The collaboration will accelerate AI innovation for genomics and precision health in Canada

Toronto, Ontario – April 16, 2024  – Today, DNAstack is proud to announce its Bronze sponsorship with the Vector Institute, a globally-renowned AI Institute that empowers researchers, businesses and governments, to develop and adopt AI responsibly. This union between industry and academia will serve to amplify the shared goal of accelerating AI-based innovation in Canada.

DNAstack develops software that is helping scientists make breakthrough discoveries in genomics and health research. Omics AI, DNAstack's flagship software suite, makes it possible to derive AI-powered insights across global networks of data, without needing to bring it all into one place. This system is being used by world leading pharmaceutical companies, hospitals, universities, patient advocacy groups, funders, sequencing facilities, government agencies, and consortiums to grow collaborative networks in diverse areas of research.

The partnership with Vector will help DNAstack continue to innovate by tapping into Vector’s research community to address challenges at the frontiers of machine learning and natural language processing. DNAstack will also leverage the institute’s talent pool and engage in Vector’s collaborative projects, workshops, and seminars to foster local growth in the field.

“Artificial intelligence is fundamentally transforming how we approach biomedical research and discoveries in ways that are rapidly accelerating our ability to understand and treat disease with molecular precision,” said Marc Fiume, CEO of DNAstack. “Our partnership with Vector Institute allows us to strengthen our technology and further cement Canada’s presence as a world leader in AI research and implementation.”  

“We are thrilled to welcome DNAstack to our Bronze sponsor community,” said Cameron Schuler, Vector’s Chief Commercialization Officer & VP, Industry Innovation. “Through this collaboration, we hope to give health clinicians and researchers better access to the diverse data collected by health systems without compromising patient privacy, ensuring that we can achieve optimal health outcomes for all.”

About DNAstack

DNAstack is a Canadian company whose mission is to save and improve lives by unlocking the collective power of the world’s genomics and health data. Omics AI is a software suite by DNAstack that enables privacy-preserving federated insights across distributed data. DNAstack is a global leader in the development of open, interoperable standards as part of the Global Alliance for Genomics & Health (GA4GH).

About the Vector Institute

Launched in 2017, the Vector Institute works with industry, institutions, startups, and governments to build AI talent and drive research excellence in AI to develop and sustain AI-based innovation to foster economic growth and improve the lives of Canadians. Vector aims to advance AI research, increase adoption in industry and health through programs for talent, commercialization, and application, and lead Canada towards the responsible use of AI. Programs for industry, led by top AI practitioners, offer foundations for applications in products and processes, company-specific guidance, training for professionals, and connections to workforce-ready talent. Vector is funded by the Province of Ontario, the Government of Canada through the Pan-Canadian AI Strategy, and leading industry sponsors from across multiple sectors of Canadian Industry.

Read the announcement on targetals.org

Scientists worldwide can access and analyze comprehensive datasets to drive biomarker and therapeutic discovery for the disease

Toronto, ON – April 2, 2024 – Target ALS, a nonprofit organization that breaks down barriers to accelerate research for Amyotrophic Lateral Sclerosis (ALS), has launched a first-of-its-kind data portal to provide no-strings-attached access to comprehensive datasets and analysis tools to fuel discovery of treatments and biomarkers for ALS.

Through the portal, researchers worldwide can access well-characterized data collections from Target ALS’ Scientific Core Facilities, including postmortem tissue, longitudinal biofluids, and stem cells. Data can be mined for multi-omic analysis to identify novel pathological and genetic biomarkers of both sporadic and genetic forms of ALS and their progression. As with all work supported by Target ALS, researchers will retain full rights to any intellectual property stemming from their discoveries. Access to the data is free, and information on storage, compute, and data management fees is available on the portal.  

New data will be uploaded every 4-6 months. Currently, the Postmortem Tissue Collection is available and contains unique datasets generated using state-of-the art methodologies including whole genome sequencing, spatial and bulk transcriptomics, semi-quantitative histopathology, digitized images of pTDP43 staining, and clinical and demographic data from 260 ALS cases, Frontotemporal Dementia (FTD) cases, and non-neurological controls. The Natural History Study and Stem Cell Collections will be launched on May 1, 2024.

The Target ALS data portal is powered by DNAstack’s Omics AI software suite. Omics AI provides researchers a new way of unveiling discoveries while simultaneously making it easier for data stewards to improve the accessibility of their datasets. Instead of following the traditional model of “data sharing”, the Omics AI-powered data portal follows a new paradigm of “data federation” where researchers keep their data in place, and allow for questions to be queried across a network of data. This approach is faster, more secure, and compliant with open standards, while also empowering data contributors to retain sovereignty, control, and measure impact of their data. “We believe that data drives discoveries, yet, too often, researchers cannot access large or diverse enough data to answer questions,” said Marc Fiume, PhD, Chief Executive Officer at DNAstack. “We are thrilled to collaborate with Target ALS to help amplify the impact of data with a shared vision to accelerate a path to effective treatments.”

Verily Workbench is a collaborative research environment for governing and analyzing global multimodal biomedical data. Target ALS uses Verily Workbench for secure access and analysis of multimodal ALS data, in order to advance understanding of the disease and accelerate treatments. “We are proud to partner with Target ALS to broaden access to high quality ALS data, with the goal of accelerating biomarker discovery and treatment development,” said Andrew Trister, M.D., PhD, Chief Medical and Science Officer at Verily. “Through the use of Workbench, researchers will have access to the world’s most comprehensive ALS datasets, and will be able to collaborate on analyses to advance their understanding of the disease.”

To ensure the best possible functionality and ease of use, Target ALS invited several scientists from academia and industry to test the portal and provide feedback. “The Target ALS Data Portal provides a convenient central platform to access the consortium’s transcriptomic, genetic, and clinical data in an analysis-ready environment. This platform will broaden access throughout the scientific community, to arguably the largest postmortem -omics repository in ALS/FTD, accelerating research in these devastating diseases,” says Dwight Newton, Ph.D., Sr. Computational Biologist at Roche Canada.

Since its founding, Target ALS has been committed to breaking down barriers that traditionally limit scientific innovation. In addition to providing grants for cutting-edge research, the organization generates and optimizes critical tools and resources, like the data portal, for scientists to advance their work. “Target ALS’ innovative model provides researchers with holistic support to accelerate their ideas toward the clinic,” says Manish Raisinghani, M.B.B.S., Ph.D., President and CEO of Target ALS. “Access to comprehensive data will enable greater understanding of ALS and fully realize the potential impact of emerging technologies like artificial intelligence and machine learning on therapeutic development.”

Learn more and access the Target ALS Data Portal at dataportal.targetals.org.

About Target ALS

Target ALS is a 501(c)(3) medical research foundation breaking down barriers to accelerate research for Amyotrophic Lateral Sclerosis (ALS) and realize a world where everyone with ALS lives. Founded in 2013 by former New York City deputy mayor Dan Doctoroff — who lost both his father and uncle to ALS and was himself diagnosed in 2021 – Target ALS has transformed ALS research through their landmark Innovation Ecosystem model. The organization has fostered unprecedented collaborations between academia and the pharma and biotech industry, lowered barriers to access for critical research tools, and become a hub of communication and networking for the worldwide scientific community, resulting in the launch of 7 clinical trials and dozens of drug discovery programs over the last decade. For more information and to get involved, visit www.targetals.org.

About DNAstack

DNAstack is a Canadian company whose mission is to save and improve lives by unlocking the collective power of the world’s genomics and health data. Omics AI is a software suite by DNAstack that enables privacy-preserving federated insights across distributed data. DNAstack is a global leader in the development of open, interoperable standards as part of the Global Alliance for Genomics & Health (GA4GH).

About Verily

Verily is an Alphabet health technology company focused on research, care, and health financing to deliver on the promise of precision health and help people live healthier lives. We are uniquely positioned at the intersection of technology, data science, and healthcare to create tools to accelerate evidence generation, products to enable more personalized care, and approaches to make costs more predictable. For more information about Verily please visit verily.com or reach out to learn more about how Viewpoint Workbench can accelerate research.

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Today, we’re excited to announce a new ISO standard, Requirements for interoperable systems for genomic surveillance. Genomic surveillance combined with rapid realtime data sharing is the most important tool we have for detecting and stopping the spread of infectious diseases, like COVID.

Throughout the COVID pandemic, we had the privilege of working together with our provincial and federal government to implement a solution for tracking and sharing information on variants of concern. It became clear that the centralized model of data sharing is fraught with issues — it makes data linkage difficult and causes significant time delays, misaligned incentives, and data hoarding. Centralization just doesn’t work at national or planet scale.

This document describes design principles and the service and standards requirements to enable an interoperable system for federated genomic surveillance. It represents a vision, shared by our partners, for the future of pandemic prevention.

Download the Requirements for interoperable systems for genomic surveillance document from the ISO website.

Toronto, Ontario — DNAstack today announced the launch of Workflows, a marketplace for data analysis pipelines.

Workflows makes it easier and safer for scientists to discover and run trusted, high-quality, reproducible computational pipelines for analyzing omics data. The marketplace includes a curated collection of best practices pipelines for processing data from popular sequencing instrument manufacturers, including PacBio, Illumina, and Oxford Nanopore. Workflows integrates with Workbench, a workflow execution manager by DNAstack, unifying the experience of performing omics data analyses across multiple sequencing instruments and cloud computing platforms.

Browse Workflow

The path to personalized care

Sequencing instruments are generating increasing volumes of genomics, transcriptomics, and epigenomics data with unprecedented resolution, throughput, cost-efficiency, and accuracy. These optimizations promise to accelerate the pace of discovery and the path to using individualized omics profiling to personalize care.Data from sequencing experiments, which can be hundreds of gigabytes per sample, first need to be processed using computationally intensive software pipelines before they can be used to inform research and clinical practice. Because of variability between manufacturers, instruments, protocols, read lengths, and accuracy, there are many instrument-specific “best practices” pipelines needed to normalize sequencing data into standard outputs, like variant calls (i.e. the set of genetic differences in sequenced individuals).

Introducing Workflows: a marketplace for omics pipelines

Workflows is a marketplace for high quality omics data analysis pipelines, starting with a curated collection of best practices pipelines for processing sequencing data from PacBio, Illumina, and Oxford Nanopore instruments. Pipelines in the marketplace are organized by manufacturer and are annotated with detailed documentation, tags, and environments they have been tested on. Many of the pipelines added to the marketplace have been authored from scratch and tested for reproducibility on Microsoft Azure, Amazon Web Services, Google Cloud Platform, and on premises.

Unifying the data analysis experience across sequencing instruments and clouds

Workflows integrates with Workbench, a workflow execution manager that is part of DNAstack’s Omics AI platform, so that pipelines from the marketplace can easily be run on private data within a customer’s own environment. The combined solution provides a single, unified experience for managing analyses across multiple sequencing instruments and cloud computing platforms.

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"The complexity of performing omics data analysis has been a bottleneck to unlocking the full potential of omics data to transform care. Similar to how Google’s Android operating system unifies the end-user experience across different smartphone devices, our vision is to unify the experience of doing omics data analysis across different  sequencing platforms and cloud computing environments."

Powered by open standards

Following the company’s commitment to open science and interoperability, DNAstack has authored the pipelines in the platform agnostic Workflow Description Language (WDL) and published them as open source. The pipelines can be run in compliance with standards developed by the GA4GH, the de facto international standards body for genomics and related data, and in adherence with international privacy regulations like PIPEDA, HIPAA, and GDPR.

Built in collaboration with algorithm developers and sequencing manufacturers

To develop and test the pipelines, DNAstack worked directly with award winning algorithm developers, like Sentieon, and sequencing instrument manufacturers, like PacBio.

Read Case Study

"We are excited to see PacBio’s data analysis pipelines available in Workbench. These pipelines follow internationally recognized open standards, making it faster and easier than ever before for our customers to go from data to discovery. DNAstack’s team helped us confirm our product would meet the needs of customers and live up to the vision of WDL standards."

Get started with Workflows

Workflows is a free online marketplace for omics analysis pipelines that is available starting today. Visit omics.ai to browse pipelines and request access to Workbench. Most pipelines are free to run. Sentieon pipelines require purchase of a third-party license. Contact info@dnastack.com for questions, support, and partnership opportunities.

About DNAstack

DNAstack is a Canadian company whose mission is to save and improve lives by unlocking the collective power of the world’s genomics and health data. Omics AI is a software suite by DNAstack that enables privacy-preserving federated insights across distributed data. DNAstack is a global leader in the development of open, interoperable standards as part of the Global Alliance for Genomics & Health (GA4GH).

Toronto, Ontario — DNAstack today launched Omics AI, a revolutionary new software suite for omics and health research.

Omics AI makes scientific discoveries faster and more powerful by enabling insights across federated networks of data, in compliance with open standards by the Global Alliance for Genomics & Health (GA4GH). The system is being used by world leading pharmaceutical companies, hospitals, universities, patient advocacy groups, funders, sequencing facilities, government agencies, and consortiums to grow collaborative networks in diverse areas of research.

Omics data are distributed

Data fuel discoveries. Yet, too often, scientists and decision makers cannot access large or diverse enough data to answer their questions. This is because the data they need are siloed across many different institutions, provinces, states, countries, clouds, devices, and software systems. Siloization makes it nearly impossible to leverage the collective power in the world’s exponentially growing number of omics and health datasets to make discoveries. 

The future is federated

Omics AI enables a new way of making discoveries that simultaneously makes it easier for data stewards to make their datasets more accessible, while making it easier for researchers to access and analyze more data than ever before. Instead of following the traditional model of “data sharing” where data contributors send data to researchers, Omics AI follows a new paradigm of “data federation” where researchers send questions to contributors. Each contributor in the federated network can approve researchers to ask specific questions in a privacy-preserving way while keeping sensitive data private. This approach is faster, more secure, scalable, and compliant, while empowering data contributors to retain sovereignty, control, measure impact, and enforce attribution.

How it works

Omics AI is a suite of three software products for creating standards compliant federated networks and running analyses across them. Publisher helps data stewards maximize the impact of their data, wherever it lives. It makes it easy to connect, organize, manage access, standardize, and register datasets with networks powered by Explorer. Explorer is a federated data portal. It provides a unified user experience for finding, accessing, and searching across federated networks, and analyzing them with analytics tools like Workbench. Workbench helps scientists turn data into discoveries. It enables scientists to run analyses across distributed datasets. This includes the capability to perform federated learning with toolkits like integrate.ai, which train AI/ML models without moving sensitive data between systems. The end-to-end software suite is compliant with GA4GH standards with support for multiple cloud platforms, Microsoft Azure, Amazon Web Services, and Google Cloud, as well as on premises.

An internet for omics and health discoveries

Omics AI builds on the award-winning efforts by DNAstack and its partners to deliver Viral AI and Neuroscience AI, global federated networks for infectious disease and neuroscience research. Now, with Omics AI, anyone can create public and private networks of their own. The launch of these products demonstrates continuity in DNAstack’s vision to make research more collaborative, diverse, accessible, equitable, sovereign, sustainable, and impactful.

Taking technology to the fight

DNAstack has partnered with world-leading organizations who are using Omics AI to create collaborative networks to help address some of the biggest challenges in human health.

Aligning Science Across Parkinson’s

Aligning Science Across Parkinson's (ASAP) is a funding initiative with a mission to accelerate the pace of discovery and inform the path to a cure for Parkinson’s disease through collaboration, research-enabling resources, and data sharing. In pursuit of this, The Michael J. Fox Foundation (MJFF) stands as a trusted implementation partner for ASAP, who is using Omics AI to power the ASAP Collaborative Research Network (CRN) Cloud platform.

Target ALS

Target ALS is a medical research foundation committed to the search for effective treatments for Amyotrophic Lateral Sclerosis (ALS). Founded in 2013 by former New York City deputy mayor Dan Doctoroff, Target ALS has transformed ALS research through their landmark Innovation Ecosystem model. The organization aims to accelerate ALS drug discovery with the goal of realizing a world in which everyone lives. Target ALS is using Omics AI to power their data portal, a platform that will accelerate data sharing, discoveries, and translational impact by a global community of ALS researchers

Roche Canada

Hoffman-La Roche Ltd. (Roche Canada) is a biotech company focused on discovering new medicines and diagnostics while establishing data-based insights that evolve the practice of medicine to help patients live longer, better lives. Roche Canada is using Omics AI to share data from clinical trials with a network of trusted researchers and leaders in neuroscience. Through efforts like federated insights, Roche Canada is demonstrating that additional value can be generated from existing data, ultimately leading to a better understanding of disease and more rapid development of patient solutions.

Canadian Platform for Genomics & Precision Health

The Canadian Platform for Genomics & Precision Health is an initiative funded with federal support through DIGITAL. The collaboration brings together Canadian and international leaders in genome science, artificial intelligence, genome sequencing, pharma, research funding, policy, and ethics on an aligned mission to create national, federated, standards compliant data infrastructure for omics and health. As part of this initiative, Omics AI is supporting multiple use cases to create and grow inter-provincial, national, and international networks.

Powered by open standards 

Omics AI is unique in that it can enable federated insights in compliance with open standards developed by the GA4GH, the de facto international standards body for genomics and related data. The system aligns with FAIR Principles by making scientific data more findable, accessible, interoperable, and reusable, while enabling data stewards and consumers to adhere to international privacy regulations like PIPEDA, HIPAA, and GDPR.

Get started today

Omics AI is available for general use starting today. For more information or to request access, visit https://omics.ai or contact info@dnastack.com.

About DNAstack

DNAstack is a Canadian company whose mission is to save and improve lives by unlocking the collective power of the world’s genomics and health data. Omics AI is a software suite by DNAstack that enables privacy-preserving federated insights across distributed data. DNAstack is a global leader in the development of open, interoperable standards as part of the Global Alliance for Genomics & Health (GA4GH) and has led multiple collaborative innovation projects as part of DIGITAL.

DNAstack CEO Dr. Marc Fiume speaks with Geraldine Van der Auwera and Michael de la Maza about the company's products and vision for the future of genomics and health research.

DNAstack CEO Marc Fiume accepts the LSO Company of the Year Award, introduced by Dr. Catalina Lopez-Correa, CSO at Genome Canada.

Thank you very much Alison.

Good evening everyone! Thank you very much for taking the time to be here tonight to celebrate Ontario’s life sciences community. The province of Ontario is home to world leading talent in life sciences – and it’s a big honour for us to be named this year’s Company of the Year.

I’m accepting this award on behalf of our entire team – who are some of the most passionate and talented people I’ve ever worked with. At DNAstack, we are on a relentless mission to improve health outcomes for millions of Ontarians, Canadians, and global citizens by better connecting the world’s genomics and health data.

I’d like to acknowledge a few people who have been instrumental to our success:

• Ryan Cook, my co-founder, who always inspires us to think big and prioritize impact, including our decision to divert as many resources as we could to support our country’s response to COVID.
• Jim Vlasblom and Miro Cupak, our technical co-founders, who joined DNAstack when it was just an idea. Jim and Miro wrote the very first lines of code from a tiny office on College St. that had no air conditioning.
• Peter Zakarow, who has been essential in operationalizing our strategy, both in Ontario and across Canada.
• And Peter Goodhand, CEO of the Global Alliance for Genomics & Health, who has been one of our best friends and mentors over the past decade.

93% of health data that patients contribute to research is not shared!

And it takes an average of 17 years for research evidence to be translated into clinical practice.

This is too slow.

From detecting infectious disease outbreaks, to improving crop yields, to better understanding neurodiversity, and finding cures for rare and complex diseases – we believe that real-time, global sharing of genomic and health data is critical to accelerate innovation across the life sciences.

Throughout the pandemic, we had the honor of serving our province and country, where – as Catalina mentioned – we worked together with government, funders, hospitals, academia, industry, and other innovators to deliver the world’s first international, federated network for genomic surveillance. Seemingly overnight, the pandemic galvanized our mission and helped break through traditional barriers to collaboration, in the face of a common threat.

1 in 15 children are diagnosed with rare disease. 1 in 6 people live with a neurological condition. And 1 in 4 Canadians die from cancer.

There is a massive, timely opportunity for us to improve these odds.

Creating systemic change in healthcare will require support and collaboration across many stakeholders. While there is still a lot of work to do, we believe that Ontario has all the ingredients needed to to revolutionize our health system and drive better outcomes for our children, our families, and each other.

We are very grateful to be a partner with you all on this journey.

Thank you.

Neuroscience AI will enable researchers to make discoveries from larger and more diverse datasets than ever before.

Toronto, Ontario — DNAstack and partners today launched Neuroscience AI, a new federated platform for collaborative neuroscience research. By enabling privacy-preserving AI-powered insights across distributed networks of data, Neuroscience AI will enable researchers to make discoveries from larger and more diverse datasets than ever before. The platform is being used to advance collaborative research in autism by connecting global members of the Autism Sharing Initiative.

With Neuroscience AI, researchers now have access to a large and growing network of high value datasets through beautiful, unified user and command line interfaces.

Towards a national strategy for autism

Autism, or sometimes called autism spectrum disorder, refers to a broad range of conditions characterized by differences with social skills, repetitive behaviours, speech and nonverbal communication. It can be understood as a lifelong neurodevelopmental difference in which autistic people perceive the world, think, and interact with others in unique ways. There are a number of conditions that may co-occur with autism such as epilepsy, anxiety, sleep disorders, learning disabilities, and digestive hypersensitivities that can significantly affect quality of life. Each person on the autism spectrum has a distinct set of strengths and differences. There is not one autism but many subtypes, influenced by a combination of genetic and environmental factors.

A recent CDC report published in March 2023 suggests that autism is even more prevalent than previously thought, with 1 in 36 children (2.7%) being diagnosed in the USA. Canadian data from 2019 indicated a prevalence of 1 in 50 (2%). Experts say that estimates of autism prevalence are rising due to increased understanding, better diagnostics, genetics, and other factors.

On March 30th 2023, the Canadian House of Commons passed the Federal Framework on Autism Spectrum Disorder Act. The bill mandates the development of a national strategy to support autistic Canadians, their families, and their caregivers, and calls for the establishment of a national research network to promote research and improve data collection.

"The Federal Framework on Autism Spectrum Disorder Act is a critical step towards providing better support and services for autistic individuals and their families. By developing a framework that will include a national research network, we can improve our understanding of autism and its co-occurring conditions, and ultimately work towards delivering more personalized and effective care,” said Jill Farber, Executive Director at Autism Speaks Canada. “Neuroscience AI will help unlock the potential of big data and artificial intelligence to help optimize outcomes for autistic people.”

Enabling a new era of precision health

Precision health refers to a new kind of healthcare that tailors services and treatments to individuals based on in-depth analysis of their genes, biology, demographics, and environment. In the context of autism, precision health creates the opportunity to better understand subgroups of autism, leading to more individualized care with the end goal of creating better outcomes for autistic individuals.

A key challenge to enabling precision health in autism is that the core attributes and co-occurring conditions are broad and complex. Researchers therefore need to collect and analyze large, diverse, and multifaceted datasets, which are not readily available. Many research studies focus on one condition at a time, with narrowly defined cohorts. To complicate matters, these datasets are siloed across many different institutions, databases, cloud providers, and regions. Being able to combine data across all these systems and geographies, while covering a range of related conditions, has the potential to dramatically increase the power of the global research enterprise to make data-driven discoveries.

Neuroscience AI: Increasing the power of research through federated learning

Neuroscience AI increases the power of global research by streamlining the ability to perform federated learning, a new technique that makes it possible to derive insights across distributed networks of data in a privacy-preserving way. Federated learning works by aggregating the results of analyses that run within controlled environments where data are stored. Compared to the alternative approach of centralized “data sharing”, federated systems are faster, more efficient, secure, scalable, and compliant, and allow data stewards to retain control, measure impact, and automate attribution. The federated design of Neuroscience AI came out of extensive engagement with stakeholders, including participant advocacy groups, families, and individuals, who expressed the need for new techniques that promote more diversity, inclusion, privacy, and autonomy in research.

“The ability to explore multiple datasets from different jurisdictions will give us both the volume and diversity of data to have the power to make transformative discoveries for the lives of kids, youth, and adults with developmental differences and disabilities,” said Dr. Evdokia Anagnostou, Vice President of Research and Director of the Bloorview Research Institute at Holland Bloorview Kids Rehabilitation Hospital. “Crucially, doing so without having to move the data from local environments will enable us to respect the requests of various communities to protect their privacy and confidentiality.”

Data stewards can use Neuroscience AI to increase the impact of datasets by registering them with the network. DNAstack provides software for stewards to easily integrate, harmonize, organize, protect, and register new datasets. Data consumers can, in turn, accelerate their research by discovering, accessing, and analyzing data connected to the network. DNAstack also provides software for researchers to analyze the large and growing universe of data on the network through simple user and programmatic interfaces within popular data science frameworks. 

“Neuroscience AI has created the opportunity to conduct secure, inter-institutional, multivariate and integrative data analyses,” said Kristina Calli, Project Manager for the iTARGET Autism Initiative at the University of British Columbia. “This means that our one-of-a-kind multi omic data resource called ASDbase, which includes whole genome, exome, metabolome and meticulously captured mind and body whole phenome, clinome and family history data, will remain securely stored in our own research facility and the de-identified data is made accessible to approved collaborators for use in other studies. This will not only enable novel genome-wide and phenome-wide association studies but will also benefit critical independent validation of each of our own study findings within an expanded cohort of data.”

Neuroscience AI is unique in that it can perform federated learning in compliance with open standards developed by the Global Alliance for Genomics & Health (GA4GH), the de facto international standards body for genomics and related data. The system aligns with FAIR Principles by making scientific data more findable, accessible, interoperable, and reusable, while enabling data stewards and consumers to adhere to international privacy regulations like PIPEDA, HIPAA, and GDPR.

A blueprint for the future of collaborative discovery

Researchers can already start using Neuroscience AI to analyze over 50 public and controlled access datasets related to autism, Alzhiemer’s, Parkinson’s, and other areas of research. Organizations such as Autism Speaks, The Centre for Applied Genomics (TCAG) at The Hospital for Sick Children (SickKids), and University of British Columbia have connected data to the network, with Hoffmann-La Roche Limited (Roche Canada), Ontario Brain Institute, Molecular You, and others coming online soon. The ecosystem will become more powerful over time, as each new dataset and researcher that joins the network creates opportunities for new cross-analyses and associations to be made.

DNAstack collaborated with Autism Speaks Canada, the Pacific Autism Family Network, and AIMS-2-TRIALS in the development of Neuroscience AI to gather and implement feedback from members of the autism community. Including the views of autistic adults, family members, and carers will continue as the platform develops.

Neuroscience AI builds on the award-winning effort by DNAstack and partners from previous projects to deliver Viral AI, the first federated network for international genomic surveillance of infectious diseases like COVID, and demonstrates continuity of the company’s vision of making global research more diverse, equitable, inclusive, sovereign, sustainable, and impactful.

“Neuroscience AI follows our blueprint for creating the future of global collaborative research,” said Dr. Marc Fiume, CEO at DNAstack. “We believe the next generation of discoveries, clinical trials, and healthcare will be enabled by building federated ecosystems that can work together to deliver deeper insights and better outcomes for individuals and families faster than ever before.”

DNAstack and its collaborators are excited to invite data stewards and researchers to join this groundbreaking effort. For more information, visit neuroscience.ai or contact info@dnastack.com.

About DNAstack

DNAstack is a Toronto-based company whose mission is to save and improve lives by unlocking the collective power of the world’s genomics and health data. DNAstack’s software platform enables a global community of stakeholders — including precision medicine initiatives, research consortiums, participant advocacy groups, hospitals, startups, funders, pharma companies, governments, and citizens — to connect and analyse distributed datasets without moving them. DNAstack is a global leader in the development of open, interoperable standards as part of the Global Alliance for Genomics & Health (GA4GH) and has led multiple collaborative innovation projects as part of the Digital ecosystem.

Neuroscience AI was developed with co-investment from Digital and in collaboration with AIMS-2-TRIALS, Autism Speaks, Autism Speaks Canada, Centre for Genomics and Policy at McGill University, Excelar Technologies, Hoffmann-La Roche Limited (Roche Canada), Holland Bloorview Kids Rehabilitation Hospital, The Centre for Applied Genomics (TCAG) at The Hospital for Sick Children (SickKids), Molecular You, Ontario Brain Institute, Pacific Autism Family Network (PAFN), and University of British Columbia.

The new project will help expand federated, AI-powered insights across distributed networks of genomics and health data. 

Toronto, Ontario — Today, a Canadian consortium led by DNAstack is announcing the launch of a new project to expand the development of a software platform to enable federated, AI-powered insights across networks of genomics and health data. The Canadian Platform for Genomics & Precision Health (CP4GPH) is a $14.5M initiative co-funded by Digital that brings together domain experts with a shared vision to deliver better outcomes for Canadians by making it easier to connect and analyze exponentially growing volumes of distributed genomics and health data. The project builds upon the multi-award-winning software platform developed by its partners as part of previous collaborations.

In order to make insights that will transform care, scientists and decision makers need data. These datasets are currently siloed between many different institutional, regional, and national systems, making it impossible to leverage their collective power to make discoveries. The traditional approach of centralized “data sharing” is not suitable because uploading copies of large and sensitive information to one datacenter is not fast, efficient, scalable, secure, or compliant, and does not empower individuals and organizations to retain control of their data, measure impact, or enforce attribution.

The solution being developed by the CP4GPH directly addresses this problem. It enables privacy-preserving “federated insights”, where questions can be answered by analyzing distributed datasets without moving them. All data remains in place and so, instead of “moving data to the question” this new approach “moves questions to the data”. This is faster, more efficient, secure, scalable, and compliant, while allowing individuals and organizations to retain control of their data, measure impact, and automate attribution.

With this new platform, health data stewards can easily connect datasets into distributed networks and grant permissions for data consumers to be able to derive privacy-preserving federated insights across them. The system is being built in compliance with FAIR principles, open standards (e.g. GA4GH, FHIR), international privacy regulations (e.g. PIPEDA, HIPAA, GDPR), and is deployable within commercial cloud and HPC environments. The platform will be used to create and grow provincial, national, and international networks in neuroscience, oncology, rare disease, infectious disease, health care, and agriculture.

“We believe that the future of genomics and precision health can only be achieved through collaborative innovation and discovery. With federated insights, we can finally break down the barriers that have traditionally prevented hospitals, researchers, clinical labs, governments, pharma, and other innovators from working together to unlock the full potential of data in a secure and privacy-preserving way,” said Dr. Marc Fiume, CEO at DNAstack. “We are excited to be at the forefront of this transformation, and to be working with incredible partners to push the boundaries of what is possible.”

This initiative combines world-leading expertise in software engineering, artificial intelligence, machine learning, cloud computing, genome sequencing, research, patient advocacy, health care, public health, diagnostics, therapeutics, standards, and policy. Project partners include Autism Speaks, Autism Speaks Canada, Cyclica, DNAstack, Genome Canada, Hoffmann-La Roche Limited (Roche Canada), Holland Bloorview Kids Rehabilitation Hospital, integrate.ai, McGill University, PacBio, the Public Health Agency of Canada, The Hospital for Sick Children (SickKids), and University of New Brunswick, advised by Genome Alberta, Genome Atlantic, Genome BC, Genome Prairie, Génome Québec, Global Alliance for Genomics & Health (GA4GH), and Ontario Genomics.

For more information, contact info@dnastack.com.

About DNAstackDNAstack is a Toronto-based company whose mission is to save and improve lives by unlocking the collective power of the world’s genomics and health data. DNAstack’s software platform enables a global community of stakeholders — including precision medicine initiatives, research consortiums, patient advocacy groups, hospitals, startups, funders, pharma companies, governments, and citizens — to connect and analyze distributed datasets without moving them. DNAstack is a global leader in the development of open, interoperable standards as part of the Global Alliance for Genomics & Health (GA4GH) and has led multiple collaborative innovation projects as part of Digital.

About Digital

Ahead of the curve starts here. Digital grows Canadian businesses and anchor enterprises through the development, adoption and deployment of Canadian-made digital technologies that keep Canadians healthy, address climate change and drive economic productivity. Through a powerful model that combines cross-sector collaboration, IP creation, digital talent development and results-based co-investment, we unlock the potential of Canadian industry to lead and succeed in the digital world. For more information, visit: https://www.digitalsupercluster.ca/

Award recognizes Toronto company’s global impact on genomics and health research.Toronto, Ontario — Today DNAstack was named 2023 Company of the Year by Life Sciences Ontario (LSO). The award celebrates DNAstack’s breakthrough software platform, which enables AI-powered insights across distributed genomics and health data. The platform is being used to support global pandemic surveillance and to advance better outcomes in neuroscience, oncology, and rare disease. The LSO Company of the Year award is given to an outstanding Ontario-based company that has demonstrated strong leadership in advancing innovative technology in the life sciences. DNAstack was also recently selected for the Technology Pioneer Award by the World Economic Forum as one of the world’s most innovative companies.The timing of this innovation could not be better, as stakeholders across the industry — including government, funders, academics, pharma, hospitals, and citizens — demand more impactful use of national genomics and health data. Health data are large, sensitive, and regulated, and as a result are often siloed and disconnected across different software systems, institutions, provinces, and countries. DNAstack directly addresses this challenge by making it possible to connect and derive insights across federated networks without needing to move data. This makes it possible for collaborators to work together to analyze larger volumes of more diverse datasets while protecting patient privacy. This technology is breaking through traditional barriers and aligning stakeholders across institutional, provincial, and national boundaries to collaborate on common goals — from tracking the evolution of emerging pathogens, to understanding the molecular causes of disease, optimizing diagnostic and treatment pathways, and measuring the efficacy of national healthcare delivery.“DNAstack has re-imagined the future of discovery in genomics and health,” said Jason Field, CEO of LSO. “Their approach to driving insights across national and international data networks in a privacy preserving way promises to modernize health data management and accelerate discoveries by innovators across the life sciences ecosystem.”“Ontario is home to world-leading expertise in genomics research and AI. We are honoured to be recognized by the LSO as Company of the Year,” said Marc Fiume, CEO of DNAstack. “With this technology, we are re-thinking the use of genomics health data in a way that is more scalable, secure, sovereign, and impactful. This is a significant step in our mission to save and improve lives by unlocking the collective power of the world’s genomics and health data.”About DNAstackDNAstack is a Toronto-based company whose mission is to save and improve lives by unlocking the collective power of the world’s genomics and health data. DNAstack’s software platform enables a global community of stakeholders — including precision medicine initiatives, research consortiums, patient advocacy groups, hospitals, startups, funders, pharma companies, governments, and citizens — to connect and analyze distributed datasets without moving them. DNAstack played an important role supporting provincial and national responses to COVID, where it partnered with the Province of Ontario and Genome Canada to provide a solution called Viral AI to help identify, track, and model the spread of variants of concern. DNAstack is a global leader in the development of open, interoperable standards as part of the Global Alliance for Genomics & Health (GA4GH) and has led multiple collaborative technology innovation projects as part of the Digital Supercluster.About Life Sciences OntarioLife Sciences Ontario is a member-driven organization that represents and promotes the province’s vibrant and diverse life sciences sector. LSO collaborates with governments, academia, industry, and other life science organizations in Ontario and across Canada to promote and encourage commercial success throughout the sector. Membership in Life Sciences Ontario includes individuals, students, emerging companies, investors, service providers, and companies with marketed products. The organization provides a wide range of networking and educational events, and operates a mentorship program that is helping to develop highly-skilled talent and build new business opportunities for the life sciences sector. LSO is an effective conduit for delivering policy options to governments, and is dedicated to promoting Ontario’s life sciences sector internationally..

David Miller, PacBio VP of product marketing, highlighted the company’s partnerships, including with Hamilton, Miroculus, the Broad Institute, Twist Biosciences, Google Health, DNAnexus, and DNAstack, for various companion offerings to enhance its sequencing workflow.

Publication in Cell on the genomic architecture of autism from comprehensive genomic analysis of over 11,000 individuals.

DNAstack CEO Marc Fiume presents a vision for an Internet for Pandemic Surveillance at the 10th Plenary Meeting of the Global Alliance for Genomics & Health (GA4GH) in Barcelona, Spain.

DNAstack CEO Dr. Marc Fiume spoke with Angie Seth of CTV on his vision for an Internet for Pandemic Surveillance.

DNAstack drives medical breakthroughs with its federated data discovery and analysis platform built on open standards.  The company was selected for establishing federated data networks and powering insights in pandemic surveillance, neuroscience, rare disease, and oncology.

About the World Economic Forum Technology Pioneers

• The World Economic Forum announced its selection of the 100 most promising Technology Pioneers of 2022 - companies that are tackling issues from sustainability and climate change to healthcare and more.
• This year’s cohort includes representation from 30 economies on six continents with reach far beyond traditional tech hubs like Silicon Valley.
• The full list of Technology Pioneers can be viewed here.

TORONTO, ON, 10 May 2022 – DNAstack, a Toronto-based Canadian company that enables scientists and health leaders to find, access, and analyze biomedical data over open standards, was selected among hundreds of candidates as one of the World Economic Forum’s “Technology Pioneers”.  DNAstack was co-founded by Dr. Marc Fiume and Ryan Cook to improve global health outcomes while fostering diversity, equity, and access in scientific research through technology that powers distributed data networks, federated learning and analysis. 

DNAstack’s mission is to improve human health by breaking down barriers to privacy-preserving  global data sharing, discovery, and analysis. The team develops software for scientists to uncover insights from the world’s exponentially growing volumes of genomic and biomedical data, enabling more effective diagnosis and treatment of complex and rare conditions.

The World Economic Forum’s Technology Pioneers are early to growth-stage companies from around the world that are involved in the use of new technologies and innovation that are poised to have a significant impact on business and society.

With their selection as Technology Pioneers, Dr. Marc Fiume and Ryan Cook will be invited to participate at World Economic Forum activities, events and discussions throughout the year. DNAstack will also contribute to Forum initiatives over the next two years, working with global leaders to help address key industry and societal issues. 

“We’re excited to welcome DNAstack to our 2022 cohort of Technology Pioneers,” says Saemoon Yoon, Community Lead, Technology Pioneers, World Economic Forum. “DNAstack and its fellow pioneers are at the forefront of industries that are critical to solving some of our world’s most complex issues today. We look forward to their contribution to the World Economic Forum in its commitment to improving the state of the world.”

“We are honoured to be recognized and grateful for the opportunity to accelerate our impact with the incredible support of the World Economic Forum,” said DNAstack’s Marc Fiume.  “No one makes discoveries like all of us. The World Economic Forum brings together the global community we need to make breakthroughs and save lives,” said Ryan Cook. 

For the first time, over one-third of selected Technology Pioneer firms are led by women, well above the industry average. The firms also come from regions all around the world, creating a truly global community. This year’s cohort includes start-ups from 30 countries, with Vietnam, Rwanda and Czech Republic represented for the first time. 

The diversity of these companies extends to their innovations as well. This year’s Tech Pioneer firms are shaping the future by advancing technologies such as AI, IoT, robotics, blockchain, biotechnology and many more. The full list of Technology Pioneers can be found here. 

Technology Pioneers have been selected based on the community’s selection criteria, which includes innovation, impact and leadership as well as the company’s relevance with the World Economic Forum’s Platforms. 

All info on this year’s Technology Pioneers can be found here: http://wef.ch/techpioneers22  

More information on past winners, information on the community and the application link can be found here. 

About DNAstack: DNAstack is improving human health by breaking down barriers to responsible global data sharing, discovery, and analysis. The team develops standards and software for scientists to more efficiently find, access, and analyze the world’s exponentially growing volumes of genomic and biomedical data, enabling more effective diagnosis and treatment of complex and rare conditions. 

About World Economic Forum: The World Economic Forum, committed to improving the state of the world, is the International Organization for Public-Private Cooperation. The Forum engages the foremost political, business and other leaders of society to shape global, regional and industry agendas. (www.weforum.org).

About the Technology Pioneers: The World Economic Forum believes that innovation is critical to the future well-being of society and to driving economic growth. Launched in 2000, the Technology Pioneer community is composed of early to growth-stage companies from around the world that are involved in the design, development and deployment of new technologies and innovations, and are poised to have a significant impact on business and society.

The World Economic Forum provides the Technology Pioneers community with a platform to engage with the public- and private-sector leaders and to contribute new solutions to overcome the current crisis and build future resiliency.

DNAstack today announced Viral AI, a federated network for genomic variant surveillance and infectious disease research. Viral AI was designed to deliver equitable access to software infrastructure, accelerate international data sharing, and empower scientists and public health officials with globally representative datasets they need to mitigate current and future infectious disease outbreaks.

Genomic surveillance is required to detect new variants that can threaten the global COVID-19 pandemic response by being more transmissible, pathogenic, evasive of diagnostics, and resistant to therapies. Regional genome sequencing, analysis, and rapid international data sharing are critical to inform public health decisions to help slow the devastating impacts of COVID-19.

Viral AI introduces a new way to share and analyze genomics, clinical, administrative, and related data, facilitating insights about transmission, severity, diagnostics and vaccine escape. As an alternative to the centralized model, where data is uploaded to a single vendor-managed database, Viral AI adopts a federated architecture to connect, analyze, and share data without moving it. This model enables faster, more efficient, regulatory compliant, and regionally sovereign data management, enabling viral surveillance efforts to be more equitable, scalable, and sustainable.

“We envision a future where global pathogen surveillance is powered by a real-time digital network of local datasets,” said Dr. Marc Fiume, CEO at DNAstack. “Viral AI democratizes access to software that follows international best practices in bioinformatics and data sharing, empowering any country or organization looking to implement local surveillance while participating in a global data sharing network.”

Viral AI accelerates science by making data uniformly accessible through a user-friendly graphical interface and powerful programmatic interfaces, integrating data across different sources from around the world, such as NCBI Sequence Read Archive (SRA), Canadian COVID Genomics Network (CanCOGeN), and European Center for Disease Prevention and Control, among others. Over one million viral sequences have been added with corresponding assemblies, variant calls, and lineage assignments, all harmonized through an open source bioinformatics pipeline. 

Researchers can use Developer Tools to analyze Viral AI data from scientific computing environments like Terra, a software platform for collaborative biomedical research co-developed by the Broad Institute of MIT and Harvard, Microsoft, and Verily Life Sciences. Terra extends native cloud services with researcher-focused capabilities, including shared workspaces to run computational workflows reproducibly and at scale. Researchers can clone a public workspace that has been created in Terra which demonstrates how to run analyses across data from Viral AI. “DNAstack is using Terra to offer researchers powerful new ways to analyze Viral AI data, increasing the data’s value, expanding Terra’s ecosystem and enabling new research frontiers,” said David Glazer, Engineering Director and Terra CTO at Verily Life Sciences. “This integration aligns with our shared vision for creating a modular, community-driven biomedical data ecosystem enabled by open, interoperable standards.”

The Viral AI network is powered by enterprise implementations of open standards created by the Global Alliance for Genomics & Health (GA4GH). The GA4GH develops technical, ethical, regulatory, and security protocols for responsible sharing of genomics and clinical datasets, designed in collaboration with world-leading organizations and precision health initiatives. “The GA4GH is working with the international community to strengthen standards that will help enable rapid and timely responses to new variants of concern domestically and around the globe,” said Peter Goodhand, CEO of GA4GH. “With Viral AI, DNAstack is demonstrating how GA4GH standards can be applied to accelerate international data sharing for pathogen surveillance and infectious disease research.”DNAstack software enables data custodians to set up independent locally-controlled infrastructure with capabilities to process, interpret, and responsibly share data with attribution. Viral AI includes a secondary analysis pipeline for genome assembly, variant calling, and lineage assignment on data from Illumina, Oxford Nanopore, and PacBio sequencers, a visual analytics dashboard for monitoring variants of concern, and a data publication tool for real-time sharing to the network. Private instances can be set up quickly within customer-managed environments on major cloud platforms and on-premises.

DNAstack is collaborating with Amazon Web Services (AWS) to harmonize, process, and share viral genome sequences deposited into NCBI SRA as part of the AWS Diagnostic Development Initiative (DDI). Sequencing data is uniformly re-processed by a secondary analysis pipeline executed through Amazon Genomics CLI and made freely available with support from the AWS Open Data Sponsorship Program. “Our goal is to accelerate innovations that can advance the collective understanding of COVID-19 and other infectious diseases,” said Maggie Carter, Global Lead, Social Impact at AWS. “We’re pleased to work with DNAstack to make it easy for the global community to tap into one of the largest open collections of SARS-CoV-2 genomes in the world.”

Viral AI is supporting the Canadian COVID-19 Genomics Network (CanCOGeN) VirusSeq initiative, part of the national genomics program led by Genome Canada. “The need for genomic surveillance will not end with this pandemic or with coronaviruses,” said Dr. Catalina Lopez-Correa, Chief Scientific Officer at Genome Canada and Executive Director of CanCOGeN. “By democratizing digital infrastructure for genomic variant surveillance and rapid data sharing, Viral AI will help create more inclusive, globally representative datasets that we can use to make better public policy decisions, diagnostics, and treatments.” The Government of Ontario is also using Viral AI to inform pandemic response and planning using insights from genomics, epidemiology, public policy, and other data.

Viral AI builds on the technology created in collaboration with a national consortium supported by Canada’s Digital Supercluster, a federal program that invests in the development and adoption of digital technologies. The COVID Cloud project, led by DNAstack, included experts in infectious disease, ethics, policy, cloud computing, and artificial intelligence. “We applaud the leadership shown by this Canadian consortium, working together with the international community to demonstrate the power of collaboration in developing new technologies to fight big challenges in health,” said Sue Paish, CEO of Canada’s Digital Technology Supercluster. “The virus that causes COVID-19 knows no boundaries, and neither should our approach to innovation and collaboration.”

About DNAstack

DNAstack’s mission is to power precision medicine through software that breaks down barriers to responsible biomedical data sharing, discovery, and analysis. For more information visit dnastack.com or contact info@dnastack.com.

Our world is constantly changing and at its core, innovation is really about responding to change in a new, creative way. It requires courage, conviction, resilience, the support of a community of collaborators, and innovation-oriented policies in order to succeed.Digital technologies are driving much of this change, rapidly outpacing our traditional systems and infrastructure. It’s more important than ever that we bolster innovation to foster effective and sustainable health care, as well as economic growth.

This week at the 21st Annual Healthcare Summit: The Future of Innovation, Personalized Medicine and Genomics, more than 50 national and international subject matter experts and leaders in digital health technology, personalized medicine, health innovation, value-based healthcare and genomics met to share ideas and discuss how to futureproof health care. At this event, our CEO Dr. Marc Fiume participated in a panel discussion on the Digital Technology Supercluster and investing in the future of healthcare. He sat down with Bill Tam, Chief Operating Officer at Canada’s Digital Technology Supercluster, to share his thoughts about how this unique funding model has helped us drive digital innovation in Canada and around the world.

Bill: What brought you to the Digital Technology Supercluster?

Marc: At DNAstack we have an audacious goal and that is to accelerate biomedical research and discovery with our software. The Supercluster is an exponent on our mission, in that it has provided a framework for us to incubate and grow software products alongside partners who believe in the same principles and future as we do. We believe that by connecting, and transparently and responsibly sharing, making accessible and computable Canada’s genomics and biomedical data, that we can accelerate translational discoveries that have profound impacts on the future of healthcare for Canadians. So that’s really what brings us to Supercluster — the opportunity to multiply our impact through collaboration.

Bill: What Supercluster projects are you currently working on and what about them excites you the most?

Marc: We’re currently working on two Supercluster projects that focus on building game-changing technology for data sharing, discovery and analysis — we are just finishing one in COVID and beginning another in autism. I will sum up my answer in one word: IMPACT. We want to change the world for the better by powering and enabling groundbreaking research. Of course, we know it takes a village, and through both of these projects, strong collaborations with our partners is essential to achieving our goals.

For example, early on in the COVID-19 pandemic, we had an overwhelming sense that the world needed technology to share genomic data about this new virus. We quickly mobilized a group of like-minded partners around COVID Cloud  , a software platform which enables real-time sharing of viral sequences over open, interoperable standards. Fast forward nearly a year and a half later, and together with an incredible consortium of industry and academic partners, we have built a great piece of technology and long-term partnerships that will help bolster Canadian innovation. This opportunity has resulted in a number of follow-on and unrelated projects with repeat partners, and our enterprise-grade solution is being used to support data-driven decision making in Ontario, as well as to share viral sequences at the national level through Canadian COVID Genomics Network (CanCOGeN)’s VirusSeq initiative.

This past spring, we kicked off the Autism Sharing Initiative (ASI) , which will build the first federated global network for data sharing to accelerate research and develop precision healthcare approaches for individuals with autism. Understanding autism requires a collaborative and globally representative ecosystem, and the siloed nature of individual research and clinical datasets is a fundamental roadblock to understanding not only autism, but the diversity of human health in general.

ASI is supporting research enabled by new technology based on the concept of “data federation,” a technique that allows search and data analysis to be performed across multiple datasets while allowing those individual datasets to remain in their protected local environments, such as a hospital where the data was originally collected.

Again, we are thrilled to be able to have such an incredible group of collaborators all focused on the goal of building technology that will provide autistic people and their families with more precision healthcare approaches. We still have a lot of work ahead of us, but the passion and commitment of the organizations who have come together to support this project is unparalleled.

Bill: To date, how has the Digital Technology Supercluster Ecosystem contributed to the success of your business?

Marc: We can’t overstate the importance of the Digital Technology Supercluster Ecosystem to the success of DNAstack. This is a unique model that fosters trust and collaboration with partners across industry, academia, and not-for-profit, rallying behind a common challenge and bringing unique expertise to the table. Our partners have common goals, and also share many of the same roadblocks in the way of working on large-scale, innovative projects such as these. The Supercluster model helps break down these walls by providing a framework for collaboration and incentivizes participating organizations to work closely together to achieve their shared objectives.

For DNAstack, the Supercluster’s support has helped us scale quickly and sustainably, enabling us to reach a stage of product maturity that we couldn’t have otherwise accomplished in this short timeframe. Since joining the Supercluster DNAstack has tripled in size and revenues, and the validation we are getting on the products we are building have helped us attract investment and partnership interest which will carry us through the next phase of our growth.

 * COVID Cloud consortium: BioSymetrics, Centre of Genomics and Policy at McGill University, DNAstack, FACIT, Genome BC, Mannin Research, McMaster University, Microsoft Canada, Ontario Genomics, Ontario Institute for Cancer Research, Roche Canada, Sunnybrook Research Institute, and Vector Institute** ASI consortium: Autism Speaks, Autism Speaks Canada, DNAstack, Excelar Technologies, McGill University’s Centre of Genomics and Policy, Molecular You, Pacific Autism Family Centre Foundation, Hoffmann-La Roche Limited (Roche Canada), SickKids and the University of British Columbia. In addition to the core consortium, partners supporting this initiative include Holland-Bloorview Kids Rehabilitation Hospital, Ontario Brain Institute, and the Autism SPectrum Interdisciplinary REsearch (ASPIRE) Program at BC Children’s Hospital Research Institute.

A coalition of researchers and healthcare providers in Canada and beyond are building what they believe to be the first global, federated network for sharing genomics and clinical data to support advances in research and patient care for autism (Subscriber content). 

Canada’s Digital Technology Supercluster and DNAstack today announced the Autism Sharing Initiative, a new project to build the first federated, global network for sharing genomics and clinical data to accelerate research with the hopes of developing precision healthcare approaches for autistic individuals.

Autism, or autism spectrum disorder, refers to a broad range of conditions characterized by challenges with social skills, repetitive behaviours, speech and nonverbal communication — each autistic person on the autism spectrum has a distinct set of strengths and challenges. There is not one autism but many subtypes, influenced by a combination of genetic and environmental factors. Autism affects approximately one in 66 Canadians.

While a great deal of genomic and clinical data are being collected in autism research, these datasets are maintained independently by institutions to protect privacy and data security. To date, it has been difficult to study these data together, limiting researchers’ ability to better understand the genetic factors involved in autism. Using new technology, the Autism Sharing Initiative will enable international collaboration between institutions, allowing researchers to search and analyze multiple de-identified datasets at the same time, without moving the data from its original organization. Because the location of the data is maintained, the levels of privacy and security will be maintained, and data will be accessed according to patient consent.

“Through leading international collaborations such as the Autism Sharing Initiative, we are fuelling the growth of Canada’s digital ecosystem, driving Canadian innovation, and supporting research to help families living with autism in Canada and around the world,” said Sue Paish, CEO of Canada’s Digital Technology Supercluster. “This project is a great example of how Canada’s Digital Technology Supercluster is bringing together the global research community, and highlights Canada’s leadership in personalized approaches to care.”

This research is enabled by new technology based on the concept of “data federation,” a technique that allows search and data analysis to be performed across multiple datasets while allowing the individual datasets to remain in their protected local environments. Through building this new federated global data sharing network of genomics, multi-omic clinical, medical, patient and family-centered data, researchers and healthcare professionals will be able to leverage artificial intelligence (AI)-based methods to mine complex datasets, which could enable earlier diagnoses and the development of precision healthcare approaches for autistic people. 

“Autism is complex and our research has demonstrated the value of connecting massive datasets to help us uncover critical genetic insights. While we have made great strides, there is still much we don’t know about the genetics of autism,” says Dr. Stephen Scherer, Director of The Centre for Applied Genomics (TCAG) at The Hospital for Sick Children (SickKids) and Lead Scientist of the Autism Speaks MSSNG program. “Each autistic person is unique and even siblings can have different forms of autism, underscoring the importance of studying individuals, families, and populations of people.”

None of this research would be possible without autistic people and their families participating in research, and the autism community will be able to engage with the project to help maximize the value to autistic people. 

The Autism Sharing Initiative will develop new easy-to-use software that allows institutions to independently manage data but virtually integrate them over distributed networks. Powered by implementations of the latest open standards developed by the Global Alliance for Genomics & Health, the software securely shares all data, allowing researchers to bring their best ideas forward in the most efficient and careful manner. Enabling scalable federated analysis and machine learning could fuel new research discoveries that could have broad impact for collaborative genomics research beyond autism.

“Understanding autism requires a collaborative and globally representative ecosystem,” said Dr. Marc Fiume, CEO of DNAstack. “The siloed nature of individual research and clinical datasets is a fundamental roadblock to realizing the promise of data-driven personalized healthcare. Recent advances in generating international standards for data sharing enable the value of data to be unlocked while protecting privacy, which promise to transform biomedical research and translation into clinical care.”

The Autism Sharing Initiative builds on research through the work of a consortium that includes Autism Speaks, Autism Speaks Canada, DNAstack, Excelar Technologies, McGill University’s Centre of Genomics and Policy, Molecular You, Pacific Autism Family Centre Foundation, Hoffmann-La Roche Limited (Roche Canada), SickKids and the University of British Columbia. The project is an $11.2 million initiative, including $4.3 million provided by Canada’s Digital Technology Supercluster. In addition to the core consortium, partners supporting this initiative include Holland-Bloorview Kids Rehabilitation Hospital, Ontario Brain Institute, and the Autism SPectrum Interdisciplinary REsearch (ASPIRE) Program at BC Children’s Hospital Research Institute.

Genome Canada launched the Canadian VirusSeq Data Portal today to track the evolving COVID-19 pandemic across Canada.  

Genome Canada, in partnership with the Government of Canada, is pleased to announce the development of a new Canadian SARS-CoV-2 Data Portal.

The Ontario government has unveiled a six-point plan to prevent and stop the spread of new COVID-19 variants. 

A consortium of Canadian informatics firms, pharmaceutical companies, and research institutes has pledged C$5.1 million to tailor a bioinformatics and health data platform for COVID-19 research across the country.

A national consortium led by DNAstack will expand development of a software platform for genomics and health data and apply it to COVID-19.

The $5.1M project, called COVID Cloud, is co-funded by Canada’s Digital Technology Supercluster and aims to increase Canada’s capacity to harness exponentially growing volumes of genomics and biomedical data to advance precision health. The platform will be used by data scientists and domain experts to help understand, predict, and treat COVID-19 with molecular precision. With a global death count of over 1.4 million people and record numbers of cases nationally, solutions that can help Canada respond to ongoing challenges of the pandemic are urgently needed.

“We are proud to continue to support this consortium’s groundbreaking work through our COVID-19 program,” said Sue Paish, CEO of the Digital Technology Supercluster. “This project shows how Canadian partnerships across multiple organizations and sectors can drive innovation, help us address global health issues, showcase Canadian expertise, and position us well to rebuild and grow our economy.”

The project — a collaboration between BioSymetrics, Centre of Genomics and Policy at McGill University, DNAstack, FACIT, Genome BC, Mannin Research, McMaster University, Microsoft Canada, Ontario Genomics, Ontario Institute for Cancer Research, Roche Canada, Sunnybrook Research Institute, and Vector Institute — brings together Canadian leaders in software engineering, artificial intelligence, cloud computing, genomics, infectious disease, pharmaceuticals, commercialization, and policy. It leverages past work of partners to address needs of infectious disease research with guidance from domain experts.

“Tools that allow us to interrogate SARS-CoV-2 at a molecular level are essential to addressing this global health crisis, both now and in the future,” said Dr. Samira Mubareka, a microbiologist and infectious diseases physician at Sunnybrook, whose team was one of the first in Canada to isolate the novel coronavirus. “The insights we will learn by analysing integrated datasets using technology platforms like COVID Cloud can increase our preparedness for future waves and outbreaks.” Dr. Mubareka will co-chair the project’s translational science efforts along with Dr. Gabriel Musso, Chief Scientific Officer for BioSymetrics. “The infrastructure developed by this initiative will propel collaborative Canadian drug discovery efforts for COVID-19,” said Musso, whose team will lead bioinformatics and computational drug discovery for the project.

A major goal of the project is to make it easy for producers of genomic and health data to share data responsibly over industry standards, and for researchers to harness the collective power of information shared through them. The project deliverables include a suite of software products powered by enterprise-grade implementations of standards developed by Global Alliance for Genomics & Health (GA4GH), protocols that are being designed to facilitate the responsible sharing of genomic and health data, which will help advance precision medicine initiatives around the world.

“The platform is being built on a foundation of open standards that will allow for distributed networks of genomics and biomedical data to be built,” said Dr. Marc Fiume, CEO at DNAstack, whose team will lead software engineering for the project. “We are excited to see these technologies breaking down barriers to data sharing, access, and analysis and create new opportunities for genomics-based discoveries for our partners.”

This project is responding to global demand for highly specialized, scalable, distributed software infrastructure to support collaborative genomics research — a need that has surged since the onset of the COVID-19 pandemic. “COVID-19 has accelerated digital transformation of many industries, especially in healthcare,” said Kevin Peesker, President of Microsoft Canada. “The incredible power of Cloud applied to COVID at scale is expanding development of an information superhighway to securely connect scientists in Canada and around the world to the data and compute power they urgently need to help us overcome one of the greatest global health crises of our time.”

The platform will be used to support a series of projects in partnership with Canadian academic, clinical, and pharmaceutical collaborators, which are being coordinated by Canadian genome centres, Genome British Columbia and Ontario Genomics. These initial projects are being prioritized based on urgency and potential impact on Canada’s response to the COVID-19 pandemic.

“The COVID Cloud is an incredible platform that brings together resources and capacity to enable timely and comprehensive genomic analysis of SARS-CoV-2 for our province and our country,” said Bettina Hamelin, President and CEO of Ontario Genomics, whose team leads the ONCoV Genomics Coalition. “This made-in-Canada solution will immediately accelerate Canada’s response to COVID-19, while being a technological springboard for translating genomic data analysis into actionable medical insights across other disease areas in years to come.”

For more information, visit here.

About DNAstack

DNAstack’s mission is to improve the lives of millions of people by breaking down barriers to data sharing and discovery. DNAstack develops standards and technologies for scientists to more efficiently find, access, and analyze the world’s exponentially growing volumes of genomic and biomedical data. For additional support or partnership interest, please contact us by email to info@dnastack.com.

About Digital Technology Supercluster

The Digital Technology Supercluster solves some of industry's and society's biggest problems through Canadian-made technologies. We bring together private and public sector organizations of all sizes to address challenges facing Canada's economic sectors including healthcare, natural resources, manufacturing and transportation. Through this 'collaborative innovation' the Supercluster helps to drive solutions better than any single organization could on its own.  The Digital Technology Supercluster is led by industry leaders such as D-Wave, Finger Food Advanced Technology Group, LifeLabs, LlamaZOO, Lululemon, MDA, Microsoft, Mosaic Forest Management, Sanctuary AI, Teck Resources Limited, TELUS,Terramera, and 1Qbit. Together, we work to position Canada as a global hub for digital innovation. A full list of Members can be found here.

About the COVID-19 Program

The COVID-19 Program aims to improve the health and safety of Canadians and support Canada's ability to address issues created by the COVID-19 outbreak. In addition, the program will build expertise and capacity to anticipate and address issues that may arise in future health crises, from healthcare to a return to work and community. More information can be found here.

The Digital Technology Supercluster has made $10.7 million in follow-on investments to five projects under its COVID-19 stream, rounding out the Supercluster’s $60 million budget for the pandemic-focused program.

Read the full article on Betakit.

Despite advances in sequencing and analysis tools, calling variants in whole-genome sequencing (WGS) data is not trivial, even when dealing with only a few dozen samples.

When the number of samples reaches into the thousands, the time, computational resources, and file storage required for analysis can quickly become overwhelming. This was the challenge faced by the MSSNG team when they sought to joint-call the largest autism cohort yet sequenced — how could they process nearly 10,000 samples in a way that would be quick, reproducible, and allow for future expansion, all without breaking the bank?

The pipeline

One of the key directives of the initiative was to allow for painless future expansion of the dataset — namely, adding new samples without full reprocessing of the entire cohort. In addition, these outputs should be reproducible and consistent across sequencing technologies and analysis tools, so data from multiple experiments across time, labs, and experimental conditions could be combined and jointly analyzed. To that end, MSSNG researchers chose to analyze their WGS data using standards defined by the Centers for Common Disease Genomics (CCDG). The CCDG provides a set of standardized data processing steps for WGS data with a focus on producing functionally equivalent results (Regier et al., 2018). These steps cover the alignment, duplicate marking, and base quality score recalibration (BQSR) tasks that convert the raw FASTQ data to CRAM-format alignment files that may be used for long-term storage and future reanalysis (Figure 1).

Though not part of the CCDG pipeline itself, the CRAM output from this upstream pipeline is used to call variants (SNPs and small indels) on a per-sample basis, outputting genomic VCF (gVCF) files. Finally, the gVCF files for all samples are combined and joint-called to produce a single VCF file. Optionally, variant quality scores are then recalibrated (variant quality score recalibration, VQSR). See Figure 1 for an overview of the pipeline steps.

The tools

After extensive testing of concordance, cost, and speed, MSSNG chose to use Sentieon to process their WGS samples. Sentieon provides a licensed toolset that implements computationally-optimized versions of common variant-calling tools, providing results up to 10x faster than GATK’s best-practices pipeline while maintaining high concordance with GATK’s results (Freed et al., 2017). Sentieon publishes comprehensive documentation outlining how to run a CCDG-compliant upstream pipeline, as well as information on common downstream analysis steps such as per-sample SNP and indel calling using HaplotypeCaller, and joint genotyping and VQSR using their GVCFtyper and VarCal algorithms.

Challenges and optimizations

Upstream Pipeline: FASTQ -> CRAM, GVCF

In the upstream part of the pipeline, raw FASTQ files are processed to per-sample CRAMs and gVCFs. This segment ran smoothly using Sentieon, taking an average of 4 hours per sample (64 core virtual machine (VM), 55 GB of RAM). In rare cases (~30/9,625 total samples) the alignment step ran out of memory and RAM was increased for these samples. Since many of the Sentieon algorithms are I/O-bound (that is, they are bottlenecked by the speed of reading and writing to the disk, rather than by CPU or memory usage), we also chose to use local SSDs for storage, which provide very fast I/O speeds.

We were able to run the upstream pipeline using preemptible VMs, a machine type that is provided at a much lower cost by Google but which may be shut down at any time if the resources are needed elsewhere. If a VM is shut down in this way, all progress on a task is lost and the task will be automatically restarted on another VM. If a VM is preempted frequently enough, the cost and time lost from running and rerunning the task can outweigh the savings of using a preemptible VM. Out of 8,377 successful runs that we inspected, we found that 7,163 runs were not preempted in any step. The average raw compute cost for these runs was $2.43 USD including storage, CPU, and RAM costs (not including the price of the Sentieon licence itself). We also observed that larger VMs (such as the 64 CPU/55GB RAM VMs used for the Sentieon steps) showed far less preemption events than smaller ones. The upstream pipeline was run in parallel, with ~500 samples run concurrently.

Downstream Pipeline: Joint Genotyping

The majority of complications occurred during the joint genotyping step, which requires merging and joint genotyping all gVCF files generated using the upstream pipeline (1 per sample). Whereas the upstream pipeline can be run massively in parallel with each sample in a separate VM, joint genotyping requires the presence of all of the data in a single VM. This raises two issues: 1) disk size required, and 2) the runtime of the pipeline.

Disk Size Requirements

With each gzipped input gVCF file taking 15–25GB of space, the disk space required for analysis runs into the tens of terabytes for input files alone. The size of the merged output file, which is around the same as the sum of all the input files, must also be considered. While the Google disk size limit of 64 TB per VM should be enough to accommodate this, the size of the output file would make it unwieldy.

Pipeline Runtime

Despite the optimizations implemented by Sentieon, the speed of many processes is limited by the speed of the zip/unzip process (which by default runs on a single core) as both input and output files are gzipped to save space. This reality dramatically slows down the analysis, especially given the size of the files involved.

Solutions

Splitting Up Joint-Genotyping By Region 

Sentieon provides a number of built-in solutions that help manage both the size of the final VCF file, as well as the speed of the analysis. First, joint genotyping may be split up to operate independently on different regions of the genome (much like many of GATK’s tools, which allow the analysis to be split up over intervals). This means that 1) the joint genotyping analysis may be run in parallel across intervals, and 2) we do not need to localize the full gVCF file for every sample in every shard — only the region corresponding to the interval we are joint calling in that shard (Figure 2a).

In order to read in only the required regions of the gVCFs without localizing the full files, we took advantage of a feature of htslib which allows bcftools to read directly from Google Cloud Storage locations. bcftools accesses Google credentials using the environment variable GCS_OAUTH_TOKEN, which can be defined as follows (assuming the user has authenticated with Google Cloud):

export GCS_OAUTH_TOKEN=$(gcloud auth application-default print-access-token)

To localize only the desired region of each gVCF file, the following command is used for each sample’s gVCF URL:

bcftools view -R ${region}.bed -Oz -o ${sample}_${region}.g.vcf.gz ${gvcf_url}

Each region.bed should specify a different region of the genome, e.g. chr1:1–50000000. The result of running this command for each gVCF URL is a smaller gVCF file that only includes calls for the region specified in the region.bed file. All of these partial gVCF files are then joint-genotyped together to output a partial VCF that has calls only for the specified region (Figure 2a). Since joint-genotyping is in this way split up into many smaller jobs that can be run in parallel for each region, the process is made considerably faster.

Merging Joint-Genotyped Files by Chromosome

Once the partial VCFs for each region are produced, they must be merged together to form a final, complete VCF file that includes all regions. After some trial and error it was decided that rather than merging all regions of the genome together to form one large final VCF file, genomic regions would be merged on a per-chromosome basis in order to output 26 final VCF files (22 autosomes, chrX, chrY, chrM, and contig regions) (Figure 2a). Although the VCFs for each chromosome are still quite large, they are individually much more manageable than a single VCF containing all regions.

Since both the partial VCFs produced by joint-calling and the merged output file are gzipped, the process of merging these partial VCFs into a single file takes several days to a week to process even a single chromosome — once again, the speed of analysis is bound by the speed of the gzipping process. Had the merge step been run for the full dataset to produce a single output file, we predicted that this step would have taken upwards of a month to complete. By merging only the partial VCFs that made up each chromosome, we were able to run the process in parallel, meaning that the merge step took a little over a week to complete.

Sentieon's " Split_By_Sample" Option For Large VCF'S 

It should be noted that Sentieon provides a different method of reducing the size of the final VCF file — they allow the output VCF to be split by sample, rather than by chromosome. This would result in a single ‘main’ file that contains only the first nine columns of the VCF (CHROM, START, STOP, etc.), and then a number of ‘samples’ files that each contain the calls for n samples (n could be 100, 500, 1000, etc. — the smaller the number of samples per file, the smaller the size of each file). Both the ‘main’ file and each of the ‘samples’ files have the data for all chromosomes present, but since each only contains a subset of the samples, each file is quite a bit smaller (Figure 2b). Since none of these files are valid VCF files, an ‘extraction’ step must be performed in order to produce a valid VCF file by combining the first 9 columns from the ‘main’ file along with the desired sample columns from the various ‘samples’ files. Although here we chose to split the final VCF by chromosome rather than by sample to reduce final file size (since we required final VCFs that included every sample), we still took advantage of Sentieon’s ‘split_by_sample’ option because of the implications for VQSR runtime.

Running VQSR On A Large DataSet 

It has been mentioned that one of our biggest problems in dealing with a cohort of this size is the bottleneck introduced by the speed of unzipping/zipping large input and output files. We were able to improve the speed of our analysis by processing smaller regions of the genome in parallel rather than trying to read the entire genome sequentially. Coming up to the VQSR step however, we realized that in order to perform this step, which recalibrates variant quality scores across the entire dataset, information from the entire genome must be read in — that is, a single VCF including all chromosomes must be used as input, and a single VCF with all chromosomes would be output. Not only would we lose the benefit of having our VCF files split by chromosome and therefore more manageable in size since we would need the full VCF, this step would again take potentially weeks to read and write these massive gzipped VCF files.

This is where Sentieon’s ‘split_by_sample’ option came in handy. Although we wanted all samples together in the final VCF and so should not have needed this option, by using it to output all sample information in a single ‘samples’ file (containing only the sample IDs and call information, that is, all columns 10-onwards in the VCF), we were also able to produce a ‘main’ file for each chromosome. The ‘samples’ file for each chromosome is quite large since it contains all calls for all samples, however the ‘main’ file is at most a few hundred MBs and contains only columns 1–9 (Figure 2b). This file is all that is needed to perform VQSR, and since it is so much smaller, a process that may have taken weeks to complete could be performed in less than a day.

The ‘main’ file for all chromosomes was combined into a single VCF-like file that contained columns 1–9 for the entire genome; VQSR was performed on this file; finally, the full-genome ‘recalibrated main’ VCF file was split once more by chromosome, to output one ‘recalibrated main’ file per chromosome. These ‘recalibrated main’ files were combined with their respective ‘samples’ files for each chromosome using Sentieon’s extraction script in order to produce a single recalibrated VCF for each chromosome, each of which includes all samples (Figure 2c). Although this extraction process was still bound by the speed of the gzip/gunzip process, it was again able to be performed in parallel across chromosomes to reduce the total runtime needed.

Joint-genotyping the MSSNG cohort was an intensive effort that involved a collaboration between DNAstack, Sentieon, and MSSNG researchers. Sentieon’s CCDG-compliant algorithms allowed for quick, reproducible results that will support straightforward expansion in the future. The speed of the gzip process, as well as the size of output files, required creative solutions to common problems in order to improve speed and workflow costs; we look forward to further improvements in optimizing these processes for large cohorts to help accelerate research.

References

• Freed, D., Aldana, R., Weber, J.A. and Edwards, J.S. 2017. The Sentieon Genomics Tools — A fast and accurate solution to variant calling from next-generation sequence data. bioRxiv. doi: https://doi.org/10.1101/115717
• Regier, A.A., Farjoun, Y., Larson, D.E., Krasheninina, O., Kang, H.M., Howrigan, D.P., Chen, B-J., Kher, M., Banks, E., Ames, D.C., English, A.C., Li, H., Xing, J., Zhang, Y., Matise, T., Abecasis, G.R., Salerno, W., Zody, M.C., Neale, B.M. & Hall, I.M. 2018. Functional equivalence of genome sequencing analysis pipelines enables harmonized variant calling across human genetics projects. Nature Communications. 9: 4038. doi: https://doi.org/10.1038/s41467-018-06159-4
• htslib: https://github.com/samtools/htslib
• bcftools: https://github.com/samtools/bcftools

Photo Credits

Microscopic image of crystallized DNA from autism genes. Photo Credit: Bianca Guimarae

Today, DNAstack revealed a software system built on standards developed by the Global Alliance for Genomics and Health (GA4GH) to enable federated analysis of genomics and related health data.

The system, demonstrated at the 8th Plenary Meeting of GA4GH earlier this week, features the first integration of multiple emerging standards for data access, discovery, and cloud computing, which are foundational for connecting secure, scalable, and distributed data sharing networks.

Enabling federated data sharing and analysis is important for advancing genomic research, where institutional and regulatory policies can restrict the use of valuable datasets that would otherwise stay siloed from each other. GA4GH has brought together a global community of collaborators that have worked for years to design domain-specific standards that facilitate the responsible sharing of genomic and related health information.

“We’re excited to debut an integrated system of GA4GH standards to help break through long-standing barriers to federated analysis of genomic data,” said Max Barkley, Senior Software Developer, Technical Lead at DNAstack, and co-lead of GA4GH Federated Analysis Systems Project (FASP). “This marks a major milestone for DNAstack in our mission to accelerate genomics medicine through data sharing.”

The DNAstack system was demonstrated through a real-world analysis of controlled access data hosted on multiple cloud platforms, including from the Autism Speaks MSSNG Project. The system was presented as one of three GA4GH 2020 Connection Demos. The two other demonstrations showed reproducibility of a bioinformatics analysis run in multiple environments, and multi-directional interoperability by combining implementations from different organizations.

“The Connection Demos are an enormous success for the members of the GA4GH Work Streams, who have collectively dedicated thousands of hours over the last three years toward standards development,” said Ewan Birney, Deputy Director General of the European Molecular Biology Laboratory (EMBL), Director of EMBL’s European Bioinformatics Institute (EMBL-EBI), and Chair of GA4GH. “The demos show how this community’s work will enable interoperability across the genomics endeavour.”

The GA4GH 2020 Connection Demos highlighted how standards can be used vertically and horizontally to share data while complying with institutional, regional, national, and international regulations as well as across cloud and analytics environments. Data sharing across platforms and institutions will enable the research community to access and analyze the tens of millions of genome sequences that have been generated for research and healthcare purposes, which has the potential to rapidly accelerate our scientific understanding, particularly in rare and complex diseases.

About DNAstack

DNAstack’s mission is to improve the lives of millions of people by breaking down barriers to data sharing and discovery. DNAstack develops standards and technologies for scientists to more efficiently find, access, and analyze the world’s exponentially growing volumes of genomic and biomedical data. For additional support or partnership interest, please contact us by email to info@dnastack.com.