R/eQTLsRegStat_GUI.R
In mortyran/NetLCP: Prioritizing combinations of regulatory elements in the heterogeneous network with variant ‘switches’ detection
Defines functions
eQTLsRegStat_GUI
Documented in
eQTLsRegStat_GUI
#' @title eQTLs of CREs statistics
#' @description eQTLs of CREs statistics
#'
#' @param regData the standard out of the function binaryRegulationExtract or multieleRegulationExtract.
#' @param eQTLsData the standard out of the function eQTLsDetection.
#' @param regulationType a character representing the CREs type, it should be one of "circRNA-miRNA", "lncRNA-miRNA", "lncRNA-mRNA", "miRNA-mRNA", "miRNA-pathway", "mRNA-pathway", "circRNA-miRNA-mRNA", "lncRNA-miRNA-mRNA", "miRNA-mRNA-pathway", "lncRNA-miRNA-mRNA-pathway", "circRNA-miRNA-mRNA-pathway".
#' @param topCREs an integer representing the number of the top prioritized CREs to exhibit.
#' @param filterDegree an integer for filtering the nodes.
#' @param selectCREs a vector of elements or CREs.
#'
#' @examples
#' eQTLsRegStat_GUI(regData = NULL, eQTLsData = NULL, regulationType = "miRNA-mRNA", filterDegree = 40, topCREs = 10, selectCREs = NULL)
#' @export
eQTLsRegStat_GUI = function(regData = NULL, eQTLsData = NULL, regulationType = NULL, topCREs = NULL, filterDegree = 40, selectCREs = NULL){
if(is.null(regData) | is.null(eQTLsData) | is.null(regulationType)){
return("Please input the valid parameter......")
}
if(is.null(regulationType) | !(regulationType %in% c("circRNA-miRNA", "lncRNA-miRNA", "lncRNA-mRNA", "miRNA-mRNA", "miRNA-pathway", "mRNA-pathway", "circRNA-miRNA-mRNA", "lncRNA-miRNA-mRNA", "miRNA-mRNA-pathway", "lncRNA-miRNA-mRNA-pathway", "circRNA-miRNA-mRNA-pathway"))){
return("Please choose a regulation type from circRNA-miRNA, lncRNA-miRNA, lncRNA-mRNA, miRNA-mRNA, miRNA-pathway, mRNA-pathway, circRNA-miRNA-mRNA, lncRNA-miRNA-mRNA, miRNA-mRNA-pathway, lncRNA-miRNA-mRNA-pathway, circRNA-miRNA-mRNA-pathway")
}
if(is.null(selectCREs)){
nodeInfo = data.frame(table(c(regData$node1, regData$node2)))
nodeFilter = nodeInfo$Var1[nodeInfo$Freq >= filterDegree]
regData = regData[regData$node1 %in% nodeFilter & regData$node2 %in% nodeFilter,]
eqtls = eQTLsData[eQTLsData$Elements %in% nodeFilter,]
}else{
if(any(grepl("_", selectCREs))){
elements_all = c()
for(i in selectCREs){
elements_all = c(unlist(strsplit(i, "_")), elements_all)
}
selectCREs = unique(elements_all)
}
regData = regData[regData$node1 %in% selectCREs & regData$node2 %in% selectCREs,]
eqtls = eQTLsData[eQTLsData$Elements %in% selectCREs,]
}
if(regulationType == "lncRNA-miRNA-mRNA-pathway" | regulationType == "circRNA-miRNA-mRNA-pathway"){
all_regtypte = unique(regData$regType)
if(length(all_regtypte) == 3){
A1 = regData %>% filter(regType == all_regtypte[1]) %>% dplyr::select(node1, node2) %>% dplyr::rename(node1=node2, node2=node1)
A2 = regData %>% filter(regType == all_regtypte[2]) %>% dplyr::select(node1, node2) %>% dplyr::rename(node2=node1, node3=node2)
A3 = regData %>% filter(regType == all_regtypte[3]) %>% dplyr::select(node1, node2) %>% dplyr::rename(node4=node1, node3=node2)
regulation = A1[,c(2,1)] %>% dplyr::left_join(A2, by = "node2") %>% dplyr::left_join(A3, by = "node3") %>% dplyr::distinct() %>% na.omit()
regulation$reg = paste(regulation$node1, regulation$node2, regulation$node3, regulation$node4, sep = "_")
eqtls_stat = table(eqtls$Elements)
regulation$eQTLs = apply(regulation[,c(1,2,3,4)], 1, function(x){
sum(eqtls_stat[rownames(eqtls_stat) %in% x])
})
regulation = regulation %>% dplyr::arrange(desc(eQTLs))
# print("saving CREs eQTLs......")
# write.csv(regulation, file = "CREs_eQTLs.csv", quote = F, row.names = F)
# print("CREs eQTLs has been output !")
if(is.null(topCREs)){
top_num = nrow(regulation)
}else{
if(topCREs <= nrow(regulation) & topCREs > 0){
top_num = topCREs
}else{
top_num = nrow(regulation)
}
}
regulation = regulation[1:top_num,]
reg_out = data.frame(regulation=regulation$reg)
pic = regulation %>% plotly::plot_ly(x = ~reg, y = ~eQTLs, type = 'bar', name = 'eQTLs') %>% plotly::layout(xaxis = list(title = "CREs", categoryorder = "trace"), yaxis = list(title = 'eQTLs'), barmode = 'stack')
return(list(reg_out, pic))
# if(ncol(eqtls_stat) == 2){
# regulation$eQTLs = apply(regulation[,c(1,2,3,4)], 1, function(x){
# sum(eqtls_stat[rownames(eqtls_stat) %in% x])
# })
# regulation$trans_eQTLs = apply(regulation[,c(1,2,3,4)], 1, function(x){
# sum(eqtls_stat[,2][rownames(eqtls_stat) %in% x])
# })
# return(regulation %>% plotly::plot_ly(regulation, x = ~reg, y = ~cis_eQTLs, type = 'bar', name = 'cis-eQTLs') %>% plotly::add_trace(y = ~trans_eQTLs, name = 'trans-eQTLs') %>% plotly::layout(xaxis = list(title = 'Regulation'), yaxis = list(title = 'eQTLs'), barmode = 'stack'))
# }else{
# regulation$cis_eQTLs = apply(regulation[,c(1,2,3,4)], 1, function(x){
# sum(eqtls_stat[,1][rownames(eqtls_stat) %in% x])
# })
# return(plotly::plot_ly(regulation, x = ~reg, y = ~cis_eQTLs, type = 'bar', name = 'cis-eQTLs') %>% plotly::layout(xaxis = list(title = 'Regulation'), yaxis = list(title = 'eQTLs'), barmode = 'stack'))
# }
}
}else if(regulationType == "lncRNA-miRNA-mRNA" | regulationType == "circRNA-miRNA-mRNA"){
all_regtypte = unique(regData$regType)
if(length(all_regtypte) == 2){
A1 = regData %>% filter(regType == all_regtypte[1]) %>% select(node1, node2) %>% dplyr::rename(node1=node2, node2=node1)
A2 = regData %>% filter(regType == all_regtypte[2]) %>% select(node1, node2) %>% dplyr::rename(node2=node1,node3=node2)
regulation = A1[,c(2,1)] %>% left_join(A2, by = "node2") %>% dplyr::distinct() %>% na.omit()
regulation$reg = paste(regulation$node1, regulation$node2, regulation$node3, sep = "_")
eqtls_stat = table(eqtls$Elements)
regulation$eQTLs = apply(regulation[,c(1,2,3,4)], 1, function(x){
sum(eqtls_stat[rownames(eqtls_stat) %in% x])
})
regulation = regulation %>% dplyr::arrange(desc(eQTLs))
# print("saving CREs eQTLs......")
# write.csv(regulation, file = "CREs_eQTLs.csv", quote = F, row.names = F)
# print("CREs eQTLs has been output !")
if(is.null(topCREs)){
top_num = nrow(regulation)
}else{
if(topCREs <= nrow(regulation) & topCREs > 0){
top_num = topCREs
}else{
top_num = nrow(regulation)
}
}
regulation = regulation[1:top_num,]
reg_out = data.frame(regulation=regulation$reg)
pic = regulation %>% plotly::plot_ly(x = ~reg, y = ~eQTLs, type = 'bar', name = 'eQTLs') %>% plotly::layout(xaxis = list(title = "CREs", categoryorder = "trace"), yaxis = list(title = 'eQTLs'), barmode = 'stack')
return(list(reg_out, pic))
#
# eqtls_stat = table(eqtls$Elements, eqtls$RegType)
# if(ncol(eqtls_stat) == 2){
# regulation$cis_eQTLs = apply(regulation[,c(1,2,3)], 1, function(x){
# sum(eqtls_stat[,1][rownames(eqtls_stat) %in% x])
# })
# regulation$trans_eQTLs = apply(regulation[,c(1,2,3)], 1, function(x){
# sum(eqtls_stat[,2][rownames(eqtls_stat) %in% x])
# })
# return(plotly::plot_ly(regulation, x = ~reg, y = ~cis_eQTLs, type = 'bar', name = 'cis-eQTLs') %>% plotly::add_trace(y = ~trans_eQTLs, name = 'trans-eQTLs') %>% plotly::layout(xaxis = list(title = 'Regulation'), yaxis = list(title = 'eQTLs'), barmode = 'stack'))
# }else{
# regulation$cis_eQTLs = apply(regulation[,c(1,2,3)], 1, function(x){
# sum(eqtls_stat[,1][rownames(eqtls_stat) %in% x])
# })
# return(plotly::plot_ly(regulation, x = ~reg, y = ~cis_eQTLs, type = 'bar', name = 'cis-eQTLs') %>% plotly::layout(xaxis = list(title = 'Regulation'), yaxis = list(title = 'eQTLs'), barmode = 'stack'))
# }
}
}else if(regulationType == "miRNA-mRNA-pathway"){
all_regtypte = unique(regData$regType)
if(length(all_regtypte) == 2){
A1 = regData %>% dplyr::filter(regType == all_regtypte[1]) %>% dplyr::select(node1, node2)
A2 = regData %>% dplyr::filter(regType == all_regtypte[2]) %>% dplyr::select(node1, node2) %>% dplyr::rename(node3=node1)
regulation = A1 %>% dplyr::left_join(A2, by = "node2") %>% dplyr::distinct() %>% na.omit()
regulation$reg = paste(regulation$node1, regulation$node2, regulation$node3, sep = "_")
eqtls_stat = table(eqtls$Elements)
regulation$eQTLs = apply(regulation[,c(1,2,3,4)], 1, function(x){
sum(eqtls_stat[rownames(eqtls_stat) %in% x])
})
regulation = regulation %>% dplyr::arrange(desc(eQTLs))
# print("saving CREs eQTLs......")
# write.csv(regulation, file = "CREs_eQTLs.csv", quote = F, row.names = F)
# print("CREs eQTLs has been output !")
if(is.null(topCREs)){
top_num = nrow(regulation)
}else{
if(topCREs <= nrow(regulation) & topCREs > 0){
top_num = topCREs
}else{
top_num = nrow(regulation)
}
}
regulation = regulation[1:top_num,]
reg_out = data.frame(regulation=regulation$reg)
pic = regulation %>% plotly::plot_ly(x = ~reg, y = ~eQTLs, type = 'bar', name = 'eQTLs') %>% plotly::layout(xaxis = list(title = "CREs", categoryorder = "trace"), yaxis = list(title = 'eQTLs'), barmode = 'stack')
return(list(reg_out, pic))
#
# eqtls_stat = table(eqtls$Elements, eqtls$RegType)
# if(ncol(eqtls_stat) == 2){
# regulation$cis_eQTLs = apply(regulation[,c(1,2,3)], 1, function(x){
# sum(eqtls_stat[,1][rownames(eqtls_stat) %in% x])
# })
# regulation$trans_eQTLs = apply(regulation[,c(1,2,3)], 1, function(x){
# sum(eqtls_stat[,2][rownames(eqtls_stat) %in% x])
# })
# return(plotly::plot_ly(regulation, x = ~reg, y = ~cis_eQTLs, type = 'bar', name = 'cis-eQTLs') %>% plotly::add_trace(y = ~trans_eQTLs, name = 'trans-eQTLs') %>% plotly::layout(xaxis = list(title = 'Regulation'), yaxis = list(title = 'eQTLs'), barmode = 'stack'))
# }else{
# regulation$cis_eQTLs = apply(regulation[,c(1,2,3)], 1, function(x){
# sum(eqtls_stat[,1][rownames(eqtls_stat) %in% x])
# })
# return(plotly::plot_ly(regulation, x = ~reg, y = ~cis_eQTLs, type = 'bar', name = 'cis-eQTLs') %>% plotly::layout(xaxis = list(title = 'Regulation'), yaxis = list(title = 'eQTLs'), barmode = 'stack'))
# }
}
}else{
regulation = regData[,c(1,2)] %>% dplyr::distinct() %>% na.omit()
if(nrow(regulation) > 0){
regulation$reg = paste(regulation$node1, regulation$node2, sep = "_")
eqtls_stat = table(eqtls$Elements)
regulation$eQTLs = apply(regulation[,c(1,2)], 1, function(x){
sum(eqtls_stat[rownames(eqtls_stat) %in% x])
})
regulation = regulation %>% dplyr::arrange(desc(eQTLs))
# print("saving CREs eQTLs......")
# write.csv(regulation, file = "CREs_eQTLs.csv", quote = F, row.names = F)
# print("CREs eQTLs has been output !")
if(is.null(topCREs)){
top_num = nrow(regulation)
}else{
if(topCREs <= nrow(regulation) & topCREs > 0){
top_num = topCREs
}else{
top_num = nrow(regulation)
}
}
regulation = regulation[1:top_num,]
reg_out = data.frame(regulation=regulation$reg)
pic = regulation %>% plotly::plot_ly(x = ~reg, y = ~eQTLs, type = 'bar', name = 'eQTLs') %>% plotly::layout(xaxis = list(title = "CREs", categoryorder = "trace"), yaxis = list(title = 'eQTLs'), barmode = 'stack')
return(list(reg_out, pic))
# eqtls_stat = table(eqtls$Elements, eqtls$RegType)
# if(ncol(eqtls_stat) == 2){
# regulation$cis_eQTLs = apply(regulation[,c(1,2)], 1, function(x){
# sum(eqtls_stat[,1][rownames(eqtls_stat) %in% x])
# })
# regulation$trans_eQTLs = apply(regulation[,c(1,2)], 1, function(x){
# sum(eqtls_stat[,2][rownames(eqtls_stat) %in% x])
# })
# regulation$reg = paste(regulation$node1, regulation$node2, sep = "_")
# return(plotly::plot_ly(regulation, x = ~reg, y = ~cis_eQTLs, type = 'bar', name = 'cis-eQTLs') %>% plotly::add_trace(y = ~trans_eQTLs, name = 'trans-eQTLs') %>% plotly::layout(xaxis = list(title = 'Regulation'), yaxis = list(title = 'eQTLs'), barmode = 'stack'))
# }else{
# regulation$cis_eQTLs = apply(regulation[,c(1,2)], 1, function(x){
# sum(eqtls_stat[,1][rownames(eqtls_stat) %in% x])
# })
# return(plotly::plot_ly(regulation, x = ~reg, y = ~cis_eQTLs, type = 'bar', name = 'cis-eQTLs') %>% plotly::layout(xaxis = list(title = 'Regulation'), yaxis = list(title = 'eQTLs'), barmode = 'stack'))
# }
}
}
}
mortyran/NetLCP documentation built on Feb. 26, 2023, 11:33 a.m.
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Defines functions eQTLsRegStat_GUI
Documented in eQTLsRegStat_GUI
#' @title eQTLs of CREs statistics
#' @description eQTLs of CREs statistics
#'
#' @param regData the standard out of the function binaryRegulationExtract or multieleRegulationExtract.
#' @param eQTLsData the standard out of the function eQTLsDetection.
#' @param regulationType a character representing the CREs type, it should be one of "circRNA-miRNA", "lncRNA-miRNA", "lncRNA-mRNA", "miRNA-mRNA", "miRNA-pathway", "mRNA-pathway", "circRNA-miRNA-mRNA", "lncRNA-miRNA-mRNA", "miRNA-mRNA-pathway", "lncRNA-miRNA-mRNA-pathway", "circRNA-miRNA-mRNA-pathway".
#' @param topCREs an integer representing the number of the top prioritized CREs to exhibit.
#' @param filterDegree an integer for filtering the nodes.
#' @param selectCREs a vector of elements or CREs.
#'
#' @examples
#' eQTLsRegStat_GUI(regData = NULL, eQTLsData = NULL, regulationType = "miRNA-mRNA", filterDegree = 40, topCREs = 10, selectCREs = NULL)
#' @export
eQTLsRegStat_GUI = function(regData = NULL, eQTLsData = NULL, regulationType = NULL, topCREs = NULL, filterDegree = 40, selectCREs = NULL){
if(is.null(regData) | is.null(eQTLsData) | is.null(regulationType)){
return("Please input the valid parameter......")
}
if(is.null(regulationType) | !(regulationType %in% c("circRNA-miRNA", "lncRNA-miRNA", "lncRNA-mRNA", "miRNA-mRNA", "miRNA-pathway", "mRNA-pathway", "circRNA-miRNA-mRNA", "lncRNA-miRNA-mRNA", "miRNA-mRNA-pathway", "lncRNA-miRNA-mRNA-pathway", "circRNA-miRNA-mRNA-pathway"))){
return("Please choose a regulation type from circRNA-miRNA, lncRNA-miRNA, lncRNA-mRNA, miRNA-mRNA, miRNA-pathway, mRNA-pathway, circRNA-miRNA-mRNA, lncRNA-miRNA-mRNA, miRNA-mRNA-pathway, lncRNA-miRNA-mRNA-pathway, circRNA-miRNA-mRNA-pathway")
}
if(is.null(selectCREs)){
nodeInfo = data.frame(table(c(regData$node1, regData$node2)))
nodeFilter = nodeInfo$Var1[nodeInfo$Freq >= filterDegree]
regData = regData[regData$node1 %in% nodeFilter & regData$node2 %in% nodeFilter,]
eqtls = eQTLsData[eQTLsData$Elements %in% nodeFilter,]
}else{
if(any(grepl("_", selectCREs))){
elements_all = c()
for(i in selectCREs){
elements_all = c(unlist(strsplit(i, "_")), elements_all)
}
selectCREs = unique(elements_all)
}
regData = regData[regData$node1 %in% selectCREs & regData$node2 %in% selectCREs,]
eqtls = eQTLsData[eQTLsData$Elements %in% selectCREs,]
}
if(regulationType == "lncRNA-miRNA-mRNA-pathway" | regulationType == "circRNA-miRNA-mRNA-pathway"){
all_regtypte = unique(regData$regType)
if(length(all_regtypte) == 3){
A1 = regData %>% filter(regType == all_regtypte[1]) %>% dplyr::select(node1, node2) %>% dplyr::rename(node1=node2, node2=node1)
A2 = regData %>% filter(regType == all_regtypte[2]) %>% dplyr::select(node1, node2) %>% dplyr::rename(node2=node1, node3=node2)
A3 = regData %>% filter(regType == all_regtypte[3]) %>% dplyr::select(node1, node2) %>% dplyr::rename(node4=node1, node3=node2)
regulation = A1[,c(2,1)] %>% dplyr::left_join(A2, by = "node2") %>% dplyr::left_join(A3, by = "node3") %>% dplyr::distinct() %>% na.omit()
regulation$reg = paste(regulation$node1, regulation$node2, regulation$node3, regulation$node4, sep = "_")
eqtls_stat = table(eqtls$Elements)
regulation$eQTLs = apply(regulation[,c(1,2,3,4)], 1, function(x){
sum(eqtls_stat[rownames(eqtls_stat) %in% x])
})
regulation = regulation %>% dplyr::arrange(desc(eQTLs))
# print("saving CREs eQTLs......")
# write.csv(regulation, file = "CREs_eQTLs.csv", quote = F, row.names = F)
# print("CREs eQTLs has been output !")
if(is.null(topCREs)){
top_num = nrow(regulation)
}else{
if(topCREs <= nrow(regulation) & topCREs > 0){
top_num = topCREs
}else{
top_num = nrow(regulation)
}
}
regulation = regulation[1:top_num,]
reg_out = data.frame(regulation=regulation$reg)
pic = regulation %>% plotly::plot_ly(x = ~reg, y = ~eQTLs, type = 'bar', name = 'eQTLs') %>% plotly::layout(xaxis = list(title = "CREs", categoryorder = "trace"), yaxis = list(title = 'eQTLs'), barmode = 'stack')
return(list(reg_out, pic))
# if(ncol(eqtls_stat) == 2){
# regulation$eQTLs = apply(regulation[,c(1,2,3,4)], 1, function(x){
# sum(eqtls_stat[rownames(eqtls_stat) %in% x])
# })
# regulation$trans_eQTLs = apply(regulation[,c(1,2,3,4)], 1, function(x){
# sum(eqtls_stat[,2][rownames(eqtls_stat) %in% x])
# })
# return(regulation %>% plotly::plot_ly(regulation, x = ~reg, y = ~cis_eQTLs, type = 'bar', name = 'cis-eQTLs') %>% plotly::add_trace(y = ~trans_eQTLs, name = 'trans-eQTLs') %>% plotly::layout(xaxis = list(title = 'Regulation'), yaxis = list(title = 'eQTLs'), barmode = 'stack'))
# }else{
# regulation$cis_eQTLs = apply(regulation[,c(1,2,3,4)], 1, function(x){
# sum(eqtls_stat[,1][rownames(eqtls_stat) %in% x])
# })
# return(plotly::plot_ly(regulation, x = ~reg, y = ~cis_eQTLs, type = 'bar', name = 'cis-eQTLs') %>% plotly::layout(xaxis = list(title = 'Regulation'), yaxis = list(title = 'eQTLs'), barmode = 'stack'))
# }
}
}else if(regulationType == "lncRNA-miRNA-mRNA" | regulationType == "circRNA-miRNA-mRNA"){
all_regtypte = unique(regData$regType)
if(length(all_regtypte) == 2){
A1 = regData %>% filter(regType == all_regtypte[1]) %>% select(node1, node2) %>% dplyr::rename(node1=node2, node2=node1)
A2 = regData %>% filter(regType == all_regtypte[2]) %>% select(node1, node2) %>% dplyr::rename(node2=node1,node3=node2)
regulation = A1[,c(2,1)] %>% left_join(A2, by = "node2") %>% dplyr::distinct() %>% na.omit()
regulation$reg = paste(regulation$node1, regulation$node2, regulation$node3, sep = "_")
eqtls_stat = table(eqtls$Elements)
regulation$eQTLs = apply(regulation[,c(1,2,3,4)], 1, function(x){
sum(eqtls_stat[rownames(eqtls_stat) %in% x])
})
regulation = regulation %>% dplyr::arrange(desc(eQTLs))
# print("saving CREs eQTLs......")
# write.csv(regulation, file = "CREs_eQTLs.csv", quote = F, row.names = F)
# print("CREs eQTLs has been output !")
if(is.null(topCREs)){
top_num = nrow(regulation)
}else{
if(topCREs <= nrow(regulation) & topCREs > 0){
top_num = topCREs
}else{
top_num = nrow(regulation)
}
}
regulation = regulation[1:top_num,]
reg_out = data.frame(regulation=regulation$reg)
pic = regulation %>% plotly::plot_ly(x = ~reg, y = ~eQTLs, type = 'bar', name = 'eQTLs') %>% plotly::layout(xaxis = list(title = "CREs", categoryorder = "trace"), yaxis = list(title = 'eQTLs'), barmode = 'stack')
return(list(reg_out, pic))
#
# eqtls_stat = table(eqtls$Elements, eqtls$RegType)
# if(ncol(eqtls_stat) == 2){
# regulation$cis_eQTLs = apply(regulation[,c(1,2,3)], 1, function(x){
# sum(eqtls_stat[,1][rownames(eqtls_stat) %in% x])
# })
# regulation$trans_eQTLs = apply(regulation[,c(1,2,3)], 1, function(x){
# sum(eqtls_stat[,2][rownames(eqtls_stat) %in% x])
# })
# return(plotly::plot_ly(regulation, x = ~reg, y = ~cis_eQTLs, type = 'bar', name = 'cis-eQTLs') %>% plotly::add_trace(y = ~trans_eQTLs, name = 'trans-eQTLs') %>% plotly::layout(xaxis = list(title = 'Regulation'), yaxis = list(title = 'eQTLs'), barmode = 'stack'))
# }else{
# regulation$cis_eQTLs = apply(regulation[,c(1,2,3)], 1, function(x){
# sum(eqtls_stat[,1][rownames(eqtls_stat) %in% x])
# })
# return(plotly::plot_ly(regulation, x = ~reg, y = ~cis_eQTLs, type = 'bar', name = 'cis-eQTLs') %>% plotly::layout(xaxis = list(title = 'Regulation'), yaxis = list(title = 'eQTLs'), barmode = 'stack'))
# }
}
}else if(regulationType == "miRNA-mRNA-pathway"){
all_regtypte = unique(regData$regType)
if(length(all_regtypte) == 2){
A1 = regData %>% dplyr::filter(regType == all_regtypte[1]) %>% dplyr::select(node1, node2)
A2 = regData %>% dplyr::filter(regType == all_regtypte[2]) %>% dplyr::select(node1, node2) %>% dplyr::rename(node3=node1)
regulation = A1 %>% dplyr::left_join(A2, by = "node2") %>% dplyr::distinct() %>% na.omit()
regulation$reg = paste(regulation$node1, regulation$node2, regulation$node3, sep = "_")
eqtls_stat = table(eqtls$Elements)
regulation$eQTLs = apply(regulation[,c(1,2,3,4)], 1, function(x){
sum(eqtls_stat[rownames(eqtls_stat) %in% x])
})
regulation = regulation %>% dplyr::arrange(desc(eQTLs))
# print("saving CREs eQTLs......")
# write.csv(regulation, file = "CREs_eQTLs.csv", quote = F, row.names = F)
# print("CREs eQTLs has been output !")
if(is.null(topCREs)){
top_num = nrow(regulation)
}else{
if(topCREs <= nrow(regulation) & topCREs > 0){
top_num = topCREs
}else{
top_num = nrow(regulation)
}
}
regulation = regulation[1:top_num,]
reg_out = data.frame(regulation=regulation$reg)
pic = regulation %>% plotly::plot_ly(x = ~reg, y = ~eQTLs, type = 'bar', name = 'eQTLs') %>% plotly::layout(xaxis = list(title = "CREs", categoryorder = "trace"), yaxis = list(title = 'eQTLs'), barmode = 'stack')
return(list(reg_out, pic))
#
# eqtls_stat = table(eqtls$Elements, eqtls$RegType)
# if(ncol(eqtls_stat) == 2){
# regulation$cis_eQTLs = apply(regulation[,c(1,2,3)], 1, function(x){
# sum(eqtls_stat[,1][rownames(eqtls_stat) %in% x])
# })
# regulation$trans_eQTLs = apply(regulation[,c(1,2,3)], 1, function(x){
# sum(eqtls_stat[,2][rownames(eqtls_stat) %in% x])
# })
# return(plotly::plot_ly(regulation, x = ~reg, y = ~cis_eQTLs, type = 'bar', name = 'cis-eQTLs') %>% plotly::add_trace(y = ~trans_eQTLs, name = 'trans-eQTLs') %>% plotly::layout(xaxis = list(title = 'Regulation'), yaxis = list(title = 'eQTLs'), barmode = 'stack'))
# }else{
# regulation$cis_eQTLs = apply(regulation[,c(1,2,3)], 1, function(x){
# sum(eqtls_stat[,1][rownames(eqtls_stat) %in% x])
# })
# return(plotly::plot_ly(regulation, x = ~reg, y = ~cis_eQTLs, type = 'bar', name = 'cis-eQTLs') %>% plotly::layout(xaxis = list(title = 'Regulation'), yaxis = list(title = 'eQTLs'), barmode = 'stack'))
# }
}
}else{
regulation = regData[,c(1,2)] %>% dplyr::distinct() %>% na.omit()
if(nrow(regulation) > 0){
regulation$reg = paste(regulation$node1, regulation$node2, sep = "_")
eqtls_stat = table(eqtls$Elements)
regulation$eQTLs = apply(regulation[,c(1,2)], 1, function(x){
sum(eqtls_stat[rownames(eqtls_stat) %in% x])
})
regulation = regulation %>% dplyr::arrange(desc(eQTLs))
# print("saving CREs eQTLs......")
# write.csv(regulation, file = "CREs_eQTLs.csv", quote = F, row.names = F)
# print("CREs eQTLs has been output !")
if(is.null(topCREs)){
top_num = nrow(regulation)
}else{
if(topCREs <= nrow(regulation) & topCREs > 0){
top_num = topCREs
}else{
top_num = nrow(regulation)
}
}
regulation = regulation[1:top_num,]
reg_out = data.frame(regulation=regulation$reg)
pic = regulation %>% plotly::plot_ly(x = ~reg, y = ~eQTLs, type = 'bar', name = 'eQTLs') %>% plotly::layout(xaxis = list(title = "CREs", categoryorder = "trace"), yaxis = list(title = 'eQTLs'), barmode = 'stack')
return(list(reg_out, pic))
# eqtls_stat = table(eqtls$Elements, eqtls$RegType)
# if(ncol(eqtls_stat) == 2){
# regulation$cis_eQTLs = apply(regulation[,c(1,2)], 1, function(x){
# sum(eqtls_stat[,1][rownames(eqtls_stat) %in% x])
# })
# regulation$trans_eQTLs = apply(regulation[,c(1,2)], 1, function(x){
# sum(eqtls_stat[,2][rownames(eqtls_stat) %in% x])
# })
# regulation$reg = paste(regulation$node1, regulation$node2, sep = "_")
# return(plotly::plot_ly(regulation, x = ~reg, y = ~cis_eQTLs, type = 'bar', name = 'cis-eQTLs') %>% plotly::add_trace(y = ~trans_eQTLs, name = 'trans-eQTLs') %>% plotly::layout(xaxis = list(title = 'Regulation'), yaxis = list(title = 'eQTLs'), barmode = 'stack'))
# }else{
# regulation$cis_eQTLs = apply(regulation[,c(1,2)], 1, function(x){
# sum(eqtls_stat[,1][rownames(eqtls_stat) %in% x])
# })
# return(plotly::plot_ly(regulation, x = ~reg, y = ~cis_eQTLs, type = 'bar', name = 'cis-eQTLs') %>% plotly::layout(xaxis = list(title = 'Regulation'), yaxis = list(title = 'eQTLs'), barmode = 'stack'))
# }
}
}
}
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