{"title":"从基于峰的单细胞ATAC-seq中捕获顺式调控元件的细胞类型特异性活性。","authors":"Mengjie Chen","doi":"10.1016/j.xgen.2025.100806","DOIUrl":null,"url":null,"abstract":"<p><p>Single-cell ATAC sequencing (scATAC-seq), a state-of-the-art genomic technique designed to map chromatin accessibility at the single-cell level, presents unique analytical challenges due to limited sampling and data sparsity. In this study, we use case studies to highlight the limitations of conventional peak-based methods for processing scATAC-seq data. These methods can fail to capture precise cell-type-specific regulatory signals, producing results that are difficult to interpret and lack portability, thereby compromising the reproducibility of research findings. To overcome these issues, we introduce CREscendo, a method that utilizes Tn5 cleavage frequencies and regulatory annotations to identify differential usage of candidate regulatory elements (CREs) across cell types. Our research advocates for moving away from traditional peak-based quantification in scATAC-seq toward a more robust framework that relies on a standardized reference of annotated CREs, enhancing both the accuracy and reproducibility of genomic studies.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":" ","pages":"100806"},"PeriodicalIF":11.1000,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11960509/pdf/","citationCount":"0","resultStr":"{\"title\":\"Capturing cell-type-specific activities of cis-regulatory elements from peak-based single-cell ATAC-seq.\",\"authors\":\"Mengjie Chen\",\"doi\":\"10.1016/j.xgen.2025.100806\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Single-cell ATAC sequencing (scATAC-seq), a state-of-the-art genomic technique designed to map chromatin accessibility at the single-cell level, presents unique analytical challenges due to limited sampling and data sparsity. In this study, we use case studies to highlight the limitations of conventional peak-based methods for processing scATAC-seq data. These methods can fail to capture precise cell-type-specific regulatory signals, producing results that are difficult to interpret and lack portability, thereby compromising the reproducibility of research findings. To overcome these issues, we introduce CREscendo, a method that utilizes Tn5 cleavage frequencies and regulatory annotations to identify differential usage of candidate regulatory elements (CREs) across cell types. Our research advocates for moving away from traditional peak-based quantification in scATAC-seq toward a more robust framework that relies on a standardized reference of annotated CREs, enhancing both the accuracy and reproducibility of genomic studies.</p>\",\"PeriodicalId\":72539,\"journal\":{\"name\":\"Cell genomics\",\"volume\":\" \",\"pages\":\"100806\"},\"PeriodicalIF\":11.1000,\"publicationDate\":\"2025-03-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11960509/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cell genomics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1016/j.xgen.2025.100806\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/3/5 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"CELL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cell genomics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.xgen.2025.100806","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/3/5 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
Capturing cell-type-specific activities of cis-regulatory elements from peak-based single-cell ATAC-seq.
Single-cell ATAC sequencing (scATAC-seq), a state-of-the-art genomic technique designed to map chromatin accessibility at the single-cell level, presents unique analytical challenges due to limited sampling and data sparsity. In this study, we use case studies to highlight the limitations of conventional peak-based methods for processing scATAC-seq data. These methods can fail to capture precise cell-type-specific regulatory signals, producing results that are difficult to interpret and lack portability, thereby compromising the reproducibility of research findings. To overcome these issues, we introduce CREscendo, a method that utilizes Tn5 cleavage frequencies and regulatory annotations to identify differential usage of candidate regulatory elements (CREs) across cell types. Our research advocates for moving away from traditional peak-based quantification in scATAC-seq toward a more robust framework that relies on a standardized reference of annotated CREs, enhancing both the accuracy and reproducibility of genomic studies.