Aiming to foster future collaborations between researchers in algorithms, bioinformatics, and molecular biology, this book serves as an up-to-date survey of the most important recent developments and computational challenges in various application areas of next-generation sequencing technologies.

CONTRIBUTORS xix PREFACE xxiii ABOUT THE COMPANION WEBSITE xxv PART I COMPUTING AND EXPERIMENTAL INFRASTRUCTURE FOR NGS 1 1 Cloud Computing for Next-Generation Sequencing Data Analysis 3Xuan Guo, Ning Yu, Bing Li, and Yi Pan 2 Introduction to the Analysis of Environmental Sequence Information Using Metapathways 25Niels W. Hanson, Kishori M. Konwar, Shang-Ju Wu, and Steven J. Hallam 3 Pooling Strategy for Massive Viral Sequencing 57Pavel Skums, Alexander Artyomenko, Olga Glebova, Sumathi Ramachandran, David S. Campo, Zoya Dimitrova, Ion I. Mândoiu, Alexander Zelikovsky, and Yury Khudyakov 4 Applications of High-Fidelity Sequencing Protocol to RNA Viruses 85Serghei Mangul, Nicholas C. Wu, Ekaterina Nenastyeva, Nicholas Mancuso, Alexander Zelikovsky, Ren Sun, and Eleazar Eskin PART II GENOMICS AND EPIGENOMICS 105 5 Scaffolding Algorithms 107Igor Mandric, James Lindsay, Ion I.Mândoiu, and Alexander Zelikovsky 6 Genomic Variants Detection and Genotyping 133Jorge Duitama 7 Discovering and Genotyping Twilight Zone Deletions 149Tobias Marschall and Alexander Schönhuth 8 Computational Approaches for Finding Long Insertions and Deletions with NGS Data 175Jin Zhang, Chong Chu, and Yufeng Wu 9 Computational Approaches in Next-Generation Sequencing Data Analysis for Genome-Wide DNA Methylation Studies 197Jeong-Hyeon Choi and Huidong Shi 10 Bisulfite-Conversion-Based Methods for DNA Methylation Sequencing Data Analysis 227Elena Harris and Stefano Lonardi PART III TRANSCRIPTOMICS 245 11 Computational Methods for Transcript Assembly from RNA-SEQ Reads 247Stefan Canzar and Liliana Florea 12 An Overview And Comparison of Tools for RNA-Seq Assembly 269Rasiah Loganantharaj and Thomas A. Randall 13 Computational Approaches for Studying Alternative Splicing in Nonmodel Organisms From RNA-SEQ Data 287Sing-Hoi Sze 14 Transcriptome Quantification and Differential Expression From NGS Data 301Olga Glebova, Yvette Temate-Tiagueu, Adrian Caciula, Sahar Al Seesi, Alexander Artyomenko, Serghei Mangul, James Lindsay, Ion I. M¢andoiu, and Alexander Zelikovsky PART IV MICROBIOMICS 329 15 Error Correction of NGS Reads from Viral Populations 331Pavel Skums, Alexander Artyomenko, Olga Glebova, David S. Campo, Zoya Dimitrova, Alexander Zelikovsky, and Yury Khudyakov 16 Probabilistic Viral Quasispecies Assembly 355Armin Töpfer and Niko Beerenwinkel 17 Reconstruction of Infectious Bronchitis Virus Quasispecies from NGS Data 383Bassam Tork, Ekaterina Nenastyeva, Alexander Artyomenko, Nicholas Mancuso, Mazhar I. Khan, Rachel O’Neill, Ion I. Mândoiu, and Alexander Zelikovsky 18 Microbiome Analysis: State of the Art and Future Trends 401Mitch Fernandez, Vanessa Aguiar-Pulido, Juan Riveros, Wenrui Huang, Jonathan Segal, Erliang Zeng, Michael Campos, Kalai Mathee, and Giri Narasimhan INDEX 425

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 algorithmsDiscusses the mathematical and computational challenges in NGS technologiesCovers NGS error correction, de novo genome transcriptome assembly, variant detection from NGS reads, and more This textis 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.