clusterNormE: Zero-centered normalisation
In puma: Propagating Uncertainty in Microarray Analysis(including Affymetrix tranditional 3' arrays and exon arrays and Human Transcriptome Array 2.0)
Description
Usage
Arguments
Details
Value
Author(s)
See Also
Examples
Description
This function normalise the data vector to have zero mean.
Usage
1
clusterNormE(x)
Arguments
x
a vector which contains gene expression level on log2 scale.
Details
Vector x is related to a gene and each element is related to a chip.
Value
The return vector is in the same format as the input x.
Author(s)
Xuejun Liu, Magnus Rattray
See Also
See Also as pumaClust and pumaClustii
Examples
1
2
#data(Clust.exampleE)
#Clust.exampleE.centered<-t(apply(Clust.exampleE, 1, clusterNormE))
puma documentation built on Nov. 8, 2020, 11:08 p.m.
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Description Usage Arguments Details Value Author(s) See Also Examples
Description
This function normalise the data vector to have zero mean.
Usage
1 | clusterNormE(x)
|
Arguments
x |
a vector which contains gene expression level on log2 scale. |
Details
Vector x is related to a gene and each element is related to a chip.
Value
The return vector is in the same format as the input x.
Author(s)
Xuejun Liu, Magnus Rattray
See Also
See Also as pumaClust and pumaClustii
Examples
1 2 | #data(Clust.exampleE)
#Clust.exampleE.centered<-t(apply(Clust.exampleE, 1, clusterNormE))
|
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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