Newman mod in main and new dynamic tree cut plots
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@ -7,6 +7,7 @@
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library(igraph)
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library(igraphdata)
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library(WGCNA)
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source("self_newman_mod.R")
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data(karate)
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data(yeast)
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@ -49,7 +50,8 @@ plot(g2, main=paste(g2.netname, " Laplace Spectral Clustering"),
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########################## Part 2: Newman Modularity ##########################
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list(Q=Q,max.lam=max.lam,weights=weights,clusters=clusters) <- newman_mod(g1)
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list(Q=Q,max.lam=max.lam,weights=weights,clusters=clusters) <- newman_mod(g2)
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##################### Part 3: Recursive Newman Modularity #####################
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# Using igraph
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@ -105,6 +107,33 @@ g2.TOM
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TOMplot(g1.TOM, lap_tree1, main=paste(g1.netname, " Heatmap Plot"))
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TOMplot(g2.TOM, lap_tree2, main=paste(g2.netname, " Heatmap Plot"))
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# dynamic tree cut
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minModuleSize = 2
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# degree = 1
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dynamicMods1 = cutreeDynamic(dendro = lap_tree1, distM = lap_dist1, deepSplit = 2,
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pamRespectsDendro = FALSE, minClusterSize = minModuleSize)
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init_mod_sizes <- table(dynamicMods)
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# you will have to work through finding and installing labels2colors.
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dynamicColors = labels2colors(dynamicMods1)
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table(dynamicColors)
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plotDendroAndColors(lap_tree1, dynamicColors, "Dynamic Tree Cut", dendroLabels = FALSE,
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hang = 0.03, addGuide = TRUE, guideHang = 0.05,
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main = paste(g1.netname, "dendogram and dynamic cut modules, degree = 1"))
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# degree = 1
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dynamicMods2 = cutreeDynamic(dendro = lap_tree2, distM = lap_dist2, deepSplit = 2,
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pamRespectsDendro = FALSE, minClusterSize = minModuleSize)
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init_mod_sizes <- table(dynamicMods)
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# you will have to work through finding and installing labels2colors.
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dynamicColors = labels2colors(dynamicMods2)
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table(dynamicColors)
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plotDendroAndColors(lap_tree2, dynamicColors, "Dynamic Tree Cut", dendroLabels = FALSE,
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hang = 0.03, addGuide = TRUE, guideHang = 0.05,
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main = paste(g2.netname, "dendogram and dynamic cut modules, degree = 1"))
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################################ Part 5: UMAP ################################
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g1.dist2 <- 1- as.matrix(g1.adj)
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g2.dist2 <- 1- as.matrix(g2.adj)
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@ -22,7 +22,7 @@ newman_mod <- function(g, weights=NULL){
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#V(g)$color <- ifelse(B[1,]>0,"green","yellow")
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V(g)$color <- ifelse(B.eigs$vectors[,1]>0,"green","yellow")
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V(g)$size <- 10
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plot(g, main=paste(g1.netname, " Newman Modularity"))
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plot(g, main=paste(g.netname, " Newman Modularity"))
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clust1 = list()
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clust2 = list()
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clusters = list()
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