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TMA-Grid: an open-source, zero-footprint web application for FAIR tissue microarray de-arraying
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DOI：10.1186/s12859-026-06638-2.png)
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Abstract
En 中文
Tissue microarrays (TMAs) significantly increase analytical efficiency in histopathology and large-scale epidemiologic studies by allowing multiple tissue cores to be scanned on a single slide. The individual cores can be digitally extracted and then linked to metadata for analysis in a process known as de-arraying. However, TMAs often contain core misalignments and artifacts from assembly, sectioning, and scanning, which can compromise the reliability of the extracted cores. Conventional de-arraying tools are desktop-based and offer limited interactivity for correcting these errors, motivating a flexible web-based approach that combines automated detection with user-driven correction in a single platform. We developed TMA-Grid, an in-browser, zero-footprint, interactive web application for TMA de-arraying. The application integrates a convolutional neural network for tissue segmentation with an interactive grid-estimation workflow that helps assign detected cores to expected row and column positions while allowing user review and correction. Users can adjust segmentation and gridding results at each step. Operating entirely in the web browser, TMA-Grid eliminates the need for downloads or installations and operates on source images in place, whether stored locally or in remote or cloud storage. The application and its components follow FAIR principles (Findable, Accessible, Interoperable, and Reusable) for integration into TMA research workflows. TMA-Grid provides an interactive, browser-based platform for TMA de-arraying that requires no installation and operates on data in place. The application is freely available and open source, and its components are reusable in other web-based digital pathology workflows.
Keywords:
Tissue microarray
De-arraying
Digital pathology
Whole slide imaging
Web application
FAIR software
TensorFlow.js
OpenSeadragon
Journal
IF:
3.3
Papers:
573
Citations:
5.2W
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