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基因表达差异的序列分析:RNA-Seq 数据分析。

Sequences to Differences in Gene Expression: Analysis of RNA-Seq Data.

机构信息

Moscow Institute of Physics and Technology, Dolgoprudny, Russia.

Universitätskilinkum Freiburg, Freiburg, Germany.

出版信息

Methods Mol Biol. 2022;2508:279-318. doi: 10.1007/978-1-0716-2376-3_20.

Abstract

RNA-Seq is now a routinely employed assay to measure gene expression. As the technique matured over the last decade, so have dedicated analytic tools. In this chapter, we first describe the mainstream as well as the most up-to-date protocols and their implications on downstream analysis. We then detail the steps entailing RNA-Seq analysis in three main stages: (i) preprocessing and data preparation, (ii) upstream processing, and (iii) high-level analyses. We review the most recent and relevant tools as one workflow following a stepwise order. The chapter further encompasses in-depth features of these tools. Details of the required code are made available throughout the chapter, as well as of the underlying statistics. We illustrate these steps with analysis of publicly available RNA-Seq data.

摘要

RNA-Seq 现在是一种常规使用的测量基因表达的方法。随着这项技术在过去十年中的发展,专用的分析工具也不断发展。在本章中,我们首先描述了主流和最新的协议及其对下游分析的影响。然后,我们详细介绍了 RNA-Seq 分析的三个主要阶段所涉及的步骤:(i)预处理和数据准备,(ii)上游处理,以及(iii)高级分析。我们按照逐步顺序回顾了最新和相关的工具作为一个工作流程。本章还包括这些工具的深入特性。整个章节都提供了所需代码的详细信息,以及基础统计信息。我们使用公共可用的 RNA-Seq 数据进行了这些步骤的演示。

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