Bioinformatics and Computational Biology Solutions Using R and Bioconductor

  • Robert Gentleman
  • Vincent J. Carey
  • Wolfgang Huber
  • Rafael A. Irizarry
  • Sandrine Dudoit

Part of the Statistics for Biology and Health book series (SBH)

Table of contents

  1. Front Matter
    Pages i-xix
  2. Preprocessing data from genomic experiments

    1. W. Huber, R. A. Irizarry, R. Gentleman
      Pages 3-12
    2. B. M. Bolstad, R. A. Irizarry, L. Gautier, Z. Wu
      Pages 13-32
    3. B. M. Bolstad, F. Collin, J. Brettschneider, K. Simpson, L. Cope, R. A. Irizarry et al.
      Pages 33-47
    4. Y. H. Yang, A. C. Paquet
      Pages 49-69
    5. W. Huber, F. Hahne
      Pages 71-90
    6. X. Li, R. Gentleman, X. Lu, Q. Shi, J.D. Iglehart, L. Harris et al.
      Pages 91-109
  3. Meta-data: biological annotation and visualization

    1. R. Gentleman, V. J. Carey, J. Zhang
      Pages 113-133
    2. V. J. Carey, D. Temple Lang, J. Gentry, J. Zhang, R. Gentleman
      Pages 135-146
    3. C. A. Smith, W. Huber, R. Gentleman
      Pages 147-160
    4. W. Huber, X. Li, R. Gentleman
      Pages 161-179
  4. Statistical analysis for genomic experiments

    1. V. J. Carey, R. Gentleman
      Pages 183-187
    2. R. Gentleman, B. Ding, S. Dudoit, J. Ibrahim
      Pages 189-208
    3. K. S. Pollard, M. J. van der Laan
      Pages 209-228
    4. D. Scholtens, A. von Heydebreck
      Pages 229-248
    5. K. S. Pollard, S. Dudoit, M. J. van der Laan
      Pages 249-271
    6. T. Hothorn, M. Dettling, P. Bühlmann
      Pages 293-311
  5. Graphs and networks

    1. R. Gentleman, W. Huber, V. J. Carey
      Pages 329-336
    2. W. Huber, R. Gentleman, V. J. Carey
      Pages 337-346
    3. V. J. Carey, R. Gentleman, W. Huber, J. Gentry
      Pages 347-368
    4. R. Gentleman, D. Scholtens, B. Ding, V. J. Carey, W. Huber
      Pages 369-394
  6. Case studies

  7. Back Matter
    Pages 443-473

About this book


Bioconductor is a widely used open source and open development software project for the analysis and comprehension of data arising from high-throughput experimentation in genomics and molecular biology. Bioconductor is rooted in the open source statistical computing environment R. This volume's coverage is broad and ranges across most of the key capabilities of the Bioconductor project, including

importation and preprocessing of high-throughput data from microarray, proteomic, and flow cytometry platforms

curation and delivery of biological metadata for use in statistical modeling and interpretation

statistical analysis of high-throughput data, including machine learning and visualization,

modeling and visualization of graphs and networks.

The developers of the software, who are in many cases leading academic researchers, jointly authored chapters. All methods are illustrated with publicly available data, and a major section of the book is devoted to exposition of fully worked case studies.

This book is more than a static collection of descriptive text, figures, and code examples that were run by the authors to produce the text; it is a dynamic document. Code underlying all of the computations that are shown is made available on a companion website, and readers can reproduce every number, figure, and table on their own computers.

Robert Gentleman is Head of the Program in Computational Biology at the Fred Hutchinson Cancer Research Center in Seattle. He is one of the two authors of the original R system and a leading member of the R core team. Vincent Carey is Associate Professor of Medicine (Biostatistics), Channing Laboratory, Brigham and Women's Hospital, Harvard Medical School. Gentleman and Carey are co-founders of the Bioconductor project. Wolfgang Huber is Group Leader in the European Molecular Biology Laboratory at the European Bioinformatics Institute in Cambridge. He has made influential contributions to the error modeling of microarray data. Rafael Irizarry is Associate Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health in Baltimore. He is co-developer of RMA and GCRMA, two of the most popular methodologies for preprocessing high-density oligonucleotide arrays. Sandrine Dudoit is Assistant Professor in the Department of Biostatistics at the University of California, Berkeley. She has made seminal discoveries in the fields of multiple testing and generalized cross-validation and spearheaded the deployment of these findings in applied genomic science.


Annotation DNA Processing bioinformatics biology calculus classification cluster analysis data analysis genes genome genomics machine learning microarray protein

Editors and affiliations

  • Robert Gentleman
    • 1
  • Vincent J. Carey
    • 2
  • Wolfgang Huber
    • 3
  • Rafael A. Irizarry
    • 4
  • Sandrine Dudoit
    • 5
  1. 1.Program in Computational Biology Division of Public Health SciencesFred Hutchinson Cancer Research CenterSeattleUSA
  2. 2.Channing Laboratory Brigham and Women’s HospitalHarvard Medical SchoolBostonUSA
  3. 3.European Molecular Biology LaboratoryEuropean Bioinformatics InstituteCambridgeUK
  4. 4.Department of BiostatisticsJohns Hopkins Bloomberg School of Public HealthBaltimoreUSA
  5. 5.Division of Biostatistics School of Public HealthUniversity of California BerkeleyBerkeleyUSA

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