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

Published:: Hoboken, New Jersey : John Wiley & Sons, 2016.
Physical Description:: 1 online resource
Additional Creators:: Măndoiu, Ion and Zelikovsky, Alexander

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Wiley series on bioinformatics

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Machine generated contents note: 1.Cloud Computing for Next-Generation Sequencing Data Analysis -- 1.1.Introduction, / Xuan Guo / Yi Pan / Bing Li / Ning Yu -- 1.2.Challenges for NGS Data Analysis, / Xuan Guo / Yi Pan / Bing Li / Ning Yu -- 1.3.Background For Cloud Computing and its Programming Models, / Xuan Guo / Yi Pan / Bing Li / Ning Yu -- 1.3.1.Overview of Cloud Computing, / Xuan Guo / Yi Pan / Bing Li / Ning Yu -- 1.3.2.Cloud Service Providers, / Xuan Guo / Yi Pan / Bing Li / Ning Yu -- 1.3.3.Programming Models, / Xuan Guo / Yi Pan / Bing Li / Ning Yu -- 1.4.Cloud Computing Services for NGS Data Analysis, / Xuan Guo / Yi Pan / Bing Li / Ning Yu -- 1.4.1.Hardware as a Service (HaaS), / Xuan Guo / Yi Pan / Bing Li / Ning Yu -- 1.4.2.Platform as a Service (PaaS), / Xuan Guo / Yi Pan / Bing Li / Ning Yu -- 1.4.3.Software as a Service (SaaS), / Xuan Guo / Yi Pan / Bing Li / Ning Yu -- 1.4.4.Data as a Service (DaaS), / Xuan Guo / Yi Pan / Bing Li / Ning Yu -- 1.5.Conclusions and Future Directions, / Xuan Guo / Yi Pan / Bing Li / Ning Yu -- References, / Xuan Guo / Yi Pan / Bing Li / Ning Yu -- 2.Introduction to the Analysis of Environmental Sequence Information Using Metapathways / Xuan Guo / Yi Pan / Bing Li / Ning Yu -- 2.1.Introduction & Overview, / Niels W. Hanson / Steven J. Hallam / Shang-Ju Wu / Kishori M. Konwar -- 2.2.Background, / Niels W. Hanson / Steven J. Hallam / Shang-Ju Wu / Kishori M. Konwar -- 2.3.Metapathways Processes, / Niels W. Hanson / Steven J. Hallam / Shang-Ju Wu / Kishori M. Konwar -- 2.3.1.Open Reading Frame (ORF) Prediction, / Niels W. Hanson / Steven J. Hallam / Shang-Ju Wu / Kishori M. Konwar -- 2.3.2.Functional Annotation, / Niels W. Hanson / Steven J. Hallam / Shang-Ju Wu / Kishori M. Konwar -- 2.3.3.Analysis Modules, / Niels W. Hanson / Steven J. Hallam / Shang-Ju Wu / Kishori M. Konwar -- 2.3.4.ePGDB Construction, / Niels W. Hanson / Steven J. Hallam / Shang-Ju Wu / Kishori M. Konwar -- 2.4.Big Data Processing, / Niels W. Hanson / Steven J. Hallam / Shang-Ju Wu / Kishori M. Konwar -- 2.4.1.A Master[—]Worker Model for Grid Distribution, / Niels W. Hanson / Steven J. Hallam / Shang-Ju Wu / Kishori M. Konwar -- 2.4.2.GUI and Data Integration, / Niels W. Hanson / Steven J. Hallam / Shang-Ju Wu / Kishori M. Konwar -- 2.5.Downstream Analyses, / Niels W. Hanson / Steven J. Hallam / Shang-Ju Wu / Kishori M. Konwar -- 2.5.1.Large Table Comparisons, / Niels W. Hanson / Steven J. Hallam / Shang-Ju Wu / Kishori M. Konwar -- 2.5.2.Pathway Tools Cellular Overview, / Niels W. Hanson / Steven J. Hallam / Shang-Ju Wu / Kishori M. Konwar -- 2.5.3.Statistical Analysis with R, / Niels W. Hanson / Steven J. Hallam / Shang-Ju Wu / Kishori M. Konwar -- 2.5.4.Venn Diagram, / Niels W. Hanson / Steven J. Hallam / Shang-Ju Wu / Kishori M. Konwar -- 2.5.5.Clustering and Relating Samples by Pathways, / Niels W. Hanson / Steven J. Hallam / Shang-Ju Wu / Kishori M. Konwar -- 2.5.6.Faceting Variables with ggplot2, / Niels W. Hanson / Steven J. Hallam / Shang-Ju Wu / Kishori M. Konwar -- 2.6.Conclusions, / Niels W. Hanson / Steven J. Hallam / Shang-Ju Wu / Kishori M. Konwar -- References, / Niels W. Hanson / Steven J. Hallam / Shang-Ju Wu / Kishori M. Konwar -- 3.Pooling Strategy for Massive Viral Sequencing / Niels W. Hanson / Steven J. Hallam / Shang-Ju Wu / Kishori M. Konwar -- 3.1.Introduction, / Pavel Skums / Alexander Artyomenko / Olga Glebova / Sumathi Ramachandran / Yury Khudyakov / Zoya Dimitrova / Ion I. Mandoiu / Alexander Zelikovsky / David S. Campo -- 3.2.Design of Pools for Big Viral Data, / Pavel Skums / Alexander Artyomenko / Olga Glebova / Sumathi Ramachandran / Yury Khudyakov / Zoya Dimitrova / Ion I. Mandoiu / Alexander Zelikovsky / David S. Campo -- 3.2.1.Pool Design Optimization Formulation, / Pavel Skums / Alexander Artyomenko / Olga Glebova / Sumathi Ramachandran / Yury Khudyakov / Zoya Dimitrova / Ion I. Mandoiu / Alexander Zelikovsky / David S. Campo -- 3.2.2.Greedy Heuristic for VSPD Problem, / Pavel Skums / Alexander Artyomenko / Olga Glebova / Sumathi Ramachandran / Yury Khudyakov / Zoya Dimitrova / Ion I. Mandoiu / Alexander Zelikovsky / David S. Campo -- 3.2.3.The Tabu Search Heuristic for the OCBG Problem, / Yury Khudyakov / Pavel Skums / Alexander Artyomenko / Olga Glebova / Alexander Zelikovsky / David S. Campo / Zoya Dimitrova / Ion I. Mandoiu / Sumathi Ramachandran -- 3.3.Deconvolution of Viral Samples from Pools, / Pavel Skums / Alexander Artyomenko / Olga Glebova / Sumathi Ramachandran / David S. Campo / Zoya Dimitrova / Ion I. Mandoiu / Alexander Zelikovsky / Yury Khudyakov -- 3.3.1.Deconvolution Using Generalized Intersections and Differences of Pools, / Pavel Skums / Alexander Artyomenko / Olga Glebova / Sumathi Ramachandran / Yury Khudyakov / Zoya Dimitrova / Ion I. Mandoiu / Alexander Zelikovsky / David S. Campo -- 3.3.2.Maximum Likelihood k-Clustering, / Pavel Skums / Alexander Artyomenko / Olga Glebova / Sumathi Ramachandran / Yury Khudyakov / Zoya Dimitrova / Ion I. Mandoiu / Alexander Zelikovsky / David S. Campo -- 3.4.Performance of Pooling Methods on Simulated Data, / Pavel Skums / Alexander Artyomenko / Olga Glebova / Sumathi Ramachandran / Yury Khudyakov / Zoya Dimitrova / Ion I. Mandoiu / Alexander Zelikovsky / David S. Campo -- 3.4.1.Performance of the Viral Sample Pool Design Algorithm, / Pavel Skums / Alexander Artyomenko / Olga Glebova / Sumathi Ramachandran / Yury Khudyakov / Zoya Dimitrova / Ion I. Mandoiu / Alexander Zelikovsky / David S. Campo -- 3.4.2.Performance of the Pool Deconvolution Algorithm, / Pavel Skums / Alexander Artyomenko / Olga Glebova / Sumathi Ramachandran / Yury Khudyakov / Zoya Dimitrova / Ion I. Mandoiu / Alexander Zelikovsky / David S. Campo -- 3.5.Experimental Validation of Pooling Strategy, / Pavel Skums / Alexander Artyomenko / Olga Glebova / Sumathi Ramachandran / Yury Khudyakov / Zoya Dimitrova / Ion I. Mandoiu / Alexander Zelikovsky / David S. Campo -- 3.5.1.Experimental Pools and Sequencing, / Pavel Skums / Alexander Artyomenko / Olga Glebova / Sumathi Ramachandran / Yury Khudyakov / Zoya Dimitrova / Ion I. Mandoiu / Alexander Zelikovsky / David S. Campo -- 3.5.2.Results, / Pavel Skums / Alexander Artyomenko / Olga Glebova / Sumathi Ramachandran / Yury Khudyakov / Zoya Dimitrova / Ion I. Mandoiu / Alexander Zelikovsky / David S. Campo -- 3.6.Conclusion, / Pavel Skums / Alexander Artyomenko / Olga Glebova / Sumathi Ramachandran / Yury Khudyakov / Zoya Dimitrova / Ion I. Mandoiu / Alexander Zelikovsky / David S. Campo -- References, / Pavel Skums / Alexander Artyomenko / Olga Glebova / Sumathi Ramachandran / Yury Khudyakov / Zoya Dimitrova / Ion I. Mandoiu / Alexander Zelikovsky / David S. Campo -- 4.Applications of High-Fidelity Sequencing Protocol to RNA Viruses / Pavel Skums / Alexander Artyomenko / Olga Glebova / Sumathi Ramachandran / Yury Khudyakov / Zoya Dimitrova / Ion I. Mandoiu / Alexander Zelikovsky / David S. Campo -- 4.1.Introduction, / Serghei Mangul / Nicholas C. Wu / Ekaterina Nenastyeva / Eleazar Eskin / Alexander Zelikovsky / Ren Sun / Nicholas Mancuso -- 4.2.High-Fidelity Sequencing Protocol, / Serghei Mangul / Nicholas C. Wu / Ekaterina Nenastyeva / Eleazar Eskin / Alexander Zelikovsky / Ren Sun / Nicholas Mancuso -- 4.3.Assembly of High-Fidelity Sequencing Data, / Ren Sun / Eleazar Eskin / Serghei Mangul / Alexander Zelikovsky / Ekaterina Nenastyeva / Nicholas Mancuso / Nicholas C. Wu -- 4.3.1.Consensus Construction, / Serghei Mangul / Nicholas C. Wu / Ekaterina Nenastyeva / Eleazar Eskin / Alexander Zelikovsky / Ren Sun / Nicholas Mancuso -- 4.3.2.Reads Mapping, / Serghei Mangul / Nicholas C. Wu / Ekaterina Nenastyeva / Eleazar Eskin / Alexander Zelikovsky / Ren Sun / Nicholas Mancuso -- 4.3.3.Viral Genome Assembler (VGA), / Serghei Mangul / Nicholas C. Wu / Ekaterina Nenastyeva / Eleazar Eskin / Alexander Zelikovsky / Ren Sun / Nicholas Mancuso -- 4.3.4.Viral Population Quantification, / Serghei Mangul / Nicholas C. Wu / Ekaterina Nenastyeva / Eleazar Eskin / Alexander Zelikovsky / Ren Sun / Nicholas Mancuso -- 4.4.Performance of VGA on Simulated Data, / Serghei Mangul / Nicholas C. Wu / Ekaterina Nenastyeva / Eleazar Eskin / Alexander Zelikovsky / Ren Sun / Nicholas Mancuso -- 4.5.Performance of Existing Viral Assemblers on Simulated Consensus Error-Corrected Reads, / Serghei Mangul / Nicholas C. Wu / Ekaterina Nenastyeva / Eleazar Eskin / Alexander Zelikovsky / Ren Sun / Nicholas Mancuso -- 4.6.Performance of VGA on Real HIV Data, / Serghei Mangul / Nicholas C. Wu / Ekaterina Nenastyeva / Eleazar Eskin / Alexander Zelikovsky / Ren Sun / Nicholas Mancuso -- 4.6.1.Validation of de novo Consensus, / Serghei Mangul / Nicholas C. Wu / Ekaterina Nenastyeva / Eleazar Eskin / Alexander Zelikovsky / Ren Sun / Nicholas Mancuso -- 4.7.Comparison of Alignment on Error-Corrected Reads, / Eleazar Eskin / Serghei Mangul / Nicholas C. Wu / Ren Sun / Nicholas Mancuso / Alexander Zelikovsky / Ekaterina Nenastyeva -- 4.8.Evaluating of Error Correction Tools Based on High-Fidelity Sequencing Reads, / Serghei Mangul / Nicholas C. Wu / Ekaterina Nenastyeva / Eleazar Eskin / Alexander Zelikovsky / Ren Sun / Nicholas Mancuso -- Acknowledgment, / Serghei Mangul / Nicholas C. Wu / Ekaterina Nenastyeva / Eleazar Eskin / Alexander Zelikovsky / Ren Sun / Nicholas Mancuso -- References, / Serghei Mangul / Nicholas C. Wu / Ekaterina Nenastyeva / Eleazar Eskin / Alexander Zelikovsky / Ren Sun / Nicholas Mancuso -- 5.Scaffolding Algorithms / Serghei Mangul / Nicholas C. Wu / Ekaterina Nenastyeva / Eleazar Eskin / Alexander Zelikovsky / Ren Sun / Nicholas Mancuso -- 5.1.Scaffolding, / Igor Mandric / Alexander Zelikovsky / Ion I. Mandoiu / James Lindsay -- 5.2.State-of-The-Art Scaffolding Tools, / Igor Mandric / Alexander Zelikovsky / Ion I. Mandoiu / James Lindsay -- 5.2.1.Sspace, / Igor Mandric / Alexander Zelikovsky / Ion I. Mandoiu / James Lindsay --, Contents note continued: 5.2.2.OPERA, / Igor Mandric / Alexander Zelikovsky / Ion I. Mandoiu / James Lindsay -- 5.2.3.SOPRA, / Igor Mandric / Alexander Zelikovsky / Ion I. Mandoiu / James Lindsay -- 5.2.4.MIP, / Igor Mandric / Alexander Zelikovsky / Ion I. Mandoiu / James Lindsay -- 5.2.5.SCARPA, / Igor Mandric / Alexander Zelikovsky / Ion I. Mandoiu / James Lindsay -- 5.3.Recent Scaffolding Tools, / Igor Mandric / Alexander Zelikovsky / Ion I. Mandoiu / James Lindsay -- 5.3.1.SILP2, / Alexander Zelikovsky / Ion I. Mandoiu / James Lindsay / Igor Mandric -- 5.3.2.ScaffMatch, / Igor Mandric / Alexander Zelikovsky / Ion I. Mandoiu / James Lindsay -- 5.4.Scaffolding Software Evaluation, / Igor Mandric / Alexander Zelikovsky / Ion I. Mandoiu / James Lindsay -- 5.4.1.Data Sets, / Igor Mandric / Alexander Zelikovsky / Ion I. Mandoiu / James Lindsay -- 5.4.2.Quality Metrics, / Igor Mandric / Alexander Zelikovsky / Ion I. Mandoiu / James Lindsay -- 5.4.3.Evaluation and Comparison, / Igor Mandric / Alexander Zelikovsky / Ion I. Mandoiu / James Lindsay -- References, / Igor Mandric / Alexander Zelikovsky / Ion I. Mandoiu / James Lindsay -- 6.Genomic Variants Detection and Genotyping / Igor Mandric / Alexander Zelikovsky / Ion I. Mandoiu / James Lindsay -- 6.1.Introduction, / Jorge Duitama -- 6.2.Methods for Detection and Genotyping of SNPs and Small Indels, / Jorge Duitama -- 6.2.1.Description of the Problem, / Jorge Duitama -- 6.2.2.Bayesian Model, / Jorge Duitama -- 6.2.3.Common Issues Affecting Genotype Quality, / Jorge Duitama -- 6.2.4.Population Variability, / Jorge Duitama -- 6.3.Methods for Detection and Genotyping of CNVs, / Jorge Duitama -- 6.3.1.Mean-Shift Approach for CNVs within a Sample, / Jorge Duitama -- 6.3.2.Identifying CNVs between Samples, / Jorge Duitama -- 6.4.Putting Everything Together, / Jorge Duitama -- References, / Jorge Duitama -- 7.Discovering and Genotyping Twilight Zone Deletions / Jorge Duitama -- 7.1.Introduction, / Tobias Marschall / Alexander Schönhuth -- 7.1.1.Twilight Zone Deletions, / Tobias Marschall / Alexander Schönhuth -- 7.2.Notation, / Tobias Marschall / Alexander Schönhuth -- 7.2.1.Alignments, / Tobias Marschall / Alexander Schönhuth -- 7.2.2.Gaps/Splits, / Tobias Marschall / Alexander Schönhuth -- 7.2.3.Deletions, / Tobias Marschall / Alexander Schönhuth -- 7.3.Non-Twilight-Zone Deletion Discovery, / Tobias Marschall / Alexander Schönhuth -- 7.3.1.Internal Segment Size-Based Approaches, / Tobias Marschall / Alexander Schönhuth -- 7.3.2.Split-Read Mapping Approaches, / Tobias Marschall / Alexander Schönhuth -- 7.3.3.Hybrid Approaches, / Tobias Marschall / Alexander Schönhuth -- 7.3.4.The "Twilight Zone": Definition, / Tobias Marschall / Alexander Schönhuth -- 7.4.Discovering "Twilight Zone" Deletions: New Solutions, / Tobias Marschall / Alexander Schönhuth -- 7.4.1.CLEVER, / Tobias Marschall / Alexander Schönhuth -- 7.4.2.Mate-Clever, / Tobias Marschall / Alexander Schönhuth -- 7.4.3.Pindel, / Tobias Marschall / Alexander Schönhuth -- 7.5.Genotyping "Twilight Zone" Deletions, / Tobias Marschall / Alexander Schönhuth -- 7.5.1.A Maximum Likelihood Approach under Read Alignment Uncertainty, / Tobias Marschall / Alexander Schönhuth -- 7.6.Results, / Tobias Marschall / Alexander Schönhuth -- 7.6.1.Data Set, / Tobias Marschall / Alexander Schönhuth -- 7.6.2.Tools, / Tobias Marschall / Alexander Schönhuth -- 7.6.3.Discovery, / Tobias Marschall / Alexander Schönhuth -- 7.6.4.Genotyping, / Tobias Marschall / Alexander Schönhuth -- 7.7.Discussion, / Tobias Marschall / Alexander Schönhuth -- 7.7.1.HiSeq, / Tobias Marschall / Alexander Schönhuth -- 7.7.2.MiSeq, / Tobias Marschall / Alexander Schönhuth -- 7.7.3.Conclusion, / Tobias Marschall / Alexander Schönhuth -- 7.8.Availability, / Tobias Marschall / Alexander Schönhuth -- Acknowledgments, / Tobias Marschall / Alexander Schönhuth -- References, / Tobias Marschall / Alexander Schönhuth -- 8.Computational Approaches for Finding Long Insertions and Deletions with NGS Data / Tobias Marschall / Alexander Schönhuth -- 8.1.Background, / Yufeng Wu / Jin Zhang / Chong Chu -- 8.2.Methods, / Jin Zhang / Chong Chu / Yufeng Wu -- 8.2.1.Signatures of Long Indels in Sequence Reads, / Jin Zhang / Chong Chu / Yufeng Wu -- 8.2.2.Methods for Discovering Long Indels without Exact Breakpoints, / Jin Zhang / Chong Chu / Yufeng Wu -- 8.2.3.Methods for Discovering Long Indels with Exact Breakpoints, / Jin Zhang / Chong Chu / Yufeng Wu -- 8.2.4.Combined Approaches, / Jin Zhang / Chong Chu / Yufeng Wu -- 8.3.Applications, / Jin Zhang / Chong Chu / Yufeng Wu -- 8.3.1.Population SV Calling, / Jin Zhang / Chong Chu / Yufeng Wu -- 8.3.2.Cancer Genomics, / Jin Zhang / Chong Chu / Yufeng Wu -- 8.4.Conclusions and Future Directions, / Yufeng Wu / Chong Chu / Jin Zhang -- Acknowledgment, / Chong Chu / Yufeng Wu / Jin Zhang -- References, / Jin Zhang / Chong Chu / Yufeng Wu -- 9.Computational Approaches in Next-Generation Sequencing Data Analysis for Genome-Wide DNA Methylation Studies / Yufeng Wu / Chong Chu / Jin Zhang -- 9.1.Introduction, / Huidong Shi / Jeong-Hyeon Choi -- 9.2.Enrichment-Based Approaches, / Jeong-Hyeon Choi / Huidong Shi -- 9.2.1.Data Analysis Procedure, / Huidong Shi / Jeong-Hyeon Choi -- 9.2.2.Available Approaches, / Jeong-Hyeon Choi / Huidong Shi -- 9.3.Bisulfite Treatment-Based Approaches, / Huidong Shi / Jeong-Hyeon Choi -- 9.3.1.Data Analysis Procedure, / Jeong-Hyeon Choi / Huidong Shi -- 9.3.2.Available Approaches, / Huidong Shi / Jeong-Hyeon Choi -- 9.4.Conclusion, / Jeong-Hyeon Choi / Huidong Shi -- References, / Huidong Shi / Jeong-Hyeon Choi -- 10.Bisulfite-Conversion-Based Methods for DNA Methylation Sequencing Data Analysis / Jeong-Hyeon Choi / Huidong Shi -- 10.1.Introduction, / Stefano Lonardi / Elena Harris -- 10.2.The Problem of Mapping BS-Treated Reads, / Elena Harris / Stefano Lonardi -- 10.3.Algorithmic Approaches to the Problem of Mapping BS-Treated Reads, / Stefano Lonardi / Elena Harris -- 10.4.Methylation Estimation, / Elena Harris / Stefano Lonardi -- 10.5.Possible Biases in Estimation of Methylation Level, / Stefano Lonardi / Elena Harris -- 10.6.Bisulfite Conversion Rate, / Elena Harris / Stefano Lonardi -- 10.7.Reduced Representation Bisulfite Sequencing, / Stefano Lonardi / Elena Harris -- 10.8.Accuracy as a Performance Measurement, / Elena Harris / Stefano Lonardi -- References, / Elena Harris / Stefano Lonardi -- 11.Computational Methods for Transcript Assembly from RNA-SEQ Reads / Elena Harris / Stefano Lonardi -- 11.1.Introduction, / Stefan Canzar / Lilian Florea -- 11.2.De Novo Assembly, / Stefan Canzar / Lilian Florea -- 11.2.1.Preprocessing of Reads, / Stefan Canzar / Lilian Florea -- 11.2.2.The De Bruijn Graph for RNA-seq Read Assembly, / Stefan Canzar / Lilian Florea -- 11.2.3.Contig Assembly, / Stefan Canzar / Lilian Florea -- 11.2.4.Filtering and Error Correction, / Stefan Canzar / Lilian Florea -- 11.2.5.Variations, / Stefan Canzar / Lilian Florea -- 11.3.Genome-Based Assembly, / Stefan Canzar / Lilian Florea -- 11.3.1.Candidate Isoforms, / Stefan Canzar / Lilian Florea -- 11.3.2.Minimality, / Stefan Canzar / Lilian Florea -- 11.3.3.Accuracy, / Stefan Canzar / Lilian Florea -- 11.3.4.Completeness, / Stefan Canzar / Lilian Florea -- 11.3.5.Extensions, / Stefan Canzar / Lilian Florea -- 11.4.Conclusions, / Stefan Canzar / Lilian Florea -- Acknowledgment, / Stefan Canzar / Lilian Florea -- References, / Stefan Canzar / Lilian Florea -- 12.An Overview And Comparison of Tools for RNA-Seq Assembly / Stefan Canzar / Lilian Florea -- 12.1.Quality Assessment, / Rasiah Loganantharaj / Thomas A. Randall -- 12.2.Experimental Considerations, / Rasiah Loganantharaj / Thomas A. Randall -- 12.3.Assembly, / Rasiah Loganantharaj / Thomas A. Randall -- 12.4.Experiment, / Rasiah Loganantharaj / Thomas A. Randall -- 12.5.Comparison, / Rasiah Loganantharaj / Thomas A. Randall -- 12.6.Results, / Rasiah Loganantharaj / Thomas A. Randall -- 12.7.Summary and Conclusion, / Rasiah Loganantharaj / Thomas A. Randall -- Acknowledgments, / Rasiah Loganantharaj / Thomas A. Randall -- References, / Rasiah Loganantharaj / Thomas A. Randall -- 13.Computational Approaches for Studying Alternative Splicing in Nonmodel Organisms From RNA-SEQ Data / Rasiah Loganantharaj / Thomas A. Randall -- 13.1.Introduction, / Sing-Hoi Sze -- 13.1.1.Alternative Splicing, / Sing-Hoi Sze -- 13.1.2.Nonmodel Organisms, / Sing-Hoi Sze -- 13.1.3.RNA-Seq Data, / Sing-Hoi Sze -- 13.2.Representation of Alternative Splicing, / Sing-Hoi Sze -- 13.2.1.de Bruijn Graph, / Sing-Hoi Sze -- 13.2.2.A Set of Transcripts, / Sing-Hoi Sze -- 13.2.3.Splicing Graph, / Sing-Hoi Sze -- 13.3.Comparison to Model Organisms, / Sing-Hoi Sze -- 13.3.1.A Set of Transcripts, / Sing-Hoi Sze -- 13.3.2.Splicing Graph, / Sing-Hoi Sze -- 13.4.Accuracy of Algorithms, / Sing-Hoi Sze -- 13.4.1.Assembly Results, / Sing-Hoi Sze -- 13.4.2.mRNA BLAST Results, / Sing-Hoi Sze -- 13.4.3.Alternative Splicing Junctions, / Sing-Hoi Sze -- 13.5.Discussion, / Sing-Hoi Sze -- References, / Sing-Hoi Sze -- 14.Transcriptome Quantification and Differential Expression From NGS Data / Sing-Hoi Sze -- 14.1.Introduction, / Olga Glebova / Yvette Temate-Tiagueu / Adrian Caciula / Sahar Al Seesi / Alexander Zelikovsky / Serghei Mangul / James Lindsay / Ion I. Mandoiu / Alexander Artyomenko -- 14.1.1.Motivation and Problems Description, / Olga Glebova / Yvette Temate-Tiagueu / Adrian Caciula / Sahar Al Seesi / Alexander Zelikovsky / Serghei Mangul / James Lindsay / Ion I. Mandoiu / Alexander Artyomenko -- 14.1.2.RNA-Seq Protocol, / Olga Glebova / Yvette Temate-Tiagueu / Adrian Caciula / Sahar Al Seesi / Alexander Zelikovsky / Serghei Mangul / James Lindsay / Ion I. Mandoiu / Alexander Artyomenko --, Contents note continued: 14.2.Overview of the State-of-the-Art Methods, / Olga Glebova / Yvette Temate-Tiagueu / Adrian Caciula / Sahar Al Seesi / Alexander Zelikovsky / Serghei Mangul / James Lindsay / Ion I. Mandoiu / Alexander Artyomenko -- 14.2.1.Quantification Methods, / Olga Glebova / Yvette Temate-Tiagueu / Adrian Caciula / Sahar Al Seesi / Alexander Zelikovsky / Serghei Mangul / James Lindsay / Ion I. Mandoiu / Alexander Artyomenko -- 14.2.2.Differential Expression Methods, / Olga Glebova / Yvette Temate-Tiagueu / Adrian Caciula / Sahar Al Seesi / Alexander Zelikovsky / Serghei Mangul / James Lindsay / Ion I. Mandoiu / Alexander Artyomenko -- 14.3.Recent Algorithms, / Olga Glebova / Yvette Temate-Tiagueu / Adrian Caciula / Sahar Al Seesi / Alexander Zelikovsky / Serghei Mangul / James Lindsay / Ion I. Mandoiu / Alexander Artyomenko -- 14.3.1.SimReg: Simulated Regression Method for Transcriptome Quantification, / Olga Glebova / Yvette Temate-Tiagueu / Adrian Caciula / Sahar Al Seesi / Alexander Zelikovsky / Serghei Mangul / James Lindsay / Ion I. Mandoiu / Alexander Artyomenko -- 14.3.2.Differential Gene Expression Analysis: IsoDE, / Olga Glebova / Yvette Temate-Tiagueu / Adrian Caciula / Sahar Al Seesi / Alexander Zelikovsky / Serghei Mangul / James Lindsay / Ion I. Mandoiu / Alexander Artyomenko -- 14.4.Experimental Setup, / Olga Glebova / Yvette Temate-Tiagueu / Adrian Caciula / Sahar Al Seesi / Alexander Zelikovsky / Serghei Mangul / James Lindsay / Ion I. Mandoiu / Alexander Artyomenko -- 14.4.1.Quantification Methods, / Olga Glebova / Yvette Temate-Tiagueu / Adrian Caciula / Sahar Al Seesi / Alexander Zelikovsky / Serghei Mangul / James Lindsay / Ion I. Mandoiu / Alexander Artyomenko -- 14.4.2.Differential Expression Methods, / Yvette Temate-Tiagueu / Adrian Caciula / Sahar Al Seesi / Alexander Artyomenko / Olga Glebova / James Lindsay / Ion I. Mandoiu / Alexander Zelikovsky / Serghei Mangul -- 14.5.Evaluation, / Olga Glebova / Yvette Temate-Tiagueu / Adrian Caciula / Sahar Al Seesi / Alexander Zelikovsky / Serghei Mangul / James Lindsay / Ion I. Mandoiu / Alexander Artyomenko -- 14.5.1.Transcriptome Quantification Methods Evaluation, / Olga Glebova / Yvette Temate-Tiagueu / Adrian Caciula / Sahar Al Seesi / Alexander Zelikovsky / Serghei Mangul / James Lindsay / Ion I. Mandoiu / Alexander Artyomenko -- 14.5.2.Differential Expression Methods Evaluation, / Olga Glebova / Yvette Temate-Tiagueu / Adrian Caciula / Sahar Al Seesi / Alexander Zelikovsky / Serghei Mangul / James Lindsay / Ion I. Mandoiu / Alexander Artyomenko -- Acknowledgments, / Olga Glebova / Yvette Temate-Tiagueu / Adrian Caciula / Sahar Al Seesi / Alexander Zelikovsky / Serghei Mangul / James Lindsay / Ion I. Mandoiu / Alexander Artyomenko -- References, / Olga Glebova / Yvette Temate-Tiagueu / Adrian Caciula / Sahar Al Seesi / Alexander Zelikovsky / Serghei Mangul / James Lindsay / Ion I. Mandoiu / Alexander Artyomenko -- 15.Error Correction of NGS Reads from Viral Populations / Olga Glebova / Yvette Temate-Tiagueu / Adrian Caciula / Sahar Al Seesi / Alexander Zelikovsky / Serghei Mangul / James Lindsay / Ion I. Mandoiu / Alexander Artyomenko -- 15.1.Next-Generation Sequencing of Heterogeneous Viral Populations and Sequencing Errors, / Olga Glebova / David S. Campo / Zoya Dimitrova / Alexander Artyomenko / Yury Khudyakov / Pavel Skums / Alexander Zelikovsky -- 15.2.Methods and Algorithms for The Ngs Error Correction in Viral Data, / Pavel Skums / Alexander Artyomenko / Olga Glebova / Yury Khudyakov / Zoya Dimitrova / Alexander Zelikovsky / David S. Campo -- 15.2.1.Clustering-Based Algorithms, / Pavel Skums / Alexander Artyomenko / Olga Glebova / Yury Khudyakov / Zoya Dimitrova / Alexander Zelikovsky / David S. Campo -- 15.2.2.k-Mer-Based Algorithms, / Pavel Skums / Alexander Artyomenko / Olga Glebova / Yury Khudyakov / Zoya Dimitrova / Alexander Zelikovsky / David S. Campo -- 15.2.3.Alignment-Based Algorithms, / Pavel Skums / Alexander Artyomenko / Olga Glebova / Yury Khudyakov / Zoya Dimitrova / Alexander Zelikovsky / David S. Campo -- 15.3.Algorithm Comparison, / Pavel Skums / Alexander Artyomenko / Olga Glebova / Yury Khudyakov / Zoya Dimitrova / Alexander Zelikovsky / David S. Campo -- 15.3.1.Benchmark Data, / Pavel Skums / Alexander Artyomenko / Olga Glebova / Yury Khudyakov / Zoya Dimitrova / Alexander Zelikovsky / David S. Campo -- 15.3.2.Results and Discussion, / Pavel Skums / Alexander Artyomenko / Olga Glebova / Yury Khudyakov / Zoya Dimitrova / Alexander Zelikovsky / David S. Campo -- References, / Pavel Skums / Alexander Artyomenko / Olga Glebova / Yury Khudyakov / Zoya Dimitrova / Alexander Zelikovsky / David S. Campo -- 16.Probabilistic Viral Quasispecies Assembly / David S. Campo / Zoya Dimitrova / Alexander Zelikovsky / Yury Khudyakov / Pavel Skums / Alexander Artyomenko / Olga Glebova -- 16.1.Intra-Host Virus Populations, / Niko Beerenwinkel / Armin Topfer -- 16.1.1.Viral Quasispecies, / Niko Beerenwinkel / Armin Topfer -- 16.1.2.Fitness, / Niko Beerenwinkel / Armin Topfer -- 16.1.3.HIV-1 as a Model System, / Niko Beerenwinkel / Armin Topfer -- 16.1.4.Recombination, / Niko Beerenwinkel / Armin Topfer -- 16.1.5.Clinical Implications, / Niko Beerenwinkel / Armin Topfer -- 16.1.6.Genotyping, / Niko Beerenwinkel / Armin Topfer -- 16.2.Next-Generation Sequencing for Viral Genomics, / Niko Beerenwinkel / Armin Topfer -- 16.2.1.Library Preparation, / Niko Beerenwinkel / Armin Topfer -- 16.2.2.Sequencing Approaches, / Niko Beerenwinkel / Armin Topfer -- 16.2.3.Specialized Viral Sequencing Methods, / Niko Beerenwinkel / Armin Topfer -- 16.2.4.Data Preprocessing and Read Alignment, / Niko Beerenwinkel / Armin Topfer -- 16.2.5.Spatial Scales of Viral Haplotype Reconstruction, / Niko Beerenwinkel / Armin Topfer -- 16.2.6.Quasispecies Assembly Performance, / Niko Beerenwinkel / Armin Topfer -- 16.3.Probabilistic Reconstruction Methods, / Niko Beerenwinkel / Armin Topfer -- 16.3.1.From Human to Viral Haplotype Reconstruction, / Niko Beerenwinkel / Armin Topfer -- 16.3.2.Viral Haplotype Inference Methods Overview, / Niko Beerenwinkel / Armin Topfer -- 16.3.3.Local Viral Haplotype Inference Approaches, / Niko Beerenwinkel / Armin Topfer -- 16.3.4.Quasispecies Assembly, / Niko Beerenwinkel / Armin Topfer -- 16.3.5.Recombinant Quasispecies Assembly, / Niko Beerenwinkel / Armin Topfer -- 16.4.Conclusion, / Niko Beerenwinkel / Armin Topfer -- References, / Niko Beerenwinkel / Armin Topfer -- 17.Reconstruction of Infectious Bronchitis Virus Quasispecies from NGS Data / Niko Beerenwinkel / Armin Topfer -- 17.1.Introduction, / Bassam Tork / Ekaterina Nenastyeva / Alexander Artyomenko / Alexander Zelikovsky / Mazhar I. Khan / Rachel O'Neill / Ion I. Mandoiu / Nicholas Mancuso -- 17.2.Background, / Ion I. Mandoiu / Alexander Zelikovsky / Bassam Tork / Rachel O'Neill / Alexander Artyomenko / Nicholas Mancuso / Mazhar I. Khan / Ekaterina Nenastyeva -- 17.2.1.Infectious Bronchitis Virus, / Bassam Tork / Ekaterina Nenastyeva / Alexander Artyomenko / Alexander Zelikovsky / Mazhar I. Khan / Rachel O'Neill / Ion I. Mandoiu / Nicholas Mancuso -- 17.2.2.High-Throughput Sequencing, / Bassam Tork / Ekaterina Nenastyeva / Alexander Artyomenko / Alexander Zelikovsky / Mazhar I. Khan / Rachel O'Neill / Ion I. Mandoiu / Nicholas Mancuso -- 17.3.Methods, / Bassam Tork / Ekaterina Nenastyeva / Alexander Artyomenko / Alexander Zelikovsky / Mazhar I. Khan / Rachel O'Neill / Ion I. Mandoiu / Nicholas Mancuso -- 17.3.1.Compared Methods, / Bassam Tork / Ekaterina Nenastyeva / Alexander Artyomenko / Alexander Zelikovsky / Mazhar I. Khan / Rachel O'Neill / Ion I. Mandoiu / Nicholas Mancuso -- 17.4.Results and Discussion, / Bassam Tork / Ekaterina Nenastyeva / Alexander Artyomenko / Alexander Zelikovsky / Mazhar I. Khan / Rachel O'Neill / Ion I. Mandoiu / Nicholas Mancuso -- 17.4.1.Data Sets, / Bassam Tork / Ekaterina Nenastyeva / Alexander Artyomenko / Alexander Zelikovsky / Mazhar I. Khan / Rachel O'Neill / Ion I. Mandoiu / Nicholas Mancuso -- 17.4.2.Validation of Error Correction Methods, / Bassam Tork / Ekaterina Nenastyeva / Alexander Artyomenko / Alexander Zelikovsky / Mazhar I. Khan / Rachel O'Neill / Ion I. Mandoiu / Nicholas Mancuso -- 17.4.3.Tuning, Comparison, and Validation of Methods for Quasispecies Reconstruction, / Ion I. Mandoiu / Alexander Zelikovsky / Bassam Tork / Rachel O'Neill / Alexander Artyomenko / Nicholas Mancuso / Mazhar I. Khan / Ekaterina Nenastyeva -- Acknowledgments, / Bassam Tork / Ekaterina Nenastyeva / Alexander Artyomenko / Alexander Zelikovsky / Mazhar I. Khan / Rachel O'Neill / Ion I. Mandoiu / Nicholas Mancuso -- References, / Bassam Tork / Ekaterina Nenastyeva / Alexander Artyomenko / Alexander Zelikovsky / Mazhar I. Khan / Rachel O'Neill / Ion I. Mandoiu / Nicholas Mancuso -- 18.Microbiome Analysis: State of the Art and Future Trends / Bassam Tork / Ekaterina Nenastyeva / Alexander Artyomenko / Alexander Zelikovsky / Mazhar I. Khan / Rachel O'Neill / Ion I. Mandoiu / Nicholas Mancuso -- 18.1.Introduction, / Mitch Fernandez / Vanessa Aguiar-Pulido / Juan Riveros / Wenrui Huang / Giri Narasimhan / Erliang Zeng / Michael Campos / Kalai Mathee / Jonathan Segal -- 18.2.The Metagenomics Analysis Pipeline, / Mitch Fernandez / Vanessa Aguiar-Pulido / Juan Riveros / Wenrui Huang / Giri Narasimhan / Erliang Zeng / Michael Campos / Kalai Mathee / Jonathan Segal -- 18.3.Data Limitations and Sources of Errors, / Mitch Fernandez / Vanessa Aguiar-Pulido / Juan Riveros / Wenrui Huang / Giri Narasimhan / Erliang Zeng / Michael Campos / Kalai Mathee / Jonathan Segal -- 18.3.1.Designing Degenerate Primers for Microbiome Work, / Mitch Fernandez / Vanessa Aguiar-Pulido / Juan Riveros / Wenrui Huang / Giri Narasimhan / Erliang Zeng / Michael Campos / Kalai Mathee / Jonathan Segal --, and Contents note continued: 18.4.Diversity and Richness Measures, / Juan Riveros / Wenrui Huang / Jonathan Segal / Erliang Zeng / Vanessa Aguiar-Pulido / Kalai Mathee / Giri Narasimhan / Mitch Fernandez / Michael Campos -- 18.5.Correlations and Association Rules, / Mitch Fernandez / Vanessa Aguiar-Pulido / Juan Riveros / Wenrui Huang / Giri Narasimhan / Erliang Zeng / Michael Campos / Kalai Mathee / Jonathan Segal -- 18.6.Microbial Functional Profiles, / Mitch Fernandez / Vanessa Aguiar-Pulido / Juan Riveros / Wenrui Huang / Giri Narasimhan / Erliang Zeng / Michael Campos / Kalai Mathee / Jonathan Segal -- 18.7.Microbial Social Interactions and Visualizations, / Mitch Fernandez / Vanessa Aguiar-Pulido / Juan Riveros / Wenrui Huang / Giri Narasimhan / Erliang Zeng / Michael Campos / Kalai Mathee / Jonathan Segal -- 18.8.Bayesian Inferences, / Mitch Fernandez / Vanessa Aguiar-Pulido / Juan Riveros / Wenrui Huang / Giri Narasimhan / Erliang Zeng / Michael Campos / Kalai Mathee / Jonathan Segal -- 18.9.Conclusion, / Mitch Fernandez / Vanessa Aguiar-Pulido / Juan Riveros / Wenrui Huang / Giri Narasimhan / Erliang Zeng / Michael Campos / Kalai Mathee / Jonathan Segal -- References, / Mitch Fernandez / Vanessa Aguiar-Pulido / Juan Riveros / Wenrui Huang / Giri Narasimhan / Erliang Zeng / Michael Campos / Kalai Mathee / Jonathan Segal.

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.

Subject(s):

ISBN:

1119272165 (pdf)
1119272173 (epub)
1119272181
9781119272168 (pdf)
9781119272175 (epub)
9781119272182
1118169484 (cloth)
9781118169483 (cloth)

Bibliography Note:

Includes bibliographical references and index.

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