bioconductor-bionar

name	bioconductor-bionar
description	the R package BioNAR, developed to step by step analysis of PPI network. The aim is to quantify and rank each protein’s simultaneous impact into multiple complexes based on network topology and clustering. Package also enables estimating of co-occurrence of diseases across the network and specific clusters pointing towards shared/common mechanisms.

BioNAR

Workflows

Standard Workflow

Build, annotate, and analyze a protein-protein interaction (PPI) network to identify central proteins, functional communities, bridging proteins, and disease/annotation overlaps.

library(BioNAR)

# 1. Build the network from a data frame
file <- system.file("extdata", "PPI_Presynaptic.csv", package = "BioNAR")
tbl <- read.csv(file, sep="\t")
gg <- buildNetwork(tbl)

# 2. Annotate vertices with gene names and diseases
gg <- annotateGeneNames(gg)
afile <- system.file(  package  
dis  read.tableafile sep skip header strip.white 
gg  annotateTopOntoOVGgg dis


gg  calcCentralitygg
mc  getCentralityMatrixgg


pFit  fitDegreeas.vectorigraphdegreegraphgg threads Nsim plot
ent  getEntropyRategg
SRprime  getEntropygg maxSr  


nm  normModularitygg alg  
mem  calcMembershipgg alg  
gg  calcClusteringgg alg  


remem  calcReclusterMatrixgg mem alg   


conmat  makeConsensusMatrixgg N   alg   type   mask   reclust  
clrob  getRobustnessgg alg   conmat


br  getBridgenessgg alg   conmat
gg  calcBridgenessgg alg   conmat
g  plotBridgenessgg alg   VIPs    Xatt