Computational methods for next generation sequencing data analysis / edited by Ion Măndoiu, Alexander Zelikovsky.

Format:

Book

Contributor:

Măndoiu, Ion, editor.

Zelikovsky, Alexander, editor.

Series:

Wiley series on bioinformatics.

Wiley series on bioinformatics : computational techniques and engineering

Language:

English

Subjects (All):

Nucleotide sequence--Methodology.

Nucleotide sequence.

Nucleotide sequence--Data processing.

Physical Description:

1 online resource (461 p.)

Edition:

1st ed.

Place of Publication:

Hoboken, New Jersey : John Wiley & Sons, [2016]

Language Note:

English

Summary:

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.

Contents:

Cover; Title Page; Copyright; Contents; Contributors; Preface; About the Companion Website; Part I Computing and Experimental Infrastructure for NGS; Chapter 1 Cloud Computing for Next-Generation Sequencing Data Analysis; 1.1 Introduction; 1.2 Challenges for NGS Data Analysis; 1.3 Background For Cloud Computing and its Programming Models; 1.4 Cloud Computing Services for NGS Data Analysis; 1.5 Conclusions and Future Directions; References; Chapter 2 Introduction to the Analysis of Environmental Sequence Information Using Metapathways; 2.1 Introduction & Overview; 2.2 Background

2.3 Metapathways Processes2.4 Big Data Processing; 2.5 Downstream Analyses; 2.6 Conclusions; References; Chapter 3 Pooling Strategy for Massive Viral Sequencing; 3.1 Introduction; 3.2 Design of Pools for Big Viral Data; 3.3 Deconvolution of Viral Samples From Pools; 3.4 Performance of Pooling Methods on Simulated Data; 3.5 Experimental Validation of Pooling Strategy; 3.6 Conclusion; References; Chapter 4 Applications of High-Fidelity Sequencing Protocol to RNA Viruses; 4.1 Introduction; 4.2 High-Fidelity Sequencing Protocol; 4.3 Assembly of High-Fidelity Sequencing Data

4.4 Performance of VGA on Simulated Data4.5 Performance of Existing Viral Assemblers on Simulated Consensus Error-Corrected Reads; 4.6 Performance of VGA on Real Hiv Data; 4.7 Comparison of Alignment on Error-Corrected Reads; 4.8 Evaluating of Error Correction Tools Based on High-Fidelity Sequencing Reads; Acknowledgment; References; Part II Genomics and Epigenomics; Chapter 5 Scaffolding Algorithms; 5.1 Scaffolding; 5.2 State-of-The-Art Scaffolding Tools; 5.3 Recent Scaffolding Tools; 5.4 Scaffolding Software Evaluation; References; Chapter 6 Genomic Variants Detection and Genotyping

6.1 Introduction6.2 Methods for Detection and Genotyping OF SNPs and Small Indels; 6.3 Methods for Detection and Genotyping of CNVs; 6.4 Putting Everything Together; References; Chapter 7 Discovering and Genotyping Twilight Zone Deletions; 7.1 Introduction; 7.2 Notation; 7.3 Non-Twilight-Zone Deletion Discovery; 7.4 Discovering ""Twilight Zone"" Deletions: New Solutions; 7.5 Genotyping ""Twilight Zone"" Deletions; 7.6 Results; 7.7 Discussion; 7.8 Availability; Acknowledgments; References; Chapter 8 Computational Approaches for Finding Long Insertions and Deletions with NGS Data

8.1 Background8.2 Methods; 8.3 Applications; 8.4 Conclusions and Future Directions; Acknowledgment; References; Chapter 9 Computational Approaches in Next-Generation Sequencing Data Analysis for Genome-Wide DNA Methylation Studies; 9.1 Introduction; 9.2 Enrichment-Based Approaches; 9.3 Bisulfite Treatment-Based Approaches; 9.4 Conclusion; References; Chapter 10 Bisulfite-Conversion-Based Methods for DNA Methylation Sequencing Data Analysis; 10.1 Introduction; 10.2 The Problem of Mapping BS-Treated Reads; 10.3 Algorithmic Approaches to the Problem Of Mapping BS-Treated Reads

10.4 Methylation Estimation

Notes:

Description based upon print version of record.

Includes bibliographical references and index.

Description based on print version record.

ISBN:

9781119272175

1119272173

9781119272168

1119272165

9781119272182

1119272181

OCLC:

959149276