ReviewCellular and molecular life sciences : CMLS2025
A comparative review of single-cell atlases: mapping cellular diversity across species and tissues.
Review in Cellular and molecular life sciences : CMLS, 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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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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0 citing papers in PubMed.
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Authors and funding
8 authors.
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Abstract
Single-cell sequencing (sc-seq) technologies have revolutionized biomedical research by enabling high-resolution analysis of cellular heterogeneity across multiple dimensions, including transcriptomics, epigenomics, and spatial profiling. These advances have led to the development of comprehensive single-cell atlases-reference maps of cell types and states across tissues and organisms, such as the Human Cell Atlas and Mouse Cell Atlas. These resources are foundational frameworks for investigating gene regulation, tissue architecture, and disease mechanisms. However, variations in biological focus, species representation, and dataset scale among available atlases necessitate a systematic comparative evaluation. This review provides an in-depth analysis of current single-cell atlases, assessing their scope, strengths, and limitations based on an updated framework derived from Hrovatin et al. We discuss the transformative role of sc-seq in oncology, immunology, and infectious disease research and highlight critical gaps in atlas development, including underrepresented species and tissue types. Finally, we propose key recommendations to guide future efforts in expanding, integrating, and standardizing single-cell atlas initiatives for enhanced translational impact.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.