Abstract
Cell type markers have been instrumental to physiological and molecular investigation of the human brain and remain essential for annotating cell type clusters in single-cell expression data and for target validation studies. However, expression of canonical markers in the target cell type (which we termed as the expression ‘fidelity’) as well as expression in unrelated cell types (which we termed as the ‘background expression’) across cortical regions remains poorly characterized. Here, leveraging nearly 500,000 high-quality single-nucleus and single-cell profiles from 19 studies, we quantified marker fidelity, revealing substantial regional variability. We developed a statistical framework that aggregates annotated barcodes into pseudo-bulk profiles, applied rigorous performance metrics, and identified markers with high fidelity, low background, and consistent expression across regions. This approach extended the canonical marker set for six major brain cell types and yielded superior subtype-specific markers. The resulting marker lists, and a user-friendly analysis interface, provide a valuable resource for cell type annotation and validation in neuroscience research.
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Acknowledgements
We thank Dr. Stephen Fleming (creator of CellBender) for detailed feedback regarding choice of CellBender parameters. We thank Prof. Gabriel Santpere Baró for his feedback on our manuscript and insightful discussions. We also thank all members of the Yi lab for discussions. We thank Karthik Somayaji, Shravan Muralidharan, and Sai Sukruth Bezugam (UC Santa Barbara) for lively conversations on machine learning and clustering.
Funding
This study was supported by NSF (EF-2021635) and NIH (HG011641 and MH134809) grants to SVY.
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Joshy, D.M., Yi, S.V. Expanding canonical cortical cell type markers in the era of single-cell transcriptomics. Sci Rep (2026). https://doi.org/10.1038/s41598-026-51501-2
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DOI: https://doi.org/10.1038/s41598-026-51501-2
