• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

单细胞 RNA 测序的异构体水平定量。

Isoform-level quantification for single-cell RNA sequencing.

机构信息

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 17177 Stockholm, Sweden.

McArdle Laboratory for Cancer Research, Department of Oncology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705-227, USA.

出版信息

Bioinformatics. 2022 Feb 7;38(5):1287-1294. doi: 10.1093/bioinformatics/btab807.

DOI:10.1093/bioinformatics/btab807
PMID:34864849
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8826380/
Abstract

MOTIVATION

RNA expression at isoform level is biologically more informative than at gene level and can potentially reveal cellular subsets and corresponding biomarkers that are not visible at gene level. However, due to the strong 3' bias sequencing protocol, mRNA quantification for high-throughput single-cell RNA sequencing such as Chromium Single Cell 3' 10× Genomics is currently performed at the gene level.

RESULTS

We have developed an isoform-level quantification method for high-throughput single-cell RNA sequencing by exploiting the concepts of transcription clusters and isoform paralogs. The method, called Scasa, compares well in simulations against competing approaches including Alevin, Cellranger, Kallisto, Salmon, Terminus and STARsolo at both isoform- and gene-level expression. The reanalysis of a CITE-Seq dataset with isoform-based Scasa reveals a subgroup of CD14 monocytes missed by gene-based methods.

AVAILABILITY AND IMPLEMENTATION

Implementation of Scasa including source code, documentation, tutorials and test data supporting this study is available at Github: https://github.com/eudoraleer/scasa and Zenodo: https://doi.org/10.5281/zenodo.5712503.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

摘要

动机

在异构体水平上的 RNA 表达比在基因水平上更具有生物学意义,并且有可能揭示在基因水平上不可见的细胞亚群和相应的生物标志物。然而,由于强烈的 3' 偏向测序方案,高通量单细胞 RNA 测序(如 Chromium Single Cell 3' 10× Genomics)的 mRNA 定量目前是在基因水平上进行的。

结果

我们通过利用转录簇和异构体同源物的概念,开发了一种用于高通量单细胞 RNA 测序的异构体水平定量方法。该方法称为 Scasa,在模拟中与竞争方法(包括 Alevin、Cellranger、Kallisto、Salmon、Terminus 和 STARsolo)相比,在异构体和基因水平的表达上都表现良好。使用基于异构体的 Scasa 对 CITE-Seq 数据集的重新分析揭示了基于基因的方法错过的 CD14 单核细胞亚群。

可用性和实现

包括支持本研究的源代码、文档、教程和测试数据的 Scasa 的实现可在 Github:https://github.com/eudoraleer/scasa 和 Zenodo:https://doi.org/10.5281/zenodo.5712503 上获得。

补充信息

补充数据可在生物信息学在线获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7e28/8826380/8999b93adc65/btab807f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7e28/8826380/015f82f22279/btab807f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7e28/8826380/8999b93adc65/btab807f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7e28/8826380/015f82f22279/btab807f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7e28/8826380/8999b93adc65/btab807f2.jpg

相似文献

1
Isoform-level quantification for single-cell RNA sequencing.单细胞 RNA 测序的异构体水平定量。
Bioinformatics. 2022 Feb 7;38(5):1287-1294. doi: 10.1093/bioinformatics/btab807.
2
Platform-integrated mRNA isoform quantification.平台整合的 mRNA 异构体定量。
Bioinformatics. 2020 Apr 15;36(8):2466-2473. doi: 10.1093/bioinformatics/btz932.
3
Deconvolution of expression for nascent RNA-sequencing data (DENR) highlights pre-RNA isoform diversity in human cells.去卷积表达新生 RNA 测序数据(DENR)突出了人类细胞中前 RNA 异构体的多样性。
Bioinformatics. 2021 Dec 11;37(24):4727-4736. doi: 10.1093/bioinformatics/btab582.
4
PennDiff: detecting differential alternative splicing and transcription by RNA sequencing.PennDiff:通过 RNA 测序检测差异剪接和转录。
Bioinformatics. 2018 Jul 15;34(14):2384-2391. doi: 10.1093/bioinformatics/bty097.
5
An expectation-maximization framework for comprehensive prediction of isoform-specific functions.一种全面预测异构体特异性功能的期望最大化框架。
Bioinformatics. 2023 Apr 3;39(4). doi: 10.1093/bioinformatics/btad132.
6
Isoform-level gene expression patterns in single-cell RNA-sequencing data.单细胞 RNA 测序数据中的异构体水平基因表达模式。
Bioinformatics. 2018 Jul 15;34(14):2392-2400. doi: 10.1093/bioinformatics/bty100.
7
IsoCell: An Approach to Enhance Single Cell Clustering by Integrating Isoform-Level Expression Through Orthogonal Projection.IsoCell:一种通过正交投影整合异构体水平表达来增强单细胞聚类的方法。
IEEE/ACM Trans Comput Biol Bioinform. 2023 Jan-Feb;20(1):465-475. doi: 10.1109/TCBB.2022.3147193. Epub 2023 Feb 3.
8
QuickIsoSeq for Isoform Quantification in Large-Scale RNA Sequencing.QuickIsoSeq 用于大规模 RNA 测序中的异构体定量。
Methods Mol Biol. 2021;2284:135-145. doi: 10.1007/978-1-0716-1307-8_8.
9
Episo: quantitative estimation of RNA 5-methylcytosine at isoform level by high-throughput sequencing of RNA treated with bisulfite.片段:通过 RNA 经亚硫酸氢盐处理后的高通量测序对 RNA 5-甲基胞嘧啶进行同型水平的定量估计。
Bioinformatics. 2020 Apr 1;36(7):2033-2039. doi: 10.1093/bioinformatics/btz900.
10
A large-scale comparative study of isoform expressions measured on four platforms.四种平台检测的异构体表达的大规模比较研究。
BMC Genomics. 2020 Mar 30;21(1):272. doi: 10.1186/s12864-020-6643-8.

引用本文的文献

1
DOLPHIN advances single-cell transcriptomics beyond gene level by leveraging exon and junction reads.DOLPHIN通过利用外显子和连接序列读取,将单细胞转录组学提升到基因水平之上。
Nat Commun. 2025 Jul 4;16(1):6202. doi: 10.1038/s41467-025-61580-w.
2
Single cell RNA-sequencing identified CCR7+/RELB+/IRF1+ T cell responding for juvenile idiopathic arthritis pathogenesis.单细胞RNA测序确定了CCR7+/RELB+/IRF1+ T细胞参与幼年特发性关节炎的发病机制。
Front Immunol. 2025 May 8;16:1528446. doi: 10.3389/fimmu.2025.1528446. eCollection 2025.
3
Shared and distinct peripheral blood immune cell landscape in MCTD, SLE, and pSS.
混合性结缔组织病、系统性红斑狼疮和原发性干燥综合征中共享和独特的外周血免疫细胞图谱。
Cell Biosci. 2025 Apr 10;15(1):42. doi: 10.1186/s13578-025-01374-1.
4
Full-length mRNA sequencing resolves novel variation in 5' UTR length for genes expressed during human CD4 T-cell activation.全长mRNA测序解析了人类CD4 T细胞激活过程中表达的基因在5'非翻译区长度上的新变异。
Immunogenetics. 2025 Feb 5;77(1):14. doi: 10.1007/s00251-025-01371-1.
5
Simultaneous profiling of RNA isoforms and chromatin accessibility of single cells of human retinal organoids.单细胞人视网膜类器官的 RNA 异构体和染色质可及性的同时分析。
Nat Commun. 2024 Sep 13;15(1):8022. doi: 10.1038/s41467-024-52335-0.
6
Single-cell genomics and regulatory networks for 388 human brains.单细胞基因组学和 388 个人类大脑的调控网络。
Science. 2024 May 24;384(6698):eadi5199. doi: 10.1126/science.adi5199.
7
Advances in single-cell long-read sequencing technologies.单细胞长读长测序技术的进展
NAR Genom Bioinform. 2024 May 20;6(2):lqae047. doi: 10.1093/nargab/lqae047. eCollection 2024 Jun.
8
Data normalization for addressing the challenges in the analysis of single-cell transcriptomic datasets.用于解决单细胞转录组数据集分析中挑战的数据标准化。
BMC Genomics. 2024 May 6;25(1):444. doi: 10.1186/s12864-024-10364-5.
9
Single-cell genomics and regulatory networks for 388 human brains.388个人类大脑的单细胞基因组学与调控网络
bioRxiv. 2024 Mar 30:2024.03.18.585576. doi: 10.1101/2024.03.18.585576.
10
Transcriptomic analysis of paired healthy human skeletal muscles to identify modulators of disease severity in DMD.对配对的健康人体骨骼肌进行转录组分析,以确定杜氏肌营养不良症(DMD)疾病严重程度的调节因子。
Front Genet. 2023 Jul 27;14:1216066. doi: 10.3389/fgene.2023.1216066. eCollection 2023.