Pancreatlas: Applying an Adaptable Framework to Map the Human Pancreas in Health and Disease
Diane C. Saunders,
James Messmer,
Irina Kusmartseva,
Maria L. Beery,
Mingder Yang,
Mark A. Atkinson,
Alvin C. Powers,
Jean-Philippe Cartailler,
Marcela Brissova
Affiliations
Diane C. Saunders
Division of Diabetes, Endocrinology, and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
James Messmer
Division of Diabetes, Endocrinology, and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
Irina Kusmartseva
Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, Diabetes Institute, University of Florida, Gainesville, FL, USA
Maria L. Beery
Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, Diabetes Institute, University of Florida, Gainesville, FL, USA
Mingder Yang
Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, Diabetes Institute, University of Florida, Gainesville, FL, USA
Mark A. Atkinson
Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, Diabetes Institute, University of Florida, Gainesville, FL, USA; Department of Pediatrics, College of Medicine, Diabetes Institute, University of Florida, Gainesville, FL, USA
Alvin C. Powers
Division of Diabetes, Endocrinology, and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; VA Tennessee Valley Healthcare System, Nashville, TN, USA; Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, USA
Jean-Philippe Cartailler
Creative Data Solutions Shared Resource, Center for Stem Cell Biology, Vanderbilt University, Nashville, TN, USA; Corresponding author
Marcela Brissova
Division of Diabetes, Endocrinology, and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Corresponding author
Summary: Human tissue phenotyping generates complex spatial information from numerous imaging modalities, yet images typically become static figures for publication, and original data and metadata are rarely available. While comprehensive image maps exist for some organs, most resources have limited support for multiplexed imaging or have non-intuitive user interfaces. Therefore, we built a Pancreatlas resource that integrates several technologies into a unique interface, allowing users to access richly annotated web pages, drill down to individual images, and deeply explore data online. The current version of Pancreatlas contains over 800 unique images acquired by whole-slide scanning, confocal microscopy, and imaging mass cytometry, and is available at https://www.pancreatlas.org. To create this human pancreas-specific biological imaging resource, we developed a React-based web application and Python-based application programming interface, collectively called Flexible Framework for Integrating and Navigating Data (FFIND), which can be adapted beyond Pancreatlas to meet countless imaging or other structured data-management needs. The Bigger Picture: Scientists need cost-effective yet fully featured database solutions that facilitate large dataset sharing in a structured and easily digestible manner. Flexible Framework for Integrating and Navigating Data (FFIND) is a data-agnostic web application that is designed to easily connect existing databases with data-browsing clients. We used FFIND to build Pancreatlas, an online imaging resource containing datasets linking imaging data with clinical data to facilitate advances in the understanding of diabetes, pancreatitis, and pancreatic cancer. FFIND architecture, which is available as open-source software, can be easily adapted to meet other field- or project-specific needs; we hope it will help data scientists reach a broader audience by reducing the development life cycle and providing familiar interactivity in communicating data and underlying stories.
