exprSet-class {Biobase} | R Documentation |
This is class representation for Microarray Data
new('exprSet',
exprs = ...., # Object of class matrix
se.exprs = ...., # Object of class matrix
phenoData = ...., # Object of class phenoData
annotation = ...., # Object of class character
description = ...., # Object of class MIAME
notes = ...., # Object of class character
)
exprs
:se.exprs
:exprs
which contains
standard error estimates for the estimated expression levels. phenoData
:phenoData
containing the patient (or case) level data. The columns of the
pData slot of this entity represent
variables and the rows represent patients or cases. annotation
exprSet
instance.description
:characterOrMIAME
has been
defined just for this.notes
:exprs
and phenoData
are subset properly. phenoData
component. exprs
. se.exprs
. exprSet
. exprSet
. exprSet
. exprSet
. exprs
. exprs
. function
to the matrix
of expressions on margin 1 (see apply
) list
in a matrix (assumes result of each function evaluation is a scalar). function
is assumed to have arguments x and y;
the pData element named by covlab will be bound to x, the
gene expression values will be iteratively bound to yphenoData
instance from the exprSet
.pData
slot of the phenoData
contained in the instance.pData
slot of the phenoData
contained in the instance.exprs
and the row
labels from pData
. The function takes preferably the
column labels of exprs
(if any).
character
and the length of the vector must be equal to the number of samples.
exprSet
.
If the length of vector
is a divisor of the number of rows
in the expression array then the expression array is
split. Subsequently, if the length of vector
is a divisor
of the number of rows of the phenoData data frame then the split
is made on this.write.table
. If
called with no arguments it is equivalent to
write.table(exprs(exprSet),file="tmp.txt",quote=FALSE,sep="t").csv
file. This file will open nicely in excel. It takes the same
arguments as write.table
. If
called with no arguments it is equivalent to
write.table(exprs(exprSet),file="tmp.csv", sep = ",", col.names = NA)
.pData(eset)[[as.character(val)]]
which
does not quite have the right semantics but it is close. This
operator extracts the named component of the pData
slot in
phenoData
.exprSet
s from
previous versions, that have a character
in description to
an object that has an instance of the class MIAME
in
the description slot. The old description is stored in the
title
slot. If the object already has a MIAME
description the same object is returned.MIAME-class
data(geneData) data(geneCov) covdesc<- list("Covariate 1", "Covariate 2", "Covariate 3") names(covdesc) <- names(geneCov) pdata <- new("phenoData", pData=geneCov, varLabels=covdesc) pdata[1,] pdata[,2] eset <- new("exprSet", exprs=geneData, phenoData=pdata) eset eset[,1:10] eset[,1] eset[1,] eset[1,1] eset[1:100,] eset[1:44,c(2,4,6)] Means <- iter(eset, f=mean) chkdich <- function(x) if(length(unique(x))!=2) stop("x not dichotomous") mytt <- function(x,y) { chkdich(x) d <- split(y,x) t.test(d[[1]],d[[2]])$p.val } Tpvals <- iter(eset, "cov1", mytt ) sp1 <- split(eset, c(1,2)) sp2 <- split(eset, c(rep(1,6), rep(2,7))) sampleNames(eset) sampleNames(eset) <- letters