swang <swang2000 at="" gmail.com=""> writes:
> Dear List:
>
> I got a file like the following, I guess the data is M ( log2
expression
> ratio) from microarray:
>
> 56071 1052 1062 3061 3081 8052 8072 10061 10062 10072 1415670_at
> 8.430148 8.899385 8.625973 8.708319 8.759182 8.281378 8.905347
8.625347
> the rows are Affymetrix probe and columns are different mice number
(arrays)
> I need to do a category analysis using category package, so I need
to
> generate a MAList or ExprSet object.
Starting with a data matrix
> samples <- 3
> sampleNames <- letters[1:samples]
> features <- 1000
> ## raw data
> exprMatrix <- matrix(0, ncol=samples,
+ nrow=features,
+ dimnames=list(1:features, sampleNames))
To create an old-style exprSet (not sure what an ExprSet is, or which
package you mean by Category ;):
> ## phenoData for exprSet
> pd2 <- new("phenoData",
+ pData=data.frame(1:samples,
+ row.names=sampleNames),
+ varLabels=list(id="sample identifier"))
> new("exprSet",
+ phenoData=pd2,
+ exprs=exprMatrix)
Expression Set (exprSet) with
1000 genes
3 samples
phenoData object with 1 variables and 3 cases
varLabels
id: sample identifier
To create an ExpressionSet (using this will require different commands
from the vignette that comes with Category) object:
> ## phenoData for ExpressionSet
> pd1 <- new("AnnotatedDataFrame",
+ data=
+ data.frame(sampleId=1:samples,
+ row.names=sampleNames),
+ varMetadata=
+ data.frame(labelDescription=I(c("Sample numeric
identifier")),
+ row.names=c("sampleId")))
> new("ExpressionSet",
+ phenoData=pd1, exprs=exprMatrix)
Instance of ExpressionSet
assayData
Storage mode: lockedEnvironment
featureNames: 1, 2, 3, ..., 999, 1000 (1000 total)
Dimensions:
exprs
Rows 1000
Samples 3
phenoData
sampleNames: a, b, c
varLabels and descriptions:
sampleId: Sample numeric identifier
Experiment data
Experimenter name:
Laboratory:
Contact information:
Title:
URL:
PMIDs:
No abstract available.
Annotation character(0)
Much of the functionality of exprSet and ExpressionSet come from
associating phenoData with expression values; the skeletons above do
not have any meaningful phenoData. Typically you might incorporate
this by reading phenotypic data from a spreadsheet or tab-delimited
file (e.g., using read.table) into data.frames, and then incorporating
the data.frame into an ExpressionSet as outlined above.
> sessionInfo()
Version 2.3.1 Patched (2006-06-20 r38364)
x86_64-unknown-linux-gnu
attached base packages:
[1] "tools" "methods" "stats" "graphics" "grDevices"
"utils"
[7] "datasets" "base"
other attached packages:
Biobase
"1.10.1"
Martin
--
Bioconductor
