2428 lines (2427 with data), 156.2 kB
{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"NMF - BioConductor layer [OK] | Shared memory capabilities [NO: bigmemory] | Cores 27/28\n",
"\n",
" To enable shared memory capabilities, try: install.extras('\n",
"NMF\n",
"')\n",
"\n",
"Loading required package: mclust\n",
"\n",
"Package 'mclust' version 5.4.6\n",
"Type 'citation(\"mclust\")' for citing this R package in publications.\n",
"\n",
"Loading required package: ade4\n",
"\n",
"\n",
"Attaching package: ‘ade4’\n",
"\n",
"\n",
"The following object is masked from ‘package:BiocGenerics’:\n",
"\n",
" score\n",
"\n",
"\n",
"\n",
"Attaching package: ‘GPArotation’\n",
"\n",
"\n",
"The following object is masked from ‘package:NMF’:\n",
"\n",
" entropy\n",
"\n",
"\n",
"\n",
"Attaching package: ‘MOFAtools’\n",
"\n",
"\n",
"The following objects are masked from ‘package:NMF’:\n",
"\n",
" featureNames, featureNames<-, predict, sampleNames, sampleNames<-\n",
"\n",
"\n",
"The following objects are masked from ‘package:Biobase’:\n",
"\n",
" featureNames, featureNames<-, sampleNames, sampleNames<-\n",
"\n",
"\n",
"The following object is masked from ‘package:stats’:\n",
"\n",
" predict\n",
"\n",
"\n",
"Loading required package: JADE\n",
"\n",
"Loading required package: lattice\n",
"\n",
"Loading required package: caTools\n",
"\n",
"Loading required package: gdata\n",
"\n",
"gdata: read.xls support for 'XLS' (Excel 97-2004) files ENABLED.\n",
"\n",
"\n",
"\n",
"gdata: read.xls support for 'XLSX' (Excel 2007+) files ENABLED.\n",
"\n",
"\n",
"Attaching package: ‘gdata’\n",
"\n",
"\n",
"The following object is masked from ‘package:Biobase’:\n",
"\n",
" combine\n",
"\n",
"\n",
"The following object is masked from ‘package:BiocGenerics’:\n",
"\n",
" combine\n",
"\n",
"\n",
"The following object is masked from ‘package:stats’:\n",
"\n",
" nobs\n",
"\n",
"\n",
"The following object is masked from ‘package:utils’:\n",
"\n",
" object.size\n",
"\n",
"\n",
"The following object is masked from ‘package:base’:\n",
"\n",
" startsWith\n",
"\n",
"\n",
"Loading required package: gtools\n",
"\n",
"\n",
"Attaching package: ‘gtools’\n",
"\n",
"\n",
"The following object is masked from ‘package:InterSIM’:\n",
"\n",
" logit\n",
"\n",
"\n",
"Loading required package: gplots\n",
"\n",
"\n",
"Attaching package: ‘gplots’\n",
"\n",
"\n",
"The following object is masked from ‘package:stats’:\n",
"\n",
" lowess\n",
"\n",
"\n"
]
}
],
"source": [
"library(\"InterSIM\", quietly = TRUE)\n",
"source(\"runfactorization.R\")"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[1] \"../data/\"\n",
"[1] \"20210329212141\"\n",
"[1] \"../data/simulations_20210329212141/\"\n",
"[1] \"../results20210329212141/\"\n"
]
}
],
"source": [
"# Base folder for data\n",
"data_folder <- \"../data/\"\n",
"# Label to identify current run\n",
"tag <- format(Sys.time(), \"%Y%m%d%H%M%S\")\n",
"# Folder containing simulated data\n",
"simul_folder <- paste0(data_folder, \"simulations_\", tag, \"/\") \n",
"# Folder for comparison results\n",
"results_folder <- paste0(\"../results\", tag, \"/\")\n",
"print(data_folder)\n",
"print(tag)\n",
"print(simul_folder)\n",
"print(results_folder)\n",
"dir.create(data_folder, showWarnings = FALSE)\n",
"dir.create(simul_folder, showWarnings = FALSE)\n",
"dir.create(results_folder, showWarnings = FALSE)\n"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [],
"source": [
"list_clusters <- seq(5,15,5)\n",
"list_distrib <- c(\"heterogeneous\",\"equal\")\n",
"\n",
"# For a given number of clusters\n",
"for(size in list_distrib) {\n",
" thisdir1 <- paste(simul_folder,size, sep=\"\")\n",
" dir.create(thisdir1, showWarnings = FALSE)\n",
" # Data distribution among clusters will either be heterogeneous or equal \n",
" for (num.clusters in list_clusters) {\n",
" thisdir2 <- paste(thisdir1,\"/\",num.clusters, sep=\"\")\n",
" dir.create(thisdir2, showWarnings = FALSE)\n",
" }\n",
" }\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [],
"source": [
"## Simulate data\n",
"## INPUTS:\n",
"# folder = location where the simulated data should be saved\n",
"# num.clusters = number of clusters to be imposed on the data\n",
"# size = heterogeneous for heterogeneous clusters, equal for equally-sized clusters\n",
"## OUPUTS: matrices of simulated data are saved to file in folder\n",
"##模拟数据\n",
"##输入：\n",
"#folder=应保存模拟数据的位置\n",
"#num.clusters =要施加在数据上的集群数\n",
"#size =对于异构集群，heterogeneous，对于相等大小的集群，equal\n",
"## OUPUTS：模拟数据矩阵保存到文件夹中的文件中\n",
"simulated_data_generation <- function(out.folder, num.clusters, size=\"heterogeneous\", predefined=TRUE) {\n",
" \n",
" # Number of clusters\n",
" num.clusters <- as.numeric(num.clusters)\n",
" # Size of the effect\n",
" effect <- 2.5\n",
" # Sample proportions per clusters defined here are those used for the paper\n",
" #此处定义的每类样本比例是本文使用的比例\n",
" prop_predefined <- list(\n",
" \"heterogeneous\" = list(\n",
" \"5\" = c(0.35, 0.13, 0.19, 0.08, 0.25),\n",
" \"10\" = c(0.20, 0.10, 0.07, 0.10, 0.15, 0.13, 0.10, 0.08, 0.05, 0.02),\n",
" \"15\" = c(0.10,0.08,0.04,0.03,0.12,0.03,0.10,0.03,0.05,0.02,0.1,0.2,0.03,0.02,0.05)\n",
" ),\n",
" \"equal\" = list(\n",
" \"5\" = c(0.25,0.2,0.2,0.2,0.15),\n",
" \"10\" = c(0.15,0.1,0.1,0.1,0.1,0.1,0.05,0.1,0.1,0.1),\n",
" \"15\" = c(0.07,0.07,0.07,0.06,0.07,0.07,0.07,0.06,0.07,0.06,0.07,0.06,0.07,0.06,0.07)\n",
" )\n",
" )\n",
"\n",
" # Check provided parameter (size) against allowed values\n",
" if(! size %in% names(prop_predefined)) {\n",
" print(paste0(\"ERROR: size can only assume value : \", \n",
" paste0(names(prop_predefined), collapse=\",\"),\n",
" \" found : \", size))\n",
" }\n",
"\n",
" # If article proportions are to be used\n",
" if(predefined) {\n",
" # Check provided parameter (number of clusters) against allowed values\n",
" if(! as.character(num.clusters) %in% names(prop_predefined[[size]])) {\n",
" print(paste0(\"ERROR: num.clusters can only assume value : \", \n",
" paste0(names(prop_predefined[[size]]), collapse=\",\"),\n",
" \" found : \",\n",
" num.clusters))\n",
" }\n",
" prop <- prop_predefined[[size]][[as.character(num.clusters)]]\n",
" prop[1] <- 1-sum(prop[-1])\n",
" }\n",
" # Otherwise\n",
" else {\n",
" if(size == \"equal\") {\n",
" # Could be simplified! Only necessary because InterSIM is \"easily offended\" :\n",
" # ensure same object type as in the heterogeneous case, and that not all \n",
" # values are exactly the same (should not impact the number of samples per group)\n",
" # - same type\n",
" equals <- rep(1, num.clusters)\n",
" prop <- equals/sum(equals)\n",
" # - slightly imbalanced\n",
" delta <- 0.05*prop[1]\n",
" prop[1] <- prop[1]+delta\n",
" prop[num.clusters] <- prop[num.clusters]-delta\n",
" # - sum is 1\n",
" prop <- round(prop, digits = 10)\n",
" prop[1] <- 1-sum(prop[-1])\n",
" }\n",
" else {\n",
" random <- runif(n = num.clusters, min = 0, max = 1)\n",
" prop <- random/sum(random)\n",
" }\n",
" }\n",
"\n",
" # Simulate data based on provided parameters\n",
" print(prop)\n",
" print(sum(prop))\n",
" print(sum(prop)==1)\n",
" sim.D <- InterSIM(n.sample=100, cluster.sample.prop=prop, \n",
" delta.methyl=effect, delta.expr=effect, delta.protein=effect, \n",
" p.DMP=0.25, p.DEG=NULL, p.DEP=NULL,\n",
" do.plot=FALSE, sample.cluster=TRUE, feature.cluster=TRUE)\n",
" \n",
" \n",
" thisdir <- paste(out.folder,size,\"/\",num.clusters, sep=\"\")\n",
" print(thisdir)\n",
" #dir.create(paste(out.folder,size,num.clusters, sep=\"/\"), showWarnings = FALSE)\n",
" #dir.create(paste(out.folder,size,num.clusters, sep=\"/\"), showWarnings = FALSE)\n",
" #dir.create(paste(out.folder,size,num.clusters, sep=\"/\"), showWarnings = FALSE)\n",
"\n",
" \n",
"\n",
" # Export simulations as tables\n",
" write.table(sim.D$clustering.assignment, paste(thisdir, \"clusters.txt\", sep=\"/\"), sep=\"\\t\")\n",
" write_table_with_index_header(t(sim.D$dat.methyl), paste(thisdir, \"omics1.txt\", sep=\"/\"))\n",
" write_table_with_index_header(t(sim.D$dat.expr), paste(thisdir, \"omics2.txt\", sep=\"/\"))\n",
" write_table_with_index_header(t(sim.D$dat.protein), paste(thisdir, \"omics3.txt\", sep=\"/\"))\n",
"\n",
" return(\"data saved in folder\")\n",
"}\n",
"\n",
"## Support function\n",
"write_table_with_index_header <- function(data, file, sep=\"\\t\") {\n",
" write.table(cbind(probe=row.names(data),data), file, sep = sep, \n",
" append = FALSE, quote = FALSE, row.names = FALSE, col.names = TRUE)\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[1] \"##########\"\n",
"[1] \"-> Distribution: heterogeneous, Nb clusters: 5\"\n",
"[1] \"-> Simulating data...\"\n",
"[1] 0.35 0.13 0.19 0.08 0.25\n",
"[1] 1\n",
"[1] TRUE\n",
"[1] \"../data/simulations_20210329212141/heterogeneous/5\"\n",
"[1] \"-> Done.\"\n",
"[1] \"##########\"\n",
"[1] \"-> Distribution: equal, Nb clusters: 5\"\n",
"[1] \"-> Simulating data...\"\n",
"[1] 0.25 0.20 0.20 0.20 0.15\n",
"[1] 1\n",
"[1] TRUE\n",
"[1] \"../data/simulations_20210329212141/equal/5\"\n",
"[1] \"-> Done.\"\n",
"[1] \"##########\"\n",
"[1] \"-> Distribution: heterogeneous, Nb clusters: 10\"\n",
"[1] \"-> Simulating data...\"\n",
" [1] 0.20 0.10 0.07 0.10 0.15 0.13 0.10 0.08 0.05 0.02\n",
"[1] 1\n",
"[1] TRUE\n",
"[1] \"../data/simulations_20210329212141/heterogeneous/10\"\n",
"[1] \"-> Done.\"\n",
"[1] \"##########\"\n",
"[1] \"-> Distribution: equal, Nb clusters: 10\"\n",
"[1] \"-> Simulating data...\"\n",
" [1] 0.15 0.10 0.10 0.10 0.10 0.10 0.05 0.10 0.10 0.10\n",
"[1] 1\n",
"[1] TRUE\n",
"[1] \"../data/simulations_20210329212141/equal/10\"\n",
"[1] \"-> Done.\"\n",
"[1] \"##########\"\n",
"[1] \"-> Distribution: heterogeneous, Nb clusters: 15\"\n",
"[1] \"-> Simulating data...\"\n",
" [1] 0.10 0.08 0.04 0.03 0.12 0.03 0.10 0.03 0.05 0.02 0.10 0.20 0.03 0.02 0.05\n",
"[1] 1\n",
"[1] TRUE\n",
"[1] \"../data/simulations_20210329212141/heterogeneous/15\"\n",
"[1] \"-> Done.\"\n",
"[1] \"##########\"\n",
"[1] \"-> Distribution: equal, Nb clusters: 15\"\n",
"[1] \"-> Simulating data...\"\n",
" [1] 0.07 0.07 0.07 0.06 0.07 0.07 0.07 0.06 0.07 0.06 0.07 0.06 0.07 0.06 0.07\n",
"[1] 1\n",
"[1] TRUE\n",
"[1] \"../data/simulations_20210329212141/equal/15\"\n",
"[1] \"-> Done.\"\n"
]
}
],
"source": [
"## Simulate data, factorize and compare the results\n",
"\n",
"list_clusters <- seq(5,15,5)\n",
"list_distrib <- c(\"heterogeneous\",\"equal\")\n",
"\n",
"# For a given number of clusters\n",
"for(num.clusters in list_clusters) {\n",
" # Data distribution among clusters will either be heterogeneous or equal \n",
" for (size in list_distrib) {\n",
" \n",
" print(\"##########\")\n",
" print(paste0(\"-> Distribution: \", size, \", Nb clusters: \", num.clusters))\n",
" \n",
" # Make simulated data\n",
" print(\"-> Simulating data...\")\n",
" simulated_data_generation(simul_folder, num.clusters, size, predefined=TRUE)\n",
" \n",
" print(\"-> Done.\")\n",
" }\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Warning message in createMOFAobject(omics):\n",
"“View names are not specified in the data, renaming them to: view_1, view_2, view_3\n",
"”\n",
"Creating MOFA object from list of matrices,\n",
" please make sure that samples are columns and features are rows...\n",
"\n",
"\n",
"Checking data options...\n",
"\n",
"Checking training options...\n",
"\n",
"Checking model options...\n",
"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[1] \"No output file provided, using a temporary file...\"\n",
"Generating warm start... \n",
"K=6:12\n"
]
}
],
"source": [
"out <- runfactorization(\"../data/simulations_20210329212141/equal/5\", paste0(\"omics\",1:3,\".txt\"), 5, sep=\"\\t\", filtering=\"none\")"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" [,1]\n",
"subject1 9\n",
"subject2 1\n",
"subject3 12\n",
"subject4 13\n",
"subject5 11\n",
"subject6 14\n",
"subject7 12\n",
"subject8 12\n",
"subject9 16\n",
"subject10 15\n",
"subject11 3\n",
"subject12 3\n",
"subject13 12\n",
"subject14 15\n",
"subject15 16\n",
"subject16 14\n",
"subject17 5\n",
"subject18 15\n",
"subject19 15\n",
"subject20 15\n",
"subject21 3\n",
"subject22 9\n",
"subject23 10\n",
"subject24 12\n",
"subject25 1\n",
"subject26 14\n",
"subject27 7\n",
"subject28 12\n",
"subject29 7\n",
"subject30 12\n",
"subject31 8\n",
"subject32 12\n",
"subject33 16\n",
"subject34 16\n",
"subject35 1\n",
"subject36 14\n",
"subject37 9\n",
"subject38 12\n",
"subject39 6\n",
"subject40 9\n",
"subject41 10\n",
"subject42 14\n",
"subject43 4\n",
"subject44 13\n",
"subject45 12\n",
"subject46 11\n",
"subject47 15\n",
"subject48 13\n",
"subject49 3\n",
"subject50 4\n",
"subject51 2\n",
"subject52 16\n",
"subject53 10\n",
"subject54 4\n",
"subject55 7\n",
"subject56 3\n",
"subject57 15\n",
"subject58 8\n",
"subject59 13\n",
"subject60 16\n",
"subject61 8\n",
"subject62 9\n",
"subject63 12\n",
"subject64 2\n",
"subject65 4\n",
"subject66 13\n",
"subject67 12\n",
"subject68 14\n",
"subject69 10\n",
"subject70 2\n",
"subject71 6\n",
"subject72 5\n",
"subject73 15\n",
"subject74 16\n",
"subject75 9\n",
"subject76 16\n",
"subject77 12\n",
"subject78 16\n",
"subject79 6\n",
"subject80 13\n",
"subject81 16\n",
"subject82 3\n",
"subject83 14\n",
"subject84 1\n",
"subject85 8\n",
"subject86 10\n",
"subject87 14\n",
"subject88 1\n",
"subject89 3\n",
"subject90 14\n",
"subject91 9\n",
"subject92 3\n",
"subject93 5\n",
"subject94 12\n",
"subject95 8\n",
"subject96 2\n",
"subject97 2\n",
"subject98 10\n",
"subject99 11\n",
"subject100 10\n"
]
}
],
"source": [
"print(out$icluster.clusters)"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Loading required package: MASS\n",
"\n",
"Loading required package: NMF\n",
"\n",
"Loading required package: pkgmaker\n",
"\n",
"Loading required package: registry\n",
"\n",
"Loading required package: rngtools\n",
"\n",
"Loading required package: cluster\n",
"\n",
"NMF - BioConductor layer [OK] | Shared memory capabilities [NO: bigmemory] | Cores 27/28\n",
"\n",
" To enable shared memory capabilities, try: install.extras('\n",
"NMF\n",
"')\n",
"\n",
"Loading required package: mclust\n",
"\n",
"Package 'mclust' version 5.4.6\n",
"Type 'citation(\"mclust\")' for citing this R package in publications.\n",
"\n",
"Loading required package: InterSIM\n",
"\n",
"Loading required package: tools\n",
"\n",
"Loading required package: ade4\n",
"\n",
"\n",
"Attaching package: ‘ade4’\n",
"\n",
"\n",
"The following object is masked from ‘package:BiocGenerics’:\n",
"\n",
" score\n",
"\n",
"\n",
"\n",
"Attaching package: ‘GPArotation’\n",
"\n",
"\n",
"The following object is masked from ‘package:NMF’:\n",
"\n",
" entropy\n",
"\n",
"\n",
"\n",
"Attaching package: ‘MOFAtools’\n",
"\n",
"\n",
"The following objects are masked from ‘package:NMF’:\n",
"\n",
" featureNames, featureNames<-, predict, sampleNames, sampleNames<-\n",
"\n",
"\n",
"The following objects are masked from ‘package:Biobase’:\n",
"\n",
" featureNames, featureNames<-, sampleNames, sampleNames<-\n",
"\n",
"\n",
"The following object is masked from ‘package:stats’:\n",
"\n",
" predict\n",
"\n",
"\n",
"Loading required package: JADE\n",
"\n",
"Loading required package: lattice\n",
"\n",
"Loading required package: caTools\n",
"\n",
"Loading required package: gdata\n",
"\n",
"gdata: read.xls support for 'XLS' (Excel 97-2004) files ENABLED.\n",
"\n",
"\n",
"\n",
"gdata: read.xls support for 'XLSX' (Excel 2007+) files ENABLED.\n",
"\n",
"\n",
"Attaching package: ‘gdata’\n",
"\n",
"\n",
"The following object is masked from ‘package:Biobase’:\n",
"\n",
" combine\n",
"\n",
"\n",
"The following object is masked from ‘package:BiocGenerics’:\n",
"\n",
" combine\n",
"\n",
"\n",
"The following object is masked from ‘package:stats’:\n",
"\n",
" nobs\n",
"\n",
"\n",
"The following object is masked from ‘package:utils’:\n",
"\n",
" object.size\n",
"\n",
"\n",
"The following object is masked from ‘package:base’:\n",
"\n",
" startsWith\n",
"\n",
"\n",
"Loading required package: gtools\n",
"\n",
"\n",
"Attaching package: ‘gtools’\n",
"\n",
"\n",
"The following object is masked from ‘package:InterSIM’:\n",
"\n",
" logit\n",
"\n",
"\n",
"Loading required package: gplots\n",
"\n",
"\n",
"Attaching package: ‘gplots’\n",
"\n",
"\n",
"The following object is masked from ‘package:stats’:\n",
"\n",
" lowess\n",
"\n",
"\n"
]
}
],
"source": [
"##### runfactoization runs all the considered multi-omics factorization\n",
"### the required inputs are:\n",
"### \"folder\" corresponding to the path to the folder where the input files are contained, in the idea that all omics matrices are organized inside a unique folder\n",
"### \"file.names\" corresponding to a vector containing the names of all the omics files\n",
"### \"num.factors\" containing the number of factors in which we desire to decompose the matrices\n",
"### \"sep=\" \"\" corresponding to the separator used in the omics files required to properly read them\n",
"### \"single.cell\" indicating if the data are single cell data. In this case the filtering of the data will be more intense in respect to other data types\n",
"### \"filtering\"\n",
"\n",
"### the input files need to be log2 transformed before running the analysis\n",
"\n",
"\n",
"library(\"RGCCA\")\n",
"library(\"r.jive\")\n",
"library(\"IntNMF\")\n",
"library(\"omicade4\")\n",
"library(\"MSFA\")\n",
"library(\"GPArotation\")\n",
"library(\"MOFAtools\")\n",
"library(\"tensorBSS\")\n",
"source(\"tICA.R\")\n",
"library(\"iCluster\")\n",
"\n",
"testrunfactorization <- function(folder,file.names,num.factors,sep=\" \",filtering=\"none\"){\n",
" factorizations<-list()\n",
" t<-1\n",
" method<-numeric(0)\n",
" \n",
" num.factors<-as.numeric(num.factors)\n",
"\n",
" \n",
" ##creating list of omics\n",
" omics <- list()\n",
" for(i in 1:length(file.names)){\n",
" omics[[i]]<-as.matrix(read.table(paste(folder,file.names[i],sep=\"/\"),sep=sep,row.names=1,header=T))\n",
" }\n",
" #print(omics)\n",
" \n",
" ####\n",
" #omics<-lapply(omics, function(x) t(x))\n",
" ######\n",
" \n",
" ##restricting to common samples and filtering\n",
" samples<-colnames(omics[[1]])\n",
" for(j in 1:length(omics)){\n",
" samples<-intersect(samples,colnames(omics[[j]]))\n",
" }\n",
" for(j in 1:length(omics)){\n",
" omics[[j]]<-omics[[j]][,samples]\n",
" if(filtering!=\"none\"){\n",
" x<-apply( omics[[j]],1,sd)\n",
" x<-as.matrix(sort(x, decreasing = T))\n",
" w<-which(x>0)\n",
" if(filtering==\"stringent\"){\n",
" selected<-rownames(x)[1:min(w[length(w)],5000)]\n",
" }else{\n",
" selected<-rownames(x)[1:min(w[length(w)],6000)]\n",
" }\n",
" m<-match(rownames(omics[[j]]),selected)\n",
" w<-which(!is.na(m))\n",
" omics[[j]]<-omics[[j]][w,]\n",
" }else{\n",
" omics[[j]]<-omics[[j]][which(apply(omics[[j]],2,sd)>0),]\n",
" }\n",
" }\n",
" print(length(omics)) \n",
" \n",
" \n",
" ##RGCCA \n",
" factorizations_RGCCA<-rgcca(lapply(omics, function(x) t(x)), ncomp = rep(num.factors, length(omics)), scheme = \"centroid\", scale = TRUE, init = \"svd\",bias = TRUE, tol = 1e-08, verbose = F)\n",
" factors_rgcca<-as.matrix(factorizations_RGCCA$Y[[1]])\n",
" metagenes_rgcca <- list()\n",
" for(j in 1:length(omics)){\n",
" metagenes_rgcca[[j]]<-as.matrix(factorizations_RGCCA$a[[j]])\n",
" rownames(metagenes_rgcca[[j]])<-rownames(omics[[j]])\n",
" colnames(metagenes_rgcca[[j]])<-1:num.factors\n",
" }\n",
" print(factors_rgcca) \n",
" factorizations[[t]]<-list(factors_rgcca,metagenes_rgcca)\n",
" t<-t+1\n",
" method<-c(method,\"RGCCA\")\n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" out<-list(factorizations=factorizations,method=method)\n",
" \n",
" return(out)\n",
"}\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[1] 3\n",
" comp1 comp2 comp3 comp4 comp5\n",
"subject1 -0.66795710 -0.1975975691 -0.300867807 -0.27752304 0.046597119\n",
"subject2 0.34576508 -0.2629359330 0.241120840 -0.28930964 -0.084342734\n",
"subject3 -0.18025509 -0.0176580168 0.248585176 0.28288886 -0.563893934\n",
"subject4 0.36050703 -0.1890522412 -0.408620222 0.17398881 -0.043598118\n",
"subject5 0.35911618 -0.3781877286 0.258566999 -0.36205334 0.226873122\n",
"subject6 0.28325320 -0.1622556746 0.181241457 -0.21227011 -0.559915019\n",
"subject7 -0.11612513 0.0788346274 0.220124930 0.33526312 -0.408510876\n",
"subject8 -0.07780757 -0.0141900772 0.335851483 0.28675003 -0.508347353\n",
"subject9 0.23910572 -0.1559110417 -0.458080182 0.26396763 -0.191666676\n",
"subject10 0.29560944 -0.1561401151 0.260168096 -0.14995656 -0.479010526\n",
"subject11 -0.48458731 -0.0735627161 -0.102832592 -0.12385138 -0.621762842\n",
"subject12 -0.40942839 -0.1172649178 -0.123315575 -0.13509267 -0.508532015\n",
"subject13 -0.19549696 -0.0472492050 0.451490816 0.50806521 -0.123621935\n",
"subject14 0.39955927 -0.2851241355 0.271590149 -0.31162352 0.072921505\n",
"subject15 0.32758984 -0.2064551003 -0.653680908 0.34347063 0.560935168\n",
"subject16 0.30672961 -0.1742978200 0.213687656 -0.20118681 -0.315973999\n",
"subject17 -0.34042109 0.0094594151 0.498483605 0.42013004 0.375227744\n",
"subject18 0.40118542 -0.2734121639 0.251444907 -0.24741560 -0.035026155\n",
"subject19 0.37087343 -0.2281502347 0.227306543 -0.13034463 -0.294658628\n",
"subject20 0.33360340 -0.2361817170 0.369069661 -0.26769134 0.022237249\n",
"subject21 -0.52471917 -0.1427221966 -0.160799669 -0.21163478 -0.034265692\n",
"subject22 -0.69679088 -0.1816307996 -0.190834122 -0.28495996 0.012379644\n",
"subject23 0.12198428 0.9913928035 -0.044774322 -0.13749865 0.118102528\n",
"subject24 -0.15083689 -0.0048478563 0.355681978 0.39781971 -0.290817913\n",
"subject25 0.37459760 -0.2149748122 0.333619860 -0.32522255 0.050167823\n",
"subject26 0.40536926 -0.3524025172 0.341182290 -0.31587600 0.569370103\n",
"subject27 0.11113972 1.2053399506 -0.164090254 -0.19666250 0.737646931\n",
"subject28 -0.26649175 -0.0039560291 0.373027247 0.46078534 -0.088915510\n",
"subject29 0.13245557 0.9972172785 -0.180399738 -0.18447479 0.036228901\n",
"subject30 0.04381088 -0.0209174788 0.230704944 0.27547222 -0.819244333\n",
"subject31 -0.42005698 -0.1287161305 -0.155971367 -0.15704278 -0.372743880\n",
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"subject34 0.36639250 -0.2101325265 -0.489283192 0.30912583 0.088598721\n",
"subject35 0.40052578 -0.2974581772 0.255015971 -0.45895052 0.290803574\n",
"subject36 0.32790701 -0.1703322633 0.240954041 -0.07700836 -0.524146348\n",
"subject37 -0.61693839 -0.0942186029 -0.177411533 -0.18328804 -0.247984667\n",
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"subject45 -0.32035124 0.0046356596 0.477170403 0.47590852 0.234729477\n",
"subject46 0.41149062 -0.4124026217 0.275973912 -0.41554365 0.502762300\n",
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"subject48 0.32737821 -0.0920039617 -0.230312555 0.17569330 -0.632712306\n",
"subject49 -0.62112071 -0.0938839090 -0.075833583 -0.18950765 -0.262536893\n",
"subject50 0.39773655 -0.2355097842 -0.639536514 0.36126441 0.572461179\n",
"subject51 0.12040917 0.7432439531 -0.018828592 -0.12949232 -0.079918547\n",
"subject52 0.29100778 -0.2047539625 -0.592615932 0.33531966 0.255890133\n",
"subject53 0.14404575 0.8066309601 -0.028532983 -0.13038362 -0.167896287\n",
"subject54 0.43806126 -0.2719940971 -0.666439000 0.27156816 0.468453204\n",
"subject55 0.16338689 0.7534885853 -0.046822843 -0.14356642 -0.258904701\n",
"subject56 -0.54330671 -0.1888214867 -0.182831910 -0.17865797 -0.066583743\n",
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"subject64 0.04786201 1.1937650392 -0.043303979 -0.19370464 0.250076084\n",
"subject65 0.30532165 -0.1704268507 -0.358892836 0.27005600 -0.249180710\n",
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"subject67 -0.22037895 0.0177286001 0.417926483 0.36863521 0.071323646\n",
"subject68 0.39512069 -0.2366673774 0.216649037 -0.29284511 0.008576342\n",
"subject69 0.12827505 0.8567863582 -0.013746448 -0.11409165 0.081832362\n",
"subject70 0.15024314 0.7453052610 0.005392764 -0.06270430 -0.173802527\n",
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"subject77 -0.27789916 -0.0048473473 0.345856825 0.39243126 -0.234121870\n",
"subject78 0.38427805 -0.2223340178 -0.656837020 0.25087347 0.354163259\n",
"subject79 -0.39981804 -0.0196969046 0.584051104 0.53694953 1.134921916\n",
"subject80 0.27705694 -0.1080970749 -0.386685037 0.24076333 -0.241880315\n",
"subject81 0.31335961 -0.2561279021 -0.682036273 0.35385352 0.453455172\n",
"subject82 -0.43985970 -0.1495504622 -0.095994877 -0.20146180 -0.264895053\n",
"subject83 0.44732835 -0.2583292762 0.202537607 -0.26059137 -0.098211699\n",
"subject84 0.39698952 -0.3499256864 0.325258636 -0.40885985 0.289307634\n",
"subject85 -0.75136801 -0.1232615110 -0.231802292 -0.26259688 -0.074211961\n",
"subject86 0.12936870 0.8954234066 -0.093754585 -0.13571839 0.105100811\n",
"subject87 0.35678871 -0.2465073482 0.249338939 -0.29102546 -0.027625860\n",
"subject88 0.45373993 -0.2961290693 0.331510086 -0.41422877 0.355016508\n",
"subject89 -0.55235599 -0.0882347574 -0.133777889 -0.24414535 -0.415535261\n",
"subject90 0.39405941 -0.3377337316 0.432651264 -0.28667185 0.678702952\n",
"subject91 -0.91228550 -0.1851716392 -0.320023754 -0.44279513 0.559760637\n",
"subject92 -0.59550423 -0.1053352454 -0.159220342 -0.25166634 -0.258521010\n",
"subject93 -0.40457224 0.0165940814 0.477644984 0.57539863 0.640072913\n",
"subject94 -0.18494150 0.0596899207 0.354371616 0.41316953 -0.272703209\n",
"subject95 -0.71579607 -0.1496541724 -0.296889784 -0.28595335 0.138126582\n",
"subject96 0.21892346 0.5690727182 -0.064691902 -0.10351738 -0.497977461\n",
"subject97 0.09944305 0.8931895607 -0.037956288 -0.10140124 0.008295167\n",
"subject98 0.14312408 0.8875227295 -0.014458296 -0.12274998 0.103570903\n",
"subject99 0.47719454 -0.3540176751 0.237126518 -0.39867246 0.707972555\n",
"subject100 0.16961816 1.0156947761 -0.069745172 -0.14946591 0.462672836\n",
" comp6 comp7 comp8 comp9 comp10\n",
"subject1 -0.120527756 0.089269771 -0.097534334 -0.1702471985 -0.193372267\n",
"subject2 0.004226896 0.213313895 0.056469727 -0.0621672992 -0.082684709\n",
"subject3 -0.009572400 -0.050562396 -0.177692353 0.0132125699 -0.030125332\n",
"subject4 -0.233439107 -0.004897228 -0.042481797 -0.0431395365 0.042920360\n",
"subject5 -0.101725554 0.152754911 -0.064126811 -0.1048910435 -0.026664461\n",
"subject6 -0.121315872 0.065821450 -0.133365238 -0.0471982522 0.047490306\n",
"subject7 -0.074883798 0.073023859 -0.251574325 0.0015331721 -0.034307365\n",
"subject8 0.031263663 0.232016560 0.064997932 0.1407648072 0.020675983\n",
"subject9 -0.002449634 -0.048508331 -0.137655422 0.0621313298 -0.199873772\n",
"subject10 -0.007289828 0.050208836 0.092218099 -0.0833417404 -0.003616362\n",
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"subject12 0.063767411 0.115550550 0.036992505 -0.0671939782 -0.047665225\n",
"subject13 0.186032236 -0.107735814 0.184641855 0.0231450173 -0.120664078\n",
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"subject99 -0.072723416 -0.007263865 -0.302585519 0.0525258812 -0.070646477\n",
"subject100 -0.054739884 0.175063171 0.017107780 -0.0267241288 0.061461970\n"
]
}
],
"source": [
"out2 <- testrunfactorization(\"../data/simulations_20210329212141/equal/5\", paste0(\"omics\",1:3,\".txt\"), 10, sep=\"\\t\", filtering=\"none\")"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[1]]\n",
"[[1]][[1]]\n",
" comp1 comp2 comp3 comp4 comp5\n",
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"subject87 -0.097703326 -0.015676309 0.156453234 -0.0203886958 -0.177227533\n",
"subject88 0.181105495 0.110829521 0.244295694 0.0699982015 0.195790279\n",
"subject89 0.088550607 0.074659343 0.072658776 -0.0131414793 0.142865901\n",
"subject90 0.111185160 -0.374737809 0.372786719 0.2175164061 0.156073099\n",
"subject91 -0.063241156 -0.035320425 0.147811183 -0.0950638683 -0.074931190\n",
"subject92 0.032442412 -0.101095705 0.056549284 0.0915908694 0.251762188\n",
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"subject95 -0.205438321 -0.075315520 -0.258885805 0.0732863894 -0.147775141\n",
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"subject99 -0.072723416 -0.007263865 -0.302585519 0.0525258812 -0.070646477\n",
"subject100 -0.054739884 0.175063171 0.017107780 -0.0267241288 0.061461970\n",
"\n",
"[[1]][[2]]\n",
"[[1]][[2]][[1]]\n",
" 1 2 3 4\n",
"cg20139214 -1.998182e-01 -0.0214569130 -0.1050743144 -0.1340864385\n",
"cg10999429 2.436173e-02 0.0117950961 -0.0116255213 -0.0008131201\n",
"cg23640701 1.305839e-02 -0.0278297573 0.0030397937 -0.0147799394\n",
"cg02956093 -3.315323e-02 0.0281695761 -0.0019699719 -0.0037421399\n",
"cg08711674 -2.217898e-01 -0.0411499187 0.0860261728 0.0705078954\n",
"cg09842540 -1.805685e-01 -0.0204251895 -0.0840965191 -0.1112591752\n",
"cg11739626 1.618832e-01 -0.1127695984 -0.0569626305 -0.0329293044\n",
"cg19073614 -3.848398e-02 -0.0827814612 0.0192287044 -0.2494513225\n",
"cg01894895 1.367579e-01 -0.0631459179 0.0547535150 -0.1318915388\n",
"cg01086868 1.629820e-02 0.2096644512 -0.0367409556 -0.0490403101\n",
"cg04755662 1.265591e-01 -0.0849238280 0.0814143068 -0.1332677954\n",
"cg05019001 8.596026e-04 -0.0276692660 -0.0133722345 0.0112721664\n",
"cg05786601 -1.786337e-01 -0.0333525566 -0.1026860373 -0.1273420694\n",
"cg07780118 3.064776e-02 0.1897745726 -0.0208630198 -0.0336585121\n",
"cg12589433 5.009120e-02 0.2113016371 -0.0403342162 -0.0775475921\n",
"cg14807303 -5.689657e-02 0.0711259928 -0.2495637414 -0.0294008212\n",
"cg16679837 -8.976965e-02 0.0523592622 0.1593712385 -0.1265128601\n",
"cg20878850 6.184810e-02 -0.0646328090 -0.1662740502 0.1149602411\n",
"cg21966410 -8.458515e-02 -0.0893072781 -0.2358558718 0.0132879277\n",
"cg27271368 1.312689e-01 -0.1612754559 0.0658534658 0.1454312102\n",
"cg04283377 1.572627e-02 -0.0027684147 -0.0165752909 0.0522837506\n",
"cg10455133 -1.890420e-01 -0.0359625127 0.0386907512 0.0865264737\n",
"cg01245656 -1.840544e-01 0.1037613386 0.0629446809 0.0486359927\n",
"cg14785449 -1.960222e-01 -0.0210067044 -0.0993539149 -0.1230358187\n",
"cg01800843 1.842359e-01 0.0269339931 -0.0530040309 -0.0746342593\n",
"cg03165700 -1.784032e-01 -0.0168573914 -0.0909093841 -0.1118593550\n",
"cg18457775 6.739214e-02 -0.0655234113 -0.1676469258 0.1307786785\n",
"cg22477592 -4.740641e-02 -0.0737514931 0.0113900755 -0.2245804122\n",
"cg24027342 8.882959e-02 -0.0900769343 -0.1651967300 0.0995918948\n",
"cg00925229 3.610238e-02 0.2464215712 -0.0211853152 -0.0526340880\n",
"cg07588779 -9.022292e-05 -0.0280726756 0.0087570604 0.0001292806\n",
"cg13620770 -9.065881e-03 -0.0035174072 0.0342894233 -0.0054209452\n",
"cg07679836 -6.766326e-02 -0.0396612814 0.1703493475 0.2160478691\n",
"cg14666892 -1.471954e-02 -0.0033786208 0.0496468774 -0.0162737329\n",
"cg22753768 -1.041897e-01 -0.1099092249 0.1672774178 -0.0932874003\n",
"cg24747396 1.866957e-01 -0.1224264471 -0.0580966960 -0.0424592983\n",
"cg14833160 -5.201762e-02 -0.0348700686 0.0030904223 -0.0001325541\n",
"cg15951107 2.984169e-02 0.2315055988 -0.0171939602 -0.0424804457\n",
"cg01803238 1.582203e-01 -0.1116372246 -0.0362645185 -0.0303896218\n",
"cg03813215 -3.252602e-02 0.0076383403 0.0183964210 -0.0163683599\n",
"cg08223235 -1.355856e-01 -0.1213929267 -0.0800035497 0.1784682354\n",
"cg08554462 -2.079760e-02 0.0075560047 0.0201175658 0.0068589937\n",
"cg09752703 9.048428e-02 0.1193918498 -0.1753183809 0.0810995300\n",
"cg11255230 -1.374272e-01 -0.0892909459 -0.0439696552 0.1671354990\n",
"cg11330108 1.531043e-02 -0.1307471024 -0.1452693557 -0.1258570602\n",
"cg12459502 1.150659e-01 -0.0723245040 0.0287363935 -0.1285489334\n",
"cg14455307 3.992597e-02 -0.0781812582 0.2049237630 0.0372688142\n",
"cg17602451 -3.471746e-02 -0.0722287966 0.0110837104 -0.2110211348\n",
"cg21602520 8.369835e-03 -0.0581420774 -0.0161931713 -0.0038580935\n",
"cg23756272 2.553128e-02 -0.0548722143 -0.0800428908 -0.0257682179\n",
"cg25059899 6.145889e-02 -0.0440103563 -0.1473016768 0.0366329284\n",
"cg00782854 -1.609597e-02 0.0051941460 0.0007177902 0.0168716345\n",
"cg16137862 -1.017091e-01 -0.0702187361 -0.2151085281 0.0125138733\n",
"cg27608154 4.485358e-02 0.1301531066 -0.0166941485 -0.0428101556\n",
"cg16225441 1.591144e-02 -0.0262436927 -0.0059459751 0.0313368250\n",
"cg26709863 -3.623720e-02 -0.0489914094 0.1628769103 0.1942529352\n",
"cg05566965 -2.100117e-02 -0.0186868401 0.0634978308 0.0027788870\n",
"cg03148461 -2.045014e-01 -0.0190397393 -0.0912175189 -0.1249560221\n",
"cg10141022 -6.865888e-02 -0.0717018423 -0.2151127357 0.0287095947\n",
"cg11414046 -2.198245e-02 -0.0028140721 0.0042863282 0.0356729568\n",
"cg14094063 1.237665e-01 -0.0709845609 0.1107100278 -0.1542230717\n",
"cg17095753 -2.596851e-02 -0.0298739810 0.0199483322 0.0665652234\n",
"cg21043558 -4.937191e-02 -0.0901378852 0.0201336245 -0.2447650058\n",
"cg23066879 -7.023439e-02 -0.0347972166 0.1838574760 0.2077950846\n",
"cg12836863 2.299353e-02 -0.0109319147 -0.0262541705 0.0097736080\n",
"cg27253386 -3.717562e-02 0.1150073223 0.1411597732 0.1479508511\n",
"cg22906389 7.021167e-02 -0.0652406967 -0.1718132131 0.1271219168\n",
"cg04677163 9.166773e-04 -0.0202540212 0.0387159096 0.0027456764\n",
"cg07964538 7.213909e-02 -0.0642885687 -0.1714185641 0.1310378257\n",
"cg17469978 -2.533875e-02 -0.0249445671 -0.0028036921 0.0452127574\n",
"cg18329349 1.363163e-01 -0.0860267268 0.1277136248 -0.1794072613\n",
"cg22126032 -3.737478e-02 0.1401891187 0.1415643068 0.1425821720\n",
"cg27242945 -3.692249e-03 0.0005167594 0.0062475594 0.0098697454\n",
"cg13849825 7.635998e-02 0.1617125530 -0.0903083547 -0.0303523290\n",
"cg23935746 3.658103e-02 0.2113897330 -0.0167199391 -0.0523549962\n",
"cg00858899 1.359960e-01 -0.0813369222 0.1177217202 -0.1641196252\n",
"cg00953256 5.426032e-02 0.1159419230 0.0176062741 0.0169889218\n",
"cg02723533 -4.761620e-04 -0.1083395596 -0.0358727059 -0.0186385110\n",
"cg04717045 -7.906173e-02 -0.1417306408 0.1509377367 -0.0466492452\n",
"cg05164185 1.473396e-02 -0.1157737652 -0.1217653545 -0.1048328146\n",
"cg05200606 1.020154e-01 0.1379524317 -0.1982444864 0.0848712982\n",
"cg06539449 3.649220e-02 0.0015292001 0.0042385830 0.0137989482\n",
"cg08170622 1.627275e-01 -0.1064622597 -0.0398413760 -0.0388536139\n",
"cg09637363 5.532293e-03 0.0095832033 0.0419885944 0.0031970005\n",
"cg10539418 -2.163660e-01 -0.0542200827 0.0818440658 0.0804101886\n",
"cg11802013 1.506523e-01 -0.1159202925 0.0003023888 0.0315859408\n",
"cg12266049 3.348925e-02 -0.0094300381 0.0301865236 -0.0030378946\n",
"cg13608094 -7.156075e-02 0.0921365265 -0.0577862535 -0.0888700686\n",
"cg16794682 1.415216e-01 -0.0350973892 0.1075894878 -0.1343804251\n",
"cg19047670 3.842232e-02 -0.0117361139 0.0645675212 0.0428203709\n",
"cg25060573 8.181338e-02 -0.0692594126 -0.2010767752 0.1514946483\n",
"cg26605086 -1.661809e-01 0.0873054613 0.0564355645 0.0421194588\n",
"cg12187567 -1.837935e-01 -0.0172248186 -0.0959742410 -0.1201402068\n",
"cg16328273 3.293909e-02 0.2292614196 -0.0214804271 -0.0461673800\n",
"cg11255163 6.269549e-04 0.0459358658 0.0260376404 0.0190380024\n",
"cg11667754 3.595623e-02 0.2250716540 -0.0090028243 -0.0501089110\n",
"cg17655614 -2.033407e-01 -0.0217101645 -0.0940529132 -0.1367491679\n",
"cg20716119 -7.206442e-04 0.0185698571 0.0310857854 -0.0042302835\n",
"cg22832044 2.208774e-02 0.2381400411 -0.0079094293 -0.0389560226\n",
"cg23989635 3.642093e-02 0.2453521061 -0.0158799620 -0.0497458958\n",
" 5 6 7 8 9\n",
"cg20139214 1.191702e-02 -0.033407743 -0.003471416 0.0446939060 1.891871e-02\n",
"cg10999429 1.335283e-01 -0.240681344 -0.101276210 0.2021944023 -2.131737e-03\n",
"cg23640701 -1.194878e-02 -0.217273447 -0.226365260 0.0751636367 -7.110590e-02\n",
"cg02956093 1.164428e-01 0.022486468 0.035403918 0.3189389677 2.869513e-01\n",
"cg08711674 -2.645669e-02 0.034832812 -0.016647198 0.0238948367 3.553509e-02\n",
"cg09842540 4.951281e-02 -0.031115396 -0.000727749 0.0623103909 -3.264866e-02\n",
"cg11739626 1.875304e-02 -0.075092294 0.020346789 0.0040866819 -1.245343e-01\n",
"cg19073614 6.182635e-02 0.020040327 -0.032070394 -0.0169291668 1.605448e-02\n",
"cg01894895 -8.616114e-02 -0.189528662 -0.113759898 -0.0254973048 4.950709e-02\n",
"cg01086868 -3.354395e-02 -0.063951860 0.097514088 -0.1243207940 -6.075905e-02\n",
"cg04755662 1.981694e-02 -0.123232250 0.042776517 -0.1605932084 -6.304571e-02\n",
"cg05019001 2.681751e-03 -0.056481365 0.048232845 -0.4779714517 2.548833e-01\n",
"cg05786601 -4.690777e-02 0.013944403 0.129799810 -0.1123544069 -7.634561e-02\n",
"cg07780118 1.453806e-02 -0.065142820 -0.080440692 -0.1923455430 2.419407e-01\n",
"cg12589433 1.832834e-02 -0.090876259 -0.105970756 -0.1279930418 1.206163e-01\n",
"cg14807303 7.783294e-03 -0.072911108 -0.044233078 -0.1321493318 -1.265950e-01\n",
"cg16679837 -9.362176e-03 -0.059888433 0.141617524 -0.1913580874 1.455272e-02\n",
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"cg13849825 -1.018683e-01 -0.045797493 0.043910461 0.0470949884 8.140363e-03\n",
"cg23935746 8.726273e-02 0.020185726 0.116721667 -0.0041578738 -5.342620e-02\n",
"cg00858899 7.917459e-02 0.123523252 -0.015758887 0.0312246077 -5.538007e-02\n",
"cg00953256 -3.174401e-02 -0.089083841 0.166040427 0.0056242601 4.049423e-02\n",
"cg02723533 -3.900157e-02 -0.194696803 0.009285833 0.1252619083 2.526024e-01\n",
"cg04717045 -5.831463e-02 -0.125768245 0.093426931 -0.0460140153 1.094484e-01\n",
"cg05164185 9.970093e-02 -0.043228178 0.063133001 0.0005539495 1.145531e-01\n",
"cg05200606 3.607500e-02 -0.046433440 -0.068964280 0.0420371065 6.363339e-03\n",
"cg06539449 -1.203098e-02 -0.150797965 0.233326383 0.1957503807 3.136770e-02\n",
"cg08170622 1.254542e-01 0.068488151 -0.027452638 0.0147941586 1.087937e-01\n",
"cg09637363 4.102344e-02 -0.092241403 0.183867708 0.0475945689 -5.114048e-02\n",
"cg10539418 3.166040e-02 -0.010957071 0.038981608 -0.0169973274 5.157786e-02\n",
"cg11802013 3.766704e-02 -0.113612709 0.025850766 0.1794698158 -1.338142e-01\n",
"cg12266049 -4.328629e-02 -0.214993113 0.122240545 0.0204164730 2.194064e-01\n",
"cg13608094 -7.609505e-02 -0.076627653 0.203093998 0.0825533198 1.942374e-02\n",
"cg16794682 -3.578745e-03 -0.125061307 0.106922532 0.0204016497 2.753403e-02\n",
"cg19047670 -3.897142e-05 -0.146023428 0.093908714 0.0476894817 3.633930e-02\n",
"cg25060573 6.358982e-02 0.057702707 -0.020977440 0.0086796431 7.540517e-05\n",
"cg26605086 9.550536e-02 -0.050433543 0.106733080 -0.0173557147 -7.085433e-02\n",
"cg12187567 3.158224e-02 -0.040912703 -0.008532636 0.0619718337 2.588840e-02\n",
"cg16328273 9.340860e-02 0.015822188 -0.035917440 0.0155915178 -6.649149e-03\n",
"cg11255163 1.833700e-01 -0.011812378 -0.013894003 0.0304328164 -1.110034e-01\n",
"cg11667754 8.723824e-02 0.041686094 -0.077975796 -0.0946710815 -3.604659e-02\n",
"cg17655614 2.580228e-02 0.037931679 -0.030052667 -0.0035120434 -5.851575e-02\n",
"cg20716119 1.963394e-01 0.036165107 -0.152992714 0.0307312469 -5.589369e-02\n",
"cg22832044 1.025453e-01 -0.017578024 0.082553566 0.0015110562 2.967508e-03\n",
"cg23989635 7.077825e-02 -0.016170697 -0.012306511 -0.0267608514 -8.931635e-03\n",
" 10\n",
"cg20139214 1.002827e-02\n",
"cg10999429 1.207567e-01\n",
"cg23640701 4.811143e-02\n",
"cg02956093 -1.457258e-02\n",
"cg08711674 7.699848e-02\n",
"cg09842540 -9.750224e-03\n",
"cg11739626 1.198649e-01\n",
"cg19073614 -9.956525e-03\n",
"cg01894895 -5.104505e-02\n",
"cg01086868 -2.342288e-02\n",
"cg04755662 2.595450e-02\n",
"cg05019001 1.093703e-01\n",
"cg05786601 8.672699e-02\n",
"cg07780118 -4.531470e-02\n",
"cg12589433 -7.313747e-02\n",
"cg14807303 1.381747e-01\n",
"cg16679837 3.905897e-02\n",
"cg20878850 -5.482074e-02\n",
"cg21966410 2.768413e-02\n",
"cg27271368 2.927637e-02\n",
"cg04283377 1.113183e-01\n",
"cg10455133 4.371044e-02\n",
"cg01245656 -4.635368e-02\n",
"cg14785449 8.597418e-04\n",
"cg01800843 4.243511e-02\n",
"cg03165700 8.178434e-05\n",
"cg18457775 -2.869589e-02\n",
"cg22477592 -9.244359e-03\n",
"cg24027342 -1.259806e-02\n",
"cg00925229 -5.525808e-02\n",
"cg07588779 2.060592e-02\n",
"cg13620770 -1.347061e-01\n",
"cg07679836 -1.835603e-02\n",
"cg14666892 -2.840567e-01\n",
"cg22753768 2.840300e-02\n",
"cg24747396 -9.927170e-03\n",
"cg14833160 -2.541554e-01\n",
"cg15951107 -5.673391e-02\n",
"cg01803238 3.996537e-02\n",
"cg03813215 -1.303554e-01\n",
"cg08223235 3.647351e-02\n",
"cg08554462 -1.375980e-02\n",
"cg09752703 -3.113491e-02\n",
"cg11255230 -9.855680e-02\n",
"cg11330108 5.368550e-02\n",
"cg12459502 -7.276521e-02\n",
"cg14455307 -1.284859e-02\n",
"cg17602451 -1.132514e-01\n",
"cg21602520 -2.076095e-01\n",
"cg23756272 8.120470e-02\n",
"cg25059899 -1.735700e-02\n",
"cg00782854 -1.107485e-01\n",
"cg16137862 -2.936238e-02\n",
"cg27608154 -9.386994e-02\n",
"cg16225441 -3.754163e-02\n",
"cg26709863 4.522898e-02\n",
"cg05566965 -3.555575e-02\n",
"cg03148461 -4.347388e-02\n",
"cg10141022 -6.485247e-02\n",
"cg11414046 -2.199963e-02\n",
"cg14094063 4.866011e-02\n",
"cg17095753 4.363418e-02\n",
"cg21043558 -1.034292e-02\n",
"cg23066879 -4.168903e-03\n",
"cg12836863 -2.954105e-01\n",
"cg27253386 -1.659819e-02\n",
"cg22906389 2.879171e-02\n",
"cg04677163 -3.142131e-02\n",
"cg07964538 3.533510e-03\n",
"cg17469978 -2.100395e-01\n",
"cg18329349 -3.303018e-02\n",
"cg22126032 9.173847e-03\n",
"cg27242945 1.966446e-01\n",
"cg13849825 -8.569561e-03\n",
"cg23935746 6.327782e-02\n",
"cg00858899 -2.712912e-02\n",
"cg00953256 -1.584662e-01\n",
"cg02723533 -1.505044e-01\n",
"cg04717045 -1.056002e-01\n",
"cg05164185 2.868877e-02\n",
"cg05200606 -3.557128e-02\n",
"cg06539449 8.024698e-02\n",
"cg08170622 4.273189e-02\n",
"cg09637363 3.085258e-01\n",
"cg10539418 4.648956e-02\n",
"cg11802013 -1.445410e-01\n",
"cg12266049 2.288073e-02\n",
"cg13608094 4.867725e-02\n",
"cg16794682 7.356945e-02\n",
"cg19047670 2.350505e-01\n",
"cg25060573 3.123252e-03\n",
"cg26605086 -6.529743e-02\n",
"cg12187567 2.038545e-02\n",
"cg16328273 -5.917483e-02\n",
"cg11255163 2.115901e-01\n",
"cg11667754 8.885887e-02\n",
"cg17655614 7.256193e-02\n",
"cg20716119 2.657788e-01\n",
"cg22832044 -5.546603e-02\n",
"cg23989635 8.374022e-02\n",
"\n",
"[[1]][[2]][[2]]\n",
" 1 2 3 4 5\n",
"ACACA -1.922805e-01 0.0142860854 -0.0681175148 -1.356159e-01 0.0079582934\n",
"ACVRL1 8.993108e-04 0.0390918095 0.0011819377 -7.204728e-04 0.2684468882\n",
"AKT1 -3.876608e-02 0.0172230435 0.0347359172 1.380618e-02 -0.0786571823\n",
"AKT1S1 -3.419939e-02 0.2215019363 0.0239869858 1.800339e-03 -0.0467832356\n",
"ANXA1 9.770849e-02 0.0591090071 0.0454229166 -1.363267e-01 0.0089829165\n",
"AR -1.806369e-02 -0.0200951835 0.0135228620 4.279454e-02 -0.0564137487\n",
"ARAF -1.913711e-01 0.0400354340 0.0794077339 4.189909e-02 0.0958157841\n",
"ASNS -1.691223e-01 -0.1224522167 0.0745847761 4.208192e-02 -0.0763015853\n",
"ATM 5.943876e-02 -0.0275742410 -0.1562454782 -1.553762e-01 -0.0954280664\n",
"BAD 4.263850e-02 -0.2236227302 -0.0042706736 -6.555145e-03 -0.0545151070\n",
"BAK1 -6.624015e-02 0.0232505460 0.1602588101 1.550227e-01 -0.0564431602\n",
"BAP1 -4.336555e-02 0.2148854501 0.0249733551 -6.004445e-03 -0.0332800617\n",
"BAX 3.553488e-02 -0.2275709958 -0.0010978081 1.160798e-02 0.0454711543\n",
"BCL2 9.446225e-05 0.0062387018 -0.0164626860 3.035738e-02 0.0032833886\n",
"BCL2L1 -7.633627e-02 0.0934935093 -0.2143311356 -4.946933e-03 -0.0314505973\n",
"BCL2L11 1.383360e-02 -0.2272458053 -0.0027417299 4.325218e-02 -0.1518272899\n",
"BECN1 -7.329712e-02 0.0232428081 0.1596873776 1.855094e-01 0.0066192709\n",
"BID -2.090075e-02 0.0099671683 0.0305736661 -3.668786e-02 -0.0344355285\n",
"BRAF -3.817766e-02 0.1954544848 0.0224735658 -1.734189e-02 -0.0063251555\n",
"BRCA2 -1.678795e-02 -0.1449090055 0.1356671010 1.272382e-01 -0.1498827500\n",
"CASP7 7.121977e-02 0.0609404253 -0.1844966583 1.056027e-01 0.0301115857\n",
"CAV1 1.532671e-01 -0.0201017067 0.0649903355 1.143789e-01 0.0739845508\n",
"CCNB1 4.162289e-02 -0.2036975961 0.0138212683 4.258207e-03 -0.0018271031\n",
"CCND1 -2.683148e-02 0.0402352996 -0.0063840713 -2.034746e-02 -0.0739442193\n",
"CCNE1 -1.319072e-01 -0.1147913564 0.0650475543 5.579030e-02 -0.0725196417\n",
"CCNE2 -8.784915e-02 -0.1502069979 -0.0649630933 -9.769081e-02 -0.0309854967\n",
"CDH1 -1.680456e-01 -0.1304620321 0.0801704783 4.763322e-02 0.0110291057\n",
"CDH2 -8.957333e-02 0.0129241473 -0.0341230531 -4.536218e-02 -0.0018174089\n",
"CDH3 -2.495631e-02 -0.1126081350 0.1022487767 1.115934e-01 -0.0487312253\n",
"CDKN1A -4.904522e-02 0.0428565646 -0.0015293561 3.528269e-03 -0.0579418236\n",
"CDKN1B 1.778657e-01 0.1104485957 -0.0543390508 2.059417e-06 0.0831193820\n",
"CHEK1 1.880590e-01 -0.0511632510 -0.0356408084 -3.898712e-02 -0.0621812564\n",
"CHEK2 1.439941e-02 -0.0536506277 0.0005284004 4.615686e-02 -0.2993494507\n",
"CLDN7 -1.909107e-01 0.0131801513 -0.0415829490 -6.942468e-02 0.0368603050\n",
"COL6A1 -5.266419e-02 -0.0664471684 -0.1957180132 -1.449808e-02 0.0960334977\n",
"CTNNB1 -1.706452e-01 0.0225153702 -0.0589304919 -1.434670e-01 0.0048677240\n",
"DIRAS3 -8.390967e-03 0.0004314582 -0.0055933533 8.314133e-03 0.0320976233\n",
"DVL3 4.767421e-03 0.0350494797 0.0031562541 -2.680572e-02 -0.2051677772\n",
"EEF2 1.363936e-01 -0.0841207275 0.0738460803 -1.495446e-01 -0.0162651326\n",
"EEF2K 1.297108e-01 -0.1095042026 0.0893211460 -1.369450e-01 0.0001610050\n",
"EGFR -1.923415e-01 0.0265404516 0.0814095357 1.925468e-02 0.0082448249\n",
"EIF4E 2.200403e-02 0.0217374605 0.0385182418 5.170885e-02 0.2041760323\n",
"EIF4EBP1 -1.215446e-01 -0.1323776889 -0.0625531603 -1.080387e-01 -0.0424860293\n",
"EIF4G1 -6.980910e-02 0.0162035683 0.1569502683 1.597224e-01 -0.1037699183\n",
"ERBB2 8.314938e-02 -0.0367379603 -0.1463150435 -1.545506e-01 0.0673444804\n",
"ERBB3 -1.144515e-01 0.0906829502 0.1643169625 -9.157749e-02 0.0349554761\n",
"ERRFI1 -7.379959e-02 0.0433981725 0.1327659884 1.480376e-01 0.0430790690\n",
"ESR1 -2.953070e-02 -0.0435233528 0.0005699838 5.133280e-02 -0.0241064605\n",
"ETS1 -6.192161e-02 -0.0959641959 -0.1947313925 -1.143377e-02 0.0750346022\n",
"FASN -1.425217e-01 0.0805002466 -0.0615203045 1.297970e-01 -0.0350857204\n",
"FN1 -1.116781e-01 -0.0846945616 -0.0568107780 -8.516664e-02 0.2120297431\n",
"FOXM1 -1.388456e-02 0.1854059320 0.0301141537 -2.319670e-02 -0.1789810726\n",
"FOXO3 5.387568e-02 0.0802142229 0.2083231288 -7.051124e-03 -0.0146483463\n",
"G6PD -1.419602e-01 -0.1415341771 -0.0624264970 -1.057744e-01 0.0408146209\n",
"GAB2 9.677943e-02 0.0638959883 0.0729326549 -1.615252e-01 -0.0808415428\n",
"GAPDH 1.209388e-01 -0.0859006724 0.0924702716 -1.495118e-01 -0.0221876420\n",
"GATA3 1.099621e-01 0.0906266151 0.0916962534 -1.785345e-01 0.0531891688\n",
"GSK3A 9.278926e-02 0.0690228933 -0.1729869145 1.537905e-01 -0.0306937404\n",
"HSPA1A 9.262086e-03 0.0083334740 0.0452416726 4.404835e-02 0.0687951100\n",
"IGFBP2 -4.281623e-02 0.0391010718 -0.1563420736 2.440855e-02 -0.1384126056\n",
"IRS1 6.668070e-02 0.0493708320 -0.1722733939 1.118580e-01 0.0456669811\n",
"ITGA2 -1.588541e-01 0.0057131971 -0.0538611564 -1.411402e-01 0.0047985680\n",
"JUN -2.560712e-02 0.0953449588 -0.0026398968 -1.907789e-01 -0.0656198514\n",
"KDR 8.916064e-02 -0.0823326677 0.1980962353 1.389394e-02 0.1223054927\n",
"KIT -1.010126e-01 0.0083156756 -0.0461163036 -1.094299e-01 0.2012419339\n",
"LCK -6.987622e-02 0.0316056265 0.1390726487 1.295769e-01 0.0645479175\n",
"MAP2K1 -2.731534e-02 0.2316529990 -0.0013345732 -6.925288e-03 -0.0840269253\n",
"MAPK1 9.096303e-02 -0.1171078175 -0.1427561471 1.409121e-01 -0.0008842903\n",
"MAPK14 -1.886998e-01 0.0255104012 -0.0787444857 -1.247127e-01 -0.0241145766\n",
"MAPK9 -7.369324e-03 0.0031566208 0.0248262612 2.705669e-02 0.4227877187\n",
"MET -1.822598e-01 0.0240323433 0.0676525254 2.182503e-02 -0.0126449001\n",
"MRE11A 1.458894e-01 -0.0908127258 0.0823642706 -1.461441e-01 -0.0324264841\n",
"MYC -1.846915e-01 0.0126227733 0.0574525948 6.043469e-02 -0.0097722021\n",
"MYH11 2.586325e-02 0.0566704434 0.0142000339 -1.765898e-02 0.0909864085\n",
"NDRG1 -1.463543e-01 0.0701344806 -0.0512731542 9.024288e-02 -0.0845659603\n",
"NF2 -1.807622e-01 0.0060011897 -0.0556196909 -1.364257e-01 0.0046573408\n",
"NFKB1 -2.306134e-02 0.0277289094 0.0304446389 6.609401e-03 0.1070514804\n",
"NOTCH1 -3.182347e-02 0.0094550727 -0.0154892683 -7.058497e-02 0.0982244154\n",
"NRAS -5.758506e-02 -0.0597215417 0.1732397462 -8.262892e-02 -0.0046841381\n",
"NRG1 1.496318e-01 -0.0215844226 0.0733758520 8.643988e-02 -0.0161604568\n",
"PARK7 2.983364e-02 -0.0205305344 -0.0039231477 7.531367e-02 -0.0378533331\n",
"PCNA -6.483663e-02 -0.0580387903 0.1808925937 -1.093270e-01 -0.0449620662\n",
"PDCD4 5.291690e-02 0.0961894374 0.2118163865 -2.674133e-03 0.0170407783\n",
"PDK1 -1.031884e-01 0.0723797515 0.1644491709 -9.710483e-02 -0.0970815523\n",
"PEA15 6.234964e-02 0.0980220410 0.1969660379 1.240774e-02 -0.0546596749\n",
"PGR 1.095082e-02 -0.1382249731 0.0100151371 2.041291e-02 -0.1997597672\n",
"PIK3R1 3.539498e-02 -0.1935240943 0.0326723496 -9.210021e-04 0.0750922554\n",
"PRDX1 1.353994e-01 -0.0911206627 0.0995174562 -1.239505e-01 -0.0503531268\n",
"PREX1 -2.246995e-02 -0.1397932196 0.1125773421 1.529635e-01 0.1170022605\n",
"PRKAA1 1.119774e-01 0.0758407949 0.0976224451 -1.687660e-01 -0.0396929883\n",
"PRKCD -3.746693e-02 -0.0827459108 0.0100210789 -2.403332e-01 -0.0751569220\n",
"PTEN -7.196702e-02 -0.0399927872 0.1575713437 -1.261308e-01 0.2121704074\n",
"PXN 8.684981e-02 0.0642126881 -0.1923442325 1.289572e-01 -0.0372918458\n",
"RAB25 -3.146321e-02 0.0941574957 0.0332263818 1.675747e-02 0.1165241977\n",
"RAD50 1.759505e-01 0.1285646042 -0.0759876678 -3.203240e-02 -0.0189439620\n",
"RAD51 -1.055621e-01 -0.1602330852 -0.0425701952 -1.089201e-01 -0.1385659711\n",
"RAF1 -1.370305e-01 -0.0928246024 -0.0898864345 1.660775e-01 -0.0519176456\n",
"RB1 2.179497e-03 0.0351169196 0.0540174596 5.209941e-02 -0.0519214324\n",
"RBM15 -2.968653e-02 0.2199943820 -0.0005566858 3.543472e-03 -0.0899800715\n",
"RPS6 4.041759e-02 -0.0982178249 -0.0216528934 2.337913e-01 0.0706640613\n",
" 6 7 8 9 10\n",
"ACACA -0.0054879690 -0.008538992 -0.0829485828 0.0868392025 0.0692186251\n",
"ACVRL1 -0.0386061861 0.123642071 -0.0545415797 -0.0200401287 0.2074588280\n",
"AKT1 -0.2816575572 0.055785526 0.2797503101 -0.2239372573 -0.0884694578\n",
"AKT1S1 -0.1016391925 0.027465324 0.0460240907 -0.0603020327 0.0659469434\n",
"ANXA1 -0.0433245351 0.076914197 -0.0208120412 -0.1673134556 0.0166884816\n",
"AR 0.1884040662 -0.072834224 0.1648958270 -0.0356965586 0.0898768831\n",
"ARAF -0.0633474852 -0.034024648 0.0426319252 -0.1159526368 -0.0170729623\n",
"ASNS -0.0047474444 0.015620051 -0.1534890217 0.0131642609 -0.0646944610\n",
"ATM 0.1082017208 -0.010102847 -0.0383862144 0.0196795603 -0.1444462459\n",
"BAD 0.0720269307 0.109507219 0.0039037512 -0.0064865703 0.0352614745\n",
"BAK1 -0.1532439547 0.086343951 0.0162062564 0.0357545378 0.0326392820\n",
"BAP1 -0.1211242148 -0.035989717 0.0320913599 -0.0732699752 -0.0425631119\n",
"BAX -0.0261342368 -0.009802316 0.0573912170 -0.0017800072 0.0782885118\n",
"BCL2 0.1903280632 -0.032262581 -0.0924099558 0.0495860941 -0.0523356318\n",
"BCL2L1 -0.0119749807 0.019923347 0.0195720700 0.0212388802 0.0063260487\n",
"BCL2L11 -0.0488508305 0.083668722 0.0180966965 -0.0556360896 -0.0303831044\n",
"BECN1 0.0178247410 -0.028773113 0.0360598249 0.0642015737 0.0013701023\n",
"BID -0.1868507403 0.170284714 -0.1407427435 0.1245808434 -0.0838610278\n",
"BRAF -0.0815603461 0.009053676 -0.1091464326 -0.2704193310 0.1074515040\n",
"BRCA2 -0.0102825140 0.032693879 0.0666148797 0.0225517912 0.1236109342\n",
"CASP7 -0.0723293036 0.113951007 0.0353809286 -0.1544875859 -0.0127362527\n",
"CAV1 0.0689865365 0.004026757 0.0226809103 0.0881955453 0.0449187879\n",
"CCNB1 -0.1135991921 -0.044714201 -0.0318841160 0.0930498691 -0.0133204415\n",
"CCND1 0.2176563354 -0.053568103 0.3008025689 -0.0696165907 -0.1528141863\n",
"CCNE1 -0.1461029297 0.130859784 0.0390921014 0.1503522182 -0.0008939865\n",
"CCNE2 -0.0562502468 0.038213534 -0.2190835792 -0.1129101495 0.0545041316\n",
"CDH1 0.0568635883 -0.027287971 0.0530404071 -0.1320654961 -0.0093925418\n",
"CDH2 0.0579034420 -0.193508927 -0.0389098494 0.0584966426 -0.3404984286\n",
"CDH3 -0.0463506161 -0.184595437 0.0858898060 -0.0075023799 0.0706684056\n",
"CDKN1A -0.0950183952 0.131648525 -0.0724590502 0.0030368449 0.0527878564\n",
"CDKN1B -0.1132520460 -0.019038098 -0.0379291266 0.0104993850 -0.0201925716\n",
"CHEK1 -0.1439846499 0.036701352 -0.1299384966 0.0414525042 -0.0346914676\n",
"CHEK2 -0.2050322851 0.029481948 -0.0703456163 0.1989091209 -0.0837541728\n",
"CLDN7 -0.0162130657 -0.017570489 0.0707706140 -0.0014928393 0.0141860331\n",
"COL6A1 -0.0908492634 0.075047076 0.1392580780 0.0933842608 0.0252934393\n",
"CTNNB1 -0.0820559798 -0.036791572 0.0171657823 -0.0757722126 0.0005885137\n",
"DIRAS3 -0.1627705247 -0.300211530 0.2970395908 0.1257447716 0.0262857397\n",
"DVL3 -0.0344889800 0.167917437 0.2846062870 -0.0027059060 -0.0133633002\n",
"EEF2 0.0090078651 0.063907140 0.1603175532 0.0019444459 -0.1018194259\n",
"EEF2K -0.0257720429 0.055538613 0.0785352882 -0.0646285382 -0.0214454224\n",
"EGFR 0.1208001201 0.075540478 0.0046412058 0.0027589320 -0.0084248463\n",
"EIF4E -0.1975920748 -0.231992475 -0.0515412019 -0.0122882846 -0.2218915934\n",
"EIF4EBP1 -0.0457520269 0.015582610 -0.0453595753 0.0308731309 0.1236310452\n",
"EIF4G1 -0.0078869390 0.123221496 0.0858604483 0.0246805789 -0.0055137906\n",
"ERBB2 0.0796949273 0.028696757 0.0957540200 -0.0081587276 0.0101083670\n",
"ERBB3 -0.0041415903 0.110805306 0.0072068986 0.0082387679 0.0621099964\n",
"ERRFI1 0.0367515110 0.008789995 -0.0609411134 0.0978803358 0.0234183577\n",
"ESR1 0.0673602808 -0.062616169 0.0312084323 -0.4305359824 0.0873697019\n",
"ETS1 -0.0601776548 0.107477295 0.0015095010 -0.0009426077 0.0428396414\n",
"FASN -0.0623766288 0.022086019 0.0803178724 -0.0445698744 -0.0261054418\n",
"FN1 -0.0576971282 0.087175099 0.0930739407 0.1011001426 -0.0024638102\n",
"FOXM1 -0.1067347422 0.021783431 0.0015977806 -0.0071580036 0.0318370322\n",
"FOXO3 0.0672226180 -0.062265582 0.1048331482 0.0184330790 0.0620849197\n",
"G6PD -0.0412773612 -0.052791044 0.0594839228 -0.0144604930 -0.0772299146\n",
"GAB2 0.0308035836 0.113155543 0.0316930107 -0.0915965831 0.0710456949\n",
"GAPDH -0.0486693716 0.032504630 0.0658235911 -0.0549631554 -0.0700148847\n",
"GATA3 -0.0486528181 -0.010852403 0.0086047127 0.0923686258 -0.0983070879\n",
"GSK3A -0.0509799375 0.058897089 0.0283102970 0.0008862686 0.0527898573\n",
"HSPA1A -0.1439698981 0.214066517 0.1514818498 -0.0419677512 -0.3601984500\n",
"IGFBP2 -0.2271504785 -0.196385680 0.1240356153 0.0025277186 0.0329673441\n",
"IRS1 0.0178381345 -0.089896898 0.0596697305 0.0300632692 0.0769469702\n",
"ITGA2 0.1171792498 -0.023458787 -0.0193333493 0.0368762124 -0.0654758695\n",
"JUN 0.0946757645 -0.066883795 -0.0301183932 0.1419815067 0.0625892158\n",
"KDR -0.0313244096 0.052760999 0.0304078440 -0.0085166863 0.0777014449\n",
"KIT -0.0722785501 -0.078068957 0.0691734144 0.2665073834 -0.0146628386\n",
"LCK -0.0699757898 0.125790635 -0.0790612369 0.1587968457 -0.0567623959\n",
"MAP2K1 -0.0605089471 -0.039548098 0.0594285128 0.0089403171 -0.0891493128\n",
"MAPK1 -0.1781366959 0.112028144 -0.0173204461 -0.0263586656 -0.0811466866\n",
"MAPK14 -0.0428846170 -0.080963026 0.0277345656 -0.0663576879 0.0571648129\n",
"MAPK9 -0.2493265222 -0.098469547 -0.0070611047 -0.2128009202 0.0363995819\n",
"MET 0.1122638237 0.049479862 -0.0374679974 -0.1068620454 -0.0620993660\n",
"MRE11A -0.0100217393 0.016766148 0.0010011451 -0.0355053598 0.0064988572\n",
"MYC 0.1576968616 -0.112107212 0.0173427672 -0.1095388279 -0.0890847565\n",
"MYH11 0.0108531992 0.060751759 0.0335129158 0.2669629031 0.1879886254\n",
"NDRG1 0.0153876872 0.228796707 -0.0402766268 -0.0218539048 0.0666892801\n",
"NF2 -0.0879697958 0.039488654 0.0432297252 0.0764433250 -0.0724061895\n",
"NFKB1 0.1397588035 0.268997554 -0.0187504554 0.0151567294 -0.2194182913\n",
"NOTCH1 0.1131135312 0.228016962 0.2107767582 0.0599665139 0.2355869746\n",
"NRAS -0.1092195455 -0.076935820 -0.0258563830 0.0922164527 0.0589834444\n",
"NRG1 0.1409002577 -0.072277328 -0.0276009175 0.0429231169 -0.2059023317\n",
"PARK7 -0.0418723049 -0.222611457 -0.0874407156 0.0880219435 0.2014845264\n",
"PCNA -0.0831181259 -0.044954976 -0.1078422602 -0.0917522150 -0.0212480760\n",
"PDCD4 0.0005813872 -0.073252124 0.0028244564 0.0251628501 0.0319641840\n",
"PDK1 -0.1173185400 -0.123205753 -0.0757563623 0.0190040212 -0.0044889871\n",
"PEA15 -0.0243585810 0.078810475 0.0111123852 -0.0495830454 0.0555739892\n",
"PGR -0.0280881614 -0.104287461 -0.0314635508 -0.0467115998 0.2081541423\n",
"PIK3R1 0.0068862986 -0.006088678 0.1123135460 -0.1671074318 -0.0590148516\n",
"PRDX1 -0.0923360002 -0.041610632 0.0421099041 -0.0075900264 -0.0574057013\n",
"PREX1 -0.0762560808 0.086166621 0.0260401682 0.0651106387 -0.1110746915\n",
"PRKAA1 -0.0539248149 -0.013536037 -0.0351639496 -0.0159619527 0.0785231848\n",
"PRKCD -0.0420830485 0.102177278 0.0657539268 -0.0448629702 0.0133295772\n",
"PTEN 0.1111038073 0.038703230 0.0124092234 -0.0050063860 -0.0714470083\n",
"PXN 0.0463995725 0.075583711 0.0628786553 0.0241667989 -0.0454527296\n",
"RAB25 -0.0409968111 0.119965117 0.1775014285 0.0733075977 0.2122433167\n",
"RAD50 -0.0449579379 0.006852360 -0.0009571342 -0.0109169727 0.0111816718\n",
"RAD51 -0.0094255508 -0.010572308 0.0163863583 -0.0007045560 0.0470430785\n",
"RAF1 -0.0111800914 -0.005503908 0.0003697090 0.0160304941 -0.0684696719\n",
"RB1 0.0964458141 -0.106218778 0.3416520683 0.1516762375 -0.0081803658\n",
"RBM15 0.0429700275 0.074035878 -0.1267399253 0.0195343464 -0.1329087760\n",
"RPS6 0.0792556717 -0.039591293 -0.0744506713 -0.0934816936 0.0378285711\n",
"\n",
"[[1]][[2]][[3]]\n",
" 1 2 3 4\n",
"ACC1 -0.148689116 0.0464705410 -0.078182626 0.1142004389\n",
"ACC_pS79 -0.149167425 0.0386757803 -0.080265475 0.1196517312\n",
"ACVRL1 -0.021036552 0.0471769535 0.011427153 0.0301869094\n",
"Akt_pS473 -0.023096244 0.0246262884 0.026419173 0.0189205576\n",
"PRAS40_pT246 -0.033814499 0.2357681044 0.003455191 0.0118030506\n",
"Annexin.1 0.086981532 0.0931502030 0.095782132 0.1582274647\n",
"AR -0.006168150 0.0007461875 -0.008226675 -0.0173869910\n",
"A.Raf_pS299 -0.183378645 0.0435391640 0.070233110 -0.0453757470\n",
"ASNS -0.148104028 -0.1177011976 0.051471108 -0.0551072373\n",
"ATM 0.064379622 -0.0187647970 -0.142537569 0.1322364064\n",
"Bad_pS112 0.027939079 -0.2076974197 0.018002807 0.0064603288\n",
"Bak -0.063514870 0.0149612299 0.162450649 -0.1746956321\n",
"Bap1.c.4 -0.023632160 0.2308733647 -0.008636205 -0.0088888680\n",
"Bax 0.021935753 -0.2369733654 0.008196731 -0.0151743619\n",
"Bcl.2 -0.018310593 -0.0149616187 0.029184903 0.0387188944\n",
"Bcl.xL -0.074451004 0.0753318965 -0.219691473 -0.0151086009\n",
"Bim 0.035912881 -0.2252218708 -0.012283692 -0.0034265606\n",
"Beclin -0.062286197 0.0198041284 0.157368004 -0.1708907861\n",
"Bid -0.027968102 -0.0617984552 0.001310626 0.0009496965\n",
"B.Raf -0.027300038 0.2162626098 -0.013259786 0.0109835701\n",
"BRCA2 -0.030949037 -0.1674038903 0.130719288 -0.1535551747\n",
"Caspase.7_cleavedD198 0.057445947 0.0448817640 -0.145574461 -0.1399267823\n",
"Caveolin.1 0.089807242 -0.0218040095 0.040004833 -0.0761454730\n",
"Cyclin_B1 0.038121442 -0.1654459140 -0.006084344 -0.0231990874\n",
"Cyclin_D1 -0.018329067 -0.0138987086 0.010064294 0.0343449119\n",
"Cyclin_E1 -0.146487771 -0.1182033270 0.032509498 -0.0353308873\n",
"Cyclin_E2 -0.113728036 -0.1557942450 -0.055492676 0.1030690723\n",
"E.Cadherin -0.127775637 -0.1187367235 0.041387398 -0.0227036946\n",
"N.Cadherin -0.158867078 0.0222552629 -0.080677945 0.1203997895\n",
"P.Cadherin -0.033029860 -0.1609079502 0.128466602 -0.1487428780\n",
"p21 -0.016230748 -0.0441671638 0.008090589 0.0050649389\n",
"p27 0.151603579 0.1286379481 -0.053762895 0.0526513381\n",
"p27_pT157 0.164892673 0.1254087898 -0.067411948 0.0529058029\n",
"p27_pT198 0.163382809 0.1264388156 -0.062416807 0.0422740937\n",
"Chk1 0.188712813 -0.0482959503 -0.058984720 0.0488951930\n",
"Chk1_pS345 0.188705342 -0.0512535067 -0.063370152 0.0486964594\n",
"Chk2 0.047192976 -0.0030387623 -0.046254437 -0.0242168595\n",
"Chk2_pT68 0.031961749 -0.0298119246 -0.039804185 0.0254295610\n",
"Claudin.7 -0.113362302 0.0162284490 -0.078708511 0.0874823456\n",
"Collagen_VI -0.060716170 -0.1059311481 -0.181736647 -0.0326438616\n",
"beta.Catenin -0.127354249 0.0247847085 -0.096834310 0.1052042832\n",
"ARHI -0.027800488 0.0256744569 0.018271011 0.0402709687\n",
"Dvl3 -0.002331544 -0.0080543794 -0.036735396 0.0023847164\n",
"eEF2 0.134379359 -0.0985366236 0.084624658 0.1600226682\n",
"eEF2K 0.134737748 -0.0886166607 0.067760343 0.1483959549\n",
"EGFR -0.188660211 0.0433645624 0.067391230 -0.0403642835\n",
"EGFR_pY1068 -0.174375962 0.0397580813 0.067139466 -0.0336435716\n",
"EGFR_pY1173 -0.193118047 0.0353877181 0.065075957 -0.0343565081\n",
"eIF4E 0.023470764 0.0356174837 -0.019612538 -0.0292507896\n",
"4E.BP1 -0.112510972 -0.1573910547 -0.065788329 0.0780261637\n",
"4E.BP1_pS65 -0.110821545 -0.1516857969 -0.068717127 0.1032039330\n",
"4E.BP1_pT70 -0.112413345 -0.1585988525 -0.068314782 0.0918423996\n",
"eIF4G -0.044350264 0.0197971278 0.109233150 -0.1590951368\n",
"HER2 0.067479442 -0.0193927266 -0.140486759 0.1479326304\n",
"HER2_pY1248 0.061239096 -0.0207602839 -0.141919994 0.1649160823\n",
"HER3 -0.089764407 0.1102597317 0.150255093 0.1381511890\n",
"HER3_pY1289 -0.084647207 0.1218879404 0.155411378 0.1179195209\n",
"MIG.6 -0.064580229 0.0091562692 0.158797045 -0.1779914466\n",
"ER.alpha 0.001214476 0.0169567804 -0.003560290 -0.0187349585\n",
"ER.alpha_pS118 0.030927817 0.0162763780 -0.010134779 0.0308334102\n",
"ETS.1 -0.051785336 -0.0957828275 -0.210048583 -0.0213687218\n",
"FASN -0.116562726 0.0845297627 -0.069264012 -0.1638411762\n",
"Fibronectin -0.097436291 -0.1143418761 -0.034546479 0.0445751094\n",
"FoxM1 -0.017998814 0.1919005123 -0.002643953 0.0025981992\n",
"FOXO3a 0.050281691 0.0850883242 0.214696457 0.0391155021\n",
"FOXO3a_pS318_S321 0.049424222 0.0871965031 0.214533656 0.0261372819\n",
"G6PD -0.119111256 -0.1494754940 -0.064196039 0.0994732404\n",
"GAB2 0.102789810 0.0688194782 0.072005267 0.1631442680\n",
"GAPDH 0.112781069 -0.0663133972 0.063070627 0.1173573927\n",
"GATA3 0.116092432 0.0918639550 0.099394328 0.1966954491\n",
"GSK3.alpha.beta 0.063427556 0.0636810096 -0.173066702 -0.1511303149\n",
"GSK3.alpha.beta_pS21_S9 0.056054275 0.0609298103 -0.162150220 -0.1459257792\n",
"GSK3_pS9 0.050260561 0.0660833913 -0.160176431 -0.1404731137\n",
"HSP70 -0.014241717 -0.0369177599 0.011754217 0.0142490266\n",
"IGFBP2 -0.067391037 0.0643025232 -0.180861021 -0.0221979552\n",
"IRS1 0.069858489 0.0557690222 -0.185065458 -0.1519147707\n",
"CD49b -0.166612159 0.0351921354 -0.070875620 0.1253580064\n",
"c.Jun_pS73 -0.032327670 0.1055897249 0.031234900 0.2618848838\n",
"VEGFR2 0.070757030 -0.0705938107 0.194279599 0.0267963365\n",
"c.Kit -0.144089037 0.0328509916 -0.065425860 0.1253446211\n",
"Lck -0.067125420 0.0130916421 0.152976085 -0.1599750804\n",
"MEK1 -0.012630777 0.2183507074 0.001308527 -0.0093474438\n",
"MEK1_pS217_S221 -0.030941528 0.2318928285 0.004010297 0.0083449824\n",
"ERK2 0.087565692 -0.1079920787 -0.139325221 -0.1254722842\n",
"p38_MAPK -0.161538014 0.0338754166 -0.076456544 0.1288425695\n",
"p38_pT180_Y182 -0.138012404 0.0436444044 -0.043680183 0.1167648673\n",
"JNK2 -0.012411337 0.0334635336 -0.004481356 -0.0354013123\n",
"c.Met_pY1235 -0.191591526 0.0382267582 0.061028161 -0.0420255564\n",
"Mre11 0.128420186 -0.1048844159 0.082303311 0.1685214665\n",
"c.Myc -0.190408782 0.0345809924 0.057704053 -0.0414294087\n",
"MYH11 -0.021060375 -0.0392854684 0.029025648 -0.0242927570\n",
"NDRG1_pT346 -0.124694096 0.0945253399 -0.066096362 -0.1231505329\n",
"NF2 -0.154265482 0.0237446020 -0.094382821 0.1229357778\n",
"NF.kB.p65_pS536 -0.002041525 -0.0061295643 0.008685604 -0.0307085765\n",
"Notch1 0.010048334 -0.0315432552 0.004176455 0.0125401124\n",
"N.Ras -0.076543536 -0.0577973189 0.185070246 0.1522937155\n",
"Heregulin 0.166827050 -0.0240122544 0.086482035 -0.1128214538\n",
"DJ.1 0.010437762 0.0009256618 0.005567332 -0.0166874375\n",
"PCNA -0.060578704 -0.0661905360 0.178153081 0.1634771358\n",
"PDCD4 0.043876756 0.1001616576 0.170416491 0.0181978212\n",
" 5 6 7 8\n",
"ACC1 -1.590916e-02 0.056637657 -0.0291572261 0.027014913\n",
"ACC_pS79 -3.672456e-05 0.067375789 -0.0215268690 0.047032868\n",
"ACVRL1 4.434559e-02 -0.019930508 -0.3379945786 -0.002002896\n",
"Akt_pS473 3.647476e-01 -0.231426290 0.2764927898 0.081113490\n",
"PRAS40_pT246 2.495298e-02 -0.005037642 0.0378536741 0.001180361\n",
"Annexin.1 -7.169524e-02 -0.021427751 0.1379080602 -0.099117637\n",
"AR -1.012086e-01 0.168390767 -0.0029531798 0.022855752\n",
"A.Raf_pS299 6.129378e-02 -0.013264752 0.0107638984 -0.026841046\n",
"ASNS -5.205255e-02 0.043039331 0.0126585860 -0.009228605\n",
"ATM -8.443678e-03 0.028295835 -0.0082518084 0.033904678\n",
"Bad_pS112 1.775954e-01 -0.015398281 0.1432272984 -0.202980362\n",
"Bak -1.113021e-02 -0.021492782 -0.0191994975 0.074005413\n",
"Bap1.c.4 -2.766827e-02 -0.032993727 -0.0602527315 0.068603073\n",
"Bax -2.527365e-03 -0.089684646 -0.0324889383 0.020198051\n",
"Bcl.2 1.947428e-01 -0.236299873 -0.2075945756 -0.122770401\n",
"Bcl.xL -1.159638e-02 -0.017889347 -0.0123764841 0.027058239\n",
"Bim 5.354875e-02 0.015700904 -0.1059000834 0.159624174\n",
"Beclin -2.370605e-02 0.047774411 0.0176662273 -0.077263626\n",
"Bid -2.192471e-01 0.163874024 -0.0380478557 0.014818161\n",
"B.Raf 7.216991e-02 0.118980205 0.0132925866 0.055094621\n",
"BRCA2 -5.277151e-03 0.012115117 -0.0045415401 0.001353572\n",
"Caspase.7_cleavedD198 -4.476196e-02 0.085136739 0.0493808789 -0.124240940\n",
"Caveolin.1 -1.685529e-01 -0.140679058 0.0415099938 0.142024070\n",
"Cyclin_B1 6.094770e-02 0.059594691 -0.0517403469 0.246032239\n",
"Cyclin_D1 -2.617888e-01 0.010794255 0.0899183499 -0.111948803\n",
"Cyclin_E1 4.338835e-02 0.072081960 0.0157535765 0.037394170\n",
"Cyclin_E2 -7.510310e-03 -0.043727599 -0.0492400256 0.037904038\n",
"E.Cadherin 6.083599e-02 0.090208653 0.0408111561 -0.221822410\n",
"N.Cadherin -1.679289e-02 -0.024245271 -0.0606337979 0.046249788\n",
"P.Cadherin 3.155054e-02 0.111604160 0.0667626986 0.009271805\n",
"p21 -2.921662e-01 -0.046596456 0.1933973552 0.233406309\n",
"p27 -2.227482e-02 -0.057994676 -0.0148583321 0.041492502\n",
"p27_pT157 -2.734349e-03 -0.007793828 -0.0018647547 -0.009119116\n",
"p27_pT198 -6.573849e-02 -0.024021745 0.0022642643 0.076815028\n",
"Chk1 -3.065943e-02 -0.092659723 -0.0214575696 -0.061071157\n",
"Chk1_pS345 -2.181779e-03 -0.043151349 0.0122576965 -0.047931655\n",
"Chk2 1.519296e-01 0.170745089 -0.1951028069 0.048401597\n",
"Chk2_pT68 1.478490e-01 0.069482105 -0.0776790368 -0.078945641\n",
"Claudin.7 -9.116777e-02 0.170758265 -0.0877943258 -0.139610300\n",
"Collagen_VI -9.821704e-02 -0.064771399 -0.0547173641 -0.025915551\n",
"beta.Catenin 5.572662e-02 0.032778495 0.0738730216 -0.115072998\n",
"ARHI -3.852530e-02 -0.195149079 -0.3613434423 0.077513579\n",
"Dvl3 9.357551e-02 -0.187034600 -0.0329803210 0.041823357\n",
"eEF2 -6.949445e-03 0.068602100 0.0096395134 -0.010223256\n",
"eEF2K -2.855109e-03 0.068850218 -0.0367871688 -0.088135612\n",
"EGFR -3.346978e-03 0.007159569 -0.0018417113 -0.021917589\n",
"EGFR_pY1068 1.831675e-02 0.112286057 -0.0043077245 0.046551938\n",
"EGFR_pY1173 -7.272145e-03 0.028026964 -0.0055559491 -0.003116126\n",
"eIF4E 9.693457e-02 -0.201545515 -0.0404870428 0.118147883\n",
"4E.BP1 -1.336148e-02 -0.044283442 -0.0221473820 0.056449365\n",
"4E.BP1_pS65 3.608542e-02 -0.002823710 0.0146358025 -0.046536973\n",
"4E.BP1_pT70 2.088600e-02 -0.019241786 0.0103147696 -0.018972511\n",
"eIF4G 3.297306e-02 0.126185241 -0.0232710441 0.148061417\n",
"HER2 -5.387541e-02 0.188236916 0.0631591644 0.101619075\n",
"HER2_pY1248 -6.650418e-02 0.095353350 -0.0049441661 0.076503004\n",
"HER3 -8.087102e-02 0.053212705 0.0491936889 -0.030630060\n",
"HER3_pY1289 -2.673808e-02 -0.073479502 -0.0067628283 0.056382878\n",
"MIG.6 -5.745966e-02 0.030867523 -0.0003629101 0.037605596\n",
"ER.alpha 3.057090e-02 0.254903715 -0.1709248514 -0.022525331\n",
"ER.alpha_pS118 -2.950234e-03 0.226883161 -0.0452795211 -0.201670453\n",
"ETS.1 -3.109059e-02 -0.017083967 -0.0251064705 -0.043981848\n",
"FASN 1.918802e-03 0.111012624 -0.1278032895 0.060660363\n",
"Fibronectin -9.564361e-02 -0.084854579 0.1117021167 0.211576291\n",
"FoxM1 9.844516e-02 0.058565636 -0.1097909505 0.177603141\n",
"FOXO3a 8.046785e-04 -0.005642557 -0.0163627252 0.055767564\n",
"FOXO3a_pS318_S321 -5.138558e-02 0.006838428 0.0605184814 0.045686863\n",
"G6PD 4.801222e-02 -0.011593056 -0.0068687968 -0.010232130\n",
"GAB2 3.090316e-02 0.173965451 -0.1096912705 0.045770380\n",
"GAPDH 1.472107e-01 0.235912189 0.0521034554 0.093595042\n",
"GATA3 1.299640e-02 -0.005892770 -0.0083276622 -0.002887516\n",
"GSK3.alpha.beta -1.562603e-02 0.031177638 0.0868463383 0.015022635\n",
"GSK3.alpha.beta_pS21_S9 9.549126e-02 -0.042409720 0.0795487928 -0.122360096\n",
"GSK3_pS9 1.152648e-01 -0.046144329 0.0700173533 -0.098335665\n",
"HSP70 -2.779555e-01 -0.079680351 -0.0689728047 -0.258213162\n",
"IGFBP2 -6.021270e-02 0.023170170 -0.0259773415 0.082125959\n",
"IRS1 -5.333218e-02 -0.016160521 -0.0306911051 -0.032450202\n",
"CD49b -3.273944e-02 -0.010940969 0.0250894241 0.008393707\n",
"c.Jun_pS73 3.864512e-02 0.002798426 0.0358482698 0.047795588\n",
"VEGFR2 -5.194025e-02 -0.117063449 0.1571438734 -0.025740083\n",
"c.Kit 1.532138e-02 -0.054946258 0.0836905486 0.072677989\n",
"Lck -2.248814e-02 -0.015239892 -0.0346068462 -0.063421200\n",
"MEK1 -9.315295e-02 0.020555002 -0.0469722791 0.005571314\n",
"MEK1_pS217_S221 -7.943575e-03 -0.037296737 0.1036411428 -0.081038923\n",
"ERK2 3.618475e-02 0.115845232 0.0962519088 -0.018074625\n",
"p38_MAPK 5.842730e-03 -0.078780167 0.0671295784 -0.066105179\n",
"p38_pT180_Y182 1.193773e-01 -0.142461140 0.0869447202 -0.204896479\n",
"JNK2 1.643955e-01 0.318699239 0.1813775234 0.030481037\n",
"c.Met_pY1235 2.211256e-03 0.012885186 0.0044558942 -0.018451216\n",
"Mre11 -4.638794e-02 -0.004655554 0.0315293053 -0.042148287\n",
"c.Myc -4.312237e-02 0.050670897 -0.0166974123 -0.012504146\n",
"MYH11 -2.347654e-01 -0.131087603 -0.0699010925 0.105206268\n",
"NDRG1_pT346 2.810678e-02 -0.123388223 0.0964591517 0.051989701\n",
"NF2 9.354895e-04 -0.013249259 0.0260392080 0.035480666\n",
"NF.kB.p65_pS536 2.627501e-03 -0.027749889 -0.3050347795 -0.281544336\n",
"Notch1 4.554585e-02 -0.077173525 -0.3083447049 0.042058640\n",
"N.Ras 1.294464e-02 0.012584551 -0.0563697378 0.007501046\n",
"Heregulin -1.076455e-02 -0.047356253 -0.0794210971 0.034309763\n",
"DJ.1 3.514215e-01 0.010367383 -0.0439090375 0.170588349\n",
"PCNA 7.834237e-02 0.027250663 -0.0395295758 0.058374930\n",
"PDCD4 5.579626e-02 -0.027653604 0.0270696469 -0.289718117\n",
" 9 10\n",
"ACC1 0.0114817550 -0.012752389\n",
"ACC_pS79 0.0446109106 -0.026128661\n",
"ACVRL1 0.0451577903 -0.347354807\n",
"Akt_pS473 0.0926598082 -0.097244266\n",
"PRAS40_pT246 0.0682105150 -0.041147230\n",
"Annexin.1 0.0526605879 0.019164135\n",
"AR -0.0425510415 0.081453198\n",
"A.Raf_pS299 0.0030370480 -0.024854489\n",
"ASNS 0.0705018700 -0.000600001\n",
"ATM -0.0664362513 0.077362522\n",
"Bad_pS112 0.0119289106 -0.100710658\n",
"Bak -0.0236948958 -0.036631421\n",
"Bap1.c.4 0.0260582048 0.061137537\n",
"Bax -0.0438368846 0.002664077\n",
"Bcl.2 -0.4090067674 0.133395459\n",
"Bcl.xL 0.0008857576 -0.024103568\n",
"Bim -0.0233034418 0.046015459\n",
"Beclin 0.0509081720 0.009786699\n",
"Bid -0.0854986397 -0.060598186\n",
"B.Raf -0.0344198321 0.151985225\n",
"BRCA2 0.0240657976 0.013884553\n",
"Caspase.7_cleavedD198 -0.0045306094 -0.058949736\n",
"Caveolin.1 -0.1671768965 0.051333255\n",
"Cyclin_B1 0.1528798894 0.185673663\n",
"Cyclin_D1 -0.1006977642 -0.170148614\n",
"Cyclin_E1 0.1440821308 0.007736146\n",
"Cyclin_E2 -0.0007672942 -0.019289437\n",
"E.Cadherin -0.0339441354 0.069161749\n",
"N.Cadherin 0.0632266327 0.017876046\n",
"P.Cadherin -0.0157946629 -0.066851655\n",
"p21 0.1272696400 -0.070974101\n",
"p27 -0.0418486426 0.028254105\n",
"p27_pT157 0.0026602109 -0.032013875\n",
"p27_pT198 -0.0076277832 -0.019257229\n",
"Chk1 0.0244436735 -0.005668330\n",
"Chk1_pS345 0.0216846891 0.012746231\n",
"Chk2 0.0774645629 -0.179509646\n",
"Chk2_pT68 0.2663443725 -0.077993954\n",
"Claudin.7 -0.1017987479 0.099981431\n",
"Collagen_VI -0.0912967043 0.008524742\n",
"beta.Catenin -0.0000509920 0.184855993\n",
"ARHI 0.0256562665 -0.231036781\n",
"Dvl3 0.2919486530 0.278113789\n",
"eEF2 0.0087893978 0.014485302\n",
"eEF2K 0.0355001523 0.105488709\n",
"EGFR -0.0339473632 -0.030156694\n",
"EGFR_pY1068 -0.0698220800 -0.053395517\n",
"EGFR_pY1173 -0.0205144876 -0.010791584\n",
"eIF4E -0.0739320945 -0.126362580\n",
"4E.BP1 -0.0172546276 -0.008676656\n",
"4E.BP1_pS65 0.0451709723 0.077385544\n",
"4E.BP1_pT70 0.0450598591 0.038727817\n",
"eIF4G 0.1461122410 0.189946728\n",
"HER2 -0.0136513465 -0.080286270\n",
"HER2_pY1248 0.0036445093 -0.082847651\n",
"HER3 -0.0368694827 -0.032804463\n",
"HER3_pY1289 0.0748268424 -0.039070364\n",
"MIG.6 0.0250656524 -0.070596313\n",
"ER.alpha 0.0335580674 0.012876857\n",
"ER.alpha_pS118 0.0520642215 -0.018212079\n",
"ETS.1 -0.0157225661 -0.103580696\n",
"FASN 0.0063518857 -0.038141014\n",
"Fibronectin -0.0011194370 -0.037079665\n",
"FoxM1 0.0970963894 0.128974406\n",
"FOXO3a -0.0765152415 0.014497060\n",
"FOXO3a_pS318_S321 -0.0132366244 -0.011959437\n",
"G6PD -0.0360939218 -0.037468093\n",
"GAB2 0.1168798415 0.019126130\n",
"GAPDH -0.1320396355 -0.071109679\n",
"GATA3 -0.0525255638 -0.022867855\n",
"GSK3.alpha.beta -0.0040756739 0.083468456\n",
"GSK3.alpha.beta_pS21_S9 -0.0077938375 -0.006356566\n",
"GSK3_pS9 0.0102960691 -0.023594230\n",
"HSP70 -0.0030839057 -0.132714557\n",
"IGFBP2 -0.0298943695 0.120678979\n",
"IRS1 -0.0318865937 -0.010640542\n",
"CD49b 0.0525262181 0.002449562\n",
"c.Jun_pS73 0.0403203821 -0.001307756\n",
"VEGFR2 -0.0535339976 0.106013548\n",
"c.Kit -0.1579858723 0.047462532\n",
"Lck -0.0738757809 -0.057426485\n",
"MEK1 -0.1110452532 0.038131300\n",
"MEK1_pS217_S221 -0.0024521375 -0.001351452\n",
"ERK2 -0.0270946368 -0.054761515\n",
"p38_MAPK -0.0309559062 0.003253390\n",
"p38_pT180_Y182 -0.0345738306 -0.088339644\n",
"JNK2 -0.4182992402 -0.007975316\n",
"c.Met_pY1235 0.0284006038 0.017920557\n",
"Mre11 0.0187340906 0.026156432\n",
"c.Myc -0.0163078605 -0.001689716\n",
"MYH11 -0.2553814960 0.288479720\n",
"NDRG1_pT346 0.0474405498 -0.055798171\n",
"NF2 -0.0034813792 -0.032068760\n",
"NF.kB.p65_pS536 0.0741507798 0.423519937\n",
"Notch1 -0.1622839848 -0.114651255\n",
"N.Ras 0.0242513748 -0.011715821\n",
"Heregulin -0.0059969500 -0.058164105\n",
"DJ.1 -0.2408137053 0.020894517\n",
"PCNA -0.0635315667 0.024288568\n",
"PDCD4 0.0520780157 -0.046847938\n",
"\n",
"\n",
"\n"
]
}
],
"source": [
"print(out2$factorizations)"
]
},
{
"cell_type": "code",
"execution_count": 82,
"metadata": {},
"outputs": [],
"source": [
"## Compare factorizations obtained through different methods\n",
"## INPUTS: \n",
"# factorizations = list of factorization results\n",
"# methods = list of ran factorization methods\n",
"# in.folder = path to input folder\n",
"# out.folder = path to output folder\n",
"# icluster.clusters = clustering result of iCluster\n",
"# intNMF.clusters = clustering result of intNMF\n",
"# number_cl = number of clusters\n",
"## OUPUTS: matrix of Jaccard Indexes is saved to table in out.folder\n",
"clusters_comparison <- function(factorizations, methods, in.folder, out.folder,number_cl) {\n",
"\n",
" ind <- 0\n",
" JI_final <- matrix(data=NA, nrow=number_cl, ncol=length(factorizations))\n",
" #cat(JI_final,\"\\n\")\n",
" # Read clusters imposed on simulated data \n",
" cl <- as.matrix(read.table(paste0(in.folder, \"clusters.txt\"), \n",
" sep=\"\\t\", row.names=1, header=TRUE))\n",
" #cat(\"cl:\",cl,\"\\t\")\n",
" cl2 <- as.matrix(as.numeric(cl[,2]))\n",
" cat(\"cl2:\",cl2[,1],\"\\n\")\n",
" rownames(cl2) <- cl[,1]\n",
" #print(length(factorizations))\n",
" # Assigning samples to cluster based on factors\n",
" for (i in 1:length(factorizations)) {\n",
" \n",
" if (methods[i]==\"iCluster\" || methods[i]==\"intNMF\") {\n",
" \n",
" } else {\n",
" \n",
" factors <- factorizations[[i]][[1]]\n",
" #print(factors)\n",
" # Clustering by Kmeans\n",
" JI_good <- numeric(0)\n",
" for (run in 1:1) {\n",
" kmeans.out <- kmeans(factors, centers=number_cl) \n",
" clust_iCluster <- as.matrix(kmeans.out$cluster)\n",
" cat(\"clust_iCluster:\",clust_iCluster,\"\\n\")\n",
" ######creation sets of samples\n",
" JI_mat <- numeric(0)\n",
" for (p in 1:number_cl) {\n",
" x1 <- rownames(clust_iCluster)[which(clust_iCluster[,1]==p)]\n",
" print(x1)\n",
" \n",
" row <- numeric(0)\n",
" for(j in 1:number_cl) {\n",
" x2 <- rownames(cl2)[which(cl2[,1]==j)]\n",
" cat(\"x2:\",x2,\"\\n\")\n",
" I <- length(intersect(x1,x2))#交集\n",
" cat(\"I:\",I,\"\\n\")\n",
" S <- I/(length(x1)+length(x2)-I)\n",
" cat(\"S:\",S,\"\\n\")\n",
" row <- cbind(row,S)\n",
" cat(\"row:\",row,\"\\n\")\n",
" }\n",
" JI_mat <- rbind(JI_mat,row)\n",
" cat(\"JI_mat:\",JI_mat,\"\\n\")\n",
" print(JI_mat)\n",
" \n",
" \n",
" }\n",
" JI_good <- rbind(JI_good,apply(JI_mat,1,max))\n",
" cat(\"JI_good:\",JI_good,\"\\n\")\n",
" }\n",
" JI_final[1:number_cl,i] <- apply(JI_good,2,mean)\n",
" }\n",
" }\n",
" \n",
" # Export JI values to a file \n",
" write.table(JI_final, paste0(out.folder,\"/JI.txt\"), sep=\"\\t\", row.names=FALSE, col.names=methods)\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": 83,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"cl2: 4 1 2 3 1 1 2 2 3 1 4 4 2 1 3 1 2 1 1 1 4 4 5 2 1 1 5 2 5 2 4 2 3 3 1 1 4 2 2 4 5 1 3 3 2 1 1 3 4 3 5 3 5 3 5 4 1 4 3 3 4 4 2 5 3 3 2 1 5 5 2 2 1 3 4 3 2 3 2 3 3 4 1 1 4 5 1 1 4 1 4 4 2 2 4 5 5 5 1 5 \n",
"[1] 1\n",
"clust_iCluster: 5 1 3 4 1 1 3 3 4 1 5 5 3 1 4 1 3 1 1 1 5 5 2 3 1 1 2 3 2 3 5 3 4 4 1 1 5 3 3 5 2 1 4 4 3 1 1 4 5 4 2 4 2 4 2 5 1 5 4 4 5 5 3 2 4 4 3 1 2 2 3 3 1 4 5 4 3 4 3 4 4 5 1 1 5 2 1 1 5 1 5 5 3 3 5 2 2 2 1 2 \n",
" [1] \"subject2\" \"subject5\" \"subject6\" \"subject10\" \"subject14\" \"subject16\"\n",
" [7] \"subject18\" \"subject19\" \"subject20\" \"subject25\" \"subject26\" \"subject35\"\n",
"[13] \"subject36\" \"subject42\" \"subject46\" \"subject47\" \"subject57\" \"subject68\"\n",
"[19] \"subject73\" \"subject83\" \"subject84\" \"subject87\" \"subject88\" \"subject90\"\n",
"[25] \"subject99\"\n",
"x2: subject2 subject5 subject6 subject10 subject14 subject16 subject18 subject19 subject20 subject25 subject26 subject35 subject36 subject42 subject46 subject47 subject57 subject68 subject73 subject83 subject84 subject87 subject88 subject90 subject99 \n",
"I: 25 \n",
"S: 1 \n",
"row: 1 \n",
"x2: subject3 subject7 subject8 subject13 subject17 subject24 subject28 subject30 subject32 subject38 subject39 subject45 subject63 subject67 subject71 subject72 subject77 subject79 subject93 subject94 \n",
"I: 0 \n",
"S: 0 \n",
"row: 1 0 \n",
"x2: subject4 subject9 subject15 subject33 subject34 subject43 subject44 subject48 subject50 subject52 subject54 subject59 subject60 subject65 subject66 subject74 subject76 subject78 subject80 subject81 \n",
"I: 0 \n",
"S: 0 \n",
"row: 1 0 0 \n",
"x2: subject1 subject11 subject12 subject21 subject22 subject31 subject37 subject40 subject49 subject56 subject58 subject61 subject62 subject75 subject82 subject85 subject89 subject91 subject92 subject95 \n",
"I: 0 \n",
"S: 0 \n",
"row: 1 0 0 0 \n",
"x2: subject23 subject27 subject29 subject41 subject51 subject53 subject55 subject64 subject69 subject70 subject86 subject96 subject97 subject98 subject100 \n",
"I: 0 \n",
"S: 0 \n",
"row: 1 0 0 0 0 \n",
"JI_mat: 1 0 0 0 0 \n",
" S S S S S\n",
"[1,] 1 0 0 0 0\n",
" [1] \"subject23\" \"subject27\" \"subject29\" \"subject41\" \"subject51\" \n",
" [6] \"subject53\" \"subject55\" \"subject64\" \"subject69\" \"subject70\" \n",
"[11] \"subject86\" \"subject96\" \"subject97\" \"subject98\" \"subject100\"\n",
"x2: subject2 subject5 subject6 subject10 subject14 subject16 subject18 subject19 subject20 subject25 subject26 subject35 subject36 subject42 subject46 subject47 subject57 subject68 subject73 subject83 subject84 subject87 subject88 subject90 subject99 \n",
"I: 0 \n",
"S: 0 \n",
"row: 0 \n",
"x2: subject3 subject7 subject8 subject13 subject17 subject24 subject28 subject30 subject32 subject38 subject39 subject45 subject63 subject67 subject71 subject72 subject77 subject79 subject93 subject94 \n",
"I: 0 \n",
"S: 0 \n",
"row: 0 0 \n",
"x2: subject4 subject9 subject15 subject33 subject34 subject43 subject44 subject48 subject50 subject52 subject54 subject59 subject60 subject65 subject66 subject74 subject76 subject78 subject80 subject81 \n",
"I: 0 \n",
"S: 0 \n",
"row: 0 0 0 \n",
"x2: subject1 subject11 subject12 subject21 subject22 subject31 subject37 subject40 subject49 subject56 subject58 subject61 subject62 subject75 subject82 subject85 subject89 subject91 subject92 subject95 \n",
"I: 0 \n",
"S: 0 \n",
"row: 0 0 0 0 \n",
"x2: subject23 subject27 subject29 subject41 subject51 subject53 subject55 subject64 subject69 subject70 subject86 subject96 subject97 subject98 subject100 \n",
"I: 15 \n",
"S: 1 \n",
"row: 0 0 0 0 1 \n",
"JI_mat: 1 0 0 0 0 0 0 0 0 1 \n",
" S S S S S\n",
"[1,] 1 0 0 0 0\n",
"[2,] 0 0 0 0 1\n",
" [1] \"subject3\" \"subject7\" \"subject8\" \"subject13\" \"subject17\" \"subject24\"\n",
" [7] \"subject28\" \"subject30\" \"subject32\" \"subject38\" \"subject39\" \"subject45\"\n",
"[13] \"subject63\" \"subject67\" \"subject71\" \"subject72\" \"subject77\" \"subject79\"\n",
"[19] \"subject93\" \"subject94\"\n",
"x2: subject2 subject5 subject6 subject10 subject14 subject16 subject18 subject19 subject20 subject25 subject26 subject35 subject36 subject42 subject46 subject47 subject57 subject68 subject73 subject83 subject84 subject87 subject88 subject90 subject99 \n",
"I: 0 \n",
"S: 0 \n",
"row: 0 \n",
"x2: subject3 subject7 subject8 subject13 subject17 subject24 subject28 subject30 subject32 subject38 subject39 subject45 subject63 subject67 subject71 subject72 subject77 subject79 subject93 subject94 \n",
"I: 20 \n",
"S: 1 \n",
"row: 0 1 \n",
"x2: subject4 subject9 subject15 subject33 subject34 subject43 subject44 subject48 subject50 subject52 subject54 subject59 subject60 subject65 subject66 subject74 subject76 subject78 subject80 subject81 \n",
"I: 0 \n",
"S: 0 \n",
"row: 0 1 0 \n",
"x2: subject1 subject11 subject12 subject21 subject22 subject31 subject37 subject40 subject49 subject56 subject58 subject61 subject62 subject75 subject82 subject85 subject89 subject91 subject92 subject95 \n",
"I: 0 \n",
"S: 0 \n",
"row: 0 1 0 0 \n",
"x2: subject23 subject27 subject29 subject41 subject51 subject53 subject55 subject64 subject69 subject70 subject86 subject96 subject97 subject98 subject100 \n",
"I: 0 \n",
"S: 0 \n",
"row: 0 1 0 0 0 \n",
"JI_mat: 1 0 0 0 0 1 0 0 0 0 0 0 0 1 0 \n",
" S S S S S\n",
"[1,] 1 0 0 0 0\n",
"[2,] 0 0 0 0 1\n",
"[3,] 0 1 0 0 0\n",
" [1] \"subject4\" \"subject9\" \"subject15\" \"subject33\" \"subject34\" \"subject43\"\n",
" [7] \"subject44\" \"subject48\" \"subject50\" \"subject52\" \"subject54\" \"subject59\"\n",
"[13] \"subject60\" \"subject65\" \"subject66\" \"subject74\" \"subject76\" \"subject78\"\n",
"[19] \"subject80\" \"subject81\"\n",
"x2: subject2 subject5 subject6 subject10 subject14 subject16 subject18 subject19 subject20 subject25 subject26 subject35 subject36 subject42 subject46 subject47 subject57 subject68 subject73 subject83 subject84 subject87 subject88 subject90 subject99 \n",
"I: 0 \n",
"S: 0 \n",
"row: 0 \n",
"x2: subject3 subject7 subject8 subject13 subject17 subject24 subject28 subject30 subject32 subject38 subject39 subject45 subject63 subject67 subject71 subject72 subject77 subject79 subject93 subject94 \n",
"I: 0 \n",
"S: 0 \n",
"row: 0 0 \n",
"x2: subject4 subject9 subject15 subject33 subject34 subject43 subject44 subject48 subject50 subject52 subject54 subject59 subject60 subject65 subject66 subject74 subject76 subject78 subject80 subject81 \n",
"I: 20 \n",
"S: 1 \n",
"row: 0 0 1 \n",
"x2: subject1 subject11 subject12 subject21 subject22 subject31 subject37 subject40 subject49 subject56 subject58 subject61 subject62 subject75 subject82 subject85 subject89 subject91 subject92 subject95 \n",
"I: 0 \n",
"S: 0 \n",
"row: 0 0 1 0 \n",
"x2: subject23 subject27 subject29 subject41 subject51 subject53 subject55 subject64 subject69 subject70 subject86 subject96 subject97 subject98 subject100 \n",
"I: 0 \n",
"S: 0 \n",
"row: 0 0 1 0 0 \n",
"JI_mat: 1 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 1 0 0 \n",
" S S S S S\n",
"[1,] 1 0 0 0 0\n",
"[2,] 0 0 0 0 1\n",
"[3,] 0 1 0 0 0\n",
"[4,] 0 0 1 0 0\n",
" [1] \"subject1\" \"subject11\" \"subject12\" \"subject21\" \"subject22\" \"subject31\"\n",
" [7] \"subject37\" \"subject40\" \"subject49\" \"subject56\" \"subject58\" \"subject61\"\n",
"[13] \"subject62\" \"subject75\" \"subject82\" \"subject85\" \"subject89\" \"subject91\"\n",
"[19] \"subject92\" \"subject95\"\n",
"x2: subject2 subject5 subject6 subject10 subject14 subject16 subject18 subject19 subject20 subject25 subject26 subject35 subject36 subject42 subject46 subject47 subject57 subject68 subject73 subject83 subject84 subject87 subject88 subject90 subject99 \n",
"I: 0 \n",
"S: 0 \n",
"row: 0 \n",
"x2: subject3 subject7 subject8 subject13 subject17 subject24 subject28 subject30 subject32 subject38 subject39 subject45 subject63 subject67 subject71 subject72 subject77 subject79 subject93 subject94 \n",
"I: 0 \n",
"S: 0 \n",
"row: 0 0 \n",
"x2: subject4 subject9 subject15 subject33 subject34 subject43 subject44 subject48 subject50 subject52 subject54 subject59 subject60 subject65 subject66 subject74 subject76 subject78 subject80 subject81 \n",
"I: 0 \n",
"S: 0 \n",
"row: 0 0 0 \n",
"x2: subject1 subject11 subject12 subject21 subject22 subject31 subject37 subject40 subject49 subject56 subject58 subject61 subject62 subject75 subject82 subject85 subject89 subject91 subject92 subject95 \n",
"I: 20 \n",
"S: 1 \n",
"row: 0 0 0 1 \n",
"x2: subject23 subject27 subject29 subject41 subject51 subject53 subject55 subject64 subject69 subject70 subject86 subject96 subject97 subject98 subject100 \n",
"I: 0 \n",
"S: 0 \n",
"row: 0 0 0 1 0 \n",
"JI_mat: 1 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 1 0 0 0 \n",
" S S S S S\n",
"[1,] 1 0 0 0 0\n",
"[2,] 0 0 0 0 1\n",
"[3,] 0 1 0 0 0\n",
"[4,] 0 0 1 0 0\n",
"[5,] 0 0 0 1 0\n",
"JI_good: 1 1 1 1 1 \n"
]
}
],
"source": [
"clusters_comparison(out2$factorizations, out2$method, \"../data/simulations_20210329212141/equal/5/\", \"./\", 5)"
]
},
{
"cell_type": "code",
"execution_count": 94,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" RGCCA\n",
"1 0.00\n",
"2 0.35\n",
"3 0.50\n",
"4 0.00\n",
"5 1.00\n",
" RGCCA_EQ\n",
"1 0.00\n",
"2 0.35\n",
"3 0.50\n",
"4 0.00\n",
"5 1.00\n"
]
},
{
"data": {
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Guv75Bzho8ac8XokRecPah32WM3x/8u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\nrkJggg==",
"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 420,
"width": 420
},
"text/plain": {
"height": 420,
"width": 420
}
},
"output_type": "display_data"
}
],
"source": [
"eq_file <- paste0(\"JI.txt\")\n",
"if(exists(\"JI.final\")) rm(JI.final)\n",
" \n",
" # Load clusters (equal distribution)\n",
"if(file.exists(eq_file)) {\n",
" JI.final <- read.table(eq_file, sep=\"\\t\", header=TRUE)\n",
" print(JI.final)\n",
" names(JI.final) <- paste0(names(JI.final), \"_EQ\")\n",
" print(JI.final)\n",
"}\n",
"#par(mar=c(25,4,2,2)+.1)\n",
"boxplot(JI.final, xaxt=\"none\", cex.axis=3.5, \n",
" col=c('gray','gray','red','red','blue','blue','blueviolet','blueviolet','deeppink','deeppink','chocolate1','chocolate1','darkgoldenrod','darkgoldenrod','green','green','darkturquoise','darkturquoise'), \n",
" ann=FALSE, outline=FALSE)"
]
},
{
"cell_type": "code",
"execution_count": 86,
"metadata": {},
"outputs": [
{
"ename": "ERROR",
"evalue": "Error in parse(text = x, srcfile = src): <text>:16:3: unexpected string constant\n30: }\n31: }'\n ^\n",
"output_type": "error",
"traceback": [
"Error in parse(text = x, srcfile = src): <text>:16:3: unexpected string constant\n30: }\n31: }'\n ^\nTraceback:\n"
]
}
],
"source": [
"# Save all boxplots in a single PDF output file\n",
"pdf(file=paste0(results_folder, \"simulated_boxplots.pdf\"), width = 15, height = 15, onefile = TRUE)\n",
"\n",
"# Output files for each distribution\n",
" eq_file <- paste0(\"JI.txt\")\n",
" if(exists(\"JI.final\")) rm(JI.final)\n",
" \n",
" # Load clusters (equal distribution)\n",
" if(file.exists(eq_file)) {\n",
" JI.final <- read.table(eq_file, sep=\"\\t\", header=TRUE)\n",
" print(JI.final)\n",
" names(JI.final) <- paste0(names(JI.final), \"_EQ\") \n",
" }\n",
" \n",
" # Load clusters (heterogeneous distribution)\n",
"'''\n",
" if(file.exists(het_file)) {\n",
" JI.het <- read.table(het_file, sep=\"\\t\", header=TRUE)\n",
" names_methods <- names(JI.het)\n",
" names(JI.het) <- paste0(names(JI.het), \"_HET\")\n",
"\n",
" # Aggregate results\n",
" if(exists(\"JI.final\")) {\n",
" JI.final <- data.frame(JI.het, JI.final)\n",
" new_order <- apply(expand.grid(c(\"_HET\", \"_EQ\"), names_methods)[, c(2,1)], 1, paste, collapse=\"\")\n",
" JI.final <- JI.final[, new_order]\n",
" }\n",
" else {\n",
" JI.final <- JI.het\n",
" }\n",
" }'''\n",
" \n",
" # Plot results\n",
" par(mar=c(25,4,2,2)+.1)\n",
" boxplot(JI.final, xaxt=\"none\", cex.axis=3.5, \n",
" col=c('gray','gray','red','red','blue','blue','blueviolet','blueviolet','deeppink','deeppink','chocolate1','chocolate1','darkgoldenrod','darkgoldenrod','green','green','darkturquoise','darkturquoise'), \n",
" ann=FALSE, outline=FALSE)\n",
" matplot(1:ncol(JI.final), t(JI.final), col=\"black\", pch=16, xaxt=\"none\", cex=0.8, add=TRUE)\n",
" axis(1, at=1:ncol(JI.final), labels=names(JI.final), \n",
" las=2, srt=45, cex=0.8, cex.lab=3.5, cex.axis=3.5, cex.main=1.5, cex.sub=1.5) \n",
" title(main=paste(i,\"clusters\",sep=\" \"), \n",
" cex.lab=0.75, line = -2.5, adj=0, cex.main=3.5)\n",
"dev.off()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "R",
"language": "R",
"name": "ir"
},
"language_info": {
"codemirror_mode": "r",
"file_extension": ".r",
"mimetype": "text/x-r-source",
"name": "R",
"pygments_lexer": "r",
"version": "3.5.1"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
Datasets
Models
