diffus_matrix: Network enhancement by diffusion process.

Description Usage Arguments Value References Examples

View source: R/diffus_matrix.R

Description

Enhances a comprehensive gene network for a disease using a gene-gene similarity network derived from a type of omics data of the disease that reflects correlations/interactions between genes for the disease.

Usage

1
diffus_matrix(s0, adjacency, alpha=0.75,iter=10, difference=1e-6)

Arguments

s0

The original general gene network.

adjacency

A gene-gene similarity network derived from a type of omics data of a disease.

alpha

A regularization parameter representing weights for signal sources where α = 0 means no disease-specific enhancement.

iter

Number of iterations.

difference

A parameter for converenge.

Value

The enhanced disease-specific network.

References

DiSNEP: a Disease-Specific gene Network Enhancement to improve Prioritizing candidate disease genes (2020), Peifeng Ruan, Shuang Wang.

Examples

1
2
3
4
5
6
7
8
#enhance the general network s0 into a disease specific network by diffusion on similarity network generated from disease omics data.
se=diffus_matrix(s0,adjacency)

#denoise the enhanced network and make it binary and symmetric.
se_post=post_process(se)

#prioritize the disease association signals.
res=diffus_vec(signals,se_post,"pvalue")

pfruan/DiSNEP documentation built on June 17, 2020, 6:05 a.m.