Pancreatlas: Applying an Adaptable Framework to Map the Human Pancreas in Health and Disease

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.

Graphical Abstract

Highlights

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  Human organ phenotyping databases benefit from intuitive user interfaces

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  Pancreatlas resource enables exploration of bioimaging data from human pancreas

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  The front-end framework of Pancreatlas, FFIND, is modular and easily adaptable

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  FFIND provides structured data-exploration capabilities across countless domains

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.

Abstract

Human tissue phenotyping generates complex imaging data that is difficult to share in publications, and many organ-specific databases lack intuitive user interfaces or have limited support for multiplexed imaging. Therefore, we built a Pancreatlas resource ( https://www.pancreatlas.org) that integrates several technologies into a unique interface, allowing users to access richly annotated web pages. To create this imaging resource, we developed a data-agnostic, React-based web application and Python-based application programming interface, collectively called Flexible Framework for Integrating and Navigating Data (FFIND; https://github.com/Powers-Brissova-Research-Group/FFIND).