Introduces readers to core algorithmic techniques for next-generation
sequencing (NGS) data analysis and discusses a wide range of
computational techniques and applications
This book provides an in-depth survey of some of the recent developments
in NGS and discusses mathematical and computational challenges in
various application areas of NGS technologies. The 18 chapters featured
in this book have been authored by bioinformatics experts and represent
the latest work in leading labs actively contributing to the
fast-growing field of NGS. The book is divided into four parts:
Part I focuses on computing and experimental infrastructure for NGS
analysis, including chapters on cloud computing, modular pipelines for
metabolic pathway reconstruction, pooling strategies for massive viral
sequencing, and high-fidelity sequencing protocols.
Part II concentrates on analysis of DNA sequencing data, covering the
classic scaffolding problem, detection of genomic variants, including
insertions and deletions, and analysis of DNA methylation sequencing
data.
Part III is devoted to analysis of RNA-seq data. This part discusses
algorithms and compares software tools for transcriptome assembly along
with methods for detection of alternative splicing and tools for
transcriptome quantification and differential expression analysis.
Part IV explores computational tools for NGS applications in
microbiomics, including a discussion on error correction of NGS reads
from viral populations, methods for viral quasispecies reconstruction,
and a survey of state-of-the-art methods and future trends in microbiome
analysis.
Computational Methods for Next Generation Sequencing Data Analysis:
- Reviews computational techniques such as new combinatorial
optimization methods, data structures, high performance computing,
machine learning, and inference algorithms
- Discusses the mathematical and computational challenges in NGS
technologies
- Covers NGS error correction, de novo genome transcriptome assembly,
variant detection from NGS reads, and more
This text is a reference for biomedical professionals interested in
expanding their knowledge of computational techniques for NGS data
analysis. The book is also useful for graduate and post-graduate
students in bioinformatics.
