Next-Generation Sequencing Data Analysis

A Practical Guide to the Highly Dynamic Area of Massively Parallel SequencingThe development of genome and transcriptome sequencing technologies has led to a paradigm shift in life science research and disease diagnosis and prevention. Scientists are now able to see how human diseases and phenotypic changes are connected to DNA mutation, polymorphi Front Cover 1 Contents 7 Chapter 1: The Cellular System and the Code of Life 17 Chapter 2: DNA Sequence: The Genome Base 31 Chapter 3: RNA: The Transcribed Sequence 49 Chapter 4: Next-Generation Sequencing (NGS) Technologies: Ins and Outs 69 Chapter 5: Early-Stage Next-Generation Sequencing (NGS) Data Analysis: Common Steps 87 Chapter 6: Computing Needs for Next-Generation Sequencing (NGS) Data Management and Analysis 101 Chapter 7: Transcriptomics by RNA-Seq 111 Chapter 8: Small RNA Sequencing 125 Chapter 9: Genotyping and Genomic Variation Discovery by Whole Genome Resequencing 133 Chapter 10: De novo Genome Assembly from Next-Generation Sequencing (NGS) Reads 145 Chapter 11: Mapping Protein–DNA Interactions with ChIP-Seq 157 Chapter 12: Epigenomics and DNA Methylation Analysis by Next-Generation Sequencing (NGS) 177 Chapter 13: Metagenome Analysis by Next-Generation Sequencing (NGS) 189 Chapter 14: What Is Next for Next-Generation Sequencing (NGS)? 205 Appendix A: Common File Types Used in Next-Generation Sequencing (NGS) Data Analysis 213 Appendix B: Glossary 217 References 227 Back Cover 251