Coverart for item
The Resource Statistical analysis of next generation sequencing data, Somnath Datta, Dan Nettleton, editors

Statistical analysis of next generation sequencing data, Somnath Datta, Dan Nettleton, editors

Label
Statistical analysis of next generation sequencing data
Title
Statistical analysis of next generation sequencing data
Statement of responsibility
Somnath Datta, Dan Nettleton, editors
Contributor
Editor
Subject
Genre
Language
eng
Summary
Next Generation Sequencing (NGS) is the latest high throughput technology to revolutionize genomic research. NGS generates massive genomic datasets that play a key role in the big data phenomenon that surrounds us today. To extract signals from high-dimensional NGS data and make valid statistical inferences and predictions, novel data analytic and statistical techniques are needed. This book contains 20 chapters written by prominent statisticians working with NGS data. The topics range from basic preprocessing and analysis with NGS data to more complex genomic applications such as copy number variation and isoform expression detection. Research statisticians who want to learn about this growing and exciting area will find this book useful. In addition, many chapters from this book could be included in graduate-level classes in statistical bioinformatics for training future biostatisticians who will be expected to deal with genomic data in basic biomedical research, genomic clinical trials and personalized medicine. About the editors: Somnath Datta is Professor and Vice Chair of Bioinformatics and Biostatistics at the University of Louisville. He is Fellow of the American Statistical Association, Fellow of the Institute of Mathematical Statistics, and Elected Member of the International Statistical Institute. He has contributed to numerous research areas in Statistics, Biostatistics and Bioinformatics. Dan Nettleton is Professor and Laurence H. Baker Endowed Chair of Biological Statistics in the Department of Statistics at Iowa State University. He is Fellow of the American Statistical Association and has published research on a variety of topics in statistics, biology, and bioinformatics
Member of
Cataloging source
N$T
Dewey number
570.15195
Illustrations
illustrations
Index
index present
LC call number
QH323.5
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
  • statistics
http://library.link/vocab/relatedWorkOrContributorDate
1962-
http://library.link/vocab/relatedWorkOrContributorName
  • Datta, Somnath
  • Nettleton, Dan
Series statement
Frontiers in probability and the statistical sciences
http://library.link/vocab/subjectName
  • Nucleotide sequence
  • Biometry
  • Genetics
  • RNA
  • NATURE
  • SCIENCE
  • SCIENCE
  • Biometry
  • Genetics
  • Nucleotide sequence
  • RNA
Label
Statistical analysis of next generation sequencing data, Somnath Datta, Dan Nettleton, editors
Instantiates
Publication
Copyright
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
Statistical Analyses of Next Generation Sequencing Data: An Overview -- Using RNA-seq Data to Detect Differentially Expressed Genes -- Differential Expression Analysis of Complex RNA-seq Experiments Using edgeR -- Analysis of Next Generation Sequencing Data Using Integrated Nested Laplace Approximation (INLA) -- Design of RNA Sequencing Experiments -- Measurement, Summary, and Methodological Variation in RNA-sequencing -- Functional PCA for differential expression testing with RNA-seq data -- Mapping of Expression Quantitative Trait Loci using RNA-seq Data -- The Role of Spike-In Standards in the Normalization of RNA-seq -- Cluster Analysis of RNA-sequencing Data -- Classification of RNA-seq Data -- Isoform Expression Analysis Based on RNA-seq Data -- RNA Isoform Discovery Through Goodness of Fit Diagnostics -- MOSAiCS-HMM: A Model-based Approach for Detecting Regions of Histone Modifications from ChIP-seq Data -- Hierarchical Bayesian Models for ChIP-Seq Data -- Genotype Calling and Haplotype Phasing from Next Generation Sequencing Data.-Analysis of Metagenomic Data -- Detecting Copy Number Changes and Structural Rearrangements using DNA Sequencing -- Statistical Methods for the Analysis of Next Generation Sequence Data from Paired Tumor-Normal Samples -- Statistical Considerations in the Analysis of Rare Variants
Control code
883248021
Dimensions
unknown
Extent
1 online resource (xiv, 432 pages)
File format
unknown
Form of item
online
Isbn
9783319072128
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other control number
10.1007/978-3-319-07212-8
Other physical details
illustrations (chiefly color).
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
(OCoLC)883248021
Label
Statistical analysis of next generation sequencing data, Somnath Datta, Dan Nettleton, editors
Publication
Copyright
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
Statistical Analyses of Next Generation Sequencing Data: An Overview -- Using RNA-seq Data to Detect Differentially Expressed Genes -- Differential Expression Analysis of Complex RNA-seq Experiments Using edgeR -- Analysis of Next Generation Sequencing Data Using Integrated Nested Laplace Approximation (INLA) -- Design of RNA Sequencing Experiments -- Measurement, Summary, and Methodological Variation in RNA-sequencing -- Functional PCA for differential expression testing with RNA-seq data -- Mapping of Expression Quantitative Trait Loci using RNA-seq Data -- The Role of Spike-In Standards in the Normalization of RNA-seq -- Cluster Analysis of RNA-sequencing Data -- Classification of RNA-seq Data -- Isoform Expression Analysis Based on RNA-seq Data -- RNA Isoform Discovery Through Goodness of Fit Diagnostics -- MOSAiCS-HMM: A Model-based Approach for Detecting Regions of Histone Modifications from ChIP-seq Data -- Hierarchical Bayesian Models for ChIP-Seq Data -- Genotype Calling and Haplotype Phasing from Next Generation Sequencing Data.-Analysis of Metagenomic Data -- Detecting Copy Number Changes and Structural Rearrangements using DNA Sequencing -- Statistical Methods for the Analysis of Next Generation Sequence Data from Paired Tumor-Normal Samples -- Statistical Considerations in the Analysis of Rare Variants
Control code
883248021
Dimensions
unknown
Extent
1 online resource (xiv, 432 pages)
File format
unknown
Form of item
online
Isbn
9783319072128
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other control number
10.1007/978-3-319-07212-8
Other physical details
illustrations (chiefly color).
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
(OCoLC)883248021

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