work/ipsd-getPPIs.R

In twesleyb/Uezu2016: iBioID Proteomics from Uezu, Kanak, Bradshaw et al., 2016

#!/usr/bin/env Rscript

## ---- inputs

root <- "~/projects/Uezu2016"

# load project's data
devtools::load_all(root)

data(ipsd)

## ---- imports

library(dplyr)
library(data.table)

# load mouse PPI dataset
data(musInteractome,package="getPPIs")


## ---- collect ppis (edges)

# keep interactions from mouse human and rat
os_keep <- c(9606, 10116, 10090)

# subset the data using dplyr's pipe %>% and filter
edges <- musInteractome %>% 
	filter(osEntrezA %in% ipsd & osEntrezB %in% ipsd) %>%
	filter(Interactor_A_Taxonomy %in% os_keep) %>%
	dplyr::select(osEntrezA,osEntrezB) %>% mutate(weight=1)


## ---- convert ppi_df to adjm

library(igraph)

G <- graph_from_data_frame(edges,directed=FALSE)

g <- simplify(G)

# convert to adjm with igraph's as_adjacency_matrix
A <- as_adjacency_matrix(g)
adjm <- as.matrix(A)


ggplotScaleFreeFit(apply(adjm,1,sum))

ggcorrplot(adjm)

m <- matrix(as.numeric(runif(100) > 0.9), ncol = 10) 
# create random sparse matrix

library(SparseM)

hc <- hclust(as.dist(1-adjm))
idx = idy = hc$order

pdf("ipsd_matrix.pdf")
image(as.matrix.csr(adjm[idx,idy]))
dev.off()