{"title":"TORC:基于靶标导向的参考构建在scRNA-seq中进行监督细胞类型鉴定","authors":"Xin Wei, Wenjing Ma, Zhijin Wu, Hao Wu","doi":"10.1186/s13059-025-03614-6","DOIUrl":null,"url":null,"abstract":"Cell-type identification is a crucial step in single cell RNA-seq (scRNA-seq) data analysis, for which supervised methods are preferred due to their accuracy and efficiency. Performance is highly dependent on the quality of the reference data, but there is no method for selecting and constructing reference data. We develop Target-Oriented Reference Construction (TORC), a widely applicable strategy for constructing reference data given a target dataset for scRNA-seq supervised cell-type identification. TORC alleviates the differences in data distribution and cell-type composition between reference and target. Extensive benchmarks on simulated and real data analyses demonstrate consistent improvements in cell-type identification from TORC.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"20 1","pages":""},"PeriodicalIF":10.1000,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"TORC: Target-Oriented Reference Construction for supervised cell-type identification in scRNA-seq\",\"authors\":\"Xin Wei, Wenjing Ma, Zhijin Wu, Hao Wu\",\"doi\":\"10.1186/s13059-025-03614-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cell-type identification is a crucial step in single cell RNA-seq (scRNA-seq) data analysis, for which supervised methods are preferred due to their accuracy and efficiency. Performance is highly dependent on the quality of the reference data, but there is no method for selecting and constructing reference data. We develop Target-Oriented Reference Construction (TORC), a widely applicable strategy for constructing reference data given a target dataset for scRNA-seq supervised cell-type identification. TORC alleviates the differences in data distribution and cell-type composition between reference and target. Extensive benchmarks on simulated and real data analyses demonstrate consistent improvements in cell-type identification from TORC.\",\"PeriodicalId\":12611,\"journal\":{\"name\":\"Genome Biology\",\"volume\":\"20 1\",\"pages\":\"\"},\"PeriodicalIF\":10.1000,\"publicationDate\":\"2025-06-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Genome Biology\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1186/s13059-025-03614-6\",\"RegionNum\":1,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOTECHNOLOGY & APPLIED MICROBIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genome Biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1186/s13059-025-03614-6","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOTECHNOLOGY & APPLIED MICROBIOLOGY","Score":null,"Total":0}
TORC: Target-Oriented Reference Construction for supervised cell-type identification in scRNA-seq
Cell-type identification is a crucial step in single cell RNA-seq (scRNA-seq) data analysis, for which supervised methods are preferred due to their accuracy and efficiency. Performance is highly dependent on the quality of the reference data, but there is no method for selecting and constructing reference data. We develop Target-Oriented Reference Construction (TORC), a widely applicable strategy for constructing reference data given a target dataset for scRNA-seq supervised cell-type identification. TORC alleviates the differences in data distribution and cell-type composition between reference and target. Extensive benchmarks on simulated and real data analyses demonstrate consistent improvements in cell-type identification from TORC.
Genome BiologyBiochemistry, Genetics and Molecular Biology-Genetics
CiteScore
21.00
自引率
3.30%
发文量
241
审稿时长
2 months
期刊介绍:
Genome Biology stands as a premier platform for exceptional research across all domains of biology and biomedicine, explored through a genomic and post-genomic lens.
With an impressive impact factor of 12.3 (2022),* the journal secures its position as the 3rd-ranked research journal in the Genetics and Heredity category and the 2nd-ranked research journal in the Biotechnology and Applied Microbiology category by Thomson Reuters. Notably, Genome Biology holds the distinction of being the highest-ranked open-access journal in this category.
Our dedicated team of highly trained in-house Editors collaborates closely with our esteemed Editorial Board of international experts, ensuring the journal remains on the forefront of scientific advances and community standards. Regular engagement with researchers at conferences and institute visits underscores our commitment to staying abreast of the latest developments in the field.