Next-Generation Sequencing

Standard Operating Procedures and Applications

Prashanth N Suravajhala, Jeff W Bizzaro

• Publisher: CRC Press
• Year: 2025
• eBook ISBN: 9781040149874
• Edition: 0
• Topic: Physical Sciences
• Subtopic: Biostatistics

This cutting-edge reference book compiles standard operating procedures, protocols, and applications of next-generation sequencing (NGS). It discusses genomic testing applications through NGS. It pays special focus on the protocols for cataloguing variants of uncertain significance. Over the years, NGS and advanced bioinformatics approaches have allowed the transition of genomic assays into translational practices. The book covers visualisation of NGS datasets, investigation of early development impairment, and metagenome protocols. It also discusses the challenges in NGS methods.

Key Points:

• Includes case studies of application of NGS in different taxa like humans, rodents, plants, and bacteria
• Compiles protocols from various reputed companies like Illumina, PacBio, and ThermoFisher
• Discusses the translational applications of NGS methods
• Reviews machine learning heuristics for NGS data interpretation
• Discusses emerging genomic assay technologies and characterising mechanisms of disease prevalence

The book is meant for researchers and industry experts in genomics, computational biology, and bioinformatics.

Chapter 7 and 9 of this book is freely available as a downloadable Open Access PDF at http://www.taylorfrancis.com under a Creative Commons [Attribution-Non Commercial-No Derivatives (CC BY-NC-ND)] 4.0 license.

Table of contents

• Cover Page
• Half-Title Page
• Title Page
• Copyright Page
• Dedication Page
• Contents
• Foreword
• Preface
• About the Editors
• List of Contributors
• Chapter 1 Technologies, Computations, and Data Analysis for Next-Generation Sequencing
• Chapter 2 Epigenetics: RNA-seq, ChIP-seq, ATAC-seq, and MeDIP-seq
• Chapter 3 Streamlining Next-Generation Sequencing Data Analysis with Nextflow and nf-core Pipelines
• Chapter 4 Best Practices for Variant Calling Using the Genome Analysis Toolkit
• Chapter 5 Implementation of WGCNA for Identifying Regulatory Modules in Biological Networks
• Chapter 6 Meta-Analysis of RNA-seq and Microarray Data
• Chapter 7 Best Practices in Single-Cell RNA-seq Data Analysis
• Chapter 8 Integration of Spatial Transcriptomics and Single-Cell RNA-seq
• Chapter 9 Metagenomic Analysis Pipelines for Microbiome Studies: QIIME and mothur
• Chapter 10 Standard Operating Procedure and Applications in Single-Cell Transcriptomics
• Chapter 11 Benchmarking and Evaluation of de novo Assembly Tools for Prokaryotic Long Reads from Oxford Nanopore Technologies
• Chapter 12 Best Practices for Reproducible Microbial Genomics Analyses
• Chapter 13 Single-Cell RNA-seq Data Analysis in the Era of Artificial Intelligence
• Chapter 14 The Central Dogma of Single-Molecule Sequencing: From DNA to RNA to Proteins
• Chapter 15 Standard Operating Procedures for Effective Galaxy Workflows
• Chapter 16 Motif Prediction Using ChIP-seq Data Analysis with Galaxy
• Chapter 17 Developing a Whole Exome Consensus Variant-Calling Pipeline to Infer Causal Pathogenic Variants
• Index