Title: | Convert Microarray Data Objects |
---|---|
Description: | Define coerce methods for microarray data objects. |
Authors: | Gordon Smyth <[email protected]>, James Wettenhall <[email protected]>, Yee Hwa (Jean Yang) <[email protected]>, Martin Morgan <[email protected]> |
Maintainer: | Yee Hwa (Jean) Yang <[email protected]> |
License: | LGPL |
Version: | 1.83.0 |
Built: | 2024-10-30 05:32:18 UTC |
Source: | https://github.com/bioc/convert |
Convert between limma, marray and Biobase data objects.
Objects can be converted (coerced) from one class to another using
as(object, Class)
where object
is an object to convert
and Class
is the name of the class to convert to. The following
conversions are provided:
From: | To: |
RGList |
marrayRaw
|
marrayRaw |
RGList
|
MAList |
marrayNorm
|
marrayNorm |
MAList
|
RGList |
NChannelSet
|
marrayRaw |
NChannelSet
|
MAList |
ExpressionSet
|
marrayNorm |
ExpressionSet
|
RGList
and marrayRaw
are coerced to
NChannelSet
. Channel values are not transformed.
MAList
and marrayNorm
are coerced so that the
ExpressionSet
slot contains log-ratios (M-values) and the
ExpressionSet
object has the same number of columns as the
original object. In this case, information on the A-values is lost.
There is intentionally no conversion from RGList
or
marrayRaw
to ExpressionSet
, as ExpressionSet
is
intended for expression values, not intensities.
Gordon Smyth and others
as
in the methods
package.
##first set up some fake intensity matrices testRed <- matrix(rnorm(5*2),5,2, dimnames=list(paste("gene",1:5, sep=""), c("S1", "S2"))) testGreen <- matrix(rnorm(5*2),5,2, dimnames=list(paste("gene",1:5, sep=""), c("S1", "S2"))) ##some sample/target info testTarget <- data.frame(slide=c("S1", "S2"), Cy3=c("T", "C"), Cy5=c("C", "T"), row.names=c("S1", "S2")) maT <- new("marrayInfo", maLabels=c("S1", "S2"), maInfo= testTarget) ##now create instances and convert x <- new("RGList") x$R <- testRed x$G <- testGreen y <- as(x,"marrayRaw") z <- as(x, "NChannelSet") x <- new("marrayRaw") x@maGf <- testGreen x@maRf <- testRed x@maTargets = maT y <- as(x,"RGList") z <- as(x, "NChannelSet") x <- new("MAList") y <- as(x,"marrayNorm") ##we construct a reasonably complete fake, small ##instance of the marrayNorm class x <- new("marrayNorm") x@maM <- testRed x@maA <- testGreen maTargets(x) = maT y <- as(x,"MAList") y <- as(x, "ExpressionSet") x <- new("MAList") x$M <- testRed x$A <- testGreen x$targets <- testTarget y <- as(x,"ExpressionSet")
##first set up some fake intensity matrices testRed <- matrix(rnorm(5*2),5,2, dimnames=list(paste("gene",1:5, sep=""), c("S1", "S2"))) testGreen <- matrix(rnorm(5*2),5,2, dimnames=list(paste("gene",1:5, sep=""), c("S1", "S2"))) ##some sample/target info testTarget <- data.frame(slide=c("S1", "S2"), Cy3=c("T", "C"), Cy5=c("C", "T"), row.names=c("S1", "S2")) maT <- new("marrayInfo", maLabels=c("S1", "S2"), maInfo= testTarget) ##now create instances and convert x <- new("RGList") x$R <- testRed x$G <- testGreen y <- as(x,"marrayRaw") z <- as(x, "NChannelSet") x <- new("marrayRaw") x@maGf <- testGreen x@maRf <- testRed x@maTargets = maT y <- as(x,"RGList") z <- as(x, "NChannelSet") x <- new("MAList") y <- as(x,"marrayNorm") ##we construct a reasonably complete fake, small ##instance of the marrayNorm class x <- new("marrayNorm") x@maM <- testRed x@maA <- testGreen maTargets(x) = maT y <- as(x,"MAList") y <- as(x, "ExpressionSet") x <- new("MAList") x$M <- testRed x$A <- testGreen x$targets <- testTarget y <- as(x,"ExpressionSet")