xrydbh 2022-02-04
library(qgraph)
library(igraph)##
## Attaching package: 'igraph'
## The following object is masked from 'package:clusterProfiler':
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## simplify
## The following object is masked from 'package:DescTools':
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## %c%
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## union
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## union
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## union
## The following objects are masked from 'package:BiocGenerics':
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## normalize, path, union
## The following objects are masked from 'package:dplyr':
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## as_data_frame, groups, union
## The following objects are masked from 'package:purrr':
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## compose, simplify
## The following object is masked from 'package:tidyr':
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## crossing
## The following object is masked from 'package:tibble':
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## as_data_frame
## The following objects are masked from 'package:stats':
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## decompose, spectrum
## The following object is masked from 'package:base':
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## union
library(tidyverse)
# Set path
# If script is running separately move up one step with setwd(".."). Only needed once (for first script run separately).
networkWeightCutOff <- 30
for (plf in c("ms","pea")){
input_path <- paste("./out_r/WGCNA/",plf,sep="")
output_path.0.0 <- input_path
output_path <- paste(output_path.0.0,"/network_plots",sep="") #"plots_wgcna_Gene.symbol/ms_Log2_norm_ab_0_na_both/softPower_12/network_plots" # coul also be set equla to plot_dir form 3_b
dir.create(output_path)
## Plot networks based on topological overlap
full_fns_TOM <- dir(input_path,"-TOM",full.names=T)
full_extracts_and_matches <- full_fns_TOM %>%
str_match("TOM(.*?).txt")
modules_of_interest <- full_extracts_and_matches[,2]
for (i in seq_along(modules_of_interest)){ #
print(modules_of_interest[i])
edglist.0.0 <- read.table(full_fns_TOM[i],
sep = "" ,
header = F,
na.strings ="",
stringsAsFactors= F) %>%
as.matrix()#, nrows = 100
edgelist.0.1 <- edglist.0.0[,c(1,2,5)]
colnames(edgelist.0.1) <- c("From","To","Weight")
edgelist.0.2 <- edgelist.0.1 %>%
as_tibble() %>%
arrange(desc(Weight)) %>%
head(networkWeightCutOff)
# convert edgelist to ?? matrix
g=graph.data.frame(edgelist.0.2, directed = F)
my_mat.0.0 <- get.adjacency(g, sparse = FALSE, attr='Weight')
class(my_mat.0.0) <- "numeric"
pdf(paste(output_path,"/TOM_network_heatmap_",modules_of_interest[i],"_module.pdf",sep=""))#plot_dir #, 2000, 2000, res=300
qgraph(my_mat.0.0,
graph= "default", #cor
layout = "spring",
edge.labels = TRUE,
palette= "ggplot2",
#groups=sign_cyts_and_gfs.lst_0[[i]],
legend=F,
#bg='lightgrey',
title.cex=1.2,
label.cex=1,
#label.norm="OOOOO",
title=paste("Hubgene TOM network",modules_of_interest[i]),
label.scale.equal=T,
labels = colnames(my_mat.0.0))
dev.off()
}
## Plot networks based on adjacency
full_fns_ADJ <- dir(input_path,"-ADJ",full.names=T)
full_extracts_and_matches <- full_fns_ADJ %>% str_match("ADJ(.*?).txt")
modules_of_interest <- full_extracts_and_matches[,2]
for (i in seq_along(modules_of_interest)){
edglist.0.0 <- read.table(full_fns_ADJ[i],
sep = "" ,
header = F,
na.strings ="",
stringsAsFactors= F) %>%
as.matrix()#, nrows = 100
edgelist.0.1 <- edglist.0.0[,c(1,2,5)]
colnames(edgelist.0.1) <- c("From","To","Weight")
edgelist.0.2 <- edgelist.0.1 %>% as_tibble() %>%
arrange(desc(Weight)) %>% head(networkWeightCutOff )
# convert edgelist to ?? matrix
g=graph.data.frame(edgelist.0.2, directed = F)
my_mat.0.0 <- get.adjacency(g, sparse = FALSE, attr='Weight')
class(my_mat.0.0) <- "numeric"
png(paste(output_path,"/ADJ_network_heatmap_",modules_of_interest[i],"_module.png",sep=""), 2000, 2000, res=300)#plot_dir
qgraph(my_mat.0.0,
graph= "default", #cor
layout = "spring",
edge.labels = TRUE,
palette= "ggplot2",
#groups=sign_cyts_and_gfs.lst_0[[i]],
legend=F,
bg='lightgrey',
title.cex=1.2,
label.cex=1,
#label.norm="OOOOO",
title=paste("Hubgene adjacency network",modules_of_interest[i]),
label.scale.equal=T,
labels = colnames(my_mat.0.0))
dev.off()
}
}## Warning in dir.create(output_path): './out_r/WGCNA/ms/network_plots' already
## exists
## [1] "blue"
## Warning in qgraph(my_mat.0.0, graph = "default", layout = "spring", edge.labels
## = TRUE, : Non-finite weights are omitted
## [1] "brown"
## Warning in qgraph(my_mat.0.0, graph = "default", layout = "spring", edge.labels
## = TRUE, : Non-finite weights are omitted
## [1] "turquoise"
## Warning in qgraph(my_mat.0.0, graph = "default", layout = "spring", edge.labels
## = TRUE, : Non-finite weights are omitted
## Warning in qgraph(my_mat.0.0, graph = "default", layout = "spring", edge.labels
## = TRUE, : Non-finite weights are omitted
## Warning in qgraph(my_mat.0.0, graph = "default", layout = "spring", edge.labels
## = TRUE, : Non-finite weights are omitted
## Warning in qgraph(my_mat.0.0, graph = "default", layout = "spring", edge.labels
## = TRUE, : Non-finite weights are omitted
## Warning in dir.create(output_path): './out_r/WGCNA/pea/network_plots' already
## exists
## [1] "black"
## Warning in qgraph(my_mat.0.0, graph = "default", layout = "spring", edge.labels
## = TRUE, : Non-finite weights are omitted
## [1] "blue"
## Warning in qgraph(my_mat.0.0, graph = "default", layout = "spring", edge.labels
## = TRUE, : Non-finite weights are omitted
## [1] "brown"
## Warning in qgraph(my_mat.0.0, graph = "default", layout = "spring", edge.labels
## = TRUE, : Non-finite weights are omitted
## [1] "green"
## Warning in qgraph(my_mat.0.0, graph = "default", layout = "spring", edge.labels
## = TRUE, : Non-finite weights are omitted
## [1] "red"
## Warning in qgraph(my_mat.0.0, graph = "default", layout = "spring", edge.labels
## = TRUE, : Non-finite weights are omitted
## [1] "turquoise"
## Warning in qgraph(my_mat.0.0, graph = "default", layout = "spring", edge.labels
## = TRUE, : Non-finite weights are omitted
## [1] "yellow"
## Warning in qgraph(my_mat.0.0, graph = "default", layout = "spring", edge.labels
## = TRUE, : Non-finite weights are omitted
## Warning in qgraph(my_mat.0.0, graph = "default", layout = "spring", edge.labels
## = TRUE, : Non-finite weights are omitted
## Warning in qgraph(my_mat.0.0, graph = "default", layout = "spring", edge.labels
## = TRUE, : Non-finite weights are omitted
## Warning in qgraph(my_mat.0.0, graph = "default", layout = "spring", edge.labels
## = TRUE, : Non-finite weights are omitted
## Warning in qgraph(my_mat.0.0, graph = "default", layout = "spring", edge.labels
## = TRUE, : Non-finite weights are omitted
## Warning in qgraph(my_mat.0.0, graph = "default", layout = "spring", edge.labels
## = TRUE, : Non-finite weights are omitted
## Warning in qgraph(my_mat.0.0, graph = "default", layout = "spring", edge.labels
## = TRUE, : Non-finite weights are omitted
## Warning in qgraph(my_mat.0.0, graph = "default", layout = "spring", edge.labels
## = TRUE, : Non-finite weights are omitted