Nothing
R/getCircos.R
In canceR: A Graphical User Interface for accessing and modeling the Cancer Genomics Data of MSKCC
Defines functions
getCircos
Documented in
getCircos
#' get Circos Layout for selected studies and selected dimensions
#' @usage
#' getCircos(dimension)
#' @param dimension string (All,mRNA, CNA, Met,RPPA, miRNA, Mut)
#' @return a plot with Circos style
#' @export
#'
#' @examples
#' readRDS(paste(path.package("canceR"),"/extdata/rdata/Circos.rds", sep=""))
#' \dontrun{
#' getCircos(dimension ="All")
#' }
#' @import circlize
getCircos <- function(dimension){
#library(circlize)
circos.clear()
if(length(myGlobalEnv$ListProfData$Expression)!=0){
getCor_ExpCNAMet(myGlobalEnv$ListProfData$Expression, dimension = "Exp")
}
if(length(myGlobalEnv$ListProfData$CNA)!=0){
getCor_ExpCNAMet(myGlobalEnv$ListProfData$CNA, dimension = "CNA")
}
if(length(myGlobalEnv$ListMetData$HM450)!=0){
if (inherits(try(getCor_ExpCNAMet(myGlobalEnv$ListMetData$HM450, dimension = "MetHM450"), silent=TRUE),"try-error"))
{
msgNoHM27 <- paste("There is more than 2 empty matrices from HM450 Data. Skip HM450")
tkmessageBox(message=msgNoHM27, icon="warning")
} else{
print("Computing of Correlaton HM450 ...")
getCor_ExpCNAMet(myGlobalEnv$ListMetData$HM450, dimension = "MetHM450")
}
}
if(length(myGlobalEnv$ListMetData$HM27)!=0){
if (inherits(try(getCor_ExpCNAMet(myGlobalEnv$ListMetData$HM27, dimension = "MetHM27"), silent=TRUE),"try-error"))
{
msgNoHM27 <- paste("There is more than 2 empty matrices from HM27 Data. Skip HM27")
tkmessageBox(message=msgNoHM27, icon="warning")
} else{
print("Computing of Correlaton HM27 ...")
getCor_ExpCNAMet(myGlobalEnv$ListMetData$HM27, dimension = "MetHM27")
}
}
if(length(myGlobalEnv$ListProfData$RPPA)!=0){
getCor_ExpCNAMet(myGlobalEnv$ListProfData$RPPA, dimension = "RPPA")
}
if(length(myGlobalEnv$ListProfData$miRNA)!=0){
getCor_ExpCNAMet(myGlobalEnv$ListProfData$miRNA, dimension = "miRNA")
}
#df1 = read.table("~/CGDS-R//Cor_Exp")
#df2 = read.table("~/CGDS-R//Cor_CNA")
if(dimension == "Exp"){
#all_disease <- unique(myGlobalEnv$Cor_Exp[[2]])
all_disease <- myGlobalEnv$checked_Studies
#all_genes <- unique(myGlobalEnv$Cor_Exp[[1]])
all_genes <- myGlobalEnv$GeneList
n_gene <- length(all_genes)
n_disease <- length(all_disease) - 1
} else if(dimension=="MetHM450"){
all_disease <- unique(myGlobalEnv$Cor_Met$HM450[[2]])
all_genes <- unique(myGlobalEnv$Cor_Met$HM450[[1]])
n_gene <- length(all_genes)
n_disease <- length(all_disease) - 1
} else if(dimension=="MetHM27") {
all_disease <- unique(myGlobalEnv$Cor_Met$HM27[[2]])
all_genes <- unique(myGlobalEnv$Cor_Met$HM27[[1]])
n_gene <- length(all_genes)
n_disease <- length(all_disease) - 1
} else if (dimension=="CNA"){
all_disease <- unique(myGlobalEnv$Cor_CNA[[2]])
all_genes <- unique(myGlobalEnv$Cor_CNA[[1]])
n_gene <- length(all_genes)
n_disease <- length(all_disease) - 1
} else if (dimension=="All"){
all_disease <- unique(myGlobalEnv$Cor_Exp[[2]])
#all_disease <- myGlobalEnv$checked_Studies
all_genes <- unique(myGlobalEnv$Cor_Exp[[1]])
#all_genes <- myGlobalEnv$GeneList
n_gene <- length(all_genes)
n_disease <- length(all_disease) - 1
}
if(exists("GeneListMSigDB", envir = myGlobalEnv)){
## set color for Gene Sets
gene_set <- myGlobalEnv$GeneListMSigDB[[1]]
names(gene_set) <- myGlobalEnv$GeneListMSigDB[[2]]
gene_set_col <- rand_color(length(unique(gene_set)))
names(gene_set_col) <- unique(gene_set)
}
## Dialog Option Circos
dialogOptionCircos()
circos.par(cell.padding = c(0, 0, 0, 0), start.degree = 90)
circos.initialize(factors = all_disease, xlim = c(0, n_gene))
## Disease/genes Track
circos.trackPlotRegion(ylim = c(0, 1), panel.fun = function(x, y) {
disease = get.cell.meta.data("sector.index")
xlim = get.cell.meta.data("xlim")
ylim = get.cell.meta.data("ylim")
circos.text(mean(xlim), min(ylim)+.2, disease, facing = "bending.inside" , cex= 0.6)
## Add Gene Symbol
## replace 1 by 0 from Data frames
if(length(nrow(myGlobalEnv$Freq_DfMutData))==1){
myGlobalEnv$Freq_DfMutData[is.na(myGlobalEnv$Freq_DfMutData)] <- 0
}
if(length(nrow(myGlobalEnv$Cor_Exp))==1){
myGlobalEnv$Cor_Exp[,c(-1,-2)][myGlobalEnv$Cor_Exp[,c(-1,-2)]==1] <- 0
}
if(length(nrow(myGlobalEnv$Cor_CNA))==1){
myGlobalEnv$Cor_CNA[,c(-1,-2)][myGlobalEnv$Cor_CNA[,c(-1,-2)]==1] <- 0
}
if(length(nrow(myGlobalEnv$Cor_Met$HM450))==1){
myGlobalEnv$Cor_Met$HM450[,c(-1,-2)][myGlobalEnv$Cor_Met$HM450[,c(-1,-2)]==1] <- 0
}
if(length(nrow(myGlobalEnv$Cor_Met$HM27))==1){
myGlobalEnv$Cor_Met$HM27[,c(-1,-2)][myGlobalEnv$Cor_Met$HM27[,c(-1,-2)]==1] <- 0
}
if(length(nrow(myGlobalEnv$ListProfData$RPPA))==1){
myGlobalEnv$RPPA[,c(-1,-2)][myGlobalEnv$RPPA[,c(-1,-2)]==1] <- 0
}
## plot only gene with high Level > Threshold
for(i in 1:n_gene){
if(myGlobalEnv$ReturnCBoxThrCircos[7] == 1&&max(myGlobalEnv$Freq_DfMutData[i,]) > myGlobalEnv$ReturnThreshCircos[7] ){
circos.text(min(xlim)+i, max(ylim)+.5, all_genes[i], facing="clockwise", cex = 0.5, col="darkgoldenrod3")
#circos.link("brca_tcga", i , "brca_tcga", 365,rou1=0.8,rou2=0.8, col = "#00000040")
}else if(myGlobalEnv$ReturnCBoxThrCircos[1] == 1&&max(myGlobalEnv$Cor_Exp[i,c(-1,-2)]) > myGlobalEnv$ReturnThreshCircos[1]){
circos.text(min(xlim)+i, max(ylim)+.5, all_genes[i], facing="clockwise", cex = 0.5,col="red3")
#circos.link("brca_tcga", i , "brca_tcga", 365,rou1=0.8,rou2=0.8, col = "#00000040")
}else if(myGlobalEnv$ReturnCBoxThrCircos[1] == 1&&max(myGlobalEnv$Cor_Exp[i,c(-1,-2)]) < -(myGlobalEnv$ReturnThreshCircos[1])){
circos.text(min(xlim)+i, max(ylim)+.5, all_genes[i], facing="clockwise", cex = 0.5,col="blue")
}else if(myGlobalEnv$ReturnCBoxThrCircos[2] == 1&&max(myGlobalEnv$Cor_CNA[i,c(-1,-2)]) > myGlobalEnv$ReturnThreshCircos[2]){
circos.text(min(xlim)+i, max(ylim)+.5, all_genes[i], facing="clockwise", cex = 0.5, col="green4")
#circos.link("brca_tcga", i , "brca_tcga", 365,rou1=0.8,rou2=0.8, col = "#00000040")
}else if(myGlobalEnv$ReturnCBoxThrCircos[3] == 1 && max(myGlobalEnv$Cor_Met$HM450[i,c(-1,-2)]) > myGlobalEnv$ReturnThreshCircos[3]){
circos.text(min(xlim)+i, max(ylim)+.5, all_genes[i], facing="clockwise", cex = 0.5,col="mediumorchid4")
#circos.link("brca_tcga", i , "brca_tcga", 365,rou1=0.8,rou2=0.8, col = "#00000040")
}else if(myGlobalEnv$ReturnCBoxThrCircos[3] == 1 && max(myGlobalEnv$Cor_Met$HM450[i,c(-1,-2)])< -(myGlobalEnv$ReturnThreshCircos[3])){
circos.text(min(xlim)+i, max(ylim)+.5, all_genes[i], facing="clockwise", cex = 0.5,col="springgreen4")
}else if(myGlobalEnv$ReturnCBoxThrCircos[4] == 1&&max(myGlobalEnv$Cor_Met$HM27[i,c(-1,-2)]) > myGlobalEnv$ReturnThreshCircos[4] ){
circos.text(min(xlim)+i, max(ylim)+.5, all_genes[i], facing="clockwise", cex = 0.5, col="mediumorchid4")
#circos.link("brca_tcga", i , "brca_tcga", 365,rou1=0.8,rou2=0.8, col = "#00000040")
}else if(myGlobalEnv$ReturnCBoxThrCircos[4] == 1 && max(myGlobalEnv$Cor_Met$HM27[i,c(-1,-2)])< -(myGlobalEnv$ReturnThreshCircos[4])){
circos.text(min(xlim)+i, max(ylim)+.5, all_genes[i], facing="clockwise", cex = 0.5,col="springgreen4")
}else if(myGlobalEnv$ReturnCBoxThrCircos[5] == 1&& max(myGlobalEnv$Cor_RPPA[i,c(-1,-2)]) > myGlobalEnv$ReturnThreshCircos[5]){
circos.text(min(xlim)+i, max(ylim)+.5, all_genes[i], facing="clockwise", cex = 0.5,col="red3" )
#circos.link("brca_tcga", i , "brca_tcga", 365,rou1=0.8,rou2=0.8, col = "#00000040")
}else if (myGlobalEnv$ReturnCBoxThrCircos[5] == 1&& max(myGlobalEnv$Cor_RPPA[i,c(-1,-2)]) < -(myGlobalEnv$ReturnThreshCircos[5])){
circos.text(min(xlim)+i, max(ylim)+.5, all_genes[i], facing="clockwise", cex = 0.5,col="blue" )
}else if(myGlobalEnv$ReturnCBoxThrCircos[6] == 1&&max(myGlobalEnv$Cor_miRNA[i,c(-1,-2)]) > myGlobalEnv$ReturnThreshCircos[6]){
circos.text(min(xlim)+i, max(ylim)+.5, all_genes[i], facing="clockwise", cex = 0.5, col="red2")
#circos.link("brca_tcga", i , "brca_tcga", 365,rou1=0.8,rou2=0.8, col = "#00000040")
}else if(myGlobalEnv$ReturnCBoxThrCircos[6] == 1&&max(abs(myGlobalEnv$Cor_miRNA[i,c(-1,-2)])) < -(myGlobalEnv$ReturnThreshCircos[6])){
circos.text(min(xlim)+i, max(ylim)+.5, all_genes[i], facing="clockwise", cex = 0.5, col="blue")
}
}
}, track.height = 0.05, bg.border = NA)
## GetSet Track
if(exists("GeneListMSigDB", envir = myGlobalEnv)){
circos.trackPlotRegion(ylim = c(0, 1), panel.fun = function(x, y) {
xlim = get.cell.meta.data("xlim")
ylim = get.cell.meta.data("ylim")
disease = get.cell.meta.data("sector.index")
# genes that belong to this disease
genes = myGlobalEnv$Cor_Exp[myGlobalEnv$Cor_Exp[[2]] == disease, 1]
## rearrange factor geneList as in all_gene (No alphabetic)
genes <- factor(genes, levels = all_genes)
for(i in seq_along(genes)) {
circos.rect(i-0.5, 0, i+0.5, 1, col = gene_set_col[gene_set[genes[i]]], border = NA)
}
circos.text(min(xlim)+15, max(ylim)+0.5, "Gene Sets", facing= "bending.inside" ,cex = 0.5, nice.facing=TRUE)
legend(x=-1.1, y=-0.8, pch = 15, col = gene_set_col, legend = names(gene_set_col),bty = "n" ,y.intersp = 0.7,pt.cex = 1, cex=0.455)
}, track.height = 0.02, bg.border = "black")
}
# Track for Gene Expression
if(length(nrow(myGlobalEnv$Cor_Exp))==1 && ncol(myGlobalEnv$Cor_Exp) == n_disease +3&&myGlobalEnv$ReturnCBoxCircos[1]==1){
print("Getting Track for Gene Expression...")
circos.trackPlotRegion(ylim = c(0, n_disease), panel.fun = function(x, y) {
xlim = get.cell.meta.data("xlim")
ylim = get.cell.meta.data("ylim")
disease <- get.cell.meta.data("sector.index")
mat <- as.matrix(myGlobalEnv$Cor_Exp[myGlobalEnv$Cor_Exp[[2]] == disease, 3:(n_disease+3)])
mat <- mat[, -which(all_disease %in% disease)]
corr_col_fun <- colorRamp2(c(-1,0 ,1), c("blue","white" ,"red3"))
for(i in seq_len(n_gene)) {
for(j in seq_len(n_disease)) {
circos.rect(i-1, j-1, i, j, col = corr_col_fun(mat[i, j]), border = NA)
}
}
circos.text(min(xlim)+15, max(ylim), "mRNA Exp", facing= "bending.inside" ,cex = 0.5)
legend(x=-1.11, y=1.1, title = "mRNA",pch = 15, col = corr_col_fun(seq(-1,1, by = 0.5)), legend = seq(-1, 1, by = 0.5),bty = "n",y.intersp=0.7,pt.cex = 1, cex=0.5)
}, track.height = 0.1)
}
# Track for CNA
if(length(nrow(myGlobalEnv$Cor_CNA))==1 && ncol(myGlobalEnv$Cor_CNA) == n_disease +3&&myGlobalEnv$ReturnCBoxCircos[2]==1){
print("Getting Track for CNA...")
circos.trackPlotRegion(ylim = c(0, n_disease), panel.fun = function(x, y) {
xlim = get.cell.meta.data("xlim")
ylim = get.cell.meta.data("ylim")
disease <- get.cell.meta.data("sector.index")
mat <- as.matrix(myGlobalEnv$Cor_CNA[myGlobalEnv$Cor_CNA[[2]] == disease, 3:(n_disease+3)])
mat <- mat[, -which(all_disease %in% disease)]
corr_col_fun <- colorRamp2(c( 0.7,0.8 ,1), c("white","greenyellow" ,"green4"))
for(i in seq_len(n_gene)) {
for(j in seq_len(n_disease)) {
circos.rect(i-1, j-1, i, j, col = corr_col_fun(mat[i, j]), border = NA)
}
}
circos.text(min(xlim)+15, max(ylim), "CNA", facing= "bending.inside" ,cex = 0.5)
legend(x=0.6,y=1.1, title = "CNA",pch = 15, col = corr_col_fun(seq(0.8, 1, by = 0.1)), legend = seq(0.8, 1, by = 0.1),bty = "n", y.intersp=0.7, pt.cex = 1, cex=0.5)
}, track.height = 0.1)
}
##track for methylation HM450
if(length(nrow(myGlobalEnv$Cor_Met$HM450))==1 && ncol(myGlobalEnv$Cor_Met$HM450) == n_disease +3&&myGlobalEnv$ReturnCBoxCircos[3]==1){
print("getting Track for methylation HM450...")
circos.trackPlotRegion(ylim = c(0, n_disease), panel.fun = function(x, y) {
xlim = get.cell.meta.data("xlim")
ylim = get.cell.meta.data("ylim")
disease = get.cell.meta.data("sector.index")
mat = as.matrix(myGlobalEnv$Cor_Met$HM450[myGlobalEnv$Cor_Met$HM450[[2]] == disease, 3:(n_disease+3)])
mat = mat[, -which(all_disease %in% disease)]
corr_col_fun = colorRamp2(c( -1,0 ,1), c("springgreen4","white" ,"mediumorchid4"))
for(i in seq_len(n_gene)) {
for(j in seq_len(n_disease)) {
circos.rect(i-1, j-1, i, j, col = corr_col_fun(mat[i, j]), border = NA)
}
}
circos.text(min(xlim)+15, max(ylim), "Met HM450", facing= "bending.inside" ,cex = 0.5)
legend(x=-0.9,y=1.1, title = "Meth",pch = 15, col = corr_col_fun(seq(-1,1, by = 0.5)), legend = seq(-1, 1, by = 0.5),bty = "n" ,y.intersp=0.7,pt.cex = 1, cex=0.5)
}, track.height = 0.1)
}
##track for methylation HM27
if(length(nrow(myGlobalEnv$Cor_Met$HM27))==1 && ncol(myGlobalEnv$Cor_Met$HM27) == n_disease +3 && myGlobalEnv$ReturnCBoxCircos[4]==1){
print("getting Track for methylation HM27...")
circos.trackPlotRegion(ylim = c(0, n_disease), panel.fun = function(x, y) {
xlim = get.cell.meta.data("xlim")
ylim = get.cell.meta.data("ylim")
disease = get.cell.meta.data("sector.index")
mat = as.matrix(myGlobalEnv$Cor_Met$HM27[myGlobalEnv$Cor_Met$HM27[[2]] == disease, 3:(n_disease+3)])
mat = mat[, -which(all_disease %in% disease)]
corr_col_fun = colorRamp2(c(-1,0 ,1), c("springgreen4","white" ,"mediumorchid4"))
for(i in seq_len(n_gene)) {
for(j in seq_len(n_disease)) {
circos.rect(i-1, j-1, i, j, col = corr_col_fun(mat[i, j]), border = NA)
}
}
circos.text(min(xlim)+15, max(ylim), "Met HM27", facing= "bending.inside" ,cex = 0.5)
legend(x=-0.9,y=1.1, title = "Meth",pch = 15, col = corr_col_fun(seq(-1,1, by = 0.5)), legend = seq(-1, 1, by = 0.5),bty = "n" ,y.intersp=0.7,pt.cex = 1, cex=0.5)
}, track.height = 0.1)
}
# Track for Reverse Phase Protein Affinity
if(length(nrow(myGlobalEnv$Cor_RPPA))==1 && ncol(myGlobalEnv$Cor_RPPA) == n_disease +3 &&myGlobalEnv$ReturnCBoxCircos[5]==1){
print("Getting Track for RPPA...")
circos.trackPlotRegion(ylim = c(0, n_disease), panel.fun = function(x, y) {
xlim = get.cell.meta.data("xlim")
ylim = get.cell.meta.data("ylim")
disease <- get.cell.meta.data("sector.index")
mat <- as.matrix(myGlobalEnv$Cor_RPPA[myGlobalEnv$Cor_Exp[[2]] == disease, 3:(n_disease+3)])
mat <- mat[, -which(all_disease %in% disease)]
corr_col_fun <- colorRamp2(c(-1,0 ,1), c("blue","white" ,"red3"))
for(i in seq_len(n_gene)) {
for(j in seq_len(n_disease)) {
circos.rect(i-1, j-1, i, j, col = corr_col_fun(mat[i, j]), border = NA)
}
}
circos.text(min(xlim)+15, max(ylim), "RPPA", facing= "bending.inside" ,cex = 0.5)
#legend("bottomleft", title = "RPPA",pch = 15, col = corr_col_fun(seq(-1,1, by = 0.5)), legend = seq(-1, 1, by = 0.5), pt.cex = 1, cex=0.6)
}, track.height = 0.1)
}
## Track for miRNA
## track for Gene Mutation
if(length(nrow(myGlobalEnv$Freq_DfMutData))==1 &&myGlobalEnv$ReturnCBoxCircos[7]==1){
print("Getting Track for Gene Mutation Frequency...")
mat <- as.matrix(myGlobalEnv$Freq_DfMutData)
mat[is.na(mat)] <- 0
corr_col_fun <- colorRamp2(c(median(mat),mean(mat),30,70,max(mat)), c("white","white","gold","darkgoldenrod2", "darkgoldenrod4"))
circos.trackPlotRegion(ylim = c(0, 1), panel.fun = function(x, y) {
xlim = get.cell.meta.data("xlim")
ylim = get.cell.meta.data("ylim")
disease <- get.cell.meta.data("sector.index")
mut = mat[, disease]
names(mut) = rownames(mat)
mut[is.na(mut)] <- 0
for(i in seq_len(n_gene)) {
circos.rect(i-0.5, 0, i+0.5, 1, col = corr_col_fun(mut[i]), border = NA)
}
circos.text(min(xlim)+15, max(ylim), "Mut", facing= "bending.inside" ,cex = 0.5)
}, track.height = 0.1)
interval <- (max(mat)-20)%/%3
legend(x=0.8,y=1.1, title = "Mutation",pch = 15, col = corr_col_fun(seq(20, max(mat), by = interval)), legend = seq(20, max(mat), by =interval ),bty = "n", y.intersp = 0.7 ,pt.cex = 1, cex=0.5)
#legend(x=-0.9,y=1.1, title = "Meth",pch = 15, col = corr_col_fun(seq(-1,1, by = 0.5)), legend = seq(-1, 1, by = 0.5),bty = "n" ,y.intersp=0.7,pt.cex = 1, cex=0.5)
}
circos.clear()
}
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Defines functions getCircos
Documented in getCircos
#' get Circos Layout for selected studies and selected dimensions
#' @usage
#' getCircos(dimension)
#' @param dimension string (All,mRNA, CNA, Met,RPPA, miRNA, Mut)
#' @return a plot with Circos style
#' @export
#'
#' @examples
#' readRDS(paste(path.package("canceR"),"/extdata/rdata/Circos.rds", sep=""))
#' \dontrun{
#' getCircos(dimension ="All")
#' }
#' @import circlize
getCircos <- function(dimension){
#library(circlize)
circos.clear()
if(length(myGlobalEnv$ListProfData$Expression)!=0){
getCor_ExpCNAMet(myGlobalEnv$ListProfData$Expression, dimension = "Exp")
}
if(length(myGlobalEnv$ListProfData$CNA)!=0){
getCor_ExpCNAMet(myGlobalEnv$ListProfData$CNA, dimension = "CNA")
}
if(length(myGlobalEnv$ListMetData$HM450)!=0){
if (inherits(try(getCor_ExpCNAMet(myGlobalEnv$ListMetData$HM450, dimension = "MetHM450"), silent=TRUE),"try-error"))
{
msgNoHM27 <- paste("There is more than 2 empty matrices from HM450 Data. Skip HM450")
tkmessageBox(message=msgNoHM27, icon="warning")
} else{
print("Computing of Correlaton HM450 ...")
getCor_ExpCNAMet(myGlobalEnv$ListMetData$HM450, dimension = "MetHM450")
}
}
if(length(myGlobalEnv$ListMetData$HM27)!=0){
if (inherits(try(getCor_ExpCNAMet(myGlobalEnv$ListMetData$HM27, dimension = "MetHM27"), silent=TRUE),"try-error"))
{
msgNoHM27 <- paste("There is more than 2 empty matrices from HM27 Data. Skip HM27")
tkmessageBox(message=msgNoHM27, icon="warning")
} else{
print("Computing of Correlaton HM27 ...")
getCor_ExpCNAMet(myGlobalEnv$ListMetData$HM27, dimension = "MetHM27")
}
}
if(length(myGlobalEnv$ListProfData$RPPA)!=0){
getCor_ExpCNAMet(myGlobalEnv$ListProfData$RPPA, dimension = "RPPA")
}
if(length(myGlobalEnv$ListProfData$miRNA)!=0){
getCor_ExpCNAMet(myGlobalEnv$ListProfData$miRNA, dimension = "miRNA")
}
#df1 = read.table("~/CGDS-R//Cor_Exp")
#df2 = read.table("~/CGDS-R//Cor_CNA")
if(dimension == "Exp"){
#all_disease <- unique(myGlobalEnv$Cor_Exp[[2]])
all_disease <- myGlobalEnv$checked_Studies
#all_genes <- unique(myGlobalEnv$Cor_Exp[[1]])
all_genes <- myGlobalEnv$GeneList
n_gene <- length(all_genes)
n_disease <- length(all_disease) - 1
} else if(dimension=="MetHM450"){
all_disease <- unique(myGlobalEnv$Cor_Met$HM450[[2]])
all_genes <- unique(myGlobalEnv$Cor_Met$HM450[[1]])
n_gene <- length(all_genes)
n_disease <- length(all_disease) - 1
} else if(dimension=="MetHM27") {
all_disease <- unique(myGlobalEnv$Cor_Met$HM27[[2]])
all_genes <- unique(myGlobalEnv$Cor_Met$HM27[[1]])
n_gene <- length(all_genes)
n_disease <- length(all_disease) - 1
} else if (dimension=="CNA"){
all_disease <- unique(myGlobalEnv$Cor_CNA[[2]])
all_genes <- unique(myGlobalEnv$Cor_CNA[[1]])
n_gene <- length(all_genes)
n_disease <- length(all_disease) - 1
} else if (dimension=="All"){
all_disease <- unique(myGlobalEnv$Cor_Exp[[2]])
#all_disease <- myGlobalEnv$checked_Studies
all_genes <- unique(myGlobalEnv$Cor_Exp[[1]])
#all_genes <- myGlobalEnv$GeneList
n_gene <- length(all_genes)
n_disease <- length(all_disease) - 1
}
if(exists("GeneListMSigDB", envir = myGlobalEnv)){
## set color for Gene Sets
gene_set <- myGlobalEnv$GeneListMSigDB[[1]]
names(gene_set) <- myGlobalEnv$GeneListMSigDB[[2]]
gene_set_col <- rand_color(length(unique(gene_set)))
names(gene_set_col) <- unique(gene_set)
}
## Dialog Option Circos
dialogOptionCircos()
circos.par(cell.padding = c(0, 0, 0, 0), start.degree = 90)
circos.initialize(factors = all_disease, xlim = c(0, n_gene))
## Disease/genes Track
circos.trackPlotRegion(ylim = c(0, 1), panel.fun = function(x, y) {
disease = get.cell.meta.data("sector.index")
xlim = get.cell.meta.data("xlim")
ylim = get.cell.meta.data("ylim")
circos.text(mean(xlim), min(ylim)+.2, disease, facing = "bending.inside" , cex= 0.6)
## Add Gene Symbol
## replace 1 by 0 from Data frames
if(length(nrow(myGlobalEnv$Freq_DfMutData))==1){
myGlobalEnv$Freq_DfMutData[is.na(myGlobalEnv$Freq_DfMutData)] <- 0
}
if(length(nrow(myGlobalEnv$Cor_Exp))==1){
myGlobalEnv$Cor_Exp[,c(-1,-2)][myGlobalEnv$Cor_Exp[,c(-1,-2)]==1] <- 0
}
if(length(nrow(myGlobalEnv$Cor_CNA))==1){
myGlobalEnv$Cor_CNA[,c(-1,-2)][myGlobalEnv$Cor_CNA[,c(-1,-2)]==1] <- 0
}
if(length(nrow(myGlobalEnv$Cor_Met$HM450))==1){
myGlobalEnv$Cor_Met$HM450[,c(-1,-2)][myGlobalEnv$Cor_Met$HM450[,c(-1,-2)]==1] <- 0
}
if(length(nrow(myGlobalEnv$Cor_Met$HM27))==1){
myGlobalEnv$Cor_Met$HM27[,c(-1,-2)][myGlobalEnv$Cor_Met$HM27[,c(-1,-2)]==1] <- 0
}
if(length(nrow(myGlobalEnv$ListProfData$RPPA))==1){
myGlobalEnv$RPPA[,c(-1,-2)][myGlobalEnv$RPPA[,c(-1,-2)]==1] <- 0
}
## plot only gene with high Level > Threshold
for(i in 1:n_gene){
if(myGlobalEnv$ReturnCBoxThrCircos[7] == 1&&max(myGlobalEnv$Freq_DfMutData[i,]) > myGlobalEnv$ReturnThreshCircos[7] ){
circos.text(min(xlim)+i, max(ylim)+.5, all_genes[i], facing="clockwise", cex = 0.5, col="darkgoldenrod3")
#circos.link("brca_tcga", i , "brca_tcga", 365,rou1=0.8,rou2=0.8, col = "#00000040")
}else if(myGlobalEnv$ReturnCBoxThrCircos[1] == 1&&max(myGlobalEnv$Cor_Exp[i,c(-1,-2)]) > myGlobalEnv$ReturnThreshCircos[1]){
circos.text(min(xlim)+i, max(ylim)+.5, all_genes[i], facing="clockwise", cex = 0.5,col="red3")
#circos.link("brca_tcga", i , "brca_tcga", 365,rou1=0.8,rou2=0.8, col = "#00000040")
}else if(myGlobalEnv$ReturnCBoxThrCircos[1] == 1&&max(myGlobalEnv$Cor_Exp[i,c(-1,-2)]) < -(myGlobalEnv$ReturnThreshCircos[1])){
circos.text(min(xlim)+i, max(ylim)+.5, all_genes[i], facing="clockwise", cex = 0.5,col="blue")
}else if(myGlobalEnv$ReturnCBoxThrCircos[2] == 1&&max(myGlobalEnv$Cor_CNA[i,c(-1,-2)]) > myGlobalEnv$ReturnThreshCircos[2]){
circos.text(min(xlim)+i, max(ylim)+.5, all_genes[i], facing="clockwise", cex = 0.5, col="green4")
#circos.link("brca_tcga", i , "brca_tcga", 365,rou1=0.8,rou2=0.8, col = "#00000040")
}else if(myGlobalEnv$ReturnCBoxThrCircos[3] == 1 && max(myGlobalEnv$Cor_Met$HM450[i,c(-1,-2)]) > myGlobalEnv$ReturnThreshCircos[3]){
circos.text(min(xlim)+i, max(ylim)+.5, all_genes[i], facing="clockwise", cex = 0.5,col="mediumorchid4")
#circos.link("brca_tcga", i , "brca_tcga", 365,rou1=0.8,rou2=0.8, col = "#00000040")
}else if(myGlobalEnv$ReturnCBoxThrCircos[3] == 1 && max(myGlobalEnv$Cor_Met$HM450[i,c(-1,-2)])< -(myGlobalEnv$ReturnThreshCircos[3])){
circos.text(min(xlim)+i, max(ylim)+.5, all_genes[i], facing="clockwise", cex = 0.5,col="springgreen4")
}else if(myGlobalEnv$ReturnCBoxThrCircos[4] == 1&&max(myGlobalEnv$Cor_Met$HM27[i,c(-1,-2)]) > myGlobalEnv$ReturnThreshCircos[4] ){
circos.text(min(xlim)+i, max(ylim)+.5, all_genes[i], facing="clockwise", cex = 0.5, col="mediumorchid4")
#circos.link("brca_tcga", i , "brca_tcga", 365,rou1=0.8,rou2=0.8, col = "#00000040")
}else if(myGlobalEnv$ReturnCBoxThrCircos[4] == 1 && max(myGlobalEnv$Cor_Met$HM27[i,c(-1,-2)])< -(myGlobalEnv$ReturnThreshCircos[4])){
circos.text(min(xlim)+i, max(ylim)+.5, all_genes[i], facing="clockwise", cex = 0.5,col="springgreen4")
}else if(myGlobalEnv$ReturnCBoxThrCircos[5] == 1&& max(myGlobalEnv$Cor_RPPA[i,c(-1,-2)]) > myGlobalEnv$ReturnThreshCircos[5]){
circos.text(min(xlim)+i, max(ylim)+.5, all_genes[i], facing="clockwise", cex = 0.5,col="red3" )
#circos.link("brca_tcga", i , "brca_tcga", 365,rou1=0.8,rou2=0.8, col = "#00000040")
}else if (myGlobalEnv$ReturnCBoxThrCircos[5] == 1&& max(myGlobalEnv$Cor_RPPA[i,c(-1,-2)]) < -(myGlobalEnv$ReturnThreshCircos[5])){
circos.text(min(xlim)+i, max(ylim)+.5, all_genes[i], facing="clockwise", cex = 0.5,col="blue" )
}else if(myGlobalEnv$ReturnCBoxThrCircos[6] == 1&&max(myGlobalEnv$Cor_miRNA[i,c(-1,-2)]) > myGlobalEnv$ReturnThreshCircos[6]){
circos.text(min(xlim)+i, max(ylim)+.5, all_genes[i], facing="clockwise", cex = 0.5, col="red2")
#circos.link("brca_tcga", i , "brca_tcga", 365,rou1=0.8,rou2=0.8, col = "#00000040")
}else if(myGlobalEnv$ReturnCBoxThrCircos[6] == 1&&max(abs(myGlobalEnv$Cor_miRNA[i,c(-1,-2)])) < -(myGlobalEnv$ReturnThreshCircos[6])){
circos.text(min(xlim)+i, max(ylim)+.5, all_genes[i], facing="clockwise", cex = 0.5, col="blue")
}
}
}, track.height = 0.05, bg.border = NA)
## GetSet Track
if(exists("GeneListMSigDB", envir = myGlobalEnv)){
circos.trackPlotRegion(ylim = c(0, 1), panel.fun = function(x, y) {
xlim = get.cell.meta.data("xlim")
ylim = get.cell.meta.data("ylim")
disease = get.cell.meta.data("sector.index")
# genes that belong to this disease
genes = myGlobalEnv$Cor_Exp[myGlobalEnv$Cor_Exp[[2]] == disease, 1]
## rearrange factor geneList as in all_gene (No alphabetic)
genes <- factor(genes, levels = all_genes)
for(i in seq_along(genes)) {
circos.rect(i-0.5, 0, i+0.5, 1, col = gene_set_col[gene_set[genes[i]]], border = NA)
}
circos.text(min(xlim)+15, max(ylim)+0.5, "Gene Sets", facing= "bending.inside" ,cex = 0.5, nice.facing=TRUE)
legend(x=-1.1, y=-0.8, pch = 15, col = gene_set_col, legend = names(gene_set_col),bty = "n" ,y.intersp = 0.7,pt.cex = 1, cex=0.455)
}, track.height = 0.02, bg.border = "black")
}
# Track for Gene Expression
if(length(nrow(myGlobalEnv$Cor_Exp))==1 && ncol(myGlobalEnv$Cor_Exp) == n_disease +3&&myGlobalEnv$ReturnCBoxCircos[1]==1){
print("Getting Track for Gene Expression...")
circos.trackPlotRegion(ylim = c(0, n_disease), panel.fun = function(x, y) {
xlim = get.cell.meta.data("xlim")
ylim = get.cell.meta.data("ylim")
disease <- get.cell.meta.data("sector.index")
mat <- as.matrix(myGlobalEnv$Cor_Exp[myGlobalEnv$Cor_Exp[[2]] == disease, 3:(n_disease+3)])
mat <- mat[, -which(all_disease %in% disease)]
corr_col_fun <- colorRamp2(c(-1,0 ,1), c("blue","white" ,"red3"))
for(i in seq_len(n_gene)) {
for(j in seq_len(n_disease)) {
circos.rect(i-1, j-1, i, j, col = corr_col_fun(mat[i, j]), border = NA)
}
}
circos.text(min(xlim)+15, max(ylim), "mRNA Exp", facing= "bending.inside" ,cex = 0.5)
legend(x=-1.11, y=1.1, title = "mRNA",pch = 15, col = corr_col_fun(seq(-1,1, by = 0.5)), legend = seq(-1, 1, by = 0.5),bty = "n",y.intersp=0.7,pt.cex = 1, cex=0.5)
}, track.height = 0.1)
}
# Track for CNA
if(length(nrow(myGlobalEnv$Cor_CNA))==1 && ncol(myGlobalEnv$Cor_CNA) == n_disease +3&&myGlobalEnv$ReturnCBoxCircos[2]==1){
print("Getting Track for CNA...")
circos.trackPlotRegion(ylim = c(0, n_disease), panel.fun = function(x, y) {
xlim = get.cell.meta.data("xlim")
ylim = get.cell.meta.data("ylim")
disease <- get.cell.meta.data("sector.index")
mat <- as.matrix(myGlobalEnv$Cor_CNA[myGlobalEnv$Cor_CNA[[2]] == disease, 3:(n_disease+3)])
mat <- mat[, -which(all_disease %in% disease)]
corr_col_fun <- colorRamp2(c( 0.7,0.8 ,1), c("white","greenyellow" ,"green4"))
for(i in seq_len(n_gene)) {
for(j in seq_len(n_disease)) {
circos.rect(i-1, j-1, i, j, col = corr_col_fun(mat[i, j]), border = NA)
}
}
circos.text(min(xlim)+15, max(ylim), "CNA", facing= "bending.inside" ,cex = 0.5)
legend(x=0.6,y=1.1, title = "CNA",pch = 15, col = corr_col_fun(seq(0.8, 1, by = 0.1)), legend = seq(0.8, 1, by = 0.1),bty = "n", y.intersp=0.7, pt.cex = 1, cex=0.5)
}, track.height = 0.1)
}
##track for methylation HM450
if(length(nrow(myGlobalEnv$Cor_Met$HM450))==1 && ncol(myGlobalEnv$Cor_Met$HM450) == n_disease +3&&myGlobalEnv$ReturnCBoxCircos[3]==1){
print("getting Track for methylation HM450...")
circos.trackPlotRegion(ylim = c(0, n_disease), panel.fun = function(x, y) {
xlim = get.cell.meta.data("xlim")
ylim = get.cell.meta.data("ylim")
disease = get.cell.meta.data("sector.index")
mat = as.matrix(myGlobalEnv$Cor_Met$HM450[myGlobalEnv$Cor_Met$HM450[[2]] == disease, 3:(n_disease+3)])
mat = mat[, -which(all_disease %in% disease)]
corr_col_fun = colorRamp2(c( -1,0 ,1), c("springgreen4","white" ,"mediumorchid4"))
for(i in seq_len(n_gene)) {
for(j in seq_len(n_disease)) {
circos.rect(i-1, j-1, i, j, col = corr_col_fun(mat[i, j]), border = NA)
}
}
circos.text(min(xlim)+15, max(ylim), "Met HM450", facing= "bending.inside" ,cex = 0.5)
legend(x=-0.9,y=1.1, title = "Meth",pch = 15, col = corr_col_fun(seq(-1,1, by = 0.5)), legend = seq(-1, 1, by = 0.5),bty = "n" ,y.intersp=0.7,pt.cex = 1, cex=0.5)
}, track.height = 0.1)
}
##track for methylation HM27
if(length(nrow(myGlobalEnv$Cor_Met$HM27))==1 && ncol(myGlobalEnv$Cor_Met$HM27) == n_disease +3 && myGlobalEnv$ReturnCBoxCircos[4]==1){
print("getting Track for methylation HM27...")
circos.trackPlotRegion(ylim = c(0, n_disease), panel.fun = function(x, y) {
xlim = get.cell.meta.data("xlim")
ylim = get.cell.meta.data("ylim")
disease = get.cell.meta.data("sector.index")
mat = as.matrix(myGlobalEnv$Cor_Met$HM27[myGlobalEnv$Cor_Met$HM27[[2]] == disease, 3:(n_disease+3)])
mat = mat[, -which(all_disease %in% disease)]
corr_col_fun = colorRamp2(c(-1,0 ,1), c("springgreen4","white" ,"mediumorchid4"))
for(i in seq_len(n_gene)) {
for(j in seq_len(n_disease)) {
circos.rect(i-1, j-1, i, j, col = corr_col_fun(mat[i, j]), border = NA)
}
}
circos.text(min(xlim)+15, max(ylim), "Met HM27", facing= "bending.inside" ,cex = 0.5)
legend(x=-0.9,y=1.1, title = "Meth",pch = 15, col = corr_col_fun(seq(-1,1, by = 0.5)), legend = seq(-1, 1, by = 0.5),bty = "n" ,y.intersp=0.7,pt.cex = 1, cex=0.5)
}, track.height = 0.1)
}
# Track for Reverse Phase Protein Affinity
if(length(nrow(myGlobalEnv$Cor_RPPA))==1 && ncol(myGlobalEnv$Cor_RPPA) == n_disease +3 &&myGlobalEnv$ReturnCBoxCircos[5]==1){
print("Getting Track for RPPA...")
circos.trackPlotRegion(ylim = c(0, n_disease), panel.fun = function(x, y) {
xlim = get.cell.meta.data("xlim")
ylim = get.cell.meta.data("ylim")
disease <- get.cell.meta.data("sector.index")
mat <- as.matrix(myGlobalEnv$Cor_RPPA[myGlobalEnv$Cor_Exp[[2]] == disease, 3:(n_disease+3)])
mat <- mat[, -which(all_disease %in% disease)]
corr_col_fun <- colorRamp2(c(-1,0 ,1), c("blue","white" ,"red3"))
for(i in seq_len(n_gene)) {
for(j in seq_len(n_disease)) {
circos.rect(i-1, j-1, i, j, col = corr_col_fun(mat[i, j]), border = NA)
}
}
circos.text(min(xlim)+15, max(ylim), "RPPA", facing= "bending.inside" ,cex = 0.5)
#legend("bottomleft", title = "RPPA",pch = 15, col = corr_col_fun(seq(-1,1, by = 0.5)), legend = seq(-1, 1, by = 0.5), pt.cex = 1, cex=0.6)
}, track.height = 0.1)
}
## Track for miRNA
## track for Gene Mutation
if(length(nrow(myGlobalEnv$Freq_DfMutData))==1 &&myGlobalEnv$ReturnCBoxCircos[7]==1){
print("Getting Track for Gene Mutation Frequency...")
mat <- as.matrix(myGlobalEnv$Freq_DfMutData)
mat[is.na(mat)] <- 0
corr_col_fun <- colorRamp2(c(median(mat),mean(mat),30,70,max(mat)), c("white","white","gold","darkgoldenrod2", "darkgoldenrod4"))
circos.trackPlotRegion(ylim = c(0, 1), panel.fun = function(x, y) {
xlim = get.cell.meta.data("xlim")
ylim = get.cell.meta.data("ylim")
disease <- get.cell.meta.data("sector.index")
mut = mat[, disease]
names(mut) = rownames(mat)
mut[is.na(mut)] <- 0
for(i in seq_len(n_gene)) {
circos.rect(i-0.5, 0, i+0.5, 1, col = corr_col_fun(mut[i]), border = NA)
}
circos.text(min(xlim)+15, max(ylim), "Mut", facing= "bending.inside" ,cex = 0.5)
}, track.height = 0.1)
interval <- (max(mat)-20)%/%3
legend(x=0.8,y=1.1, title = "Mutation",pch = 15, col = corr_col_fun(seq(20, max(mat), by = interval)), legend = seq(20, max(mat), by =interval ),bty = "n", y.intersp = 0.7 ,pt.cex = 1, cex=0.5)
#legend(x=-0.9,y=1.1, title = "Meth",pch = 15, col = corr_col_fun(seq(-1,1, by = 0.5)), legend = seq(-1, 1, by = 0.5),bty = "n" ,y.intersp=0.7,pt.cex = 1, cex=0.5)
}
circos.clear()
}
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