R Programming for BioinformaticsDue 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 exper |
Contents
| 1 | |
| 5 | |
ObjectOriented Programming in R | 67 |
Input and Output in R | 119 |
Working with Character Data | 145 |
Foreign Language Interfaces | 183 |
R Packages | 211 |
Data Technologies | 229 |
Debugging and Profiling | 273 |
| 301 | |
| 305 | |
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Common terms and phrases
Affymetrix appropriate array attr(,"match.length basic Biobase Bioconductor Bioinformatics Browse[1 browser call stack character vector chromosome class attribute code chunk column command computations corresponding create data frame data set data structures data.frame database debug defined described dimnames discuss dispatch document elements environment error evaluation example Exercise FALSE FIFO formal arguments FORTRAN function call function(x garbage collection genes handlers implementation input instance integer interactions interface internal invoked language length lexical scope likelihood function loaded logical value manual match matrix memory myidea name space NAMESPACE NULL operator output palindromes parsing programming query random number regular expression return value routines S4 classes search path Section sequence SEXP shared library signature slot specific SQLite subclass subscript subset substring superclass supplied Sweave symbol syntax TRUE TRUE tryCatch types users variables write XPath zero