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Statistical Genomics

  • Fester Einband
  • 418 Seiten
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This volume expands on statistical analysis of genomic data by discussing cross-cutting groundwork material, public data repositor... Weiterlesen
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Beschreibung

This volume expands on statistical analysis of genomic data by discussing cross-cutting groundwork material, public data repositories, common applications, and representative tools for operating on genomic data. Statistical Genomics: Methods and Protocols is divided into four sections. The first section discusses overview material and resources that can be applied across topics mentioned throughout the book. The second section covers prominent public repositories for genomic data. The third section presents several different biological applications of statistical genomics, and the fourth section highlights software tools that can be used to facilitate ad-hoc analysis and data integration. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, step-by-step, readily reproducible analysis protocols, and tips on troubleshooting and avoiding known pitfalls.

Through and practical, Statistical Genomics: Methods and Protocols, explores a range of both applications and tools and is ideal for anyone interested in the statistical analysis of genomic data.



Includes cutting-edge methods and protocols

Provides step-by-step detail essential for reproducible results

Contains key notes and implementation advice from the experts



Inhalt
Part I Groundwork 1. Overview of Sequence Data Formats Hongen Zhang 2. Integrative Exploratory Analysis of Two or More Genomic Datasets Chen Meng and Aedin Culhane 3. Study Design for Sequencing Studies Loren Honaas, Naomi Altman, and Martin Krzywinski 4. Genomic Annotation Resources in R/Bioconductor Marc RJ Carlson, Hervé Pagès, Sonali Arora, Valerie Obenchain, and Martin Morgan Part II Public Genomic Data 5. The Gene Expression Omnibus Database Emily Clough and Tanya Barrett 6. A Practical Guide to the Cancer Genome Atlas (TCGA) Zhining Wang, Mark A. Jensen, and Jean Claude Zenklusen Part III Applications 7. Working with Oligonucleotide Arrays Benilton S. Carvalho 8. Meta-Analysis in Gene Expression Studies Levi Waldron and Markus Riester 9. Practical Analysis of Genome Contact Interaction Experiments Mark A. Carty and Olivier Elemento 10. Quantitative Comparison of Large-Scale DNA Enrichment Sequencing Data Matthias Lienhard and Lukas Chavez 11. Variant Calling From Next Generation Sequence Data Nancy F. Hansen 12. Genome-Scale Analysis of Cell-Specific Regulatory Codes Using Nuclear Enzymes Songjoon Baek and Myong-Hee Sung Part IV Tools 13. NGS-QC Generator: A Quality Control System for ChIP-seq and Related Deep Sequencing-Generated Datasets Marco Antonio Mendoza-Parra, Mohamed-Ashick M. Saleem, Matthias Blum, Pierre Etienne Cholley, and Hinrich Gronemeyer 14. Operating on Genomic Ranges Using BEDOPS Shane Neph, Alex P. Reynolds, M. Scott Kuehn, and John A. Stamatoyannopoulos 15. GMAP and GSNAP for Genomic Sequence Alignment: Enhancements to Speed, Accuracy, and Functionality Thomas D. Wu, Jens Reeder, Michael Lawrence, Gabe Becker, and Matthew Brauer 16. Visualizing Genomic Data using Gviz and Bioconductor Florian Hahne and Robert Ivanek 17. Introducing Machine Learning Concepts with WEKA Tony C. Smith and Eibe Frank 18. Experimental Design and Power Calculation for RNA-Seq Experiments Zhijin Wu and Hao Wu 19. It's DE-licious: A Recipe for Differential Expression Analyses of RNA-Seq Experiments Using Quasi-Likelihood Methods in EdgeR Aaron T.L. Lun, Yunshun Chen, and Gordon K. Smyth

Produktinformationen

Titel: Statistical Genomics
Untertitel: Methods and Protocols
Editor:
EAN: 9781493935765
ISBN: 978-1-4939-3576-5
Format: Fester Einband
Herausgeber: Springer, Berlin
Genre: Medizin
Anzahl Seiten: 418
Gewicht: g
Größe: H30mm x B283mm x T260mm
Jahr: 2016
Auflage: 1st ed. 2016

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