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RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

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Updated: Jul 15, 2025

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

在单细胞RNA-seq和ATAC-seq数据集成中,scBridge包含了细胞异质性.

Yunfan Li¹, Dan Zhang², Mouxing Yang¹

¹School of Computer Science, Sichuan University, Chengdu, Sichuan, China.

Nature communications

|September 28, 2023

概括

细胞异质性可以改善单细胞多组组合的整合. scBridge利用这一点将细胞整合为异质,减少omics差异并增强数据分析以获得更好的生物洞察力.

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Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

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科学领域:

计算生物学计算生物学
基因组学就是基因组学.
生物信息学是一种生物信息学.

背景情况:

单细胞多omics数据集成旨在在保持细胞身份的同时调整不同的数据类型.
细胞异质性使分辨奥米克和细胞类型特定变异变得复杂.
现有的方法往往难以解释这种固有的生物变异性.

研究的目的:

开发一种用于单细胞多组数据集成的新方法,利用细胞异质性.
改进从单个单元格集成多种omics数据集的准确性和稳定性.
为了应对在异质细胞群中区分细胞类型差异和细胞特征差异的挑战.

主要方法:

提出了scBridge,一种异质的多omics集成方法.
scBridge 以代方式识别出具有最小的奥米克差异 (可靠的细胞) 的细胞.
将这些可靠的细胞与其他omics数据 (例如,scRNA-seq) 集成,以弥合omics差距.

主要成果:

证明了利用细胞异质性进行数据整合的有效性.
scBridge成功地减少了omics差异,同时保持了细胞类型的区别.
在七个多主题数据集中表现优于六种代表性基线方法.

结论:

细胞异质性是一个有价值的特征,不仅仅是噪声,用于多omics集成.
通过处理异质性,scBridge提供了一种优越的方法来实现单细胞多omics数据集成.
该方法提高了使用多omics数据分析复杂生物系统的能力.