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.
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.