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

• Record Nr.: UNINA9910812209403321
• Pubbl/distr/stampa: Hoboken, New Jersey : , : John Wiley & Sons, , [2016]; ©2016
• ISBN: 1-119-27217-3; 1-119-27216-5; 1-119-27218-1
• Descrizione fisica: 1 online resource (461 p.)
• Collana: Wiley series on bioinformatics : computational techniques and engineering
• Disciplina: 611/.0181663
• Soggetti: Nucleotide sequence - Methodology; Nucleotide sequence - Data processing
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: 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