\alias{cbind.DNAbin}
\alias{as.matrix.DNAbin}
\alias{c.DNAbin}
+\alias{as.list.DNAbin}
\alias{labels.DNAbin}
\title{Manipulate DNA Sequences in Bit-Level Format}
\description{
\method{[}{DNAbin}(x, i, j, drop = FALSE)
\method{as.matrix}{DNAbin}(x, \dots)
\method{c}{DNAbin}(\dots, recursive = FALSE)
+\method{as.list}{DNAbin}(x, \dots)
\method{labels}{DNAbin}(object, \dots)
}
\arguments{
are dropped.}
\item{i, j}{indices of the rows and/or columns to select or to drop.
They may be numeric, logical, or character (in the same way than for
- standard R objects).}
+ standard \R objects).}
\item{drop}{logical; if \code{TRUE}, the returned object is of the
lowest possible dimension.}
\item{recursive}{for compatibility with the generic (unused).}
\details{
These are all `methods' of generic functions which are here applied to
DNA sequences stored as objects of class \code{"DNAbin"}. They are
- used in the same way than the standard R functions to manipulate
+ used in the same way than the standard \R functions to manipulate
vectors, matrices, and lists. Additionally, the operators \code{[[}
and \code{$} may be used to extract a vector from a list. Note that
the default of \code{drop} is not the same than the generic operator:
\code{as.matrix} may be used to convert DNA sequences (of the same
length) stored in a list into a matrix while keeping the names and the
- class.
+ class. \code{as.list} does the reverse operation.
}
\value{
an object of class \code{"DNAbin"} in the case of \code{rbind},
\author{Emmanuel Paradis}
\seealso{
\code{\link{as.DNAbin}}, \code{\link{read.dna}},
- \code{\link{read.GenBank}}, \code{\link{write.dna}}
+ \code{\link{read.GenBank}}, \code{\link{write.dna}}, ,
+ \code{\link{image.DNAbin}}
The corresponding generic functions are documented in the package
\pkg{base}.
\examples{
data(woodmouse)
woodmouse
-summary(woodmouse)
-summary(woodmouse, 15, 6)
-summary(woodmouse[1:5, 1:300], 15, 6)
+print(woodmouse, 15, 6)
+print(woodmouse[1:5, 1:300], 15, 6)
### Just to show how distances could be influenced by sampling:
dist.dna(woodmouse[1:2, ])
dist.dna(woodmouse[1:3, ])