diffus_vec: Prioritizing signal genes by diffusion process

In pfruan/DiSNEP: DiSNEP: a Disease-Specific Enhancement for gene Network Enhancement to improve Prioritizing candidate disease genes

Prioritizing signal genes by diffusion process

Description

Prioritizing signal genes by diffusion process with a gene network.

Usage

diffus_vec(t_score, snet, type, beta=0.75, iter=10, difference=1e-6, top=100)

Arguments

t_score	A matrix of original gene signals, with the first colomn is the gene names and the second column is the association signals.
snet	A gene network.
type	The type of input association signals, p value or z score.
beta	A regularization parameter representing weights for signal sources where beta = 0 means no priotitization.
iter	Number of iterations.
difference	A parameter for converenge.
top	A parameter for how many candidate genes will be selected.

Value

The prioritized candidate genes with signal scores from large to small.

References

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

Examples

#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 Oct. 12, 2023, 3:29 p.m.