Impact of the Human Cell Atlas on medicine

Spatial reconstruction of single-cell gene expression data

Satija, R., Farrell, J. A., Gennert, D., Schier, A. F., & Regev, A. (2015) · Nature Biotechnology · doi:10.1038/nbt.3192 · Cited by 7,055

Oncology meets immunology: the cancer-immunity cycle.

Chen, D. S., & Mellman, I. (2013) · Immunity · doi:10.1016/j.immuni.2013.07.012 · Cited by 6,929

A Unique Microglia Type Associated with Restricting Development of Alzheimer’s Disease

Keren-Shaul, H., Spinrad, A., Weiner, A., Matcovitch-Natan, O., Dvir-Szternfeld, R., Ulland, T. K., David, E., Baruch, K., Lara-Astaiso, D., Toth, B., et al. (2017) · Cell · doi:10.1016/j.cell.2017.05.018 · Cited by 5,493

SARS-CoV-2 entry factors are highly expressed in nasal epithelial cells together with innate immune genes

HCA Lung Biological Network, Sungnak, W., Huang, N., Bécavin, C., Berg, M., Queen, R., Litvinukova, M., Talavera-López, C., Maatz, H., Reichart, D., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0868-6 · Cited by 2,501

Single-cell RNA-seq data analysis on the receptor ACE2 expression reveals the potential risk of different human organs vulnerable to 2019-nCoV infection

Zou, X., Chen, K., Zou, J., Han, P., Hao, J., & Han, Z. (2020) · Frontiers of Medicine · doi:10.1007/s11684-020-0754-0 · Cited by 2,287

SARS-CoV-2 Receptor ACE2 Is an Interferon-Stimulated Gene in Human Airway Epithelial Cells and Is Detected in Specific Cell Subsets across Tissues

Ziegler, C. G. K., Allon, S. J., Nyquist, S. K., Mbano, I. M., Miao, V. N., Tzouanas, C. N., Cao, Y., Yousif, A. S., Bals, J., Hauser, B. M., et al. (2020) · Cell · doi:10.1016/j.cell.2020.04.035 · Cited by 2,284

The human cell atlas

Regev, A., Teichmann, S. A., Lander, E. S., Amit, I., Benoist, C., Birney, E., Bodenmiller, B., Campbell, P., Carninci, P., Clatworthy, M., et al. (2017) · eLife · doi:10.7554/elife.27041 · Cited by 2,232

Complex cell-state changes revealed by single cell RNA sequencing of 76,149 microglia throughout the mouse lifespan and in the injured brain

Hammond, T. R., Dufort, C., Dissing-Olesen, L., Giera, S., Young, A., Wysoker, A., Walker, A. J., Segel, M., Nemesh, J., Saunders, A., et al. (2018) · doi:10.1101/406140 · Cited by 2,225

Defining T Cell States Associated with Response to Checkpoint Immunotherapy in Melanoma

Sade-Feldman, M., Yizhak, K., Bjorgaard, S. L., Ray, J. P., de Boer, C. G., Jenkins, R. W., Lieb, D. J., Chen, J. H., Frederick, D. T., Barzily-Rokni, M., et al. (2018) · Cell · doi:10.1016/j.cell.2018.10.038 · Cited by 2,053

Perturb-Seq: Dissecting Molecular Circuits with Scalable Single-Cell RNA Profiling of Pooled Genetic Screens

Dixit, A., Parnas, O., Li, B., Chen, J., Fulco, C. P., Jerby-Arnon, L., Marjanovic, N. D., Dionne, D., Burks, T., Raychowdhury, R., et al. (2016) · Cell · doi:10.1016/j.cell.2016.11.038 · Cited by 1,863

Additional file 2 of Panpipes: a pipeline for multiomic single-cell and spatial transcriptomic data analysis

Curion, F., Rich‐Griffin, C., Agarwal, D., Ouologuem, S., Rue-Albrecht, K., May, L., Garcia, G. E. L., Heumos, L., Thomas, T. R., Lason, W., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26211618

Additional file 1 of Panpipes: a pipeline for multiomic single-cell and spatial transcriptomic data analysis

Curion, F., Rich‐Griffin, C., Agarwal, D., Ouologuem, S., Rue-Albrecht, K., May, L., Garcia, G. E. L., Heumos, L., Thomas, T. R., Lason, W., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26211351

Additional file 4 of hadge: a comprehensive pipeline for donor deconvolution in single-cell studies

Curion, F., Wu, X., Heumos, L., André, M. M. G., Halle, L., Ozols, M., Grant‐Peters, M., Rich‐Griffin, C., Yeung, H.-Y., Dendrou, C. A., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26713103

Additional file 1 of An atlas of cell-type-specific interactome networks across 44 human tumor types

Li, Z., Liu, G., Yang, X., Shu, M., Jin, W., Tong, Y., Liu, X., Wang, Y., Yuan, J., & Yang, Y. (2024) · Figshare · doi:10.6084/m9.figshare.25210504

Additional file 2 of hadge: a comprehensive pipeline for donor deconvolution in single-cell studies

Curion, F., Wu, X., Heumos, L., André, M. M. G., Halle, L., Ozols, M., Grant‐Peters, M., Rich‐Griffin, C., Yeung, H.-Y., Dendrou, C. A., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26713094

Additional file 2 of An atlas of cell-type-specific interactome networks across 44 human tumor types

Li, Z., Liu, G., Yang, X., Shu, M., Jin, W., Tong, Y., Liu, X., Wang, Y., Yuan, J., & Yang, Y. (2024) · Figshare · doi:10.6084/m9.figshare.25210831

The Brazilian Population Tumor Atlas Project: addressing representation in cancer genomics in Brazil

Boroni, M., Conteville, L. C., Pinto, L. F. R., & Viola, J. P. B. (2026) · The Lancet Regional Health - Americas · doi:10.1016/j.lana.2026.101397

Beyond the Transcriptome: Leveraging Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) for Deeper Cellular Insights

Fernandez, M. L., Gajardo-Escobar, F., Sjöberg-Herrera, M. K., Romagnoli, P. A., & Ceschin, D. G. (2026) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-092724-061209

RECOMBINE identifies recurrent composite markers of cell types and statesPreprint

Li, X., Nguyen, J., & Korkut, A. (2026) · Genome Research · doi:10.1101/gr.280817.125

Robust semi-supervised scRNA-seq integration from virtual adversarial learningPreprint

He, C., Filippidis, P., Xing, J., Kleinstein, S., & Guan, L. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.06.07.730754

Nadir Hastalıklar: Tanım, Epidemiyoloji, Moleküler Temeller ve Modern Sınıflandırma Yaklaşımları

Bayramcı, N. S., & Turan, F. (2026) · Özgür Yayınları eBooks · doi:10.58830/ozgur.pub1358.c5467

Nadir Hastalıkların Klinik Sistem Temelli Sınıflandırılması: Modern Moleküler Biyoloji, Sistem Biyolojisi ve Translasyonel Tıp Perspektifleri

Bayramcı, N. S., & Demirkaya, R. (2026) · Özgür Yayınları eBooks · doi:10.58830/ozgur.pub1358.c5470

An integrated skin cell atlas decodes the pilosebaceous unit

Düz, T., Törőcsik, D., Momnougui, S. M. E., Oubounyt, M., Al, B., Gallinat, S., Baumbach, J., & Holzscheck, N. (2026) · Journal of Investigative Dermatology · doi:10.1016/j.jid.2026.06.1282 · Cited by 1

scCT: Mapping Single-Cell Data to Human Reference Atlases to Identify Deviated Cell States

Li, Y., Yin, Z., Wu, Y., & Gu, J. (2026) · Lecture notes in computer science · doi:10.1007/978-981-92-3716-6_15

FloREN: Decoding Immune Regulatory Networks through Interpretable Graph Transformer Patient RepresentationsPreprint

Clemente‐Larramendi, I., Hillion, S., Cornec, D., Jamin, C., & Foulquier, N. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.07.12.738088

Single-cell long-read transcriptomics: from technologies to biological insights

Ren, Z.-H., Liu, W. T., Yin, J., & Liu, C. (2026) · GigaScience · doi:10.1093/gigascience/giag082

The Single-Cell Atlas Revolution: Integrating Lineage, Space, and Evolution to Decode Animal Biology

Rehman, S. U., Ali, R., Husien, H. M., & Wang, M. (2026) · DNA and Cell Biology · doi:10.1177/10445498261460199

Single-cell multiomic mapping of genetic predisposition to childhood B-cell acute lymphoblastic leukemiaPreprint

Lee, A., Neehus, A., Wahlster, L., Agarwal, G., Weng, C., Zhang, A., Liu, T., Shelton, S. D., Ye, T., della Volpe, L., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.08.06.743308

Harnessing single-cell gene regulatory networks for precision health

López-Castiblanco, J. A., López-Kleine, L., & Cuesta-Astroz, Y. (2026) · Journal of Investigative Medicine · doi:10.1177/10815589261483678

Clonal evolution in gastrointestinal cancers: multi-omics insights into tumor heterogeneity, microenvironmental selection, and translational biomarkers

Fan, W., & Zheng, C. (2026) · Frontiers in Oncology · doi:10.3389/fonc.2026.1907210

Atlas-scale single-cell analysis beyond in-memory paradigm with scAtlasPyPreprint

Xu, H., Ye, Y., Zhang, S., Xie, R., Li, J., Lin, J., Hu, Y., & Gao, L. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.09.03.748766

Cell Painting and machine learning for mechanistic profiling of hepatotoxic botanicals and their constituentsPreprint

Ollitrault, G., Mitchell, C. A., Ferguson, S., Roe, A. L., White, B., Titterton, K., & Ewald, J. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.10.05.756246

The Human Gut Cell Atlas v1.0: A Unified, Community-Built Reference of Cellular Diversity Across the GutPreprint

Kimler, K., Lance, C., Bohár, B., Ahmed, A., Zhou, R. R., Bartolomé-Casado, R., Gudiño, V., Flores, R. O. R., Junghus, F. V., Mörbe, U., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.10.09.753994

Multi-omic profiling of follicular lymphoma tumors reveals changes in tissue architecture and enhanced stromal remodeling in high-risk patients

Radtke, A. J. (2024) · Discovery Research Portal (University of Dundee) · doi:10.17867/10000199

Cell Atlases as Roadmaps in Health and Disease

Regev, A. (2020) · The Keio Journal of Medicine · doi:10.2302/kjm.69-002-abst

The Human Cell Atlas from a cell census to a unified foundation model

Rood, J., Wynne, S., Robson, L., Hupalowska, A., Randell, J., Teichmann, S. A., & Regev, A. (2024) · Nature · doi:10.1038/s41586-024-08338-4 · Cited by 173

Human cross-tissue cell atlases: unprecedented resources towards systematic understanding of physiology and diseases

Zhang, P., & Li, S. (2022) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-022-01201-w · Cited by 13

Exploring cell-type associations of rare disease phenotypes using non-diseased cell atlases

Novoa, J., Pazos, F., & Chagoyen, M. (2026) · Briefings in Bioinformatics · doi:10.1093/bib/bbag426 · Cited by 1

Mining single-cell data for cell type–disease associations

Chen, K., Farley, K. O., & Lassmann, T. (2024) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqae180