Description Usage Arguments Details Value Examples
For internal use only. Performs Principal Componenent analysis.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | topoCompPCsWithResampling(resampling, exp, shrink, cliques, k)
sparseCompPCsWithResampling(resampling, exp, shrink, k)
compPCsWithResampling(resampling, exp, shrink, k)
computePCs(exp, shrink = FALSE, method = c("regular", "topological",
"sparse"), cliques = NULL, maxPCs = 3)
topoCompPCs(exp, shrink, cliques, k)
sparseCompPCs(exp, shrink, k)
compPCs(exp, shrink, k)
|
resampling |
list of resampled columns |
exp |
a matrix |
shrink |
logical, whether to shrink or not. |
cliques |
the pathway topology summarized in a list of cliques |
k |
the number of components to use |
method |
one of 'regular', 'topological' and 'sparse' |
maxPCs |
the maximum number of PCs to consider |
Three methods are implemented: * regular: a regular PCA ('prcomp') * topological: PCA using a pathway topology. * sparse: sparse PCA analysis implemented by 'elasticnet'
a list with the following elements:
x |
the computed PCs |
sdev |
the standard deviation captured by the PCs |
loadings |
the loadings |
a list with the following elements:
x |
the computed PCs |
sdev |
the standard deviation captured by the PCs |
loadings |
the loadings |
a list with the following elements:
x |
the computed PCs |
sdev |
the standard deviation captured by the PCs |
loadings |
the loadings |
a list with the following elements:
x |
the computed PCs |
sdev |
the standard deviation captured by the PCs |
loadings |
the loadings |
1 2 | fakeExp <- randomExpression(4)
computePCs(t(fakeExp))
|
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