使用基因表达的个体间变异去复杂化单细胞RNA测序数据
Isar Nassiri1,2,3,4, Andrew J Kwok2,5, Aneesha Bhandari2
1Nuffield Department of Medicine, Centre for Human Genetics, Oxford-GSK Institute of Molecular and Computational Medicine (IMCM), University of Oxford, Oxford, OX3 7BN, United Kingdom.
Bioinformatics advances
|June 24, 2024
概括
表达意识解复 (Expression-Aware Demultiplexing,简称EAD) 是一种新的计算方法,用于分析聚合的单细胞RNA测序数据. EAD使用基因共同表达模式来准确地识别来自不同个体的细胞,而不需要额外的实验步骤.
科学领域:
- 基因组学就是基因组学.
- 计算生物学 计算生物学
- 生物信息学是一种生物信息学.
背景情况:
- 在单细胞RNA测序 (scRNA-seq) 中的聚合设计增加了吞吐量,减少了批量效应.
- 在复杂的实验中,去复杂化聚合样本对于区分细胞起源至关重要.
- 现有的方法可能需要额外的实验程序或缺乏准确性.
研究的目的:
- 介绍表达意识解复合 (EAD),一种用于解复合聚合scRNA-seq样本的计算方法.
- 通过合成和真实生物数据验证EAD的有效性.
- 为了证明EAD在不同细胞类型和条件中的适用性.
主要方法:
- 开发了EAD,一种利用个人之间的差异性共同表达模式的计算方法.
- 利用合成样本池来识别关键的个体间差异性共同表达的基因.
- 将EAD应用于来自同源小鼠,败血症/健康个体和大脑单核转录组的组合样本.
主要成果:
- 顶部个体间差异性共同表达的基因形成了每个个体不同的细胞群,突出了代谢调节.
- 与遗传信息相结合的EAD在败血症/健康样本中实现了高的分配准确性 (平均0.98).
- 将EAD与条码技术相结合,平均提高了1.4%的分配精度.
- EAD成功地在不同激活状态下识别了来自同一捐赠者的细胞,并且适用于非免疫性脑细胞.
结论:
- 在没有额外的实验步骤的情况下,EAD提供了一种有效的,以计算驱动的解决方案,用于解复合聚合的scRNA-seq数据.
- 该方法可以根据个体间的共同表达变异准确区分细胞起源.
- EAD提高了分类准确性,并在各种生物环境中提供了广泛的适用性.
更多相关视频
10:23Single-cell Gene Expression Using Multiplex RT-qPCR to Characterize Heterogeneity of Rare Lymphoid Populations
Published on: January 19, 2017
11.0K
09:34A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations
Published on: October 25, 2018
6.7K
相关概念视频
03:21RNA-seq
9.9K
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...
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
9.9K
02:24Ribosome Profiling
3.5K
Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
3.5K