Next-Generation Sequencing Data Analysis

Next-generation DNA and RNA sequencing has revolutionized biology and medicine. With sequencing costs continuously dropping and our ability to generate large datasets rising, data analysis becomes more important than ever. Next-Generation Sequencing Data Analysis walks readers through next-generation sequencing (NGS) data analysis step by step for a wide range of NGS applications.

For each NGS application, this book covers topics from experimental design, sample processing, sequencing strategy formulation, to sequencing read quality control, data preprocessing, read mapping or assembly, and more advanced stages that are specific to each application. Major applications include:

• RNA-seq: Both bulk and single cell (separate chapters)
• Genotyping and variant discovery through whole genome/exome sequencing
• Clinical sequencing and detection of actionable variants
• De novo genome assembly
• ChIP-seq to map protein-DNA interactions
• Epigenomics through DNA methylation sequencing
• Metagenome sequencing for microbiome analysis

Before detailing the analytic steps for each of these applications, the book presents introductory cellular and molecular biology as a refresher mostly for data scientists, the ins and outs of widely used NGS platforms, and an overview of computing needs for NGS data management and analysis. The book concludes with a chapter on the changing landscape of NGS technologies and data analytics.

The second edition of this book builds on the well-received first edition by providing updates to each chapter. Two brand new chapters have been added to meet rising data analysis demands on single-cell RNA-seq and clinical sequencing. The increasing use of long-read sequencing has also been reflected in all NGS applications. This book discusses concepts and principles that underlie each analytic step, along with software tools for implementation. It highlights key features of the tools while omitting tedious details to provide an easy-to-follow guide for practitioners in life sciences, bioinformatics, biostatistics, and data science. Tools introduced in this book are open source and freely available.

下一代DNA和RNA测序已经彻底改变了生物学和医学。随着测序成本不断下降和我们生成大型数据集的能力不断提高，数据分析变得比以往任何时候都更加重要。《下一代测序数据分析》逐步引导读者进行各种下一代测序（NGS）应用的数据分析。

对于每个NGS应用，本书涵盖了从实验设计、样品处理、测序策略制定，到测序读取质量控制、数据预处理、读取映射或组装，以及针对每个应用特定的更高级阶段的主题。主要应用包括：

- RNA测序：包括批量和单细胞（分开的章节）
- 通过全基因组/外显子测序进行基因分型和变异发现
- 临床测序和可操作变异的检测
- 新基因组组装
- ChIP-seq用于映射蛋白质-DNA相互作用
- 通过DNA甲基化测序进行表观基因组学
- 用于微生物组分析的宏基因组测序

在详细介绍每个应用的分析步骤之前，本书为数据科学家提供了细胞和分子生物学的入门知识，介绍了广泛使用的NGS平台的内外情况，并概述了NGS数据管理和分析的计算需求。本书以关于NGS技术和数据分析变化的章节作为结尾。

本书的第二版在第一版的基础上进行了更新，每个章节都进行了更新。为了满足对单细胞RNA测序和临床测序日益增长的数据分析需求，增加了两个全新的章节。长读序列测序的使用也在所有NGS应用中得到了反映。本书讨论了每个分析步骤的概念和原则，以及用于实施的软件工具。它突出了工具的关键特点，省略了繁琐的细节，为生命科学、生物信息学、生物统计学和数据科学从业人员提供了易于跟随的指南。本书介绍的工具是开源且免费提供的。

Dr. Xinkun Wang is a research professor and the director of the Next-Generation Sequencing Facility at Northwestern University in Chicago. Dr. Wang's first foray into the genomics field was during his doctoral training, performing microarray-based gene expression analysis. From 2005 to 2015, he was the founding director of the University of Kansas Genomics Facility, prior to moving to Northwestern to head the Northwestern University Sequencing Facility (NUSeq) in late 2015. Dr. Wang is a renowned expert on genomics technologies and data mining, and their applications to the biomedical field. Besides his monographic publications, he has published extensively in neuroscience, with a focus on brain aging and neurodegenerative diseases (mostly Alzheimer's disease).

Dr. Wang has served as principal investigator on dozens of grants. Dr. Wang's other professional activities include serving on journal editorial boards, and as reviewers for journals, publishers, and funding agencies. Dr. Wang is a member of American Society of Human Genetics, Association of Biomolecular Resource Facilities, the Honor Society of Phi Kappa Phi, and Society for Neuroscience. Dr. Wang was born in Shandong province, China, and is a first-generation college graduate. His off-work hobbies include cycling and Alpine skiing.

「Dr. Xinkun Wang」是芝加哥西北大學的研究教授，也是該校「Next-Generation Sequencing Facility」的主任。Dr. Wang在基因組學領域的首次嘗試是在他的博士訓練期間，進行基於微陣列的基因表達分析。從2005年到2015年，他擔任堪薩斯大學基因組學設施的創始主任，之後於2015年底轉至西北大學擔任西北大學测序設施（NUSeq）的負責人。Dr. Wang是基因組學技術和數據挖掘以及其在生物醫學領域的應用的知名專家。除了他的專著出版物外，他在神經科學領域也有廣泛的發表，尤其關注腦老化和神經退行性疾病（主要是阿茲海默症）。

「Dr. Wang」擔任過數十個研究計劃的首席調查員。Dr. Wang的其他專業活動包括擔任期刊編輯委員會成員，以及期刊、出版商和資助機構的審稿人。Dr. Wang是美國人類遺傳學會、生物分子資源設施協會、Phi Kappa Phi榮譽學會和神經科學學會的成員。Dr. Wang出生於中國山東省，是第一代大學畢業生。他在工作之餘的愛好包括騎自行車和高山滑雪。