Atlas-scale metabolic activities inferred from single-cell and spatial transcriptomics.

ABSTRACT: Metabolism supplies energy, building blocks, and signaling molecules vital for cell function and communication, but methods to directly measure it at single-cell and/or spatial resolutions remain technically challenging and inaccessible for most researchers. Single-cell and spatial transcriptomics offer high-throughput data alternatives with a rich ecosystem of computational tools. Here, we present scCellFie, a computational framework to infer metabolic activities from human and mouse transcriptomic data at single-cell and spatial resolution. Applied to ~30 million cell profiles, we generated a comprehensive metabolic atlas across human organs, identifying organ- and cell-type-specific activities. In the endometrium, scCellFie reveals metabolic programs contributing to healthy tissue remod

SUBMITTER: Armingol E 

PROVIDER: S-EPMC12132331 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature