Atgenomix is an enterprise cloud-native BioMed-IT platform specifically built for biotechnology and clinical laboratory industries.
Biomedical analysis workflows mix tasks and models together and entangle them with tight dependency on external datasets. Since changing anything changes everything, the increasing complexity of workflows results in the erosion of boundaries, making workload optimization and pipeline improvement impossible. Bioinformatics code is only a small fraction of real-world biomedical analysis workflow systems. Workload and dataset dependencies cost more than code dependencies at many orders of magnitude.
The Atgenomix Platform-as-a Service (PaaS) provides the required surrounding infrastructure and accelerated bioinformatics framework for all your biomedical workloads throughout the lifecycle of building a fully managed precision medicine operation.
Standardize your own workflows from genome, multi-omics, to all biomedical data analyses without boundaries.
Use the industry best-practice, human-readable and -writable OpenWDL to design and analyze entire dataset processing workflows without regard to their vast and complex infrastructure technology. The description language makes it straightforward to specify command/SQL/ML tasks, glue them together in directed data flows, and optimize their cost-efficient execution.
Optimize performance for all steps in a workflow production system including version control, data integration, verification, deployment, and runtime management.
Leverage a set of GA4GH industry standards and in-memory parallel computing to develop and automate workflows in production reliably and efficiently. The technology makes it simple to connect to a variety of data workload dependencies using common practices and to process workload acceleration at scale and speed.
Turning central labs into decentralized profit centers is as simple as deciding on where to grow your portfolio of analysis services.
Operate your biomedical software as a service with enterprise-grade regulatory compliance, cybersecurity, and resource management. The IT infrastructure automation enables workflow systems that are predictable, reproducible, and auditable while ensuring code, data, and execution integrity.
Decentralized virtual private cloud for building the fully-managed operation in users’ own subscription account.
Azure Active Directory credential authentication and authorization.
Accelerated and reproducible WDL (Workflow Description Language) workflow automation.
GA4GH Data Repository Service V1, Tool Registry Service V2, and Workflow Execution Service V1 standards.
Role-based access control and activity audit logging.
Run workflows faster and scale entire workflows with implicit and dynamic parallel processing for performance and fault tolerance.
Provision batch compute resources on demand and optimize cost-performance at workflow or individual task granularity.
Ecosystem integrations via CLI, SDK, RESTful application programming interface.
An integrated platform for cohort-based annotation and interpretation of genetic variants on Spark https://www.biorxiv.org/content/10.1101/239962v1
Accelerating String Graph Construction for De Novo Assembly on Spark https://www.biorxiv.org/content/10.1101/321729v1
Machine-learning optimized long-range genome analysis workflow for next-generation sequencing https://www.biorxiv.org/content/10.1101/776807v2
DeepVariant-on-Spark: Small-Scale Genome Analysis Using a Cloud-Based Computing Framework https://www.hindawi.com/journals/cmmm/2020/7231205/?utm_medium=author&utm_source=Hindawi
Detect rare MECP2 gene missense mutations in schizophrenic patients
Copy number variant hotspots in Han Taiwanese population induced pluripotent stem cell lines - lessons from establishing the Taiwan human disease iPSC Consortium Bank
Identification of Rare Mutations of Two Presynaptic Cytomatrix Genes BSN and PCLOin Schizophrenia and Bipolar Disorder
Identification of a novel nonsense homozygous mutation of LINS1 gene in two sisters with intellectual disability, schizophrenia, and anxiety
Involvement of Rare Mutations of SCN9A, DPP4, ABCA13, and SYT14 in Schizophrenia and Bipolar Disorder