{"title":"通过底层 DNA 序列的指导来标注单细胞 ATAC 数据中的细胞类型","authors":"","doi":"10.1038/s43588-024-00626-3","DOIUrl":null,"url":null,"abstract":"SANGO efficiently removed batch effects between the query and reference single-cell ATAC signals through the underlying genome sequences, to enable cell type assignment according to the reference data. The method achieved superior performance on diverse datasets and could detect unknown tumor cells, providing valuable functional biological signals.","PeriodicalId":74246,"journal":{"name":"Nature computational science","volume":null,"pages":null},"PeriodicalIF":12.0000,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Annotating cell types in single-cell ATAC data via the guidance of the underlying DNA sequences\",\"authors\":\"\",\"doi\":\"10.1038/s43588-024-00626-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"SANGO efficiently removed batch effects between the query and reference single-cell ATAC signals through the underlying genome sequences, to enable cell type assignment according to the reference data. The method achieved superior performance on diverse datasets and could detect unknown tumor cells, providing valuable functional biological signals.\",\"PeriodicalId\":74246,\"journal\":{\"name\":\"Nature computational science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":12.0000,\"publicationDate\":\"2024-04-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature computational science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.nature.com/articles/s43588-024-00626-3\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature computational science","FirstCategoryId":"1085","ListUrlMain":"https://www.nature.com/articles/s43588-024-00626-3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Annotating cell types in single-cell ATAC data via the guidance of the underlying DNA sequences
SANGO efficiently removed batch effects between the query and reference single-cell ATAC signals through the underlying genome sequences, to enable cell type assignment according to the reference data. The method achieved superior performance on diverse datasets and could detect unknown tumor cells, providing valuable functional biological signals.
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