post_process: Post process of enhanced network.

Description Usage Arguments Value References Examples

View source: R/post_process.R

Description

Denoise the enhanced network and make it binary and symmetric.

Usage

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post_process(se,percent=0.9)

Arguments

se

The enhanced disease specific network.

percent

what percentage of edges to be considered as noise.

Value

The denoised and symmetric enhanced disease-specific network.

References

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

Examples

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#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.