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定量转录基因和表观基因数据分析:一本基础书

Louis Coussement¹, Wim Van Criekinge¹, Tim De Meyer¹

¹Department of Data Analysis and Mathematical Modelling, Ghent University, Ghent, 9000, Belgium.

Bioinformatics advances

|April 8, 2024

概括

本研究介绍了一种分析定量转录基因和表观基因数据的通用工作流,解决了分子生物学研究向奥米克数据分析的转变. 它旨在为研究人员提供概念洞察力,这些研究人员具有基本的奥米克专业知识.

科学领域:

分子生物学分子生物学
生物信息学是一种生物信息学.
基因组学就是基因组学.

背景情况:

微阵列和下一代测序技术使得全面的转录组和表观组分析成为可能.
进步允许单细胞分辨率,将研究瓶转移到数据分析.
现有的文献往往假定专家知识,并专注于数据类型特定的方法.

研究的目的:

提供对全基因组定量转录和表观基因组数据分析的概念洞察力.
描述一种通用的工作流程,适用于不同的omics数据类型.
为了让读者具有基本的奥米克专业知识,能够理解一般的策略和陷.

主要方法:

描述一个通用的工作流程,用于OMIC数据分析.
解释基础原则和假设.
为特定数据类型引入数据分析解决方案.

主要成果:

介绍了一个对OMIC数据分析的通用框架.
强调了基于数据类型的定制解决方案的需求.
增强对OMIC数据分析的概念和统计理解.

结论:

通用工作流有助于理解复杂的数据分析.
它弥合了基本的奥米克专业知识和专业文献之间的差距.
研究人员可以更好地应对转录基因和表观基因组数据分析的挑战.

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RNA-seq

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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...