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However, achieving unified annotation of DSCSs in heterogeneous single-cell datasets remains a challenge. In this study, we developed the gPRINT algorithm (generalized approach for cell subtype identification with single cell\u2019s voicePRINT). Inspired by the principles of speech recognition in noisy environments, gPRINT transforms gene position and gene expression information into voiceprints based on ordered and clustered gene expression phenomena, obtaining unique \u201cgene print\u201d patterns for each cell. Then, we integrated neural networks to mitigate the impact of background noise on cell identity label mapping. We demonstrated the reproducibility of gPRINT across different donors, single-cell sequencing platforms, and disease subtypes, and its utility for automatic cell subtype annotation across datasets. Moreover, gPRINT achieved higher annotation accuracy of 98.37% when externally validated based on the same tissue, surpassing other algorithms. Furthermore, this approach has been applied to fibrosis-associated diseases in multiple tissues throughout the body, as well as to the annotation of fibroblast subtypes in a single tissue, tendon, where fibrosis is prevalent. We successfully achieved automatic prediction of tendinopathy-specific cell subtypes, key targets, and related drugs. In summary, gPRINT provides an automated and unified approach for identifying DSCSs across datasets, facilitating the elucidation of specific cell subtypes under different disease states and providing a powerful tool for exploring therapeutic targets in diseases.<\/jats:p>","DOI":"10.1093\/procel\/pwaf001","type":"journal-article","created":{"date-parts":[[2025,3,14]],"date-time":"2025-03-14T02:16:17Z","timestamp":1741918577000},"page":"685-704","source":"Crossref","is-referenced-by-count":0,"title":["Gene print-based cell subtypes annotation of human disease across heterogeneous datasets with gPRINT"],"prefix":"10.1093","volume":"16","author":[{"given":"Ruojin","family":"Yan","sequence":"first","affiliation":[{"name":"Department of Orthopedic Surgery of Sir Run Run Shaw Hospital, and Liangzhu Laboratory, Zhejiang University School of Medicine , Hangzhou 310011 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the Chinese University of Hong Kong , Hong Kong SAR ,","place":["China"]},{"name":"Kunming Institute of Zoology Chinese Academy of Sciences, the Chinese University of Hong Kong Joint Laboratory of Bioresources and Molecular Research of Common Diseases , Hong Kong SAR ,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tingzhang","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province , Hangzhou 310000 ,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zi","family":"Yin","sequence":"additional","affiliation":[{"name":"Department of Orthopedic Surgery of Sir Run Run Shaw Hospital, and Liangzhu Laboratory, Zhejiang University School of Medicine , Hangzhou 310011 ,","place":["China"]},{"name":"Institute of Cell Biology, Zhejiang University , Hangzhou 310058 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