The Chan Zuckerberg Initiative (CZI) seeks applications for projects that aim to use and gain insights into health and disease from existing single-cell datasets to help accelerate progress toward challenges associated with the compilation and exploration of large atlas-scale data. Given the growth of single-cell biology and the rapid increase in available data, CZI is looking to support projects that will advance the fields of single-cell biology and data science. Grantees will be expected to interact with a network among participating groups that builds community and accelerates progress. Applications are encouraged from computational experts outside the field of single-cell biology but with expertise relevant to overcoming current bottlenecks. Projects may include dedicated efforts to refine existing computational tools, benchmark classes of tools, improve standards, integrate available data that enables greater biological insight, develop new features that support interoperability of data or tools, and other major challenges brought forward. This request for applications is the second of three cycles planned for the coming years, with successful projects receiving 18 months of funding support.
Applications for two types of grants are welcome and will be reviewed independently. The maximum budgets for proposed projects are $400,000 total costs for Expanded Projects and $200,000 total costs for Focused Projects. All projects awards will be for an 18-month duration. The goal of this opportunity is to create a network of projects that address broad computational challenges and needs within single-cell biology at a variety of scales. If applicants wish to highlight existing or prospective collaboration among projects, that is encouraged and allowable, but all applications will be reviewed for their individual merit and impact.
Single-cell biology has undergone rapid growth over the last five years, with a recent increase in the volume of available and openly accessible data. This funding opportunity is specifically intended to motivate and incentivize the development, refinement, and implementation of tools and approaches that make it possible for greater insights to be gained from available single-cell data. With this in mind, any form of data generation is considered out of scope. Projects must propose and rely on existing data that is openly and freely available (count matrices at minimum) at the time of application via the inclusion of a link to specific datasets in the applications. Furthermore, we strongly encourage applications to utilize data generated outside of their labs to enable interoperability and advances that are extensible to a wider segment of interested researchers.
Addressing computational challenges and bottlenecks in single-cell biology will drive the field forward and make it possible for a greater number of scientists to benefit from emerging datasets and tissue atlases. This opportunity puts forward a broad scope that fundamentally aims to enable greater insight to be gleaned from single-cell data. Successful proposals are likely to incorporate some, or multiple, of the following attributes:
- Meta-analysis of single-cell datasets that highlights their characteristics, usability, and utility and enables insight into more specific biological questions.
- Develop scalable and robust tools and methods for data analysis problems in spatial transcriptomics.
- Increase the robustness and performance of tools of broad interest for various tasks, such as data integration, scaling to higher dimensionalities, or mapping new data sets to a reference atlas that allow deeper insights. This includes enhancing or developing tools such as the stack of matrices and annotated (SOMA) suitable for the analysis of large, growing collections of single-cell data.
- Develop benchmarking frameworks, tasks, and infrastructure that enable comparisons among a class of tools and methods to stimulate future development that increases scale, efficiency, and reproducibility and accelerates scientific discovery.
- Improve existing tools, standards and/or increase interoperability among multiple tools.
It is also an explicit goal of this effort to build a community among international participants that encourages collaboration and coordination, and we envision that the overlap between funding cycles will allow continuity and learning. CZI will support the coordination of this community and promote opportunities for training, documentation, and knowledge sharing across projects and cycles.