Accelerating Multi-modal Biomarker Discovery in Translational Research with Cloud Data Integration

Cytobank, Inc., Santa Clara CA

Investigators

Linked publications & trials

Abstract

Project Summary/Abstract Cytobank is the leading cloud-based platform for analysis and storage of single cell flow and mass cytometry data, technologies that are essential for investigating the interplay between the immune system and disease conditions including cancer. There are numerous data analysis steps between raw data and insight especially for many single-cell technologies, where the data analysis is complex, highly expert-driven and/or reliant on novel computational methodologies. Cytobank already makes major contributions (1) centralizing single-cell cytometry data, (2) providing data analysis traceability that removes knowledge sharing complexities, and (3) establishing a platform that increases access to cutting edge algorithms and makes complex machine learning methods easy for biologists to use. However, as the amount, complexity, and different types of single cell data and other associated data increases and the number of workflows and single-cell algorithms to analyze the data also increases, the need for open and easy access to existing and new tools and secure, complete storage of the workflows and the resulting data has increased to the point of being critical for supporting basic and translational research collaborations and enabling them to efficiently achieve their objectives including biomarker discovery and development. The proposed project significantly extends the capabilities of the Cytobank platform. This will benefit the community by (1) enabling scalable and secure access to a number of new single-cell data analysis tools that will result in new automated workflows, and (2) enable more efficient cross platform knowledge generation with increased meta-analysis capabilities across experiments and data types. The potential of this project is that thousands of scientists around the world will be able to more easily leverage additional single-cell cytometry, transcript, and other data in their translational research data analysis including automating analysis that has primarily been dominated by expert-driven annotation, thus providing a central repository and knowledge management framework that will accelerate biomarker discovery and precision medicine.