ODM

Genestack Open Data Manager (ODM) is a life science data management platform designed to catalog, curate, harmonize, and search large volumes of biological data from multiple sources. It makes data Findable, Accessible, Interoperable, and Reusable (FAIR), enabling organizations to unlock the full value of their omics and related datasets. ODM is built for a collaborative data ecosystem, offering dedicated APIs and a graphical user interface (GUI) tailored to different user classes — including data managers, bioinformaticians, and discovery scientists — so that every stakeholder can harness the power of life science data in their day-to-day work.

At scale, ODM has demonstrated the ability to support over 10,000 public studies imported from five sources, index one million variants queried per minute, and manage up to 500 TB of life science data across customer instances. Its flexible design and high degree of configurability allow it to integrate seamlessly into the existing IT landscape and data workflows of any organization.

Data Catalog

• Provides a centralized repository for recording studies, samples, data files, and associated metadata across multiple omics types.
• The catalog GUI gives users an overview of the full scope of data in the system, including volume, omics type, and common sample descriptors.
• Ensures no dataset is ever lost by acting as a single source of truth for life science data after processing from an instrument.
• Can also be used prior to data generation to design studies and collect information in a controlled fashion.

Curation Tools

• Enables validation and harmonization of metadata across studies, ensuring completeness and conformance to an organization's data model.
• Supports ontology-based annotation, allowing curators to standardize metadata using controlled vocabularies and ontologies such as NCBI Taxonomy, UBERON, Cell Ontology, Cellosaurus, Disease Ontology, and ChEBI.
• Metadata values are validated on-the-fly against designated controlled vocabularies or ontologies, including programmatically imported metadata.
• Custom ontologies and dictionaries can be uploaded in CSV, OBO, or OWL formats.
• Supports bulk curation operations including bulk replace, Excel-like drag-and-drop in the GUI, auto fill-down, and rule-based replacements via Python scripts.
• High-quality, curated data is made ready for AI/ML pipelines without further wrangling.

Analytical Search

• Enables large-scale, cross-study, and cross-omics integrative queries via well-documented REST APIs.
• ODM indexes not only metadata (e.g. sample information) but also the underlying data (e.g. gene expression levels per sample), enabling complex multi-omics queries such as finding studies with specific patient demographics, gene expression profiles, and genetic mutations simultaneously.
• Increases data discoverability and liquidity across an organization's entire data estate.

Data Types and Multi-Omics Support

• ODM is designed to be agnostic to data types; by default it supports genomics and transcriptomics, with proteomics support forthcoming.
• Can be adapted to other data types including imaging and flow-cytometry data.
• Multi-omics capability allows cross-study, cross-omics queries that span genomics, transcriptomics, and proteomics in a single search.

Data Sharing and User Management

• Studies can be shared between relevant groups of users with role-based privileges.
• User roles include non-sharing users (view only), sharing users (can share data), and group administrators (can invite/remove users and manage privileges).
• Both a no-code GUI and programmatic RESTful APIs are available, making ODM accessible to users with and without programming skills.

Data Visualization and Integration

• ODM's APIs support data querying and streaming, enabling bioinformaticians and data scientists to build custom visualizations.
• Lightweight R-Shiny and Jupyter Notebook examples are available, such as gene expression look-up applications and t-SNE plots from single-cell RNA-seq data.
• Built-in RESTful APIs allow import and export of metadata to and from electronic lab notebooks (ELNs) and other upstream or downstream systems.
• ODM is not a data analysis tool itself, but data can be exported programmatically via API for use with third-party analysis pipelines.

Security and Compliance

• Supports multiple user authentication mechanisms: login/password, Single Sign-On (SSO) via SAML, and OAuth 2.0.
• Built-in admin, write, and read authorization levels with group-based access controls.
• Authorization model can be synced with external permission systems such as Active Directory.

ODM can be deployed on the cloud (SaaS and VPC) or on-premises, with minimum hardware requirements of 8 CPU cores and 64 GB RAM. Genestack provides a structured onboarding process including needs assessment, use-case mapping, a supported Proof of Concept project with training workshops, gap analysis reporting, and full deployment with ongoing maintenance and development services.