randomWalkByMatrixInv-matrix-method: Smooth data on graph by computing the closed-form steady...
In netSmooth: Network smoothing for scRNAseq
Description
Usage
Arguments
Value
Description
The closed-form solution is given by
f_ss = (1 - alpha) * (I - alpha * A)^-1 * f_0
and is computed by matrix inversion in this function.
Usage
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## S4 method for signature 'matrix'
randomWalkByMatrixInv(
f0,
adjMatrix,
alpha,
normalizeAdjMatrix = c("rows", "columns")
)
Arguments
f0
initial data matrix [NxM]
adjMatrix
adjacency matrix of graph to network smooth on
will be column-normalized.
alpha
smoothing coefficient (1 - restart probability of
random walk)
Value
network-smoothed gene expression
netSmooth documentation built on Nov. 8, 2020, 5:33 p.m.
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Description Usage Arguments Value
Description
The closed-form solution is given by f_ss = (1 - alpha) * (I - alpha * A)^-1 * f_0 and is computed by matrix inversion in this function.
Usage
1 2 3 4 5 6 7 | ## S4 method for signature 'matrix'
randomWalkByMatrixInv(
f0,
adjMatrix,
alpha,
normalizeAdjMatrix = c("rows", "columns")
)
|
Arguments
f0 |
initial data matrix [NxM] |
adjMatrix |
adjacency matrix of graph to network smooth on will be column-normalized. |
alpha |
smoothing coefficient (1 - restart probability of random walk) |
Value
network-smoothed gene expression
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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