perform_network_ppi: Perform network module of PPI-based approach.

In ys-amms/bionexr: Integrative network-based analysis of cancer somatic mutation and expression data

Description

Perform network module of PPI-based approach.

Usage

perform_network_ppi(df_mut_score_wide, whole_fc_genes, mcutoff = 2,
  fraction = 0.6, nei_order = 2, mweight = 0.6, padj = 0.01,
  log2_fold_change = 2)

Arguments

df_mut_score_wide	A dataframe.
whole_fc_genes	A list.
mcutoff	A float number between 0 and 6, default is 2.
fraction	A float number between 0 and 1, default is 0.6.
nei_order	The order of neighborhood from the mutant gene, default is 2.
mweight	weight of mutation score for combined score, default is 0.6.
padj	Adjusted p value threshold for differential analysis, default is 0.01.
log2_fold_change	log2 transformed fold change threshold for differential analysis, default is 2.

Value

A list.

Examples

## Not run: 

prepare_ma()
res.gene <- perform_gene_ppi(hnsc_mut_part, hnsc_exp_part)
res.network <- perform_network_ppi(res.gene[[2]], res.gene[[3]])

## End(Not run)

ys-amms/bionexr documentation built on May 4, 2019, 5:33 p.m.