Bioconductor Case Studies (Google eBook)

Front Cover
Springer, Jun 9, 2010 - Bioconductor (Computer file) - 296 pages
2 Reviews
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 are able to reproduce every computation, figure, and table.
  

What people are saying - Write a review

We haven't found any reviews in the usual places.

Related books

Contents

2 R and BioconductorIntroduction
5
3 Processing AffymetrixExpression Data
25
4 TwoColor Arrays
46
5 FoldChanges LogRatios Background Correction Shrinkage Estimation and Variance Stabilization
63
6 Easy Differential Expression
83
7 Differential Expression
89
8 Annotation and Metadata
103
9 Supervised Machine Learning
120
11 Using Graphs for Interactome Data
159
12 Graph Layout
173
13 Gene Set Enrichment Analysis
192
14 Hypergeometric Testing Used for Gene Set Enrichment Analysis
207
15 Solutions to Exercises
221
References
270
Index
277
Copyright

10 Unsupervised Machine Learning
137

Common terms and phrases

Bibliographic information