R/IVIVEGadget.R
In sahu27/sahu: Population Life Course Exposure to Health Effects Modeling
#' Command line function for running the IVIVE gadget
#' @description Launches the IVIVE gadget for estimating age dependent metabolism
#' @param save_flag Boolean. Should the data generated be saved to a csv file. The name of the file can then be defined in the UI
#' @param base_path if save_flag is True, must specify a base path where the result file will be
#' @export
iviveGadget <- function(save_flag = F,base_path = NULL){
ui <- miniPage(
shinyjs::useShinyjs(),
gadgetTitleBar("Perform In-vitro to In-vivo Extrapolation",
left = miniTitleBarCancelButton(),
right = miniTitleBarButton("done","Done")),
miniTabstripPanel(
miniTabPanel("Physiological Parameters",
miniContentPanel(
fillCol(flex = c(1,1,4),
fillRow(flex = c(16,2,3,1),
fillRow(
numericInput("age","Reference Age(Years)",25,0.1,80,0.1),
selectInput("gender","Gender",choices = c("Male"="M","Female"="F")),
numericInput("bw","Body Weight(kg)",80.15),
numericInput("liv_wt","Liver Weight(kg)",1.5)
),
tags$div(),
fillRow(
shinyWidgets::searchInput("out_age","Additional output ages",btnSearch = icon("plus"))),
tags$div()
),
fillRow(flex = c(8,14),
fillRow(
numericInput("km","Michaelis-Menten Constant",0),
numericInput("hpgl","10^6 Hepatocytes/gm Liver",137)
),
tags$div()
),
fillRow(flex = c(0.5,2,0.5,8,1,2,1),
tags$div(),
DT::dataTableOutput("mgpglTble"),
tags$div(),
DT::dataTableOutput("cypDb"),
tags$div(),
tags$div(
DT::dataTableOutput("ageTble"),
actionButton("rem_row","Remove Row")
),
tags$div()
)
)
)
),
miniTabPanel("Cellular Clearance \n in Reference Age",
miniContentPanel(
fillCol(flex = c(1,2,1),
fillRow(flex = c(2,1,2),
tags$div(),
selectInput("heptype","Hepatic Clearance",
choices= list("None"="hep_null",
"Whole Hepatocyte"= "hep_whole",
"S9 Fraction" = "hep_s9",
"Subcellular Fraction"= "hep_sc",
"Premeasured Value"="hep_fnl")),
tags$div()
),
fillRow(flex = c(1,1),
fillCol(
fillRow(flex = c(1,5,3,1),
tags$div(),
numericInput("num_whcl",
"Measure Whole Hepatocyte Clearance",0),
selectInput("sel_whunit",label = "Units",
choices = list("L/h"="Lh",
"L/h/10^6 Hepatocytes"="LhmH")),
tags$div()
),
fillRow(flex = c(1,5,3,1),
tags$div(),
numericInput("num_S9cl",
"Measured S9 Fraction Clearance",0),
selectInput("sel_s9unit",label = "Units",
choices = list("\u03BCL/min/mg Protein"="ulmmP",
"\u03BCL/h/mg Protein"="ulhmP",
"mL/min/mg Protein"="mlmmP",
"mL/h/mg Protein"="mlhmP")),
tags$div()
)
),
fillCol(
fillRow(flex = c(1,4,3,1),
tags$div(),
numericInput("num_mscl","Measure Microsomal Clearance",0),
selectInput("sel_msunit",label = "Units",
choices = list("\u03BCmol/min/mg Protein"="ummmP",
"\u03BCL/min/mg Protein"="ulmmP",
"\u03BCL/h/mg Protein"="ulhmP",
"mL/min/mg Protein"="mlmmP",
"mL/h/mg Protein"="mlhmP")),
tags$div()
),
fillRow(flex = c(1,4,3,1),
tags$div(),
numericInput("num_cycl","Measure Cytosolic Clearance",0),
selectInput("sel_cyunit",label = "Units",
choices = list("\u03BCL/min/mg Protein"="ulmmP",
"\u03BCL/h/mg Protein"="ulhmP",
"mL/min/mg Protein"="mlmmP",
"mL/h/mg Protein"="mlhmP")),
tags$div()
)
)
),
fillRow(flex = c(2,1,2),
tags$div(),
numericInput("num_pmcl","Precalculated Scaled clearance(L/h)",0),
tags$div()
)
)
)),
miniTabPanel("Enzymatic Clearance \n in Reference Age",
miniContentPanel(
fillCol(flex = c(3,1),
# fillRow(flex=c(6,1,6),
# tags$div(),
# tags$h4("clearance in uL/min/pmol"),
# tags$div()
# ),
fillRow(flex = c(2,3,2),
tags$div(),
DT::DTOutput("cypCl"),
tags$div()
),
fillRow(flex = c(2,2,5),
fileInput("cypCl_upload","Upload Cyp Clearance",
multiple = F,placeholder = "Select CSV File",
buttonLabel = icon("search"),
accept = c("text/csv")
),
downloadLink("cypCl_temp","Template for the CSV file"),
tags$div()
)
)
)
),
miniTabPanel("Output",
miniContentPanel(
fillCol(flex = c(1,7,4),
fillRow(
actionButton("run","Do IVIVE")
),
fillRow(flex= c(1,4,1,4,1),
tags$div(),
DT::DTOutput("out_heptble"),
tags$div(),
DT::DTOutput("out_enztble"),
tags$div()),
fillRow(
fillCol(flex = c(1,1),
fillRow(
shinyWidgets::radioGroupButtons("ret_data","Select Data to return",
choiceNames = c("None",
"Total clearance at reference age",
"Total Clearance at all ages",
"Detailed clearance data"),
choiceValues = c("none","cl_ref",
"cl_all",
"cl_detail"),
checkIcon = list(yes = icon("ok",lib = "glyphicon")),
individual = T,
justified = T)
),
# fillRow(flex = c(2,NA),
# tags$h4("Downloads"),
# tags$div()),
fillRow(
shinyjs::hidden(textInput("fname_vmax", "File name for scaled Vmax values")),
shinyjs::hidden(textInput("fname_vliv","File name for scaled Liver Clerance"))
)
)
)
)
#textOutput("cl_val")
))
)
)
server <- function(input,output,session){
if(save_flag){
shinyjs::show("fname_vmax")
shinyjs::show("fname_vliv")
}
observe({
hep_type <- input$heptype
hep_ids <- c("num_whcl","sel_whunit","num_S9cl",
"sel_s9unit","num_mscl","sel_msunit",
"num_cycl","sel_cyunit","num_pmcl")
lapply(hep_ids,shinyjs::disable)
if(hep_type == "hep_whole"){
lapply(c("num_whcl","sel_whunit"),shinyjs::enable)
}else if(hep_type == "hep_s9"){
lapply(c("num_s9cl","sel_s9unit"),shinyjs::enable)
}else if(hep_type == "hep_sc"){
lapply(c("num_mscl","sel_msunit","num_cycl","sel_cyunit"),shinyjs::enable)
}else if(hep_type == "hep_fnl"){
lapply(c("num_pmcl"),shinyjs::enable)
}
})
#Get Cyp Data from main database
query <- "SELECT name,abundance,isef,fumic,loc FROM CypData;"
cypdata <- mainDbSelect(query)
# cypCl <- reactiveVal(data.frame("Names"= cypdata[["name"]],"Clearance"= rep(0,length(cypdata[["name"]])),stringsAsFactors = F))
#Create reactive object to store changing values
react_obj <- reactiveValues()
react_obj$SCData <- list()
react_obj$text_list <- reactiveVal(c())
react_obj$ageTble <- reactive({vector()})
react_obj$SCData <- reactive({
MPCPPGL <- calcMPCPPGL(input$age)
#MPCPPGL <- as.vector(MPCPPGL)
MPPGL <- signif(MPCPPGL$MPPGL,4)
CPPGL <- signif(MPCPPGL$CPPGL,4)
return(data.frame("Fraction"=c("Microsomal","Cytosolic"),
"Values"=c(MPPGL,CPPGL)))
})
observe({
age <- input$age
gender <- input$gender
liv_wt <- getLifecourseLiverVolume(age,gender)
bw <- getLifecourseBodyWeight(age,gender)
updateNumericInput(session,"liv_wt",value = signif(liv_wt,4))
updateNumericInput(session,"bw",value = signif(bw,4))
})
output$mgpglTble <- DT::renderDT(DT::datatable(react_obj$SCData(),
caption = "Proteins/gm Liver Values",
rownames = NULL,autoHideNavigation = T,
options= list(dom = "t")),server = T)
cypDb <- reactive({
data <- as.data.frame(getAllCypData(input$age),stringsAsFactors = F)
data <- merge(cypdata,data,by.x = "name",by.y = "Enzymes")
data[["Ontogeny"]]<- signif(data[["Ontogeny"]],4)
return(data)
})
output$cypDb <- DT::renderDT(DT::datatable(cypDb(),
caption = "CYP Data",
rownames = NULL,autoHideNavigation = T,
colnames = c("Name","Abundance","ISEF","fumic","Location","Ontogeny"),
options= list(dom = "tp",pageLength = 5)),server = T)
observeEvent(input$out_age_search,{
temp <- gsub("[';',' ']",",",input$out_age)
out_age_vector <-do.call("as.numeric",(strsplit(temp,",")))
req(!(any(is.na(out_age_vector))))
current_list <- react_obj$ageTble()
react_obj$ageTble <- reactiveVal(append(current_list,out_age_vector))
},ignoreInit = T,ignoreNULL = T)
output$ageTble <- DT::renderDT(DT::datatable(as.data.frame(react_obj$ageTble()),
caption = "Output Ages",
colnames = "Age",rownames = NULL,
options= list(dom = "tp",pageLength = 5)),
server = T)
observeEvent(input$rem_row,{
selected_row <- input$ageTble_rows_selected
current_list <- react_obj$ageTble()
react_obj$ageTble <<- reactiveVal(current_list[-selected_row])
})
# download handler for CSV file template
output$cypCl_temp <- downloadHandler(
filename= function(){return("Cyp_template.csv")},
content = function(file){
data <- data.frame("Names"= cypdata[["name"]],
"Clearance"= rep(0,length(cypdata[["name"]])),
stringsAsFactors = F)
write.csv(data,file,row.names = F)
},
contentType = c("text/csv")
)
# The selected file
cypFile <- reactive({
input$cypCl_upload
})
# The user's data, parsed into a data frame
cypCl <- reactive({
if(!(is.null(input$cypCl_upload))){
ret_dat <- read.csv(cypFile()$datapath)
}else{
ret_dat <- data.frame("Names"= cypdata[["name"]],"Clearance"= rep(0,length(cypdata[["name"]])),stringsAsFactors = F)
}
return(ret_dat)
})
output$cypCl <- DT::renderDT(DT::datatable(cypCl(),
caption = "Clearance in \u00B5L/min/pmol",
rowname = NULL,
options= list(dom = "tp",pageLength = 5)),
server = T
)
cypcl_proxy = DT::dataTableProxy('cypCl')
# observeEvent(input$cypCl_cell_edit,{
# databck <- input$cypCl_cell_edit
# row <- databck$row
# col <- databck$col+1
# val <- databck$value
# old_table<- cypCl()
# old_table[row,col]<- val
# cypCL <<- old_table
# DT::replaceData(cypcl_proxy,cypCl(),resetPaging = F,rownames = F)
# })
result_vals <- eventReactive(input$run,{
hepcl_type <- input$heptype
org <- "human"
age <- input$age
liver_wt<- input$liv_wt
hpgl <- input$hpgl
km <- input$km
scaled_hepcl <- switch(hepcl_type,
"hep_sc"=calculateScaledSCClearance(c(input$num_mscl,input$num_cycl),
c(input$sel_msunit,input$sel_cyunit),
org,age,
liver_wt,km,return_total = F),
"hep_s9"=calculateScaledS9Clearance(input$num_s9cl,input$sel_s9unit,
org,age,
liver_wt),
"hep_whole"=calculateScaledWholeHepClearance(input$num_whcl,input$sel_whunit,
liver_wt,hpgl,km),
"hep_fnl" = input$num_pmcl,
0
)
# hep_vals_2_return <- do.call(cbind,list(names(scaled_hepcl),scaled_hepcl))
recombList <- lapply(cypCl()$Clearance,'as.numeric')
names(recombList)<- as.list(cypCl()$Names)
scaled_recomcl <- calculateRecombClearance(recombList,"human",age,liver_wt,cypDb(),return_total = F)
# get the ages for which scaling has to happen
out_ages <- react_obj$ageTble()
if((length(out_ages)==0)){
out_ages <- c(age)
}else{
out_ages <- c(age,out_ages)
}
tot_scaled_recomcl <- sum(unname(scaled_recomcl))/liver_wt
tot_scaled_hepcl <- sum(unname(scaled_hepcl))/liver_wt
if (tot_scaled_hepcl>0 && tot_scaled_recomcl>0){
age_wise_enzymecl_table <- scale_cellular_enzymatic(out_ages,tot_scaled_hepcl,
tot_scaled_recomcl,cypDb(),
recombList,
input$gender)
}else{
age_wise_enzymecl_table <- scale_enzymatic(out_ages,
tot_scaled_recomcl,cypDb(),
recombList,
input$gender)
}
hep_vals_2_return <- switch(hepcl_type,
"hep_sc"= data.frame("name" =c("Microsomes","Cytosol"),val = unname(scaled_hepcl)/liver_wt),
"hep_s9"= data.frame("name"="S9Fraction","val"=scaled_hepcl/liver_wt,stringsAsFactors = F),
"hep_whole"= data.frame("name"="Whole Hepatocyte","val"=scaled_hepcl/liver_wt,stringsAsFactors = F),
"hep_fnl"= data.frame("name"="Precomputed","val"=scaled_hepcl/liver_wt,stringsAsFactors = F),
data.frame("name"="No Cellular Clearance","val"=0,stringsAsFactors = F)
)
recom_vals_2_return <-data.frame("name" = names(scaled_recomcl),"val"= unname(scaled_recomcl)/liver_wt,stringsAsFactors = F)
return(list("cellular_tble"=hep_vals_2_return,
"enzymatic_tble"=recom_vals_2_return,
"all_data" = list("ages"= out_ages,
"cellular_clearance"= scaled_hepcl/liver_wt,
"enzymatic_clearance" = age_wise_enzymecl_table)
))
})
output$out_heptble <- DT::renderDT(DT::datatable(result_vals()$cellular_tble,
caption = "Cellular Clearance",
colnames = c("Type","Clearance(L/h/kg liver)"),
rownames = NULL,autoHideNavigation = T,
options = list(dom = "tp",pageLength = 5)),server = T)
output$out_enztble <- DT::renderDT(DT::datatable(result_vals()$enzymatic_tble,
caption = "Recombinant Enzyme Clearance",
colnames = c("Type","Clearance(L/h/kg liver)"),
rownames = NULL,
options = list(dom = "tp",pageLength = 5)),server = T)
observeEvent(input$done,{
# handle data to be returned to the console
if (input$ret_data == "cl_ref"){
final_vals <- result_vals()$all_data
age <- final_vals$ages[1]
cellular_clearance <- sum(unname(final_vals$cellular_clearance))
enzymatic_clearance <- final_vals$enzymatic_clearance["Total",as.character(age)]
ret_data <- data.frame("Age"= age,"Cellular"= cellular_clearance,"Enzymatic"= enzymatic_clearance)
}else if(input$ret_data == "cl_all"){
final_vals <- result_vals()$all_data
age <- final_vals$ages
enzymatic_clearance <- final_vals$enzymatic_clearance["Total",]
cellular_clearance <- sum(unname(final_vals$cellular_clearance))
cellular_clearance <- c(cellular_clearance,rep(0,length(age)-1))
ret_data <- data.frame("Age"= age,"Cellular"= cellular_clearance,"Enzymatic"= enzymatic_clearance)
}else if(input$ret_data == "cl_detail"){
final_vals <- result_vals()$all_data
age <- final_vals$ages
enzymatic_clearance <- final_vals$enzymatic_clearance["Total",]
cellular_clearance <- sum(unname(final_vals$cellular_clearance))
cellular_clearance <- c(cellular_clearance,rep(0,length(age)-1))
cl_data <- data.frame("Age"= age,"Cellular"= cellular_clearance,"Enzymatic"= enzymatic_clearance)
ret_data <- list()
ret_data$tot_cl_data <- cl_data
ret_data$ind_enzyme_cl <- final_vals$enzymatic_clearance
ret_data$enzyme_data <- cypDb()
}else if(input$ret_data == "none"){
ret_data <- NULL
}
# handle file saving for vmax and vliv clearance if save flag is set to true
if(save_flag){
final_vals <- result_vals()$all_data
if (all(final_vals$enzymatic_clearance["Total",]!=0)){
vliv <- final_vals$enzymatic_clearance["Total",]
age <- final_vals$ages
}else{
vliv <- sum(unname(final_vals$cellular_clearance))
age <- final_vals$ages[1]
}
vmax <- vliv*input$km*input$liv_wt/(input$bw^0.75)
if(input$fname_vliv != ""){
write_data <- data.frame("Age"= age,"Clearance"=vliv,stringsAsFactors = F)
write.csv(write_data,file.path(base_path,paste0(input$fname_vliv,".csv")),row.names = F)
}
if(input$fname_vmax != ""){
write_data <- data.frame("Age"= age,"Clearance"=vmax,stringsAsFactors = F)
write.csv(write_data,file.path(base_path,paste0(input$fname_vmax,".csv")),row.names = F)
}
}
stopApp(returnValue = ret_data)
})
}
runGadget(ui,server,viewer =dialogViewer("IVIVE",width = 1200,height = 1800)) #dialogViewer("IVIVE",width = 800) )
}
sahu27/sahu documentation built on May 30, 2019, 2:06 a.m.
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#' Command line function for running the IVIVE gadget
#' @description Launches the IVIVE gadget for estimating age dependent metabolism
#' @param save_flag Boolean. Should the data generated be saved to a csv file. The name of the file can then be defined in the UI
#' @param base_path if save_flag is True, must specify a base path where the result file will be
#' @export
iviveGadget <- function(save_flag = F,base_path = NULL){
ui <- miniPage(
shinyjs::useShinyjs(),
gadgetTitleBar("Perform In-vitro to In-vivo Extrapolation",
left = miniTitleBarCancelButton(),
right = miniTitleBarButton("done","Done")),
miniTabstripPanel(
miniTabPanel("Physiological Parameters",
miniContentPanel(
fillCol(flex = c(1,1,4),
fillRow(flex = c(16,2,3,1),
fillRow(
numericInput("age","Reference Age(Years)",25,0.1,80,0.1),
selectInput("gender","Gender",choices = c("Male"="M","Female"="F")),
numericInput("bw","Body Weight(kg)",80.15),
numericInput("liv_wt","Liver Weight(kg)",1.5)
),
tags$div(),
fillRow(
shinyWidgets::searchInput("out_age","Additional output ages",btnSearch = icon("plus"))),
tags$div()
),
fillRow(flex = c(8,14),
fillRow(
numericInput("km","Michaelis-Menten Constant",0),
numericInput("hpgl","10^6 Hepatocytes/gm Liver",137)
),
tags$div()
),
fillRow(flex = c(0.5,2,0.5,8,1,2,1),
tags$div(),
DT::dataTableOutput("mgpglTble"),
tags$div(),
DT::dataTableOutput("cypDb"),
tags$div(),
tags$div(
DT::dataTableOutput("ageTble"),
actionButton("rem_row","Remove Row")
),
tags$div()
)
)
)
),
miniTabPanel("Cellular Clearance \n in Reference Age",
miniContentPanel(
fillCol(flex = c(1,2,1),
fillRow(flex = c(2,1,2),
tags$div(),
selectInput("heptype","Hepatic Clearance",
choices= list("None"="hep_null",
"Whole Hepatocyte"= "hep_whole",
"S9 Fraction" = "hep_s9",
"Subcellular Fraction"= "hep_sc",
"Premeasured Value"="hep_fnl")),
tags$div()
),
fillRow(flex = c(1,1),
fillCol(
fillRow(flex = c(1,5,3,1),
tags$div(),
numericInput("num_whcl",
"Measure Whole Hepatocyte Clearance",0),
selectInput("sel_whunit",label = "Units",
choices = list("L/h"="Lh",
"L/h/10^6 Hepatocytes"="LhmH")),
tags$div()
),
fillRow(flex = c(1,5,3,1),
tags$div(),
numericInput("num_S9cl",
"Measured S9 Fraction Clearance",0),
selectInput("sel_s9unit",label = "Units",
choices = list("\u03BCL/min/mg Protein"="ulmmP",
"\u03BCL/h/mg Protein"="ulhmP",
"mL/min/mg Protein"="mlmmP",
"mL/h/mg Protein"="mlhmP")),
tags$div()
)
),
fillCol(
fillRow(flex = c(1,4,3,1),
tags$div(),
numericInput("num_mscl","Measure Microsomal Clearance",0),
selectInput("sel_msunit",label = "Units",
choices = list("\u03BCmol/min/mg Protein"="ummmP",
"\u03BCL/min/mg Protein"="ulmmP",
"\u03BCL/h/mg Protein"="ulhmP",
"mL/min/mg Protein"="mlmmP",
"mL/h/mg Protein"="mlhmP")),
tags$div()
),
fillRow(flex = c(1,4,3,1),
tags$div(),
numericInput("num_cycl","Measure Cytosolic Clearance",0),
selectInput("sel_cyunit",label = "Units",
choices = list("\u03BCL/min/mg Protein"="ulmmP",
"\u03BCL/h/mg Protein"="ulhmP",
"mL/min/mg Protein"="mlmmP",
"mL/h/mg Protein"="mlhmP")),
tags$div()
)
)
),
fillRow(flex = c(2,1,2),
tags$div(),
numericInput("num_pmcl","Precalculated Scaled clearance(L/h)",0),
tags$div()
)
)
)),
miniTabPanel("Enzymatic Clearance \n in Reference Age",
miniContentPanel(
fillCol(flex = c(3,1),
# fillRow(flex=c(6,1,6),
# tags$div(),
# tags$h4("clearance in uL/min/pmol"),
# tags$div()
# ),
fillRow(flex = c(2,3,2),
tags$div(),
DT::DTOutput("cypCl"),
tags$div()
),
fillRow(flex = c(2,2,5),
fileInput("cypCl_upload","Upload Cyp Clearance",
multiple = F,placeholder = "Select CSV File",
buttonLabel = icon("search"),
accept = c("text/csv")
),
downloadLink("cypCl_temp","Template for the CSV file"),
tags$div()
)
)
)
),
miniTabPanel("Output",
miniContentPanel(
fillCol(flex = c(1,7,4),
fillRow(
actionButton("run","Do IVIVE")
),
fillRow(flex= c(1,4,1,4,1),
tags$div(),
DT::DTOutput("out_heptble"),
tags$div(),
DT::DTOutput("out_enztble"),
tags$div()),
fillRow(
fillCol(flex = c(1,1),
fillRow(
shinyWidgets::radioGroupButtons("ret_data","Select Data to return",
choiceNames = c("None",
"Total clearance at reference age",
"Total Clearance at all ages",
"Detailed clearance data"),
choiceValues = c("none","cl_ref",
"cl_all",
"cl_detail"),
checkIcon = list(yes = icon("ok",lib = "glyphicon")),
individual = T,
justified = T)
),
# fillRow(flex = c(2,NA),
# tags$h4("Downloads"),
# tags$div()),
fillRow(
shinyjs::hidden(textInput("fname_vmax", "File name for scaled Vmax values")),
shinyjs::hidden(textInput("fname_vliv","File name for scaled Liver Clerance"))
)
)
)
)
#textOutput("cl_val")
))
)
)
server <- function(input,output,session){
if(save_flag){
shinyjs::show("fname_vmax")
shinyjs::show("fname_vliv")
}
observe({
hep_type <- input$heptype
hep_ids <- c("num_whcl","sel_whunit","num_S9cl",
"sel_s9unit","num_mscl","sel_msunit",
"num_cycl","sel_cyunit","num_pmcl")
lapply(hep_ids,shinyjs::disable)
if(hep_type == "hep_whole"){
lapply(c("num_whcl","sel_whunit"),shinyjs::enable)
}else if(hep_type == "hep_s9"){
lapply(c("num_s9cl","sel_s9unit"),shinyjs::enable)
}else if(hep_type == "hep_sc"){
lapply(c("num_mscl","sel_msunit","num_cycl","sel_cyunit"),shinyjs::enable)
}else if(hep_type == "hep_fnl"){
lapply(c("num_pmcl"),shinyjs::enable)
}
})
#Get Cyp Data from main database
query <- "SELECT name,abundance,isef,fumic,loc FROM CypData;"
cypdata <- mainDbSelect(query)
# cypCl <- reactiveVal(data.frame("Names"= cypdata[["name"]],"Clearance"= rep(0,length(cypdata[["name"]])),stringsAsFactors = F))
#Create reactive object to store changing values
react_obj <- reactiveValues()
react_obj$SCData <- list()
react_obj$text_list <- reactiveVal(c())
react_obj$ageTble <- reactive({vector()})
react_obj$SCData <- reactive({
MPCPPGL <- calcMPCPPGL(input$age)
#MPCPPGL <- as.vector(MPCPPGL)
MPPGL <- signif(MPCPPGL$MPPGL,4)
CPPGL <- signif(MPCPPGL$CPPGL,4)
return(data.frame("Fraction"=c("Microsomal","Cytosolic"),
"Values"=c(MPPGL,CPPGL)))
})
observe({
age <- input$age
gender <- input$gender
liv_wt <- getLifecourseLiverVolume(age,gender)
bw <- getLifecourseBodyWeight(age,gender)
updateNumericInput(session,"liv_wt",value = signif(liv_wt,4))
updateNumericInput(session,"bw",value = signif(bw,4))
})
output$mgpglTble <- DT::renderDT(DT::datatable(react_obj$SCData(),
caption = "Proteins/gm Liver Values",
rownames = NULL,autoHideNavigation = T,
options= list(dom = "t")),server = T)
cypDb <- reactive({
data <- as.data.frame(getAllCypData(input$age),stringsAsFactors = F)
data <- merge(cypdata,data,by.x = "name",by.y = "Enzymes")
data[["Ontogeny"]]<- signif(data[["Ontogeny"]],4)
return(data)
})
output$cypDb <- DT::renderDT(DT::datatable(cypDb(),
caption = "CYP Data",
rownames = NULL,autoHideNavigation = T,
colnames = c("Name","Abundance","ISEF","fumic","Location","Ontogeny"),
options= list(dom = "tp",pageLength = 5)),server = T)
observeEvent(input$out_age_search,{
temp <- gsub("[';',' ']",",",input$out_age)
out_age_vector <-do.call("as.numeric",(strsplit(temp,",")))
req(!(any(is.na(out_age_vector))))
current_list <- react_obj$ageTble()
react_obj$ageTble <- reactiveVal(append(current_list,out_age_vector))
},ignoreInit = T,ignoreNULL = T)
output$ageTble <- DT::renderDT(DT::datatable(as.data.frame(react_obj$ageTble()),
caption = "Output Ages",
colnames = "Age",rownames = NULL,
options= list(dom = "tp",pageLength = 5)),
server = T)
observeEvent(input$rem_row,{
selected_row <- input$ageTble_rows_selected
current_list <- react_obj$ageTble()
react_obj$ageTble <<- reactiveVal(current_list[-selected_row])
})
# download handler for CSV file template
output$cypCl_temp <- downloadHandler(
filename= function(){return("Cyp_template.csv")},
content = function(file){
data <- data.frame("Names"= cypdata[["name"]],
"Clearance"= rep(0,length(cypdata[["name"]])),
stringsAsFactors = F)
write.csv(data,file,row.names = F)
},
contentType = c("text/csv")
)
# The selected file
cypFile <- reactive({
input$cypCl_upload
})
# The user's data, parsed into a data frame
cypCl <- reactive({
if(!(is.null(input$cypCl_upload))){
ret_dat <- read.csv(cypFile()$datapath)
}else{
ret_dat <- data.frame("Names"= cypdata[["name"]],"Clearance"= rep(0,length(cypdata[["name"]])),stringsAsFactors = F)
}
return(ret_dat)
})
output$cypCl <- DT::renderDT(DT::datatable(cypCl(),
caption = "Clearance in \u00B5L/min/pmol",
rowname = NULL,
options= list(dom = "tp",pageLength = 5)),
server = T
)
cypcl_proxy = DT::dataTableProxy('cypCl')
# observeEvent(input$cypCl_cell_edit,{
# databck <- input$cypCl_cell_edit
# row <- databck$row
# col <- databck$col+1
# val <- databck$value
# old_table<- cypCl()
# old_table[row,col]<- val
# cypCL <<- old_table
# DT::replaceData(cypcl_proxy,cypCl(),resetPaging = F,rownames = F)
# })
result_vals <- eventReactive(input$run,{
hepcl_type <- input$heptype
org <- "human"
age <- input$age
liver_wt<- input$liv_wt
hpgl <- input$hpgl
km <- input$km
scaled_hepcl <- switch(hepcl_type,
"hep_sc"=calculateScaledSCClearance(c(input$num_mscl,input$num_cycl),
c(input$sel_msunit,input$sel_cyunit),
org,age,
liver_wt,km,return_total = F),
"hep_s9"=calculateScaledS9Clearance(input$num_s9cl,input$sel_s9unit,
org,age,
liver_wt),
"hep_whole"=calculateScaledWholeHepClearance(input$num_whcl,input$sel_whunit,
liver_wt,hpgl,km),
"hep_fnl" = input$num_pmcl,
0
)
# hep_vals_2_return <- do.call(cbind,list(names(scaled_hepcl),scaled_hepcl))
recombList <- lapply(cypCl()$Clearance,'as.numeric')
names(recombList)<- as.list(cypCl()$Names)
scaled_recomcl <- calculateRecombClearance(recombList,"human",age,liver_wt,cypDb(),return_total = F)
# get the ages for which scaling has to happen
out_ages <- react_obj$ageTble()
if((length(out_ages)==0)){
out_ages <- c(age)
}else{
out_ages <- c(age,out_ages)
}
tot_scaled_recomcl <- sum(unname(scaled_recomcl))/liver_wt
tot_scaled_hepcl <- sum(unname(scaled_hepcl))/liver_wt
if (tot_scaled_hepcl>0 && tot_scaled_recomcl>0){
age_wise_enzymecl_table <- scale_cellular_enzymatic(out_ages,tot_scaled_hepcl,
tot_scaled_recomcl,cypDb(),
recombList,
input$gender)
}else{
age_wise_enzymecl_table <- scale_enzymatic(out_ages,
tot_scaled_recomcl,cypDb(),
recombList,
input$gender)
}
hep_vals_2_return <- switch(hepcl_type,
"hep_sc"= data.frame("name" =c("Microsomes","Cytosol"),val = unname(scaled_hepcl)/liver_wt),
"hep_s9"= data.frame("name"="S9Fraction","val"=scaled_hepcl/liver_wt,stringsAsFactors = F),
"hep_whole"= data.frame("name"="Whole Hepatocyte","val"=scaled_hepcl/liver_wt,stringsAsFactors = F),
"hep_fnl"= data.frame("name"="Precomputed","val"=scaled_hepcl/liver_wt,stringsAsFactors = F),
data.frame("name"="No Cellular Clearance","val"=0,stringsAsFactors = F)
)
recom_vals_2_return <-data.frame("name" = names(scaled_recomcl),"val"= unname(scaled_recomcl)/liver_wt,stringsAsFactors = F)
return(list("cellular_tble"=hep_vals_2_return,
"enzymatic_tble"=recom_vals_2_return,
"all_data" = list("ages"= out_ages,
"cellular_clearance"= scaled_hepcl/liver_wt,
"enzymatic_clearance" = age_wise_enzymecl_table)
))
})
output$out_heptble <- DT::renderDT(DT::datatable(result_vals()$cellular_tble,
caption = "Cellular Clearance",
colnames = c("Type","Clearance(L/h/kg liver)"),
rownames = NULL,autoHideNavigation = T,
options = list(dom = "tp",pageLength = 5)),server = T)
output$out_enztble <- DT::renderDT(DT::datatable(result_vals()$enzymatic_tble,
caption = "Recombinant Enzyme Clearance",
colnames = c("Type","Clearance(L/h/kg liver)"),
rownames = NULL,
options = list(dom = "tp",pageLength = 5)),server = T)
observeEvent(input$done,{
# handle data to be returned to the console
if (input$ret_data == "cl_ref"){
final_vals <- result_vals()$all_data
age <- final_vals$ages[1]
cellular_clearance <- sum(unname(final_vals$cellular_clearance))
enzymatic_clearance <- final_vals$enzymatic_clearance["Total",as.character(age)]
ret_data <- data.frame("Age"= age,"Cellular"= cellular_clearance,"Enzymatic"= enzymatic_clearance)
}else if(input$ret_data == "cl_all"){
final_vals <- result_vals()$all_data
age <- final_vals$ages
enzymatic_clearance <- final_vals$enzymatic_clearance["Total",]
cellular_clearance <- sum(unname(final_vals$cellular_clearance))
cellular_clearance <- c(cellular_clearance,rep(0,length(age)-1))
ret_data <- data.frame("Age"= age,"Cellular"= cellular_clearance,"Enzymatic"= enzymatic_clearance)
}else if(input$ret_data == "cl_detail"){
final_vals <- result_vals()$all_data
age <- final_vals$ages
enzymatic_clearance <- final_vals$enzymatic_clearance["Total",]
cellular_clearance <- sum(unname(final_vals$cellular_clearance))
cellular_clearance <- c(cellular_clearance,rep(0,length(age)-1))
cl_data <- data.frame("Age"= age,"Cellular"= cellular_clearance,"Enzymatic"= enzymatic_clearance)
ret_data <- list()
ret_data$tot_cl_data <- cl_data
ret_data$ind_enzyme_cl <- final_vals$enzymatic_clearance
ret_data$enzyme_data <- cypDb()
}else if(input$ret_data == "none"){
ret_data <- NULL
}
# handle file saving for vmax and vliv clearance if save flag is set to true
if(save_flag){
final_vals <- result_vals()$all_data
if (all(final_vals$enzymatic_clearance["Total",]!=0)){
vliv <- final_vals$enzymatic_clearance["Total",]
age <- final_vals$ages
}else{
vliv <- sum(unname(final_vals$cellular_clearance))
age <- final_vals$ages[1]
}
vmax <- vliv*input$km*input$liv_wt/(input$bw^0.75)
if(input$fname_vliv != ""){
write_data <- data.frame("Age"= age,"Clearance"=vliv,stringsAsFactors = F)
write.csv(write_data,file.path(base_path,paste0(input$fname_vliv,".csv")),row.names = F)
}
if(input$fname_vmax != ""){
write_data <- data.frame("Age"= age,"Clearance"=vmax,stringsAsFactors = F)
write.csv(write_data,file.path(base_path,paste0(input$fname_vmax,".csv")),row.names = F)
}
}
stopApp(returnValue = ret_data)
})
}
runGadget(ui,server,viewer =dialogViewer("IVIVE",width = 1200,height = 1800)) #dialogViewer("IVIVE",width = 800) )
}
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