RAWtunda: a Tool to Convert a Multi-Channel Raw Image into TIFF and OME-TIFF Formats
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Motivation
High-resolution biological imaging in spatial biology produces data in many proprietary formats. The lack of compatibility between these formats restricts reproducibility and analysis, creates access issues, and makes early data analysis a challenge.
Results
Here, we introduce a graphical user interface (GUI) application designed to convert proprietary image formats into standardized formats like OME-TIFF and TIFF which we have termed Rawtunda. This tool addresses the need for easy and efficient handling of large, complex imaging data generated in spatial biology and microscopy, facilitating data sharing, analysis, and long-term storage. Featuring an intuitive interface the application supports users in converting.mcd and.ndpi formats, generated from Image Mass Cytometry (IMC) and Digital Pathology scanners, respectively. This resource aims to improve interoperability of spatial biology datasets, streamline data management workflows, and promote reproducibility in imaging research and analysis, preserving crucial image metadata. The app ensures compatibility with downstream tools and is designed for both bioinformaticians and bench biologists without experience in coding.
Availability and implementation
The software, the documentation, and examples are available as open-source a https://med.virginia.edu/spatial-biology-core/rawtunda/ under the Copywrite of University of Virginia.
