ArticleGenome research2025
A unified analysis of atlas single-cell data.
Article in Genome research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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4 authors.
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Abstract
Recent efforts to generate atlas-scale single-cell data provide opportunities for joint analysis across tissues and modalities. Existing methods use cells as the reference unit, hindering downstream gene-based analysis and removing genuine biological variation. Here we present GIANT, an integration method designed for atlas-scale gene analysis across cell types and tissues. GIANT converts data sets into gene graphs and recursively embeds genes without additional alignment. Applying GIANT to two recent atlas data sets yields unified gene-embedding spaces across human tissues and data modalities. Further evaluations demonstrate GIANT's usefulness in discovering diverse gene functions and underlying gene regulation in cells from different tissues.
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