R Programming for Bioinformatics

R Programming for Bioinformatics

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Features

  • Covers the fundamentals of the R language and object-oriented programming in R
  • Discusses XML, SOAP, and other data mark-up and web services languages and tools
  • Deals with many of the standard sequence similarity tools that play a prominent role in computational biology
  • Explores the interaction of R with other languages, such as C, FORTRAN, Perl, and Python
  • Explains how to write your own software packages and how to debug and profile R code
  • Contains complete source code on the book’s website
  • Summary

    Due to its data handling and modeling capabilities as well as its flexibility, R is becoming the most widely used software in bioinformatics. R Programming for Bioinformatics explores the programming skills needed to use this software tool for the solution of bioinformatics and computational biology problems.

    Drawing on the author’s first-hand experiences as an expert in R, the book begins with coverage on the general properties of the R language, several unique programming aspects of R, and object-oriented programming in R. It presents methods for data input and output as well as database interactions. The author also examines different facets of string handling and manipulations, discusses the interfacing of R with other languages, and describes how to write software packages. He concludes with a discussion on the debugging and profiling of R code.

    With numerous examples and exercises, this practical guide focuses on developing R programming skills in order to tackle problems encountered in bioinformatics and computational biology.

    Table of Contents

    Introducing R
    Motivation
    A note on the text
    R Language Fundamentals
    Data structures
    Managing your R session
    Language basics
    Subscripting and subsetting
    Vectorized computations
    Replacement functions
    Functional programming
    Writing functions
    Flow control
    Exception handling
    Evaluation
    Lexical scope
    Graphics
    Object-Oriented Programming in R
    The basics of OOP
    S3 OOP
    S4 OOP
    Using classes and methods in packages
    Documentation
    Debugging
    Managing S3 and S4 together
    Navigating the class and method hierarchy
    Input and Output in R
    Basic file handling
    Connections
    File input and output
    Source and sink: capturing R output
    Tools for accessing files on the Internet
    Working with Character Data
    Built-in capabilities
    Regular expressions
    Prefixes, suffixes and substrings
    Biological sequences
    Matching patterns
    Foreign Language Interfaces
    Calling C and FORTRAN from R
    Writing C code to interface with R
    Using the R API
    Loading libraries
    Advanced topics
    Other languages
    R Packages
    Package basics
    Package management
    Package authoring
    Initialization
    Data Technologies
    Using R for data manipulation
    Example
    Database technologies
    XML
    Bioinformatics resources on the WWW
    Debugging and Profiling
    The browser function
    Debugging in R
    Debugging C and other foreign code
    Profiling R code
    Managing memory
    References
    An Introduction appears at the beginning of each chapter.

    Editorial Reviews

    "This is a very excellent book. … I think this is actually the best handbook on R programming that is currently available. … the nine chapters provide an indispensable handbook for R programmers, and an excellent textbook for a graduate course in R programming."
    Journal of Statistical Software

    Downloads / Updates

    Resource OS Platform Updated Description Instructions
    Platform type July 28, 2008 For code, figures and solutions, go to www.bioconductor.fhcrc.org/pub/RBioinf/websupp/

     
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