4.1 Article

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

Journal

PATTERNS
Volume 1, Issue 8, Pages -

Publisher

CELL PRESS
DOI: 10.1016/j.patter.2020.100120

Keywords

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Funding

  1. Leona M. and Harry B. Helmsley Charitable Trust
  2. NIDDK-supported Human Islet Research Network [RRID:SCR_014393, UC4 DK104211, DK108120, DK112232, DK123716, DK120456, DK106755, DK20593]
  3. Department of Veterans Affairs [BX000666]

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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.

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