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

Abstract

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.

State‐of‐the‐art microscopy to understand islets of Langerhans: what to expect next?

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Exploiting open source omics data to advance pancreas research

“…This movement toward open sharing of data and data-mining tools has reshaped scientific inquiry and discovery by facilitating a tremendous opportunity to repurpose the freely available data to either generate novel hypotheses for empirical testing in experimental models and clinical samples or to mine the data with specific questions. At present, the dissemination of open source data extend beyond the traditional omics platforms and encompasses large-scale datasets from spatial atlases (eg, Pancreatlas [2] ; http://www.pancreatlas.org) of different tissues in various organisms, thus providing affirmation for the success of the open source data sharing concept. However, the precious open data resources are still largely underutilized.…”

Islet cells in human type 1 diabetes: from recent advances to novel therapies – a symposium-based roadmap for future research

“…org/ d atase ts/53 1/ove rview). Dr Brissova and her colleagues at Vanderbilt University participate on various levels in all five programs, four of which are currently connected via the data-agnostic Pancreatlas platform (Saunders et al 2020) (https://pancreatlas.org/), a curated resource to share imaging datasets developed by the Vanderbilt team. To integrate functional, genomic and genetic data with key donor characteristics across age, sex, ancestry and disease state, a robust islet phenotyping pipeline was developed (Brissova et al 2018, Hart et al 2018…”