Muutke küpsiste eelistusi

Statistical Genomics: Methods and Protocols 1st ed. 2016 [Kõva köide]

Edited by , Edited by
  • Formaat: Hardback, 418 pages, kõrgus x laius: 254x178 mm, kaal: 9513 g, 85 Illustrations, color; 28 Illustrations, black and white; XI, 418 p. 113 illus., 85 illus. in color., 1 Hardback
  • Sari: Methods in Molecular Biology 1418
  • Ilmumisaeg: 24-Mar-2016
  • Kirjastus: Humana Press Inc.
  • ISBN-10: 1493935763
  • ISBN-13: 9781493935765
Teised raamatud teemal:
  • Kõva köide
  • Hind: 113,55 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Tavahind: 133,59 €
  • Säästad 15%
  • Raamatu kohalejõudmiseks kirjastusest kulub orienteeruvalt 2-4 nädalat
  • Kogus:
  • Lisa ostukorvi
  • Tasuta tarne
  • Tellimisaeg 2-4 nädalat
  • Lisa soovinimekirja
Statistical Genomics: Methods and Protocols 1st ed. 2016Suurem pilt
  • Formaat: Hardback, 418 pages, kõrgus x laius: 254x178 mm, kaal: 9513 g, 85 Illustrations, color; 28 Illustrations, black and white; XI, 418 p. 113 illus., 85 illus. in color., 1 Hardback
  • Sari: Methods in Molecular Biology 1418
  • Ilmumisaeg: 24-Mar-2016
  • Kirjastus: Humana Press Inc.
  • ISBN-10: 1493935763
  • ISBN-13: 9781493935765
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781493935765.html
Märksõnad:

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.

 

Arvustused

This collection of articles offers a thorough overview of the field, making it an opportune and useful addition to the literature. The book is written in an accessible language and the variety of the topics which are presented recommends it as an excellent starting point or updated reference of the field. It is suitable for both post-graduate and established researchers, and the numerous examples that accompany the discussed topics recommend it as an asset. (Irina Ioana Mohorianu, zbMATH 1346.92003, 2016)

Preface v
Contributors ix
PART I GROUNDWORK
1 Overview of Sequence Data Formats
3(16)
Hongen Zhang
2 Integrative Exploratory Analysis of Two or More Genomic Datasets
19(20)
Chen Meng
Aedin Culhane
3 Study Design for Sequencing Studies
39(28)
Loren A. Honaas
Naomi S. Altman
Martin Krzywinski
4 Genomic Annotation Resources in R/Bioconductor
67(26)
Marc R.J. Carlson
Herve Pages
Sonali Arora
Valerie Obenchain
Martin Morgan
PART II PUBLIC GENOMIC DATA
5 The Gene Expression Omnibus Database
93(18)
Emily Clough
Tanya Barrett
6 A Practical Guide to The Cancer Genome Atlas (TCGA)
111(34)
Zhining Wang
Mark A. Jensen
Jean Claude Zenklusen
PART III APPLICATIONS
7 Working with Oligonucleotide Arrays
145(16)
Benilton S. Carvalho
8 Meta-Analysis in Gene Expression Studies
161(16)
Levi Waldron
Markus Riester
9 Practical Analysis of Genome Contact Interaction Experiments
177(14)
Mark A. Carty
Olivier Elemento
10 Quantitative Comparison of Large-Scale DNA Enrichment Sequencing Data
191(18)
Matthias Lienhard
Lukas Chavez
11 Variant Calling From Next Generation Sequence Data
209(16)
Nancy F. Hansen
12 Genome-Scale Analysis of Cell-Specific Regulatory Codes Using Nuclear Enzymes
225(18)
Songjoon Baek
Myong-Hee Sung
PART IV TOOLS
13 NGS-QC Generator: A Quality Control System for ChIP-Seq and Related Deep Sequencing-Generated Datasets
243(24)
Marco Antonio Mendoza-Parra
Mohamed-Ashick M. Saleem
Matthias Blum
Pierre-Etienne Cholley
Hinrich Gronemeyer
14 Operating on Genomic Ranges Using BEDOPS
267(16)
Shane Neph
Alex P. Reynolds
M. Scott Kuehn
John A. Stamatoyannopoulos
15 GMAP and GSNAP for Genomic Sequence Alignment: Enhancements to Speed, Accuracy, and Functionality
283(52)
Thomas D. Wu
Jens Reeder
Michael Lawrence
Gabe Becker
Matthew J. Brauer
16 Visualizing Genomic Data Using Gviz and Bioconductor
335(18)
Florian Hahne
Robert Ivanek
17 Introducing Machine Learning Concepts with WEKA
353(26)
Tony C. Smith
Eibe Frank
18 Experimental Design and Power Calculation for RNA-seq Experiments
379(12)
Zhijin Wu
Hao Wu
19 It's DE-licious: A Recipe for Differential Expression Analyses of RNA-seq Experiments Using Quasi-Likelihood Methods in edgeR
391(26)
Aaron T.L. Lun
Yunshun Chen
Gordon K. Smyth
Index 417