Cancer Data Analysis

Jackson Laboratory, Bar Harbor ME

Investigators

Linked publications, trials & patents

Abstract

PROJECT SUMMARY CANCER DATA ANALYSIS SHARED RESOURCE (CDA) The overall mission of The Jackson Laboratory Cancer Center (JAXCC) is to bring genomic solutions to cancer medicine. Our basic research goal is to tackle the question of “Genetics and Genomics of Aging and Cancer”, while our translational intent is to contribute new concepts, technologies, and clinical education initiatives originating from basic science to advance precision cancer medicine. The JAX Cancer Data Analysis Shared Resource (CDA) is central to the achievement of the JAXCC's Research Program goals. As cancer research has become increasingly data intensive, it is vital that investigators have support for interpreting and leveraging vast data sets, both publicly available and internally generated, to understand cancer biology. CDA services are spread across three main resource delivery areas that function in a modular manner so that JAXCC members can access the right mix of expertise and resources tailored to their scientific. These areas are, first, Biostatistics and Technologies, which develops multi-modal data integration approaches to better model human disease; cross-species genetic and genomic analyses; systems and algorithms to analyze short- and long-read sequencing data; and standardization of bioinformatics, genetic analyses, and other omics workflows across JAX to facilitate research reproducibility. Second, Genomic Computing, which develops and applies computational methods for single-cell sequencing, single-cell imaging, and related spatially aware approaches; provides expert analysis; supports data interpretation; and supports the development, maintenance, and improvement of scientific databases and web applications, with a focus on FAIR and TRUSTworthy ecosystems for data governance. Third, Machine Learning and Imaging, which develops and applies deep learning methods for genomic, epigenomic, proteomic, metabolomic, and imaging data analysis, and explores application of Large Language Models (LLMs) for mining literature, integrating data, and supporting tumor boards. In the next funding cycle, CDA will expand into big data analytical platforms pursuing expanded hybrid cloud and in-house high- performance computing capabilities and will provide support for artificial intelligence (AI) applications. The Specific Aims of CDA are: Aim 1: To support JAXCC members in developing cutting-edge analytical procedures for emerging problems in cancer genomics, and to carry out integrative analysis in fundamental and translational cancer research; Aim 2: To develop bioinformatics applications, maintain scientific analysis workflows, and provide data architecture and software engineering expertise for the development and management of scientific data portals pertaining to specific scientific questions addressed by JAXCC members; and Aim 3: To assist in resource planning for and management of complex computational projects and long-term information technology and data science development for JAXCC members.