SmCCNet (version 2.0.3)

summarizeNetSHy: NetSHy Summarization Score

Description

Implement NetSHy network summarization via a hybrid approach (Vu et al.,) to summarize network by considering the network topology with Laplacian matrix.

Usage

summarizeNetSHy(X, A, npc = 1)

Value

A list consists of (1) subject-level network summarization score, (2) principal component importance information: standard deviation, percent of variance explained, and cumulative proportion of variance explained, and (3) principal component feature-level loadings.

Arguments

X

An \(n\times m\) data matrix with \(m\) features and \(n\) subjects.

A

Corresponding adjacency matrix of size \(p\) by \(p\).

npc

Number of principal components used to summarize the network, default is set to 1.

References

Vu, Thao, Elizabeth M. Litkowski, Weixuan Liu, Katherine A. Pratte, Leslie Lange, Russell P. Bowler, Farnoush Banaei-Kashani, and Katerina J. Kechris. "NetSHy: network summarization via a hybrid approach leveraging topological properties." Bioinformatics 39, no. 1 (2023): btac818.

Examples

# simulate omics data
OmicsData <- matrix(rnorm(200,0,1), nrow = 10, ncol = 20)
# simulate omics adjacency matrix
set.seed(123)
w <- rnorm(20)
w <- w/sqrt(sum(w^2))
featurelabel <- paste0('omics',1:20)
abar <- getAbar(w, FeatureLabel = featurelabel)
# extract NetSHy summarization score
netshy_score <- summarizeNetSHy(OmicsData, abar)