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scATAC-seq预处理和归算评估系统用于可视化,集群和数字足迹

Pavel Akhtyamov^1,2, Layal Shaheen^1,2, Mikhail Raevskiy³

¹Department of Biomedical Physics, Moscow Institute of Physics and Technology (National Research University), 9 Institutskiy per., 141701, Moscow Region, Russian Federation.

Briefings in bioinformatics

|December 12, 2023

概括

对于大多数单细胞ATAC-seq分析,使用Boruta进行预处理是最好的,而归算则有助于较小的数据集. SAPIEnS对这些策略进行了表观遗传见解的基准测试.

科学领域:

基因组学就是基因组学.
表观遗传学在表观遗传学中,表观遗传学是指表观遗传学.
计算生物学计算生物学

背景情况:

单细胞ATAC-seq (scATAC-seq) 能够在单细胞分辨率下进行染色质可访问性和转录因子结合分析.
在scATAC-seq中的数据稀疏性需要归算,而大型特征集需要预处理以提高计算效率.
对于 scATAC-seq 归算和预处理的最佳组合策略仍未得到充分探索.

研究的目的:

为了对scATAC-seq数据的归算框架进行基准测试.
评估归算和预处理对下游分析的综合影响.
为各种 scATAC-seq 应用程序确定最佳的预处理-归算策略.

主要方法:

开发了SAPIEnS (scATAC-seq预处理和计算评估系统).
整合最先进的归算方法与常见的预处理技术.
使用基准策略对聚类,可视化和数字基因足迹的评估.

主要成果:

在大多数scATAC-seq分析任务中,Boruta预处理方法被证明是有益的.
鉴定策略在较小的数据集中是最有效的.
根据分析类型和数据集特征数量确定了最佳策略.

结论:

SAPIEnS提供了一个评估scATAC-seq数据处理管道的框架.
预处理通常比归算更具影响力,特别是在较大的数据集中.
该研究为特定的scATAC-seq研究问题提供了选择归算和预处理方法的指导.

关键词:

数字足迹的数字足迹归算是指指责一个人.预处理预处理这就是 scATAC-seqq.一个单细胞的单细胞.

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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 microarray-based...