Bioconductor Case Studies
(Sprache: Englisch)
In this volume, the authors present a collection of cases to apply Bioconductor tools in the analysis of microarray gene expression data. Each chapter describes an analysis of real data using hands-on example driven approaches. Short exercises are included.
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In this volume, the authors present a collection of cases to apply Bioconductor tools in the analysis of microarray gene expression data. Each chapter describes an analysis of real data using hands-on example driven approaches. Short exercises are included.
Klappentext zu „Bioconductor Case Studies “
Bioconductor software has become a standard tool for the analysis and comprehension of data from high-throughput genomics experiments. Its application spans a broad field of technologies used in contemporary molecular biology. In this volume, the authors present a collection of cases to apply Bioconductor tools in the analysis of microarray gene expression data. Topics covered include: (1) import and preprocessing of data from various sources; (2) statistical modeling of differential gene expression; (3) biological metadata; (4) application of graphs and graph rendering; (5) machine learning for clustering and classification problems; (6) gene set enrichment analysis.
Each chapter of this book describes an analysis of real data using hands-on example driven approaches. Short exercises help in the learning process and invite more advanced considerations of key topics. The book is a dynamic document. All the code shown can be executed on a local computer, and readers areable to reproduce every computation, figure, and table.
Inhaltsverzeichnis zu „Bioconductor Case Studies “
- The ALL Dataset- R and Bioconductor Introduction
- Processing Affymetrix Expression Data
- Two Color Arrays
- Fold Changes, Log Ratios, Background Correction, Shrinkage Estimation, and Variance Stabilization
- Easy Differential Expression
- Differential Expression
- Annotation and Metadata
- Supervised Machine Learning
- Unsupervised Machine Learning
- Using Graphs for Interactome Data
- Graph Layout
- Gene Set Enrichment Analysis
- Hypergeometric Testing Used for Gene Set Enrichment Analysis
- Solutions to Exercises
Bibliographische Angaben
- Autoren: Florian Hahne , Wolfgang Huber , Robert Gentleman
- 2008, 284 Seiten, Maße: 15,5 x 23,5 cm, Kartoniert (TB), Englisch
- Verlag: Springer, New York
- ISBN-10: 0387772391
- ISBN-13: 9780387772394
- Erscheinungsdatum: 15.08.2008
Sprache:
Englisch
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