In jgockley62/igraphNetworkExpansion: Trace Subnetworks from an AD Necortical Network of Protein-Protein Interactions

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

Pull SIF intereaction files from synapse

library(foreach)
syn <- igraphNetworkExpansion::log_into_synapse()

#> Define the SIF formatted files stored in synapse to use for net construction 
sif_files <- c(
  'syn21914063', 'syn21914056', 'syn21914057', 'syn21914059', 'syn21914061',
  'syn21914064', 'syn21914065', 'syn21914070', 'syn21914071', 'syn21914072',
  'syn21914078', 'syn21914082', 'syn21914083', 'syn21914087', 'syn21914090',
  'syn21914091', 'syn21914093', 'syn21914094', 'syn21914074'
)

names(sif_files) <- c(
  'Detailed',  'bind',  'biogrid',  'corum',  'ctd',
  'dip', 'drugbank', 'hprd', 'humancyc', 'intacsyngnc',
  'msigdb', 'netpath', 'panther', 'pathbank', 'pid',
  'psp', 'reactome', 'reconx', 'kegg'
)

#> Load the SIF Files and Construct the igraph Network Object
#Data <- sif_loader(sif_files, syn$synapse)
loaded_data <- igraphNetworkExpansion::sif_loader(sif_files, syn$synapse)
total <- loaded_data$df
net_oldStyle <- loaded_data$net
graph <- loaded_data$graph

#> Network Interaction Summary
tot <- 0
for(type in levels(total$interaction) ){
  message(paste0(
    type, ": ",
    eval(parse(text=paste0(
      'length(igraph::E(graph$`',
      type,
      '`))'
    )))
  ))
  tot <- eval(parse(text=paste0(
    'length(igraph::E(graph$`',
    type,
    '`))'
  ))) + tot
}
message( paste0( "Total Interactions = ", tot ) )


#> EdgeRep The number of distinct edge types between from_gene and to_gene
total$EdgeRep <- 0
total$Edge <- paste0( total$from, ':',  total$to )
key <- table( total$Edge )
total$EdgeRep <- key[ total$Edge ]

#> total_occurence The number of times from_gene and to_gene are connected 
#> total_occurence is regaurdless of interaction or database. It is the gross
#> sum of interactions
total_occurence <- rep(0, length(names(key)))
names( total_occurence ) <- names(key)

sumtally <- function(name, df) {
  value <- sum( df[ df$Edge == name, ]$Occurance )
  return(c(name, value))
}

temp_total <- total[ ,c('Edge','Occurance')]
temp_total$Occurance <- as.numeric(temp_total$Occurance)

#> Run Sum Tally this can take a while!
cl <- parallel::makeCluster( parallel::detectCores()-2 )
doParallel::registerDoParallel(cl)

len <- length(names(total_occurence))
mark<-Sys.time()
total_occurances <- foreach(i=names(total_occurence)[1:len], .combine=rbind ) %dopar% sumtally(i, temp_total)
Sys.time()-mark

parallel::stopCluster(cl)

row.names(total_occurances) <- total_occurances[,1]
total_occurances <- as.data.frame(total_occurances)
total_occurances$V2 <- as.numeric(as.character(total_occurances$V2))
head(total_occurances[ total$Edge, ])

total$SumOccurence <- total_occurances[ total$Edge, ]$V2

genes <- c( as.character(total$from), as.character(total$to) )
genes <- genes[ !duplicated(genes) ]
genes <- as.data.frame( genes )

graph <- list()
total$interaction <- as.factor(total$interaction)
for(type in levels(total$interaction) ){
    eval(parse(text=paste0(
      'graph$`',
      type,
      '` <- igraph::graph_from_data_frame(d=total[ total$interaction == \'',
      type,
      '\', ], vertices=genes, directed=T) '
    )))
}

#> Finalize the data frame object and base network
network <- igraph::graph_from_data_frame(d=total, vertices=genes, directed=T) 
data <- list(
  data_frame=total,
  network = network,
  graph = graph
)
#> Data corresponds to the object imported by:
#> network - data(basic_network, package = "igraphNetworkExpansion")
#> graph - data(basic_network_interactions, package = "igraphNetworkExpansion")
#> data_frame - data(basic_network_table, package = "igraphNetworkExpansion")

jgockley62/igraphNetworkExpansion documentation built on April 15, 2022, 12:14 a.m.