The Development Cell Atlas - Data Coordination Centre

The Human Cell Atlas is developing a blueprint to better understand how cells function in normal life and in diseases; a foundational dataset which is part this initiative is the Developmental Cell Atlas. By understanding how cells function in normal tissues and how they change over time during development we provide an atlas which researchers can use to better understand how different cell types emerge in vivo and how things go wrong in diseased tissues. The data and knowledge generated can be used to design new drugs, to repurpose drugs and to detect diseases earlier as we can see when normal processes change before diseases can be diagnosed. In order to maximise the impact of the Developmental Cell Atlas the data generated should be collected, versioned and made available to the research community, both academic and industrial. This is a big data problem and needs tools that are able to collect and share genetic data and images, databases that can store these data and preserve it for years and tools to ensure that the results from the data can be used in different ways, such as drug development and basic academic research. This proposal provides the necessary infrastructure to collect, share and preserve the data, respecting the ethical constraints on the data and enabling the wide community of researchers to access the data. The standards, tools and services generated during this project will also be provided to the research community and portable and use cloud technologies meaning they can use the latest techniques for accessing data anywhere in the world.

The MRC Developmental Cell Atlas Data Coordination Centre (DCC) will take a systematic data-driven approach in order to facilitate the collection and sharing of data generated by scientists as part of the MRC Developmental Cell Atlas (DCA) call. Deposition, validation and quality assurance of new data types in the scRNA-Seq and spatial transcriptomics is a complex process that requires researcher engagement and coordination. To facilitate this process the DCC will implement a community engagement strategy, including dedicated bioinformatics support. We will provide customised submission spreadsheets and JSON format APIs for manual and programmatic based submission ensuring that contributors are supported at every level. The DCC will work with the Developmental Atlas Community to evolve the standards and metadata schemas created by Human Cell Atlas-Data Coordination Platform (HCA-DCP) to capture information that includes the many facets of a cell's identity such as tissue source, developmental stage as well as experimental details. Data captured in a well-structured form that utilises ontologies maximises the downstream usefulness of the data and provides the ability to query and compute over the Human Cell Atlas and supports the Findable, Accessible, Interoperable and Reusable principles. Regular releases of the DCA data will be made and computational researchers will be supported by providing direct access to both primary and processed data (from grantees) through well-documented consumer APIs. Efficient access will ensure scientific analysis methods can keep pace with the transformative advances and rapid innovation in imaging and sequencing based methods. Establishing the DCA-DCC will maximise the utility of the Developmental Atlas Data and is critical to achieve the long-term vision to create a reference map of all human cells at different developmental stages that is both accessible and useful to the scientific and medical community.

Recent transformative advances in experimental and computational methods are enabling high-throughput, quantitative and spatially resolved profiling of individual cells. The Developmental Cell Atlas will provide a foundational dataset that will enable us to understand how cells function in normal tissues and how they change over time during development in normal life and in disease. This will facilitate a deeper insight into human health and diagnosing, monitoring and treating disease and the Developmental Cell Atlas Data Coordination Platform (DCA DCC) will provide the necessary infrastructure to collect, share and preserve these data, respecting the ethical constraints.
Existing challenges in data science and reproducibility of biomedical data in the academic research context call for uniform metadata standards to ensure reproducibility and correct interpretation of resulting data. The DCC will deliver the infrastructure, standards and processes to address these challenges for the developmental atlas and critically will provide the wide community of researchers with a dataset that is interoperable with a much larger dataset than the Developmental Atlas alone. Freely available code and unique interoperable and accessible datasets with robust, semantically comparable data, that make data cleaning significantly easier and enable machine learning approaches, will benefit data scientist and analysts worldwide and provide a benchmark dataset that might be used for comparison different analytical approaches.
This dataset will enhance the research capacity, data, knowledge and skills beyond academic research, as data and tools with clear and permissive licenses are accessible and intended to be used by third parties from industry (big pharma, SMEs) in the biotech, AI, and data management sectors through existing databases such as ENA and via the Human Cell Atlas - Data Coordination Platform. The data and knowledge generated can be used by researchers in industry to design new drugs, to repurpose drugs and in early disease detection.
The DCA DCC will bring together support for novel data generation technologies, for example, imaging, bioinformatics and big data use of cloud technology and thereby maximise the impact of data among diverse academic communities and promote multidisciplinary research between these communities. By collaboration with the parallel Developmental Atlas training proposal all the resources will be shared more widely through the international 'Train Online' Platform (https://www.ebi.ac.uk/training/online/) and a webinar on the work of the DCA DCC will be shared via the Human Cell Atlas communications channels, via ELIXIR and via the EMBL-EBI train online platform.

DCC Beneficiaries:
- Grantees for the call will benefit as they will generate FAIR data stored in sustainable resources.
- Biological researchers will benefit as they will be able to access and query scRNA-Seq data and linked spatial transcriptomics data.
- Bioinformatics resource providers will benefit as they will be able to access the data and integrate this with their own resources. They will be also able to access code under a permissive licence.
- Publishers will be able to link consistently to the datasets supporting publications.
- Translational researchers in industry and academia will benefit from well annotated data with standard metadata, promoting sharing and re-use. This maximises value for research spend and researcher effort as well as promoting data sharing.
- Methods researchers will benefit as there will be a stable data releases of data with with to work and the data will conform to metadata standards.
- Scientists in training will benefit from access to stable, versioned data resources critical for training activities which can then be linked to the data releases.