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Abstract

Leveraging single cell reference atlases to analyse new data has brought about a paradigm shift in single cell data science akin to the first reference genome in genomics. However methods to perform this mapping require computational expertise as well as sometimes considerable compute power, and thus may exclude the researchers from this innovation who may benefit the most from it. ArchMap, a no-code query-to-reference mapping tool, removes this barrier by providing all-in-one automated mapping, cell type annotation, and collaborative features to analyse single-cell datasets from a wide range of integrated, often published, reference atlases and allows extension of atlases with the growing Human Cell Atlas and related efforts. This paves the way for a democratisation of reference mapping capabilities.

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02 /Specification & Classification

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