tobacco genome (comprised of 4.5 billion base pairs), which is tetraploid in nature and highly repetitive.

Session 2: Simplifying Structural Variant Discovery
June 16, 2016
8:00am PST, 11:00am EST, 5:00pm CET


AndrewAndrew Carroll, PhD, Vice President, Science at DNAnexus will present how current solutions that use PacBio data can greatly improve the accuracy of SV-calling by using fast and easy to run cloud-optimized apps (PBHoney, Parliament, & Sniffles). We will also explore the current work we are doing with Genome in a Bottle (GIAB) to develop high confidence truth sets for structural variants. Finally, Andrew will discuss how sequencing coverage correlates with the ability to accurately call structural variants, to inform decisions about the ideal depth to sequence.

Who should attend?
Researchers currently working with or those who desire to work with PacBio RSII and/or Sequel data.