eig_score_adj: Determines how much a patient is connected to its friends...
In LucaGiudice/Simpati: Pathway-based classifier exploits patient similarity network paradigm
Description
Usage
Arguments
Value
View source: R/funs_measures.R
Description
Function which computes how much a node is connected to its class, its enemies and then
it produces the adjusted eigenscore centrality of the nodes. Higher are both the measures
and higher is the score
Usage
1
eig_score_adj(m2, nAs)
Arguments
m2
Matrix of profiles (genes x samples)
nAs
number of elements of the first group
Value
A similarity matrix for the column objects
LucaGiudice/Simpati documentation built on Jan. 27, 2022, 11:42 p.m.
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Description Usage Arguments Value
View source: R/funs_measures.R
Description
Function which computes how much a node is connected to its class, its enemies and then it produces the adjusted eigenscore centrality of the nodes. Higher are both the measures and higher is the score
Usage
1 | eig_score_adj(m2, nAs)
|
Arguments
m2 |
Matrix of profiles (genes x samples) |
nAs |
number of elements of the first group |
Value
A similarity matrix for the column objects
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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