subset.loring.eset: An ExpressionSet Object containing published data from M?ller...
In attract: Methods to Find the Gene Expression Modules that Represent the Drivers of Kauffman's Attractor Landscape
Description
Usage
Format
Value
References
See Also
Examples
Description
This is an ExpressionSet object containing a subset of the published data from M?ller et al. (NCBI GEO
accession id GSE11508). The expression data set contains 5522 probes for 68 samples. This ExpressionSet object
was created specifically to demonstrate the functions in this package. If you're looking for the full M?ller data set,
see loring.eset.
Usage
1
Format
An ExpressionSet object.
Value
An ExpressionSet object containing a subset of the published data from M?ller et al. (NCBI GEO
accession id GSE11508). The expression data set contains 5522 probes for 68 samples.
References
M\"uller, F, et al., Regulatory networks define phenotypic classes of human stem cell lines. Nature, 2008. 455(7211): p. 401-405.
See Also
exprs.dat, samp.info, loring.eset
Examples
1
2
data(subset.loring.eset)
subset.exprs.dat <- exprs(subset.loring.eset) # gene expression matrix
attract documentation built on Nov. 8, 2020, 8:04 p.m.
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Description Usage Format Value References See Also Examples
Description
This is an ExpressionSet object containing a subset of the published data from M?ller et al. (NCBI GEO
accession id GSE11508). The expression data set contains 5522 probes for 68 samples. This ExpressionSet object
was created specifically to demonstrate the functions in this package. If you're looking for the full M?ller data set,
see loring.eset.
Usage
1 |
Format
An ExpressionSet object.
Value
An ExpressionSet object containing a subset of the published data from M?ller et al. (NCBI GEO
accession id GSE11508). The expression data set contains 5522 probes for 68 samples.
References
M\"uller, F, et al., Regulatory networks define phenotypic classes of human stem cell lines. Nature, 2008. 455(7211): p. 401-405.
See Also
exprs.dat, samp.info, loring.eset
Examples
1 2 | data(subset.loring.eset)
subset.exprs.dat <- exprs(subset.loring.eset) # gene expression matrix
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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