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script.R
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script.R
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options(stringsAsFactors = FALSE)
if(!require("dplyr")) {install.packages("dplyr")}
library(dplyr)
if(!require("stringr")) {install.packages("stringr")}
library(stringr)
if(!require("igraph")) {install.packages("igraph")}
library(igraph)
if(!require("visNetwork")) {install.packages("visNetwork")}
library(visNetwork)
library(ggplot2)
generate_cie10<-function(path="~/Documents/diseasomeCMBD2016/CIE10.txt"){
cie10<-read.csv(path, sep=";", header=FALSE, encoding = "UTF-8")
cie10$V1<-NULL
cie10$V4<-NULL
names(cie10)[1]<-"id"
names(cie10)[2]<-"str"
cie10$str<-enc2utf8(cie10$str)
return(cie10)
}
generate_cmbd<-function(sex,age_min,age_max,path="~/Downloads/cmbd_madrid/CMBD_HOS_ANONIMO_20160101_20161231.csv"){
cmbd <- read.csv(path, sep=";", encoding = "UTF-8")
cmbd<-cmbd[!duplicated(cmbd$HISTORIA_Anonimo),]
cmbd$age<-as.numeric(format(as.Date(cmbd$FECING,"%d/%m/%Y"),"%Y"))-as.numeric(format(as.Date(cmbd$FECNAC,"%d/%m/%Y"),"%Y"))
cmbd<-cmbd[cmbd$SEXO==sex&cmbd$age>=age_min&cmbd$age<=age_max,]
cmbd$diag<-paste(cmbd$C1,
cmbd$C2,
cmbd$C3,
cmbd$C4,
cmbd$C5,
cmbd$C6,
cmbd$C7,
cmbd$C8,
cmbd$C9,
cmbd$C10,
cmbd$C11,
cmbd$C12,
cmbd$C13,
cmbd$C14,
cmbd$C15,
cmbd$C16,
cmbd$C17,
cmbd$C18,
cmbd$C19,
cmbd$C20,
sep="|")
reduced.cmbd<-data.frame(
sex=cmbd$SEXO,
age=cmbd$age,
diag=cmbd$diag
)
return(reduced.cmbd)
}
generate_l<-function(cmbd){
l<-cmbd$diag %>%
str_split("\\|") %>%
lapply(function(x){x[!x==""]})
return(l)
}
generate_v<-function(l){
v<-l %>%
unlist %>%
table %>%
data.frame %>%
arrange(-Freq)
v$id<-v$.
return(v)
}
generate_e<-function(l,v) {
e <- l %>%
lapply(function(x) {
expand.grid(x, x, weight = 1, stringsAsFactors = FALSE)
}) %>%
bind_rows
e <- apply(e[, -3], 1, str_sort) %>%
t %>%
data.frame(stringsAsFactors = FALSE) %>%
mutate(weight = e$weight)
e <- group_by(e, X1, X2) %>%
summarise(weight = sum(weight)/2) %>%
filter(X1 != X2)
e<-e %>% filter(weight>1)
e<-mutate(e,wobs=(weight/length(l)))
e<-mutate(e,wexpA=(as.numeric(v[v['.']==X1][2])/length(l)))
e$.<-e$X2
e<-merge(e,v,by=".")
e<-mutate(e,wexpB=Freq/length(l))
e<-mutate(e,wexp=wexpA*wexpB)
e<-mutate(e,weight=wobs/wexp)
e$.<-NULL
e$wexpA<-NULL
e$wexpB<-NULL
e$Freq<-NULL
e<-mutate(e,pvalue=apply(e[, c(4,6)], 1, function(row) prop.test(x=c(row[1]*length(l), row[2]*length(l)), n=c(length(l), length(l)))$p.value))
return(e)
}
build_edges<-function(v,e){
e <- e %>% filter(weight>1)
e <- e %>% filter(pvalue<0.01)
e<-mutate(e,width=weight/mean(weight))
names(e)[1]<-"from"
names(e)[2]<-"to"
e<-e[e$from %in% v$id | e$to %in% v$id,]
e$id<-NULL
e$label<-round(e$weight,1)
return(e)
}
build_nodes<-function(edges,original_nodes,cie10){
v<-original_nodes
ef<-edges
v<-merge(v,cie10,by="id")
v2<-v[v$id %in% ef$from,]
v3<-v[v$id %in% ef$to,]
v4<- rbind(v3,v2[!v2$id %in% v3$id,])
v4$label<-substr(v4$str,1,30)
v4$title<-v4$str
v4$group<-substr(v4$id,1,1)
v4$.<-NULL
return(v4)
}
build_igraph<-function(sex,age_min,age_max,cie10,cmbd_file="CMBD_HOS_ANONIMO_20160101_20161231.csv"){
age_min<-max(age_min,0)
age_max<-min(age_max,120)
cmbd<-generate_cmbd(sex,age_min,age_max,cmbd_file)
l<-generate_l(cmbd)
v<-generate_v(l)
e<-generate_e(l,v)
edges<-build_edges(v,e)
vertex<-build_nodes(edges,v,cie10)
g<-graph.data.frame(edges,vertices=vertex)
g.sym <- as.undirected(g, mode= "collapse")
write_graph(g.sym,paste0(sex,formatC(age_min,width=3,format="d",flag="0"),formatC(age_max,width=3,format="d",flag="0"),".graphml"),"graphml")
return(g.sym)
}
load_igraph<-function(sex,age_min,age_max) {
return(read_graph(paste0(sex,formatC(age_min,width=3,format="d",flag="0"),formatC(age_max,width=3,format="d",flag="0"),".graphml"),"graphml"))
}
build_summary_edges<-function(sex,age_min,age_max,g.sym){
r.degree <- degree(g.sym)
r.degree <- data.frame(id=names(r.degree),degree=r.degree)
r.strength <- strength(g.sym)
r.strength <- data.frame(id=names(r.strength),strength=r.strength)
r.closeness <- closeness(g.sym,normalized=TRUE)
r.closeness <- data.frame(id=names(r.closeness),closeness=r.closeness)
r.betweenness <- betweenness(g.sym)
r.betweenness <- data.frame(id=names(r.betweenness),betweenness=r.betweenness)
r.summary <- merge(cie10,r.strength,by="id")
r.summary <- merge(r.summary,r.degree,by="id")
r.summary <- merge(r.summary,r.closeness,by="id")
r.summary <- merge(r.summary,r.betweenness,by="id")
return(r.summary)
}
build_summary_global<-function(sex,age_min,age_max,g.sym){
return(data.frame(sex=sex,
age_min=age_min,
age_max=age_max,
num_vertex=length(V(g.sym)),
num_edges=length(E(g.sym)),
w_diameter=diameter(g.sym,directed=F),
diameter=diameter(g.sym,directed=F,weights=NA),
mean_distance=mean_distance(g.sym,directed=F),
edge_density=edge_density(g.sym),
transitivity=transitivity(g.sym)))
}
plot_commorbidity<-function(my_igraph,layout,size_by,min_size,max_size,physics,smooth) {
if(size_by=="betweenness"){
vector<-betweenness(my_igraph)
V(my_igraph)$size<- min_size + ((max_size-min_size)*((vector-min(vector))/(max(vector)-min(vector))))
} else {
vector<-degree(my_igraph)
V(my_igraph)$size<- min_size + ((max_size-min_size)*((vector-min(vector))/(max(vector)-min(vector))))
}
V(my_igraph)$size[V(my_igraph)$size<min_size]<-min_size
V(my_igraph)$size[V(my_igraph)$size>max_size]<-max_size
main<-"Red de comorbilidad (Autor: Julio Bonis)"
visIgraph(my_igraph, layout=layout, physics=physics, smooth=smooth) %>%
visPhysics(solver="barnesHut",
barnesHut=list(
gravitationalConstant=-10000,
centralGravity=0.5,
springLength=95,
springConstant=0.01,
damping=0.05,
avoidOverlap=0.8
),
stabilization=F)
}
precalculate<-function(){
cie10_file<-"CIE10.txt"
cie10<-generate_cie10(cie10_file)
for(sex in c(1,2)) {
for(age_min in c(0,10,20,30,40,50,60,70,80)) {
if(age_min<80){
print(c(sex,age_min,age_min+9))
build_igraph(sex,age_min,age_min+9,cie10)
} else {
print(c(sex,age_min,age_min+9))
build_igraph(sex,age_min,120,cie10)
}
}
}
}
plot_nice_commorbidity_network<-function(sex,age_min,age_max,only_main,node_size_by){
age_min<-max(0,age_min)
age_max<-min(120,age_max)
if(sex==1) {sex_label<-"men"} else {sex_label<-"women"}
if(only_main) {
igraph<-get(paste0("igraph.",sex,formatC(age_min,width=3,format="d",flag="0"),formatC(age_max,width=3,format="d",flag="0"),".main"))
} else {
igraph<-get(paste0("igraph.",sex,formatC(age_min,width=3,format="d",flag="0"),formatC(age_max,width=3,format="d",flag="0")))
}
vertex<-as.data.frame(vertex_attr(igraph))
vertex$id<-vertex$name
if(node_size_by=="degree") {
vertex$size<-eval(10 + ((100-10)*((degree(igraph)-min(degree(igraph)))/(max(degree(igraph))-min(degree(igraph))))))
} else {
if(node_size_by=="betweenness") {
vertex$size<-eval(10 + ((100-10)*((betweenness(igraph)-min(betweenness(igraph)))/(max(betweenness(igraph))-min(betweenness(igraph))))))
} else {
vertex$size<-eval(10 + ((100-10)*((vertex$Freq-min(vertex$Freq))/(max(vertex$Freq)-min(vertex$Freq)))))
}
}
edges<-data.frame(
from=ends(igraph,E(igraph))[,1],
to=ends(igraph,E(igraph))[,2],
width=eval(1 + ((30-1)*((edge_attr(igraph)$weight-min(edge_attr(igraph)$weight))/(max(edge_attr(igraph)$weight)-min(edge_attr(igraph)$weight))))),
label=round(edge_attr(igraph)$weight,1)
)
visNetwork(vertex,edges,main=paste0("Commorbidity network for ",sex_label," ",age_min," to ",age_max," years (Author: Julio Bonis [email protected])")) %>%
visLayout(improvedLayout=TRUE) %>%
visEdges(shadow=T,smooth=T,dashes=F) %>%
visPhysics(solver="barnesHut",
barnesHut=list(
gravitationalConstant=-10000,
centralGravity=0.1,
springLength=95,
springConstant=0.01,
damping=0.5,
avoidOverlap=0.8
),
stabilization=F) %>%
visNodes(shadow=T) %>%
visOptions(highlightNearest = list(enabled = T, degree = 1, hover = F),
selectedBy="group",
collapse=FALSE)
}
setwd("C:/Users/jbonis_fcsai/Developer/trusty32/code/diseasomeCMBD2016")
cie10_file<-"CIE10.txt"
cie10<-generate_cie10(cie10_file)
#loadin the precalculated graphs by age and sex and
for(sex in c(1,2)) {
for(age_min in c(0,10,20,30,40,50,60,70,80)) {
if(age_min<80){
age_max<-age_min+9
} else {
age_max<-120
}
print(c(sex,age_min,120))
var_name<-paste0(sex,formatC(age_min,width=3,format="d",flag="0"),formatC(age_max,width=3,format="d",flag="0"))
mygraph<-read_graph(paste0(var_name,".graphml"),"graphml")
assign(paste0("igraph.",var_name),mygraph)
assign(paste0("igraph.",var_name,".main"),decompose.graph(mygraph)[[which.max(components(mygraph)$csize)]])
}
}
# launching the summary calculations for graphs by age and sex
if(exists("summary.global.main")){remove("summary.global.main")}
if(exists("summary.global")){remove("summary.global")}
for(sex in c(1,2)) {
for(age_min in c(0,10,20,30,40,50,60,70,80)) {
if(age_min<80){
age_max<-age_min+9
} else {
age_max<-120
}
print(c(sex,age_min,age_max))
var_name<-paste0(sex,formatC(age_min,width=3,format="d",flag="0"),formatC(age_max,width=3,format="d",flag="0"))
mygraph<-get(paste0("igraph.",var_name))
mygraph.main<-get(paste0("igraph.",var_name,".main"))
assign(paste0("igraph.",var_name,".summary.edges"),build_summary_edges(sex,age_min,age_max,mygraph))
assign(paste0("igraph.",var_name,".summary.global"),build_summary_global(sex,age_min,age_max,mygraph))
if(exists("summary.global.main")){
print(c("añado summary.global.main",sex,age_min,age_max))
new_row.main<-build_summary_global(sex,age_min,age_max,mygraph.main)
summary.global.main<-rbind(summary.global.main,new_row.main)
new_row<-build_summary_global(sex,age_min,age_max,mygraph)
summary.global<-rbind(summary.global,new_row)
} else {
print(c("Creo summary.global.main",sex,age_min,age_max))
summary.global.main<-build_summary_global(sex,age_min,age_max,mygraph.main)
summary.global<-build_summary_global(sex,age_min,age_max,mygraph)
}
assign(paste0("igraph.",var_name,".main.summary.edges"),build_summary_edges(sex,age_min,age_max,mygraph.main))
assign(paste0("igraph.",var_name,".main.summary.global"),build_summary_global(sex,age_min,age_max,mygraph.main))
assign(paste0("igraph.",var_name,".summary.edges"),build_summary_edges(sex,age_min,age_max,mygraph))
assign(paste0("igraph.",var_name,".summary.global"),build_summary_global(sex,age_min,age_max,mygraph))
}
}
#plotting the graphs by age and sex
plot_commorbidity(igraph.1000009,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.1010019,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.1020029,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.1030039,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.1040049,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.1050059,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.1060069,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.1070079,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.1080120,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.2000009,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.2010019,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.2020029,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.2030039,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.2040049,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.2050059,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.2060069,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.2070079,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.2080120,"layout_nicely","betweenness",10,100,T,T)
#plotting the nice graphs by age and sex
plot_commorbidity(igraph.1000009,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.1010019,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.1020029,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.1030039,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.1040049,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.1050059,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.1060069,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.1070079,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.1080120,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.2000009,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.2010019,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.2020029,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.2030039,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.2040049,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.2050059,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.2060069,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.2070079,"layout_nicely","betweenness",10,100,T,T)
plot_commorbidity(igraph.2080120,"layout_nicely","betweenness",10,100,T,T)
plot_global_summary<-function(summary,metric){
ggplot(data=summary, aes(x=age_min, y=get(metric), group=sex))+
geom_line(aes(color=factor(sex)))+
geom_point(aes(color=factor(sex)))+
labs(title=paste0(metric," by age and sex"),x="age_min", y = metric)+
theme_light()
}
plot_global_summary(summary.global,"num_vertex")
plot_global_summary(summary.global,"num_edges")
plot_global_summary(summary.global,"diameter")
plot_global_summary(summary.global,"w_diameter")
plot_global_summary(summary.global,"mean_distance")
plot_global_summary(summary.global,"edge_density")
plot_global_summary(summary.global,"transitivity")