8.2 Individual nodes
Here we illustrate how to calculate attackness for each node in the 50-gene subnetwork (see subg above). Independent of previous steps, this subnetwork (subg) can be also imported from subnetwork_node_info.txt and subnetwork_edge_info.txt; see below.
library(tidyverse)
library(igraph)
RData.location <- "http://galahad.well.ox.ac.uk/Myocarditis"## ig: 50-gene subnetwork
df_nodes <- str_c(RData.location, '/subnetwork_node_info.txt') %>% read_delim(delim="\t") %>% select(name, description)
df_edges <- str_c(RData.location, '/subnetwork_edge_info.txt') %>% read_delim(delim="\t")
subg <- igraph::graph_from_data_frame(d=df_edges, directed=F, vertices=df_nodes)
## attackness for each node
df_nodes %>% pull(name) %>% utils::combn(1,simplify=F) -> combine
attackness <- CombAttack(subg, combine)
## append 'attackness' to df_nodes
df_nodes %>% inner_join(attackness %>% transmute(name=nodes.removed, attackness=frac.disconnected), by='name') %>% arrange(desc(attackness)) -> df_nodesThe results are stored in a tibble called df_nodes, a data frame with three columns name, description and attackness (sorted in a descending order).
df_nodes
## # A tibble: 50 x 3
## name description attackness
## <chr> <chr> <dbl>
## 1 Traf2 TNF receptor-associated factor 2 0.5
## 2 Nfkb1 nuclear factor of kappa light polypeptide gene enhancer … 0.42
## 3 Ccl5 chemokine (C-C motif) ligand 5 0.18
## 4 Rac1 Rac family small GTPase 1 0.14
## 5 Vav1 vav 1 oncogene 0.06
## 6 Vcam1 vascular cell adhesion molecule 1 0.06
## 7 Ncf1 neutrophil cytosolic factor 1 0.04
## 8 Tnfrsf1b tumor necrosis factor receptor superfamily, member 1b 0.04
## 9 Lck lymphocyte protein tyrosine kinase 0.04
## 10 Gsdmd gasdermin D 0.04
## # … with 40 more rows