2764 lines
102 KiB
R
2764 lines
102 KiB
R
################################################################################
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# 4PL and Linear bioassay evaluation
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# Author: Franz Innerbichler
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# 1.4.2026
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################################################################################
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library(shiny)
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library(shinydashboard)
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library(shinyjs)
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library(shinyAce)
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library(shinycssloaders)
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library(shinyBS)
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library(purrr)
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library(gslnls)
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library(tidyverse)
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library(ggplot2)
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library(reshape2)
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library(openxlsx)
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library(DT)
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library(ggpubr)
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library(gridExtra)
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library(drc)
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library(twopartm)
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library(car)
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library(dplyr)
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library(scales)
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source("../R/Global.R")
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#### ui ----
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ui <- dashboardPage(
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dashboardHeader(title = "Plateflow"),
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dashboardSidebar(
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sidebarMenu(
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img(src = "logov2.png", width = 230),
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menuItem("Home", tabName = "home", icon = icon("home")),
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menuItem("Data template",
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tabName = "template", icon = icon("table"),
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menuSubItem(tags$li(a("EXCEL File", target = "self", href = "TestFile.xlsx")))
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),
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# menuItem("User Manual /Validation", tabName = "manual", icon=icon("book"), # tabName here and in dashboard body need to be identical
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# menuSubItem(icon = NULL, tags$li(a("Document", target="self",href="UserManual.pdf")))
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# ),
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menuItem("INSPECT your data", tabName = "Dataupload", icon = icon("magnet", lib = "glyphicon")),
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menuItem("EXPLORE 4PL and linear reg", tabName = "fourPL", icon = icon("chart-line", lib = "font-awesome")),
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# menuItem("XLSX diagnostics", tabName="XLdiagn", icon=icon("chart-bar", lib="font-awesome")),
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# menuItem("Linear regression + report", tabName="pla", icon=icon("pencil", lib="glyphicon")),
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menuItem("OPTIMIZE with wizard", tabName = "wizard", icon = icon("chart-column", lib = "font-awesome")) # ,
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# menuItem("Documentation", tabName="documentation", icon=icon("chart-area", lib="font-awesome"))
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),
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tags$footer(
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HTML(paste(
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tags$strong(tags$u("InnerAnalytics")), paste(rep(" ", 9), collapse = ""),
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"Developer:", paste(rep(" ", 9), collapse = ""),
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"Host on:", paste(rep(" ", 9), collapse = ""),
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"Version:"
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)),
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align = "left", style =
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"position:fixed; bottom:0;width=100%; background: #FFC337BB; font-family: Times New Roman; font-size:100%;
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padding: 5px; color:#4545BA; box-sizing: border-box; z-index: 1000;"
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)
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),
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dashboardBody(
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fluidPage(
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tabItems(
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tabItem(tabName = "home", htmlOutput("homePage")),
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tabItem(tabName = "Dataupload", uiOutput("Dataupload")),
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tabItem(tabName = "fourPL", uiOutput("fourPL")),
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# tabItem(tabName = "XLdiagn", uiOutput("XLdiagn")),
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# tabItem(tabName = "pla", uiOutput("pla")),
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tabItem(tabName = "wizard", uiOutput("wizard")) # ,
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# tabItem(tabName = "documentation", uiOutput("docu"))
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)
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)
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),
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skin = "blue"
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)
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#### server ----
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server <- function(input, output, session) {
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#### reactive values ----
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Dat <- reactiveValues()
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REP <- reactiveValues()
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REPlin <- reactiveValues()
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# this sets the environment of all functions that need to have access to the
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# reactiveValues objects to the environment of the server function.
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# this way, the reactiveValues are specific to the server namespace
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environment(plot_f) <- environment()
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environment(pot4plFUNC) <- environment()
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environment(tests_FUNC) <- environment()
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#### renderUIs Home ----
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output$homePage <- renderUI({
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navbarPage(
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"Home",
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tabPanel(
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"Introduction",
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tags$style(HTML("pre { color: black; background-color: #7FAEFF55;
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font-family: 'Helvetica Neue', Helvetica, Arial, sans-serif;font-size: 12px;} ")),
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h4("Introduction to the plateflow software"),
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# tags$mark("linear regression"), br(),
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column(
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6,
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"INSPECT your plate reader data: This is the right place if you want to visualize your data in the context of a 4 PL fit or a linear regression fit. ",
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"Bring your data in a readable format and start inspecting.", br(),
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"Example of EXCEL/csv/numbers file:", br(),
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tags$img(src = "ExampleXL.png", class = "adv_logo", width = "100%"),
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"It needs to contain 1 column with the dilution concentrations (first or last column) and at least 2 columns of reference and test sample readouts, respectively.",
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"The reference readout columns have to be before the test sample readout columns. The column names for reference and test are free to set, but different for all columns.",
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"The column name of the dilution concentrations can be as follows: concentration, dose, log_concentration, log_dose (first letter can be capital)",
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"It is assumed, that the concentrations are in anti-log or in natural log mode.",
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),
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column(6, )
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),
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tabPanel(
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"Documentation",
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h4("Introduction "),
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h4("Information on dilution setting"),
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"(for details see:", a(href = "ADONIS.pdf", "Whitepaper", download = NA, target = "_blank"), ")", tags$br(),
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"Bend points are calculated according to following formula:",
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withMathJax(" $$bp_{1/2} = \\pm\\frac{1.31696}{Hill's slope}$$")
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),
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tabPanel(
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"Configuration",
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verbatimTextOutput("sessioninfo")
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)
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)
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})
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##### UI XL ----
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output$Dataupload <- renderUI({
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navbarPage(
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title = "",
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tabPanel(
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title = "Real data",
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tabsetPanel(
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tabPanel(
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"Data input",
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column(
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3,
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# img(src="Screenshot.png", width=200),
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box(
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title = "Upload", status = "warning", solidHeader = TRUE, width = 12, "Please upload your EXCEL file here",
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fileInput("iFile", "", accept = ".xlsx")
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),
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uiOutput(outputId = "sheetName"),
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"For data format in the EXCEL file see Data template",
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"If no data are uploaded, the settings to the right are used for calculations.",
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tags$head(tags$style(HTML("label {font-size:80%;margin-bottom: 3px;margin-top: 3px;}"))),
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div(checkboxInput("PureErr", "Should pure error be used for calculation of CIs?", FALSE),
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style = "font-size: 24px !important;color: #C2173F"
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),
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# actionLink("selectall","SelectAll"),
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h5("\n\n\n Author: Franz Innerbichler, InnerAnalytics")
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),
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column(
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4,
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h4("Suitability tests for 4-parametric logistic regression"),
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"(potency CI test is set per default)",
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checkboxGroupInput("selectedSSTs", "Which suitability tests to be used?",
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choices = c(
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"F-test on Regr." = "1",
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"EQ-test on lower asymptote difference" = "2",
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"EQ-test on ratio of lower asymptote" = "3", "EQ-test on ratio of Hill slopes" = "4",
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"EQ-test on ratio of upper asymptote" = "5", "F-test on Lack-of-Fit" = "6",
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"EQ-test on ratio of asymptote differences" = "7"
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),
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selected = c("1", "4", "5", "6", "7")
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),
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h4("Suitability tests for Parallel Line Assay"),
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checkboxGroupInput("selectedSSTsLinear", "Which suitability tests to be used?",
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choices = c(
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"F-test on Regr." = "1",
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"F-test on non-linearity" = "2",
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"F-test on R^2 A" = "3", "F-test on R^2 B" = "4",
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"F-test on slope A" = "5", "F-test on slope B" = "6",
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"F-test on non-parallelism" = "7", "F-test on preparation" = "8"
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),
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selected = c("1", "2", "3", "4", "5", "6", "7", "8")
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)
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),
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column(2,
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style = "background: #7FAEFF88",
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numericInput("lEACratiola", "lower EAC ratio of LAs", 0.005, step = 0.001),
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numericInput("uEACratiola", "upper EAC for ratio of LAs", 100, step = 1),
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numericInput("lEACratioSlope", "lower EAC for ratio of slopes", 0.55, step = 0.01),
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numericInput("uEACratioSlope", "upper EAC for ratio of slopes", 1.84, step = 0.1),
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numericInput("lEACratioua", "lower EAC for ratio of UAs", 0.75, step = 0.1),
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numericInput("uEACratioua", "upper EAC for ratio of UAs", 1.33, step = 0.1)
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),
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column(2,
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style = "background: #7FAEFF88",
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numericInput("lowerPot", "lower EAC for potency", 75, step = 1),
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numericInput("upperPot", "upper EAC for potency", 133, step = 1),
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numericInput("lEACratioAdiff", "lower EAC of ratio of asymptote differences", 0.75, step = 0.01),
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numericInput("uEACratioAdiff", "upper EAC of ratio of asymptote differences", 1.33, step = 0.01),
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numericInput("lEACdiffla", "lower EAC for diff. of LA", -0.175, step = 0.001),
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numericInput("uEACdiffla", "upper EAC for diff. of LA", 0.189, step = 0.001)
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)
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),
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tabPanel(
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"4pl-Analysis",
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tags$style(HTML("pre { color: black; background-color: #FFE1FF;
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font-family: 'Helvetica Neue', Helvetica, Arial, sans-serif;font-size: 12px;} ")),
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wellPanel(
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fluidRow(
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column(
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4,
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# h5("Diagnostics only shown if EXCEL is uploaded"),
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htmlOutput("PureErrW2"),
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tags$head(tags$style("#PureErrW2{color: red;
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font-size: 16px;
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font_style: italic;}")),
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tableOutput("Filesampl"),
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tableOutput("relpotTestTab"),
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plotOutput("relpotTestPlot", width = "300px", height = "150px"), # Pot CI plot
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h4("Akaike Information Criterion"),
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tableOutput("AIC"),
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h5("First row: restricted model; 2nd row: unrestricted model"),
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h5("Smaller values of AIC indicate better fit to the data"),
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box(
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title = "Useful information", status = "info", solidHeader = TRUE, width = 12, "", collapsible = TRUE,
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tableOutput("VarDiagn")
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)
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),
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column(
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8,
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plotOutput("XLplot"),
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htmlOutput("No4PLFitText"),
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DTOutput("pottab4plXL"),
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box(
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title = "Residuals and QQ-plot", status = "info", solidHeader = TRUE, width = 12, "", collapsible = TRUE,
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plotOutput("diagnplot")
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),
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box(
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title = "Assay Suitability Tests", status = "info", solidHeader = TRUE, width = 12, "", collapsible = TRUE,
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DTOutput("EQtests")
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),
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DTOutput("pottab4plTransXL"),
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box(
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title = "ANOVA", status = "info", solidHeader = TRUE, width = 12, "", collapsible = TRUE,
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tableOutput("ANOVAXLS")
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)
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)
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)
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)
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),
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tabPanel(
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"linear Analysis",
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sidebarLayout(
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sidebarPanel(
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width = 2,
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fluidRow(
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column(
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12,
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numericInput("EACLinlow", "Potency CL to be > than", value = 80),
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numericInput("EACLinupp", "Potency CL to be < than", value = 125)
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)
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)
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),
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mainPanel(
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tabsetPanel(
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id = "tabs",
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tabPanel(
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"Plot and models",
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column(
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12,
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htmlOutput("PureErrWLinXL"),
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tags$head(tags$style("#PureErrWLinXL{color: red;
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font-size: 16px;
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font_style: italic;}")),
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plotOutput("plotLin"),
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"Delta method is used for potency CIs",
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DT::dataTableOutput("pottab"),
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h4("Unrestricted linear model (SSSI):"),
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tableOutput("SummaryModABu"),
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h4("Restricted linear model (CSSI):"),
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tableOutput("SummaryModAB"),
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)
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),
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tabPanel(
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"Tests and ANOVAA",
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column(
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12,
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h3("Tests for linear PLA:"),
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box(
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title = "Suitability tests", status = "primary", solidHeader = TRUE, width = 12,
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DTOutput("TESTSlin")
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),
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h5("The estimate is the p-value of the test"),
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h5("F-tests on regression, significance of slopes, and preparation need to have a p-value <0.05 to pass"),
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h5("All other tests pass if p-value > 0.05"),
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"SST CI for difference of slopes:",
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# tableOutput("SlopeDiffCI"),
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h3("ANOVA for parallel line assay"),
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DTOutput("ANOVAlin")
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)
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),
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# tabPanel("Report",
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# h4("Settings for report"),
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#
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# )
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)
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)
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)
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),
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tabPanel(
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"parameter estimates",
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htmlOutput("PureErrWParEst"),
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tags$head(tags$style("#PureErrWParEst{color: red;
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font-size: 16px;
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font_style: italic;}")),
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column(3,
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style = "background: #4FCBD922",
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br(),
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h4("Regression results restricted"),
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tableOutput("coeffs_r"),
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"Bend points restricted",
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tableOutput("bends_r2")
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),
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column(3,
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style = "background: #B5C74022",
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br(),
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h4("Regression results unrestricted"),
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tableOutput("coeffs_unr")
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),
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column(3,
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style = "background: #F9545422",
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h4("Regression results (ln-transformed)"),
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tableOutput("logcoeffs_r"),
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tableOutput("bends_unr2"),
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tableOutput("logcoeffs_unr")
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)
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),
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tabPanel(
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"Report",
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h4("Settings for report"),
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useShinyjs(),
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actionButton("btn", "Download 4PL PDF report", icon = icon("download")),
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downloadButton("downloadXLReport", style = "visibility: hidden;"),
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#downloadButton("downloadXLReport", label = "Download 4PL PDF report", class = "butt"),
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tags$style(type = "text/css", "#downloadXLReport {background-color: orange; color: black;font-family: Courier New}"),
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downloadButton("downloadXLReportLin", label = "Download linear PLA PDF report", class = "butt"),
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tags$style(type = "text/css", "#downloadXLReportLin {background-color: #4FCBD9; color: black;font-family: Courier New}"),
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textInput("Author", "Author", value = ""),
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textInput("RepIdentifier", "Report name", value = ""),
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textInput("NoP", "Product name", value = ""),
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textInput("Assay", "Assay name", value = "")
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)
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)
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)
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)
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})
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##### UI Meta ----
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output$fourPL <- renderUI({
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navbarPage(
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title = "4PL+linear reg",
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tabPanel(
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"Analysis and Plots",
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# sidebarLayout(
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# sidebarPanel(
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# width=4,
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# fluidRow(
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# )
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# ),
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mainPanel(
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width = 12,
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tabsetPanel(
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id = "tabs",
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tabPanel(
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"Settings",
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h4("Settings of 4PL regression"),
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div(checkboxInput("PureErrMeta", "Should pure error be used for calculation of CIs?", FALSE),
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style = "font-size: 24px !important;color: #C2173F"
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),
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h4("User help"),
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h5("If new dilutions are entered, please adjust EC50 to avoid calculation errors"),
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# numericInput("Limits",p("limit to be >", bsButton("q4",label="", icon=icon("info"), style="primary", size="extra-small")),
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# bsPopover(id="q4", title="", content="The calculated limits ...")),
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# h5("Diagnostics only shown if EXCEL is uploaded"),
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column(
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2,
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h3("Settings"),
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helpText("Vary the slider to see the effect of special cause"),
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sliderInput("sdfac", "Variability as % of lower to upper asymptote", max = 10, value = 3, min = 0.1, step = 0.1),
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checkboxInput("heterosked", "heteroskedastic noise", FALSE),
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sliderInput("potencydiff", "potency of test (%)", max = 200, min = 50, value = 100, step = 1),
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# sliderInput("outlL","outlier in lower asymptote", min=0, max=1.5, value=0, step=0.1),
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# sliderInput("outlM","outlier in mid part", min=0, max=1.5,value=0, step=0.1),
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# sliderInput("outlU","outlier in upper asymptote", min=0, max=1.5,value=0, step=0.1)
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),
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column(2,
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style = "background: #7FAEFF",
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# actionButton("StartCalc", "Click, when calculations to be started"),
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h4("curve settings"),
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numericInput("lowAsymptREF", "lower asymptote REF", 10, step = 1, min = 0),
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numericInput("lowAsymptTEST", "lower asymptote TEST", 10, step = 1, min = 0),
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numericInput("uppAsymptREF", "upper asymptote REF", 110, step = 1, min = 0),
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numericInput("uppAsymptTEST", "upper asymptote TEST", 110, step = 1, min = 0)
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),
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column(2,
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style = "background: #7FAEFF",
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numericInput("slopeREF", "slope REF", 1, step = 0.1, min = -10),
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numericInput("slopeTEST", "slope TEST", 1, step = 0.1, min = -10),
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numericInput("EC50", "EC50 REF", -3.5),
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numericInput("potDiff", "potency difference", 0)
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),
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column(2,
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style = "background: #627ADD",
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h4("dilutions"),
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numericInput("CONC1", "highest concentration", 0.3, min = -3.5),
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numericInput("CONC2", "2nd concentration", 0.15),
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numericInput("CONC3", "3rd concentration", 0.075),
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numericInput("CONC4", "4th concentration", 0.0375),
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numericInput("CONC5", "5th concentration", 0.01875),
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numericInput("CONC6", "6th concentration", 0.00938)
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),
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column(2,
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style = "background: #627ADD",
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numericInput("CONC7", "7th concentration", 0.00469),
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numericInput("CONC8", "8thd concentration", 0.00235),
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numericInput("CONC9", "9thd concentration", value = NA),
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numericInput("CONC10", "10th concentration", value = NA),
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numericInput("CONC11", "11th concentration", value = NA),
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numericInput("CONC12", "lowest concentration", NA)
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),
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column(2,
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style = "background: #4FCBD9",
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h4("geometric dilution scheme"),
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numericInput("ConcStart", "starting concentration", value = NA, min = 0),
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numericInput("dilutionFac", "dilution factor", value = NA, min = 0, max = 10),
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numericInput("NoDil", "no. of dilutions", value = NA, min = 8),
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numericInput("NoDilSer", "no. of dil. series", value = NA),
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verbatimTextOutput("dilutions")
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),
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h4("log-dilutions from settings above"),
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column(
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8,
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box(
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title = "Simulated data per log-concentration", status = "warning", solidHeader = TRUE, width = 12, "incl. mean, sd and CV%",
|
|
DT::dataTableOutput("ConctabMeta")
|
|
),
|
|
verbatimTextOutput("logdil")
|
|
)
|
|
|
|
# )
|
|
),
|
|
#### 4pl fits ----
|
|
tabPanel(
|
|
"4pl-fit",
|
|
wellPanel(
|
|
fluidRow(
|
|
column(
|
|
10,
|
|
htmlOutput("PureErrW4plMeta"),
|
|
tags$head(tags$style("#PureErrW4plMeta{color: red;
|
|
font-size: 16px;
|
|
font_style: italic;}")),
|
|
plotOutput("plot4plMeta", width = "80%"),
|
|
DTOutput("pottab4pl"),
|
|
"Footnote: test performed on relative CIs.",
|
|
DTOutput("EQtests4pl"), # SSTs
|
|
h5("*...The estimate for F-test on regression and on Lack-of-Fit is the p-value"),
|
|
h5("F-test on regression passes if F-value > F-crit and thus p < 0.05"),
|
|
h5("F-test on Lack-of-Fit passes if F-value < F-crit and thus p > 0.05"),
|
|
h5("Test results outcome: 0 ... test passed (for EQ tests: CI within limits);
|
|
1 ... test failed (for EQ tests CI not within limits);
|
|
-1 ... calculations unbound/denominator too close to 0"),
|
|
# plotOutput("CIplot, height=50%")
|
|
),
|
|
column(
|
|
8,
|
|
"4 PL ANOVA unrestricted",
|
|
box(
|
|
title = "ANOVA unrestricted", status = "warning", solidHeader = TRUE, width = 12, "",
|
|
DT::dataTableOutput("ANOVA")
|
|
),
|
|
h5("Please note that for the CIs of rel. potency the RSS of the restricted model is used"),
|
|
h5("RSS ... 'Residual error' in the SumSquares column"),
|
|
h5("MSE ... 'Residual error' in the MeanSquaress column"),
|
|
h5("SSE ... 'Pure error' in the SumSquares column"),
|
|
h5("RMSE ... Square root of the 'Residual Error' in the MeanSquares column"),
|
|
verbatimTextOutput("RMSE")
|
|
)
|
|
)
|
|
)
|
|
),
|
|
tabPanel(
|
|
"ln-transformed y",
|
|
htmlOutput("PureErrWLogMeta"),
|
|
tags$head(tags$style("#PureErrWLogMeta{color: red;
|
|
font-size: 16px;
|
|
font_style: italic;}")),
|
|
h4("ln-transformed y-axis plots"),
|
|
plotOutput("plot4plTransMeta", width = "80%"),
|
|
DT::dataTableOutput("pottab4plTrans"),
|
|
),
|
|
tabPanel(
|
|
"linear regression",
|
|
htmlOutput("PureErrW3"),
|
|
h4("Evaluations from meta-data"),
|
|
tags$head(tags$style("#PureErrW3{color: red;
|
|
font-size: 16px;
|
|
font_style: italic;}")),
|
|
column(
|
|
12,
|
|
plotOutput("plotLinMeta"),
|
|
"Delta method is used for potency CIs",
|
|
DTOutput("pottabMeta")
|
|
),
|
|
column(
|
|
5,
|
|
h3("Tests for linear PLA:"),
|
|
box(
|
|
title = "Suitability tests", status = "primary", solidHeader = TRUE, collapsible = TRUE, width = 12,
|
|
DTOutput("TESTSlinMeta")
|
|
),
|
|
h5("The estimate is the p-value of the test"),
|
|
h5("F-tests on regression, significance of slopes, and preparation need to have a p-value <0.05 to pass"),
|
|
h5("All other tests pass if p-value > 0.05"),
|
|
box(
|
|
title = "Unrestricted linear model (SSSI):", status = "primary", solidHeader = TRUE, collapsible = TRUE, width = 12,
|
|
tableOutput("SummaryModABuMeta")
|
|
),
|
|
h4("Restricted linear model (CSSI):"),
|
|
box(
|
|
title = "Restricted linear model (CSSI):", status = "primary", solidHeader = TRUE, collapsible = TRUE, width = 12,
|
|
tableOutput("SummaryModABMeta")
|
|
)
|
|
),
|
|
column(
|
|
6,
|
|
h3("ANOVA for parallel line assay"),
|
|
box(
|
|
title = "ANOVA for simultated data", status = "primary", solidHeader = TRUE, collapsible = TRUE, width = 12,
|
|
DTOutput("ANOVAlinMeta")
|
|
),
|
|
" CI for difference of slopes:",
|
|
tableOutput("SlopeDiffCIMeta"),
|
|
)
|
|
),
|
|
tabPanel(
|
|
"Report",
|
|
h4("Settings for report"),
|
|
downloadButton("downloadXLReport", label = "Download PDF report", class = "butt"),
|
|
tags$style(type = "text/css", "#downloadXLReport {background-color: orange; color: black;font-family: COurier New}"),
|
|
)
|
|
)
|
|
)
|
|
# )
|
|
)
|
|
)
|
|
})
|
|
|
|
output$sessioninfo <- renderPrint(sessionInfo())
|
|
|
|
output$pla <- renderUI({
|
|
navbarPage(
|
|
title = "pla",
|
|
tabPanel("Analysis and Plots", )
|
|
)
|
|
})
|
|
|
|
|
|
#### UI wizard ----
|
|
output$wizard <- renderUI({
|
|
navbarPage(
|
|
title = "Dilution setting",
|
|
tabPanel(
|
|
"Plots",
|
|
sidebarLayout(
|
|
sidebarPanel(
|
|
width = 3,
|
|
fluidRow(
|
|
|
|
box(
|
|
title = "Upload multiple worksheets", status = "warning", solidHeader = TRUE, width = 12, "Please upload your EXCEL file here",
|
|
fileInput("MiFile", "", accept = ".xlsx")
|
|
)
|
|
)
|
|
),
|
|
mainPanel(
|
|
tabsetPanel(
|
|
id = "tabs",
|
|
tabPanel("4pl",
|
|
box(
|
|
title = "ANOVA table", status = "primary", solidHeader = TRUE, width = 12,
|
|
tableOutput("Anovatab")
|
|
),
|
|
|
|
column(12,
|
|
# h3("Confidence intervals"),
|
|
# tableOutput("CIs"),
|
|
# "The confidence interval table is interactive for changes in: variability slider (%SD), potency of test-slider,
|
|
# and 'Adjust the dilutions'-slider",
|
|
# tableOutput("optimalDils"),
|
|
plotOutput("sigPlotREF"),
|
|
plotOutput("sigPlotTEST"),
|
|
#selectInput(inputId = "scenario", label = "Select an 'optimal' scenario:", choices = c("scenario 2", "scenario 3", "scenario 6", "steep slope"))
|
|
|
|
plotOutput("plotfordilutions"),
|
|
# h4("in grey: most extreme bend point lines of theoretical samples with 50% and 200% potency"),
|
|
# sliderInput("dilslider", "Adjust the dilutions(+-change in %)", min = -100, max = 100, value = 0, step = 1, round = 0),
|
|
# checkboxInput("fixupper", "Fix highest concentration (if unticked, the center is fixed)", FALSE),
|
|
# h5("Dilution factors"),
|
|
# tableOutput("adjlogdil"),
|
|
# "Short guidance: wider dilution ranges increase the CIs of rel. potency, and decrease the CIs of upper and lower asymptote ratios, as well as Hill's slope ratios", br(),
|
|
# "Narrower dilution ranges decrease the CIs of rel. potency, and increase the CIs of upper and lower asymptote ratios, ands Hill's slope ratios",
|
|
|
|
),
|
|
column(
|
|
3,
|
|
h3("Bend points"),
|
|
tableOutput("bps"),
|
|
tableOutput("extremebps"),
|
|
h4("Explanation of the plots")
|
|
)
|
|
),
|
|
tabPanel("Histograms",
|
|
h4("Histograms of parameters"),
|
|
plotOutput("histCIs"),
|
|
plotOutput("histEC50REF"),
|
|
plotOutput("histLasREF"),
|
|
plotOutput("histUasREF"),
|
|
|
|
),
|
|
tabPanel(
|
|
"Report",
|
|
h4("Settings for report")
|
|
)
|
|
)
|
|
)
|
|
)
|
|
)
|
|
)
|
|
})
|
|
|
|
|
|
v <- reactiveValues(num_dose = 0, next.dose.t = 0)
|
|
|
|
sigmoid <- reactive({
|
|
sig <- c(
|
|
input$lowAsymptREF, input$lowAsymptTEST, input$uppAsymptREF, input$uppAsymptTEST,
|
|
input$slopeREF, input$slopeTEST, input$EC50, input$potDiff
|
|
)
|
|
sig
|
|
})
|
|
|
|
CONC <- reactive({
|
|
Konz_ <- c(
|
|
input$CONC1, input$CONC2, input$CONC3, input$CONC4,
|
|
input$CONC5, input$CONC6, input$CONC7, input$CONC8,
|
|
input$CONC9, input$CONC10, input$CONC11, input$CONC12
|
|
)
|
|
if (any(na.omit(Konz_) == 0)) Konz_[Konz_ == 0] <- 0.0000001
|
|
Konz <- na.omit(Konz_)
|
|
})
|
|
|
|
Dils <- reactive({
|
|
Dilutions <- c(input$ConcStart, input$dilutionFac, input$NoDil, input$NoDilSer)
|
|
})
|
|
|
|
#### input EXCEL file ----
|
|
|
|
observe({
|
|
if (!is.null(input$iFile)) {
|
|
inFile <- input$iFile
|
|
ext <- tools::file_ext(inFile$name)
|
|
file.rename(inFile$datapath, paste(inFile$datapath, ".xlsx", sep = ""))
|
|
t.filelocation <- gsub("\\\\", "/", paste(inFile$datapath, ext, sep = "."))
|
|
sheets <- openxlsx::getSheetNames(t.filelocation)
|
|
dat <- lapply(sheets, openxlsx::read.xlsx, xlsxFile = t.filelocation)
|
|
names(dat) <- sheets
|
|
Dat$wb <- dat
|
|
names(Dat$wb) <- sheets
|
|
Dat$sheets <- sheets
|
|
Dat$FileName <- input$iFile[["name"]]
|
|
}
|
|
})
|
|
output$sheetName <- renderUI({
|
|
if (!is.null(Dat$wb)) {
|
|
cnSheets <- Dat$sheets
|
|
cnSheets2 <- c("please choose", cnSheets)
|
|
selectInput(inputId = "sheet", label = "Select a sheet:", choices = cnSheets)
|
|
}
|
|
})
|
|
observeEvent(input$sign_out, {
|
|
unlink(input$iFile$datapath)
|
|
reset(id = "") # from shinyjs package
|
|
})
|
|
|
|
|
|
observe({
|
|
if (!is.null(input$MiFile)) {
|
|
MinFile <- input$MiFile
|
|
ext <- tools::file_ext(MinFile$name)
|
|
file.rename(MinFile$datapath, paste(MinFile$datapath, ".xlsx", sep = ""))
|
|
t.filelocation <- gsub("\\\\", "/", paste(MinFile$datapath, ext, sep = "."))
|
|
sheets <- openxlsx::getSheetNames(t.filelocation)
|
|
dat <- lapply(sheets, openxlsx::read.xlsx, xlsxFile = t.filelocation)
|
|
names(dat) <- sheets
|
|
Dat$Mws <- dat
|
|
names(Dat$Mws) <- sheets
|
|
Dat$Msheets <- sheets
|
|
Dat$MFileName <- input$MiFile[["name"]]
|
|
}
|
|
})
|
|
|
|
#### process XLSX file ----
|
|
observe({
|
|
if (!is.null(input$iFile)) {
|
|
if (!is.null(input$sheet)) {
|
|
if (input$sheet != "please choose") {
|
|
Dat$RepIdentifier <- input$RepIdentifier
|
|
Dat$Author <- input$Author
|
|
Dat$NoP <- input$NoP
|
|
Dat$Assay <- input$Assay
|
|
Dat$FITsFlag <- FALSE
|
|
# browser()
|
|
XLdat <- Dat$wb[input$sheet][[1]]
|
|
if (is.null(XLdat)) XLdat <- Dat$wb[Dat$sheets[1]][[1]]
|
|
cn <- colnames(XLdat)
|
|
logI <- grep("log|ln", cn)
|
|
logDoseI <- grep("log_dose", cn)
|
|
if (length(logI) > 0 & length(logDoseI) == 0) {
|
|
XLdat$log_dose <- XLdat[, logI]
|
|
XLdat2 <- XLdat[, -logI]
|
|
CORro <- cor(XLdat$log_dose, XLdat[, 3])
|
|
} else if (length(logI) == 0 & length(logDoseI) == 0) {
|
|
Ind <- grep(".ilution|.ose|.onc", cn)
|
|
XLdat$log_dose <- log(XLdat[, Ind])
|
|
CORro <- cor(XLdat[, Ind], XLdat[, 3])
|
|
XLdat2 <- XLdat[, -Ind]
|
|
} else if (length(logI) > 0 & length(logDoseI) > 0) {
|
|
XLdat2 <- XLdat
|
|
CORro <- cor(XLdat[, logI], XLdat[, 3])
|
|
}
|
|
Dat$EXCEL <- XLdat2
|
|
PureErrFlag <- input$PureErr
|
|
warning_text2 <- reactive({
|
|
ifelse(PureErrFlag, "Pure Error is selected", "")
|
|
})
|
|
output$PureErrW2 <- renderText(warning_text2())
|
|
|
|
warning_textPureErr <- reactive({
|
|
ifelse(PureErrFlag, "Pure Error is selected", "")
|
|
})
|
|
output$PureErrWParEst <- renderText(warning_textPureErr())
|
|
|
|
REP$PureErr <- PureErrFlag
|
|
|
|
noDilSeries <- (ncol(XLdat2) - 1) / 2
|
|
noDils <- nrow(XLdat2)
|
|
Dat$noDilSeriesXL <- noDilSeries
|
|
|
|
all_l <- melt(data.frame(XLdat2), id.vars = "log_dose", variable.name = "replname", value.name = "readout")
|
|
isRef <- rep(c(1, 0), 1, each = nrow(XLdat2) * noDilSeries)
|
|
isSample <- rep(c(0, 1), 1, each = nrow(XLdat2) * noDilSeries)
|
|
all_l$isRef <- isRef
|
|
all_l$isSample <- isSample
|
|
all_l$Conc <- exp(all_l$log_dose)
|
|
# all_l$readout[all_l$readout < 0] <- 0.01
|
|
REP$all_l <- all_l
|
|
|
|
#### XLSX eval ----
|
|
#if (CORro < 0) SLOPE <- -1 else SLOPE <- 1
|
|
FITs <- Fitting_FUNC(XLdat2, TransFlag = FALSE)
|
|
|
|
#### if no 4pl fit is possible ----
|
|
if (!is.null(FITs)) {
|
|
if (is.character(FITs)) {
|
|
Dat$FITsFlag <- TRUE
|
|
|
|
pSing <- plotSingularity(XLdat2)
|
|
|
|
output$plotSing <- renderPlot({
|
|
pSing
|
|
})
|
|
|
|
output$XLplot <- renderPlot({
|
|
REP$XLplotSing <- pSing
|
|
|
|
pSing
|
|
})
|
|
|
|
warning_textNo4PLFit <- reactive({
|
|
ifelse(Dat$FITsFlag, "No meaningful 4PL fit was possible. This may havea several reasons: \nA control sample was tested/\n
|
|
the EC50 is not catched with the dilutions/\n the assay/reader had a problem",
|
|
"Footnote: bendpoints (linear part) and asymptote points (point where asymptote is reached) are plotted in dashed and dotted lines. They indicate whether the linear part and asymptotes are catched with the current dilutions.
|
|
Black line is the true slope at EC50 of REF."
|
|
)
|
|
})
|
|
output$No4PLFitText <- renderText(warning_textNo4PLFit())
|
|
|
|
output$relpotTestTab <- renderTable({
|
|
NULL
|
|
})
|
|
output$relpotTestPlot <- renderPlot({
|
|
NULL
|
|
})
|
|
|
|
output$AIC <- renderTable({
|
|
NULL
|
|
})
|
|
output$VarDiagn <- renderTable({
|
|
NULL
|
|
})
|
|
|
|
output$pottab4plXL <- renderDT({
|
|
NULL
|
|
})
|
|
output$diagnplot <- renderPlot({
|
|
NULL
|
|
})
|
|
output$EQtests <- renderDT({
|
|
NULL
|
|
})
|
|
#
|
|
output$pottab4plTransXL <- renderDT({
|
|
NULL
|
|
})
|
|
output$ANOVAXLS <- renderTable({
|
|
NULL
|
|
})
|
|
|
|
output$coeffs_r <- renderTable({
|
|
NULL
|
|
})
|
|
|
|
output$bends_r2 <- renderTable({
|
|
NULL
|
|
})
|
|
output$coeffs_unr <- renderTable({
|
|
NULL
|
|
})
|
|
output$logcoeffs_r <- renderTable({
|
|
NULL
|
|
})
|
|
output$bends_unr2 <- renderTable({
|
|
NULL
|
|
})
|
|
output$logcoeffs_unr <- renderTable({
|
|
NULL
|
|
})
|
|
|
|
|
|
return(NULL)
|
|
}
|
|
}
|
|
|
|
Smr <- FITs[[1]] # summary(mr)
|
|
Smu <- FITs[[2]] # summary(mu)
|
|
coeffsMR <- Smr$coefficients[, 1]
|
|
coeffsMU <- Smu$coefficients[, 1]
|
|
Dat$coeffsMRes <- coeffsMR
|
|
Dat$coeffsMUnr <- coeffsMU
|
|
Dat$coeffs_UN <- coeffsMU
|
|
names(coeffsMU) <- c("lowAsym REF", "slope REF", "upperAsym REF", "EC50 REF", "lowAsym TEST", "slope TEST", "upperAsym TEST", "r")
|
|
XbendMUlREF <- coeffsMU[4] - 1.5434 / abs(coeffsMU[2])
|
|
XbendMUuREF <- coeffsMU[4] + 1.5434 / abs(coeffsMU[2])
|
|
XbendMUlTEST <- coeffsMU[4] - coeffsMU[8] - 1.5434 / abs(coeffsMU[6])
|
|
XbendMUuTEST <- coeffsMU[4] + coeffsMU[8] + 1.5434 / abs(coeffsMU[6])
|
|
XbendMRlREF <- coeffsMR[4] - 1.5434 / abs(coeffsMR[2])
|
|
XbendMRuREF <- coeffsMR[4] + 1.5434 / abs(coeffsMR[2])
|
|
XbendMRlTEST <- coeffsMR[4] - coeffsMR[5] - 1.5434 / abs(coeffsMR[2])
|
|
XbendMRuTEST <- coeffsMR[4] - coeffsMR[5] + 1.5434 / abs(coeffsMR[2])
|
|
XasymlREF <- coeffsMR[4] - 3 / abs(coeffsMR[2])
|
|
XasymuREF <- coeffsMR[4] + 3 / abs(coeffsMR[2])
|
|
XasymlTEST <- coeffsMR[4] - coeffsMR[5] - 3 / abs(coeffsMR[2])
|
|
XasymuTEST <- coeffsMR[4] - coeffsMR[5] + 3 / abs(coeffsMR[2])
|
|
BPsMR_MU <- data.frame(
|
|
points = c(
|
|
"lower bendpoint REF", "upper bendpoint REF", "lower bendpoint TEST", "upper bendpoint TEST",
|
|
"lower asymp. point REF", "upper asymp. point REF", "lower asymp. point TEST", "upper asymp. point TEST",
|
|
"bendREF_lower_unrestr", "bendREF_upper_unrestr", "bendTESTE_lower_unrestr", "bendTEST_upper_unrestr"
|
|
),
|
|
estimates = c(
|
|
round(XbendMRlREF, 3), round(XbendMRuREF, 3), round(XbendMRlTEST, 3), round(XbendMRuTEST, 3),
|
|
round(XasymlREF, 3), round(XasymuREF, 3), round(XasymlTEST, 3), round(XasymuTEST, 3),
|
|
round(XbendMRlREF, 3), round(XbendMRuREF, 3), round(XbendMRlTEST, 3), round(XbendMRuTEST, 3)
|
|
)
|
|
)
|
|
Dat$bendsAll <- BPsMR_MU
|
|
REP$bendsAll <- BPsMR_MU
|
|
|
|
if (!PureErrFlag) {
|
|
pot_est <- FITs[[3]]
|
|
potU_est <- FITs[[4]]
|
|
colnames(pot_est) <- c("estimate", "lowerCI", "upperCI")
|
|
colnames(potU_est) <- c("estimate", "lowerCI", "upperCI")
|
|
} else {
|
|
FitAnova <- anova(lm(readout ~ factor(log_dose) * isSample, all_l))
|
|
meanPureErr <- FitAnova[4, 3]
|
|
DFsPure <- FitAnova[4, 1]
|
|
# VCOV <- vcov(mr)
|
|
V_V <- Smr$cov.unscaled # VCOV/Smr$sigma^2
|
|
# VCOVpure <- V_V*meanPureErr
|
|
SEsPure <- sqrt(diag(V_V) * meanPureErr)
|
|
pot_est <- data.frame(
|
|
estimate = exp(coeffsMR[5]), lowerCI = exp(coeffsMR[5] - qt(0.975, DFsPure) * SEsPure[5]),
|
|
upperCI = exp(coeffsMR[5] + qt(0.975, DFsPure) * SEsPure[5])
|
|
)
|
|
# VCOVu <- vcov(mu)
|
|
V_Vu <- Smu$cov.unscaled
|
|
# VCOVpure <- V_Vu*meanPureErr
|
|
SEsPureU <- sqrt(diag(V_Vu) * meanPureErr)
|
|
potU_est <- data.frame(
|
|
estimate = exp(coeffsMU[8]), lowerCI = exp(coeffsMU[8] - qt(0.975, DFsPure) * SEsPureU[8]),
|
|
upperCI = exp(coeffsMU[8] + qt(0.975, DFsPure) * SEsPureU[8])
|
|
)
|
|
}
|
|
|
|
|
|
Dat$potDiffXL <- potU_est[1] * 100
|
|
RMSE_unr_diagn <- Smu$sigma # sqrt(SU$resVar)
|
|
RMSE_res_diagn <- Smr$sigma # sqrt(SR$resVar)
|
|
up_lowDiffDiagn <- Smu$coefficients["ds", 1] - Smu$coefficients["as", 1]
|
|
ProzSD_diagn <- RMSE_unr_diagn * 100 / up_lowDiffDiagn
|
|
Dat$ProzSD_XL <- ProzSD_diagn
|
|
|
|
observe({
|
|
pot_est3 <- data.frame(pot_est * 100)
|
|
MaxPl <- max(input$upperPot, pot_est3$upperCI)
|
|
MinPl <- min(input$lowerPot, pot_est3$lowerCI)
|
|
MaxPl_ <- MaxPl * 1.2
|
|
MinPl_ <- MinPl * 0.8
|
|
p_relCI <- ggplot(data = pot_est3, aes(xmin = lowerCI, xmax = upperCI, y = 1)) +
|
|
geom_linerange(size = 4, col = "darkseagreen", alpha = 0.5) +
|
|
geom_point(aes(x = estimate, y = 1), col = "grey15", shape = 13, size = 10) +
|
|
geom_vline(xintercept = c(input$lowerPot, input$upperPot), col = "indianred") +
|
|
annotate("text", x = input$lowerPot - 13, y = 1.040, label = paste("lower EAC:", input$lowerPot), col = "indianred") +
|
|
annotate("text", x = input$upperPot + 13, y = 1.040, label = paste("upper EAC:", input$upperPot), col = "indianred") +
|
|
annotate("text", x = pot_est3$lowerCI - 10, y = 1.020, label = paste("lower CL:", round(pot_est3$lowerCI, 1)), col = "darkgreen") +
|
|
annotate("text", x = pot_est3$upperCI + 10, y = 1.020, label = paste("upper CL:", round(pot_est3$upperCI, 1)), col = "darkgreen") +
|
|
annotate("text", x = pot_est3$estimate, y = 0.98, label = paste("rel. potency:", round(pot_est3$estimate, 1)), col = "black") +
|
|
ylim(c(0.95, 1.05)) +
|
|
xlim(c(MinPl_, MaxPl_)) +
|
|
xlab("relative potency + confidence interval") +
|
|
theme_bw() +
|
|
theme(
|
|
axis.title.y = element_blank(),
|
|
axis.text.y = element_blank(),
|
|
axis.ticks.y = element_blank()
|
|
)
|
|
output$relpotTestPlot <- renderPlot({
|
|
p_relCI
|
|
})
|
|
REP$relpotTestPlot <- p_relCI
|
|
|
|
output$relpotTestTab <- renderTable({
|
|
pot_est3
|
|
})
|
|
})
|
|
|
|
|
|
ANOVAtab2 <- ANOVA4plUnresfunc(ro_new = XLdat2)
|
|
output$ANOVAXLS <- renderTable({
|
|
ANOVAtab2
|
|
})
|
|
|
|
REP$ANOVAXLS <- ANOVAtab2
|
|
|
|
FITsTrans <- Fitting_FUNC(XLdat2, TransFlag = TRUE)
|
|
#
|
|
|
|
SUlog <- FITsTrans[[2]]
|
|
SRlog <- FITsTrans[[1]]
|
|
RMSE_unrlog_diagn <- SUlog$sigma
|
|
RMSE_reslog_diagn <- SRlog$sigma
|
|
|
|
up_lowDifflogDiagn <- SUlog$coefficients["ds", 1] - SUlog$coefficients["as", 1]
|
|
ProzSDlog_diagn <- RMSE_unrlog_diagn * 100 / up_lowDifflogDiagn
|
|
|
|
#### Diagnostic RMSE table ####
|
|
DiagnTable <- data.frame(
|
|
parameter = c(
|
|
"RMSE unrestricted", "RMSE_restr.", "Diff_upper-lowerAsymp", "%SD (unrestricted)",
|
|
"RMSE log_unrestricted", "RMSE log_restr", "diff_up-lowAsymp_log", "%SD (log unrestricted)"
|
|
),
|
|
result = c(
|
|
round(RMSE_unr_diagn, 4), round(RMSE_res_diagn, 4),
|
|
round(up_lowDiffDiagn, 4), round(ProzSD_diagn, 4),
|
|
round(RMSE_unrlog_diagn, 4), round(RMSE_reslog_diagn, 4),
|
|
round(up_lowDifflogDiagn, 4), round(ProzSDlog_diagn, 4)
|
|
)
|
|
)
|
|
|
|
Dat$DiagnTable <- DiagnTable
|
|
REP$DiagnTable <- DiagnTable
|
|
|
|
logpotest <- FITsTrans[[3]] # exp(confintd(mrlog, "r", method = "asymptotic")) # compParm(logpot, "c")
|
|
logpotUest <- FITsTrans[[4]] # exp(confintd(mulog, "r", method = "asymptotic")) # compParm(logpotu, "c")
|
|
|
|
# Berechnung der Konfidenzintervalle (CI)
|
|
# logpotCI <- c(exp(Smrlog[5,1] - qt(0.975, nrow(all_1)-5) * Smrlog[5,2]), exp(Smrlog[5,1]), exp(Smrlog[5,1] + qt(0.975, nrow(all_1)-5) * Smrlog[5,2]))
|
|
colnames(logpotest) <- c("estimate", "lowerCI", "upperCI")
|
|
|
|
colnames(logpotUest) <- c("estimate", "lowerCI", "upperCI")
|
|
cnXL <- colnames(XLdat2)
|
|
Filesample <- data.frame(Test = c("FILE NAME:", "SAMPLES"), Test2 = c(Dat$FileName, paste(cnXL[1], " vs ", cnXL[4])))
|
|
colnames(Filesample) <- c("", "")
|
|
output$Filesampl <- renderTable(
|
|
{
|
|
Filesample
|
|
},
|
|
rownames = FALSE
|
|
)
|
|
|
|
UnRPLAausw <- data.frame(
|
|
Information = c(
|
|
"model", "lower asymptote Ref", "Hill's slope Ref", "upper asymptote Ref", "EC50 Ref",
|
|
"lower asymptote Test", "Hill's slope Test",
|
|
"upper asymptote Test", "EC50 Difference",
|
|
"relative potency", "lower CI", "upper CI"
|
|
),
|
|
Results = unlist(c("UNRESTRICTED", round(coeffsMU, 3), round(potU_est * 100, 3)))
|
|
) # von psl_nls
|
|
|
|
# "log relative potency", "log lower CI", "log upper CI", round(logpotest, 3), round(compParm(potu, "c", display = FALSE), 3)
|
|
|
|
output$coeffs_unr <- renderTable({
|
|
UnRPLAausw
|
|
})
|
|
|
|
UnRPLAausw2 <- data.frame(Dat$bendpointsTRANS)
|
|
if (length(UnRPLAausw2) > 0) {
|
|
colnames(UnRPLAausw2) <- c("bendpoints log")
|
|
UnrBendLog <- data.frame(
|
|
Bendpoint = c(
|
|
"REF_lower", "REF_upper",
|
|
"TEST_lower", "REF_lower"
|
|
),
|
|
bendpoints_logscale = UnRPLAausw2
|
|
)
|
|
|
|
output$bends_unr2 <- renderTable({
|
|
UnrBendLog
|
|
})
|
|
}
|
|
REP$UnRPLAausw <- UnRPLAausw
|
|
REP$UnRPLAausw2 <- UnRPLAausw2
|
|
|
|
coeffs_R <- coeffsMR # pot$coefficients
|
|
coeffs_R[5] <- coeffs_R[4] - coeffs_R[5]
|
|
names(coeffs_R) <- c("lower A", "slope", "upper A", "EC50 REF", "EC50 TEST")
|
|
|
|
# --- Ergebnistabelle: RESTRICTED ---
|
|
PLAAusw <- data.frame(
|
|
Information = c(
|
|
"model", "lower asymptote", "Hill's slope", "upper asymptote", "EC50 Ref",
|
|
"EC50 Test", "relative potency",
|
|
"lower CI", "upper CI"
|
|
),
|
|
Results = unlist(c(
|
|
"RESTRICTED", round(coeffs_R, 3),
|
|
round(pot_est[1, ] * 100, 3)
|
|
))
|
|
) # von gs1_nls
|
|
output$coeffs_r <- renderTable({
|
|
PLAAusw
|
|
})
|
|
|
|
bendsAll <- data.frame(Dat$bendsAll[1:8, ])
|
|
output$bends_r2 <- renderTable(
|
|
{
|
|
bendsAll
|
|
},
|
|
digits = 3,
|
|
rownames = TRUE
|
|
)
|
|
|
|
REP$PLAausw <- PLAAusw
|
|
REP$PLBend <- bendsAll
|
|
|
|
#### Parameter extraktion ----
|
|
logcoeffs_R <- SRlog$coefficients[, 1] # logpot$coefficients
|
|
names(logcoeffs_R) <- c("lower A", "Hill's slope", "upper A", "EC50 REF", "EC50 DIFF")
|
|
|
|
# --- Ergebnistabelle: LOG RESTRICTED ---
|
|
|
|
LogPLAAusw <- data.frame(
|
|
Information = c(
|
|
"model", "lower asymptote", "Hill's slope", "upper asymptote", "EC50 Ref",
|
|
"EC50 difference", "log relative potency",
|
|
"log lower CI", "log upper CI"
|
|
),
|
|
Results = unlist(c(
|
|
"LOG RESTRICTED", round(logcoeffs_R, 3),
|
|
round(logpotest * 100, 3)
|
|
))
|
|
) # von gsl_nls
|
|
|
|
output$logcoeffs_r <- renderTable({
|
|
LogPLAAusw
|
|
})
|
|
REP$LogPLAausw <- LogPLAAusw
|
|
|
|
logcoeffs_UNR <- SUlog$coefficients[, 1]
|
|
names(logcoeffs_UNR) <- c(
|
|
"lower asymptote Ref", "Hill's slope Ref", "upper asymptote Ref", "EC50 Ref",
|
|
"lower asymptote Test", "Hill's slope Test", "upper asymptote Test", "EC50 Diff"
|
|
)
|
|
|
|
# --- Ergebnistabelle: LOG UNRESTRICTED ---
|
|
|
|
LogUnrPLAAusw <- data.frame(
|
|
Information = c(
|
|
"model", "lower asymptote Ref", "Hill's slope Ref", "upper asymptote Ref", "EC50 Ref",
|
|
"lower asymptote Test", "Hill's slope Test", "upper asymptote Test", "EC50 Diff",
|
|
"relative potency", "lower CI", "upper CI"
|
|
),
|
|
Results = unlist(c(
|
|
"LOG UNRESTRICTED", round(logcoeffs_UNR, 3),
|
|
round(logpotUest * 100, 3)
|
|
))
|
|
) # von gsl_nls
|
|
|
|
output$logcoeffs_unr <- renderTable({
|
|
LogUnrPLAAusw
|
|
})
|
|
REP$LogUnrPLAausw <- LogUnrPLAAusw
|
|
|
|
|
|
if (exists("Ind")) {
|
|
Dat$dilution <- XLdat[, Ind]
|
|
} else {
|
|
Dat$dilution <- exp(XLdat[, logI])
|
|
}
|
|
|
|
##### Plot XL 4PL ----
|
|
output$XLplot <- renderPlot({
|
|
XLplot4pl <- plot_f(XLdat2, TransFlag = FALSE)
|
|
REP$XLplot4pl <- XLplot4pl
|
|
|
|
XLplot4pl
|
|
})
|
|
|
|
REP$XLdat2 <- XLdat2
|
|
|
|
# --- Diagnose-Plots (Residualanalyse) ---
|
|
output$diagnplot <- renderPlot({
|
|
op <- par(mfrow = c(2, 2), mar = c(3.2, 3.2, 2, .5), mgp = c(2, .7, 0))
|
|
PREDs <- FITs[[5]]
|
|
PREDsU <- FITs[[6]]
|
|
# 1. Residuals vs Fitted
|
|
plot(Smr$residuals ~ PREDs, main = "Residuals restricted")
|
|
abline(h = 0)
|
|
qqnorm(Smr$residuals)
|
|
qqline(Smr$residuals)
|
|
plot(Smu$residuals ~ PREDsU, main = "Residuals unrestricted")
|
|
abline(h = 0)
|
|
|
|
qqnorm(Smu$residuals)
|
|
qqline(Smu$residuals)
|
|
|
|
par(op) # Parameter zurücksetzen
|
|
})
|
|
|
|
|
|
pot <- drm(readout ~ Conc, isSample,
|
|
data = all_l, fct = LL.4(names = c("b", "d", "a", "c")),
|
|
pmodels = data.frame(1, 1, 1, isSample)
|
|
)
|
|
potU <- drm(readout ~ Conc, isSample,
|
|
data = all_l, fct = LL.4(names = c("b", "d", "a", "c")),
|
|
pmodels = data.frame(isSample, isSample, isSample, isSample)
|
|
)
|
|
output$AIC <- renderTable({
|
|
AIC <- AIC(pot, potU)
|
|
})
|
|
|
|
output$VarDiagn <- renderTable(
|
|
{
|
|
DiagnTable
|
|
},
|
|
digits = 4
|
|
)
|
|
|
|
output$relpotplot <- renderPlot({
|
|
relpot(potU,
|
|
intervall = "fieller", bty = "l",
|
|
main = "Quality of rel. potency over response"
|
|
)
|
|
})
|
|
} # !please choose
|
|
} # input$sheet
|
|
} # input$iFile
|
|
})
|
|
|
|
#### make geomDils reactive ----
|
|
observe({
|
|
if (is.null(input$ConcStart)) {
|
|
return(NULL)
|
|
}
|
|
if (!is.na(input$ConcStart) & !is.na(input$dilutionFac) & !is.na(input$NoDil) & !is.na(input$NoDilSer)) {
|
|
upR <- input$ConcStart
|
|
noDil <- input$NoDil
|
|
noDilSer <- input$NoDilSer
|
|
Div <- input$dilutionFac
|
|
res <- c()
|
|
N_ <- 1
|
|
Conc <- c(upR, divFUN(upR, Div, N = N_, res, noDil))
|
|
|
|
Dat$MetaConc <- Conc
|
|
}
|
|
})
|
|
|
|
|
|
observe({
|
|
if (!is.null(Dat$MetaConc)) {
|
|
updateNumericInput(session, "CONC1",
|
|
value = as.numeric(Dat$MetaConc[1])
|
|
)
|
|
updateNumericInput(session, "CONC2",
|
|
value = as.numeric(Dat$MetaConc[2])
|
|
)
|
|
updateNumericInput(session, "CONC3",
|
|
value = as.numeric(Dat$MetaConc[3])
|
|
)
|
|
updateNumericInput(session, "CONC4",
|
|
value = as.numeric(Dat$MetaConc[4])
|
|
)
|
|
updateNumericInput(session, "CONC5",
|
|
value = as.numeric(Dat$MetaConc[5])
|
|
)
|
|
updateNumericInput(session, "CONC6",
|
|
value = as.numeric(Dat$MetaConc[6])
|
|
)
|
|
updateNumericInput(session, "CONC7",
|
|
value = as.numeric(Dat$MetaConc[7])
|
|
)
|
|
updateNumericInput(session, "CONC8",
|
|
value = as.numeric(Dat$MetaConc[8])
|
|
)
|
|
updateNumericInput(session, "CONC9",
|
|
value = as.numeric(Dat$MetaConc[9])
|
|
)
|
|
updateNumericInput(session, "CONC10",
|
|
value = as.numeric(Dat$MetaConc[10])
|
|
)
|
|
updateNumericInput(session, "CONC11",
|
|
value = as.numeric(Dat$MetaConc[11])
|
|
)
|
|
updateNumericInput(session, "CONC12",
|
|
value = as.numeric(Dat$MetaConc[12])
|
|
)
|
|
}
|
|
})
|
|
|
|
#### render logDilsText ----
|
|
output$logdil <- renderText({
|
|
if (!is.null(Dat$MetaConc)) {
|
|
Conc <- Dat$MetaConc
|
|
} else {
|
|
Conc <- CONC()
|
|
}
|
|
logdilu <- log(Conc)
|
|
logdilu
|
|
})
|
|
|
|
|
|
#### reactive dataset sim ----
|
|
|
|
sim <- reactive({
|
|
if (is.null(sigmoid())) {
|
|
return(NULL)
|
|
}
|
|
sd_fac_ <- as.numeric(input$sdfac)
|
|
r_ <- log(as.numeric(input$potencydiff) / 100)
|
|
as <- sigmoid()[1]
|
|
bs <- sigmoid()[5]
|
|
cs <- sigmoid()[7]
|
|
ds <- sigmoid()[3]
|
|
at <- sigmoid()[2]
|
|
bt <- sigmoid()[6]
|
|
r <- sigmoid()[8]
|
|
ct <- cs - r_
|
|
dt <- sigmoid()[4]
|
|
if (!is.null(Dat$MetaConc)) Conc <- Dat$MetaConc else Conc <- CONC()
|
|
log_conc <- log(Conc)
|
|
av_test <- as + (ds - as) / (1 + exp(bs * (cs - log_conc)))
|
|
av_ref <- at + (dt - at) / (1 + exp(bt * (ct - log_conc)))
|
|
if (!is.na(input$NoDilSer)) {
|
|
noDilSer <- input$NoDilSer
|
|
} else if (!is.null(Dat$noDilSeriesXL)) noDilSer <- Dat$noDilSeriesXL else noDilSer <- 3
|
|
if (!is.na(input$NoDil)) noDil <- input$NoDil else noDil <- length(log_conc)
|
|
isRef <- rep(c(1, 0), 1, each = noDilSer * noDil)
|
|
isSample <- rep(c(0, 1), 1, each = noDilSer * noDil)
|
|
|
|
# if (is.null(Dat$EXCEL)) {
|
|
ro_new <- Calc_DilRes(
|
|
as = as, at = at, ds = ds, dt = dt, cs = cs, ct = ct, r = r_, bt = bt, bs = bs, log_conc = log_conc,
|
|
sd_fac = sd_fac_,
|
|
# auslenkU=outlierU,
|
|
# auslenkM=outlierM,
|
|
# auslenkL=outlierL,
|
|
heteroNoise = input$heterosked, noDilSeries = noDilSer, noDils = noDil
|
|
)
|
|
# } else ro_new <- Dat$EXCEL
|
|
})
|
|
# })
|
|
|
|
#### sim2 ----
|
|
sim2 <- reactive({
|
|
tab <- sim()
|
|
# if (is.null(Dat$EXCEL)) return(tab) else return(Dat$EXCEL)
|
|
})
|
|
|
|
|
|
#### Plot 4pl Meta ----
|
|
output$plot4plMeta <- renderPlot({
|
|
PureErrFlag <- input$PureErrMeta
|
|
warning_text3 <- reactive({
|
|
ifelse(PureErrFlag, "Pure error selected", "")
|
|
})
|
|
|
|
output$PureErrW4plMeta <- renderText(warning_text3())
|
|
|
|
sigmoid <- sigmoid()
|
|
det_sig <- NULL
|
|
plot_f(sim2(), TransFlag = FALSE)
|
|
})
|
|
|
|
#### Plot 4pl Meta Transformed ----
|
|
output$plot4plTransMeta <- renderPlot({
|
|
PureErrFlag <- input$PureErrMeta
|
|
warning_text3 <- reactive({
|
|
ifelse(PureErrFlag, "Pure error selected", "")
|
|
})
|
|
|
|
output$PureErrWLogMeta <- renderText(warning_text3())
|
|
sigmoid <- sigmoid()
|
|
det_sig <- NULL
|
|
plot_f(sim2(), TransFlag = TRUE)
|
|
})
|
|
|
|
|
|
#### Testergebnisse für 4PL Meta ----
|
|
observe({
|
|
if (is.null(sim2())) {
|
|
return(NULL)
|
|
}
|
|
if (is.null(input$PureErrMeta)) {
|
|
return(NULL)
|
|
}
|
|
# observeEvent(input$StartCalc,{
|
|
PureErrFlag <- input$PureErrMeta
|
|
warning_text3 <- reactive({
|
|
ifelse(PureErrFlag, "Pure error selected", "")
|
|
})
|
|
|
|
output$PureErrW3 <- renderText(warning_text3())
|
|
|
|
Limite <- list(
|
|
as.numeric(input$lEACdiffla), as.numeric(input$uEACdiffla),
|
|
as.numeric(input$lEACratiola), as.numeric(input$uEACratiola),
|
|
as.numeric(input$lEACratioSlope), as.numeric(input$uEACratioSlope),
|
|
as.numeric(input$lEACratioua), as.numeric(input$uEACratioua),
|
|
as.numeric(input$lowerPot), as.numeric(input$upperPot),
|
|
as.numeric(input$lEACratioAdiff), as.numeric(input$uEACratioAdiff)
|
|
)
|
|
Dat$limite <- Limite
|
|
|
|
tab <- tests_FUNC(sim2(), Limite, PureErrFlag = PureErrFlag)
|
|
if (length(tab) > 1) {
|
|
tab[1, 6:7] <- c("-", "-")
|
|
Dat$tests_FUNC <- tab
|
|
REP$testsTab <- tab
|
|
tab2 <- tab[1:7, ]
|
|
|
|
dat <- datatable(tab2, rownames = FALSE, options = list(
|
|
paging = TRUE,
|
|
dom = "t",
|
|
rownames = FALSE
|
|
)) |> formatStyle("test_results",
|
|
target = "row",
|
|
backgroundColor = styleEqual(
|
|
c(-1, 0, 1),
|
|
c("pink", "lightgreen", "lightgrey")
|
|
)
|
|
)
|
|
} else {
|
|
dat <- datatable(data.frame(test_results = "Convergeance failed for the uploaded dataset"))
|
|
}
|
|
output$EQtests4pl <- renderDT({
|
|
dat
|
|
})
|
|
}) # observe
|
|
|
|
#### Testergebnisse 4PL für XLSX ----
|
|
observe({
|
|
if (is.null(Dat$EXCEL)) {
|
|
return(NULL)
|
|
}
|
|
if (is.null(input$PureErr)) {
|
|
return(NULL)
|
|
}
|
|
if (Dat$FITsFlag) {
|
|
return(NULL)
|
|
}
|
|
|
|
# observeEvent(input$StartCalc,{
|
|
PureErrFlag <- input$PureErr
|
|
warning_text3 <- reactive({
|
|
ifelse(PureErrFlag, "Pure error selected", "")
|
|
})
|
|
|
|
|
|
output$PureErrW3 <- renderText(warning_text3())
|
|
|
|
Limite <- list(
|
|
as.numeric(input$lEACdiffla), as.numeric(input$uEACdiffla),
|
|
as.numeric(input$lEACratiola), as.numeric(input$uEACratiola),
|
|
as.numeric(input$lEACratioSlope), as.numeric(input$uEACratioSlope),
|
|
as.numeric(input$lEACratioua), as.numeric(input$uEACratioua),
|
|
as.numeric(input$lowerPot), as.numeric(input$upperPot),
|
|
as.numeric(input$lEACratioAdiff), as.numeric(input$uEACratioAdiff)
|
|
)
|
|
Dat$limite <- Limite
|
|
SelTests <- as.numeric(input$selectedSSTs)
|
|
tab <- tests_FUNC(Dat$EXCEL, Limite, PureErrFlag = PureErrFlag)
|
|
|
|
tab[1, 6:7] <- c("-", "-")
|
|
|
|
tab2 <- tab[SelTests, ]
|
|
Dat$tests_FUNC <- tab2
|
|
REP$testsTab <- tab2
|
|
|
|
dat <- datatable(tab2,
|
|
rownames = FALSE, options = list(
|
|
paging = TRUE,
|
|
dom = "t"
|
|
)
|
|
) |> formatStyle("test_results",
|
|
target = "row",
|
|
backgroundColor = styleEqual(
|
|
c(-1, 0, 1),
|
|
c("pink", "lightgreen", "lightgrey")
|
|
)
|
|
)
|
|
|
|
output$EQtests <- renderDT({
|
|
dat
|
|
})
|
|
}) # observe
|
|
|
|
#### plot CIs XL----
|
|
# observe({
|
|
# tab <- Dat$tests_FUNC
|
|
# if (is.null(tab)) return(NULL)
|
|
#
|
|
# tab2 <- tab[-c(1,2,3,6),]
|
|
# tab2[,3:ncol(tab2)] <- apply(tab2[,3:ncol(tab2)],2,as.numeric)
|
|
# tab2[4:5,3:7] <- tab2[4:5,3:7]/100
|
|
#
|
|
# p_CIs <- ggplot(tab2,aes(x=test,y=estimate, color=test,group=test)) +
|
|
# geom_point() +
|
|
# geom_errorbar(aes(ymin=lower_CI, ymax=upper_CI), width=0.4) +
|
|
# geom_crossbar(aes(ymin=lower_limit, ymax=upper_limit), size=0.8) +
|
|
# coord_flip() +
|
|
# theme_bw() +
|
|
# theme(legend.position = "none",text = element_text(size=20))
|
|
#
|
|
# output$CIplot <- renderPlot({ p_CIs}, height=200)
|
|
#
|
|
# REP$CIplot <- p_CIs
|
|
# })
|
|
|
|
#### simulated data tab Meta ----
|
|
output$simdat <- DT::renderDataTable({
|
|
tab <- sim2()
|
|
if (is.character(tab)) stop(tab)
|
|
|
|
tab2 <- round(tab, 5)
|
|
colnames(tab2) <- c(
|
|
paste("T", seq(1, (ncol(tab2) - 1) / 2)),
|
|
paste("R", seq(1, (ncol(tab2) - 1) / 2)), "log_conc"
|
|
)
|
|
dat <- datatable(tab2, options = list(
|
|
paging = TRUE,
|
|
pageLength = 20,
|
|
dom = "t"
|
|
))
|
|
})
|
|
##### Concentrationtab Meta ----
|
|
output$ConctabMeta <- DT::renderDataTable({
|
|
if (!is.na(Dils()[1]) & is.na(Dils()[4])) {
|
|
return(NULL)
|
|
}
|
|
tab <- sim2()
|
|
if (is.character(tab)) stop(tab)
|
|
if (!is.na(Dils()[4])) {
|
|
noDilSer <- Dils()[4]
|
|
} else if (!is.null(Dat$noDilSeriesXL)) {
|
|
noDilSer <- Dat$noDilSeriesXL
|
|
} else {
|
|
noDilSer <- 3
|
|
}
|
|
|
|
Conc <- CONC()
|
|
Conctab <- perConcTab(tab, noDilSeries = noDilSer)
|
|
Dat$Conctab <- Conctab
|
|
|
|
dat <- datatable(Conctab, options = list(
|
|
paging = TRUE,
|
|
pageLength = 12,
|
|
dom = "t"
|
|
)) |>
|
|
formatStyle(0,
|
|
target = "row",
|
|
backgroundColor = styleEqual(
|
|
c("avs", "sds", "cv", "avs_test", "sds_test", "cv_test"),
|
|
c("lightgrey", "lightgreen", "pink", "lightgrey", "lightgreen", "pink")
|
|
)
|
|
) |>
|
|
formatRound(columns = colnames(Conctab), digits = 3)
|
|
})
|
|
|
|
output$Conctab <- DT::renderDataTable({
|
|
if (!is.na(Dils()[1]) & is.na(Dils()[4])) {
|
|
return(NULL)
|
|
}
|
|
tab <- sim2()
|
|
if (is.character(tab)) stop(tab)
|
|
if (!is.na(Dils()[4])) {
|
|
noDilSer <- Dils()[4]
|
|
} else if (!is.null(Dat$noDilSeriesXL)) {
|
|
noDilSer <- Dat$noDilSeriesXL
|
|
} else {
|
|
noDilSer <- 3
|
|
}
|
|
|
|
Conc <- CONC()
|
|
Conctab <- perConcTab(tab, noDilSeries = noDilSer)
|
|
Dat$Conctab <- Conctab
|
|
|
|
dat <- datatable(Conctab, options = list(
|
|
paging = TRUE,
|
|
pageLength = 12,
|
|
dom = "t"
|
|
)) |>
|
|
formatStyle(0,
|
|
target = "row",
|
|
backgroundColor = styleEqual(
|
|
c("avs", "sds", "cv", "avs_test", "sds_test", "cv_test"),
|
|
c("lightgrey", "lightgreen", "pink", "lightgrey", "lightgreen", "pink")
|
|
)
|
|
) |>
|
|
formatRound(columns = colnames(Conctab), digits = 3)
|
|
})
|
|
|
|
#### process XL linearly, Plot output ----
|
|
output$plotLin <- renderPlot({
|
|
if (is.null(Dat$EXCEL)) {
|
|
return(NULL)
|
|
}
|
|
tab <- Dat$EXCEL
|
|
|
|
# tab <- sim2()
|
|
if (is.character(tab)) stop(tab)
|
|
log_conc <- tab$log_dose
|
|
noDilSer <- (ncol(tab) - 1) / 2
|
|
noDil <- nrow(tab)
|
|
Conctab <- perConcTab(tab, noDilSer)
|
|
# if (!is.na(Dils()[3])) noDil <- Dils()[3] else noDil = length(Conc)
|
|
#
|
|
slopeSt <- slopeTe <- matrix(NA, nrow = noDil - 2, ncol = 2)
|
|
for (i in 1:(noDil - 2)) {
|
|
avs <- Conctab[noDilSer + 1, ]
|
|
threes <- data.frame(lnC = log_conc[i:(i + 2)], resp = avs[i:(i + 2)])
|
|
lm3St <- lm(resp ~ lnC, data = threes)
|
|
slopeSt[i, ] <- lm3St$coefficients
|
|
avt <- Conctab[noDilSer * 2 + 4, ]
|
|
threet <- data.frame(lnC = log_conc[i:(i + 2)], resp = avt[i:(i + 2)])
|
|
lm3Te <- lm(resp ~ lnC, data = threet)
|
|
slopeTe[i, ] <- lm3Te$coefficients
|
|
}
|
|
|
|
indS <- which(abs(slopeSt[, 2]) == max(abs(slopeSt[, 2])))
|
|
indT <- which(abs(slopeTe[, 2]) == max(abs(slopeTe[, 2])))
|
|
|
|
pl_ <- slopeSt[indS, 1] + slopeSt[indS, 2] * log_conc
|
|
pl_T <- slopeTe[indT, 1] + slopeTe[indT, 2] * log_conc
|
|
pl_df <- data.frame(lnC = log_conc, plotS = pl_, plotT = pl_T)
|
|
|
|
all_l <- melt(data.frame(tab), id.vars = "log_dose", variable.name = "replname", value.name = "readout")
|
|
isRef <- rep(c(1, 0), 1, each = nrow(all_l) / 2)
|
|
isSample <- rep(c(0, 1), 1, each = nrow(all_l) / 2)
|
|
all_l2 <- cbind(all_l, isRef, isSample)
|
|
all_l2S <- all_l2[all_l2$isRef == 1, ]
|
|
all_l2T <- all_l2[all_l2$isRef == 0, ]
|
|
all_mS <- all_l2S[order(all_l2S$log_dose, decreasing = TRUE), ]
|
|
all_mT <- all_l2T[order(all_l2T$log_dose, decreasing = TRUE), ]
|
|
|
|
circleS <- all_mS[(indS * noDilSer - (noDilSer - 1)):((indS + 2) * noDilSer), ]
|
|
circleT <- all_mT[(indT * noDilSer - (noDilSer - 1)):((indT + 2) * noDilSer), ]
|
|
circle <- rbind(circleS, circleT)
|
|
|
|
Dat$circles <- circle
|
|
REPlin$circles <- circle
|
|
if (Dat$FITsFlag) sigmoid <- NULL else sigmoid <- Dat$coeffsMUnr
|
|
|
|
pLin <- PlotLinPLA_FUNC(circle, sigmoid = sigmoid, all_l2, pl_df, indS, indT)
|
|
REPlin$pLin <- pLin
|
|
|
|
pLin
|
|
})
|
|
|
|
#### process metadata, Plot output ----
|
|
output$plotLinMeta <- renderPlot({
|
|
tab <- sim2()
|
|
|
|
if (is.null(tab)) {
|
|
return(NULL)
|
|
}
|
|
if (is.character(tab)) stop(tab)
|
|
if (!is.na(Dils()[4])) noDilSer <- Dils()[4] else noDilSer <- (ncol(tab) - 1) / 2
|
|
Conc <- CONC()
|
|
log_conc <- log(Conc)
|
|
Conctab <- perConcTab(tab, noDilSer)
|
|
if (!is.na(Dils()[3])) noDil <- Dils()[3] else noDil <- length(Conc)
|
|
|
|
slopeSt <- slopeTe <- matrix(NA, nrow = noDil - 2, ncol = 2)
|
|
for (i in 1:(noDil - 2)) {
|
|
avs <- Conctab[noDilSer + 1, ]
|
|
threes <- data.frame(lnC = log(Conc[i:(i + 2)]), resp = avs[i:(i + 2)])
|
|
lm3St <- lm(resp ~ lnC, data = threes)
|
|
slopeSt[i, ] <- lm3St$coefficients
|
|
avt <- Conctab[noDilSer * 2 + 4, ]
|
|
threet <- data.frame(lnC = log(Conc[i:(i + 2)]), resp = avt[i:(i + 2)])
|
|
lm3Te <- lm(resp ~ lnC, data = threet)
|
|
slopeTe[i, ] <- lm3Te$coefficients
|
|
}
|
|
|
|
indS <- which(abs(slopeSt[, 2]) == max(abs(slopeSt[, 2])))
|
|
indT <- which(abs(slopeTe[, 2]) == max(abs(slopeTe[, 2])))
|
|
|
|
pl_ <- slopeSt[indS, 1] + slopeSt[indS, 2] * log_conc
|
|
pl_T <- slopeTe[indT, 1] + slopeTe[indT, 2] * log_conc
|
|
pl_df <- data.frame(lnC = log_conc, plotS = pl_, plotT = pl_T)
|
|
|
|
all_l <- melt(data.frame(tab), id.vars = "log_dose", variable.name = "replname", value.name = "readout")
|
|
isRef <- rep(c(1, 0), 1, each = nrow(all_l) / 2)
|
|
isSample <- rep(c(0, 1), 1, each = nrow(all_l) / 2)
|
|
all_l2 <- cbind(all_l, isRef, isSample)
|
|
all_l2S <- all_l2[all_l2$isRef == 1, ]
|
|
all_l2T <- all_l2[all_l2$isRef == 0, ]
|
|
all_mS <- all_l2S[order(all_l2S$log_dose, decreasing = TRUE), ]
|
|
all_mT <- all_l2T[order(all_l2T$log_dose, decreasing = TRUE), ]
|
|
|
|
circleS <- all_mS[(indS * noDilSer - (noDilSer - 1)):((indS + 2) * noDilSer), ]
|
|
circleT <- all_mT[(indT * noDilSer - (noDilSer - 1)):((indT + 2) * noDilSer), ]
|
|
circle <- rbind(circleS, circleT)
|
|
|
|
Dat$circlesMeta <- circle
|
|
sigmoid <- sigmoid()
|
|
pLin2 <- PlotLinPLA_FUNC(circle, sigmoid = sigmoid, all_l2, pl_df, indS, indT)
|
|
pLin2
|
|
})
|
|
|
|
#### linear PLA tests Metadata ----
|
|
output$TESTSlinMeta <- DT::renderDataTable({
|
|
tab <- sim2()
|
|
if (is.null(tab)) {
|
|
return(NULL)
|
|
}
|
|
Conc <- CONC()
|
|
Limite <- Dat$limite
|
|
|
|
circlesMeta <- Dat$circlesMeta
|
|
PureErrFlag <- input$PureErrMeta
|
|
warning_text <- reactive({
|
|
ifelse(PureErrFlag, "Pure error is selected", "")
|
|
})
|
|
output$PureErrW <- renderText(warning_text())
|
|
LIN <- ANOVAlintests(tab, circlesMeta, Limite, PureErrFlag = PureErrFlag)
|
|
df <- LIN[[1]]
|
|
su_modU <- LIN[[2]]
|
|
su_mod2 <- LIN[[4]]
|
|
|
|
output$SummaryModABuMeta <- renderTable(
|
|
{
|
|
su_modU
|
|
},
|
|
digits = 5
|
|
)
|
|
output$SummaryModABMeta <- renderTable(
|
|
{
|
|
su_mod2
|
|
},
|
|
digits = 5
|
|
)
|
|
|
|
slopeDiffCI <- t(data.frame(LIN[[3]]))
|
|
colnames(slopeDiffCI) <- c("slope difference", "lower CI", "upper CI")
|
|
output$SlopeDiffCIMeta <- renderTable(
|
|
{
|
|
slopeDiffCI
|
|
},
|
|
digits = 5
|
|
)
|
|
|
|
SelTestsL <- as.numeric(input$selectedSSTsLinear)
|
|
df2 <- df
|
|
|
|
Dat$ANOVAMeta <- df[, 4:length(df)]
|
|
dat <- datatable(df2[, 1:3],
|
|
options = list(
|
|
paging = TRUE, dom = "t", rownames = FALSE
|
|
)
|
|
) |> formatStyle("test_results", target = "row", backgroundColor = styleEqual(
|
|
c(-1, 0, 1),
|
|
c("pink", "lightgreen", "lightgrey")
|
|
))
|
|
})
|
|
|
|
#### linear PLA tests XLinput ----
|
|
# output$TESTSlin <- DT::renderDataTable({
|
|
observe({
|
|
if (is.null(Dat$EXCEL)) {
|
|
return(NULL)
|
|
}
|
|
|
|
tab <- Dat$EXCEL
|
|
if (is.character(tab)) stop(tab)
|
|
Conc <- exp(tab$log_dose)
|
|
Limite <- list(
|
|
as.numeric(input$lEACdiffla), as.numeric(input$uEACdiffla),
|
|
as.numeric(input$lEACratiola), as.numeric(input$uEACratiola),
|
|
as.numeric(input$lEACratioSlope), as.numeric(input$uEACratioSlope),
|
|
as.numeric(input$lEACratioua), as.numeric(input$uEACratioua),
|
|
as.numeric(input$EACLinlow), as.numeric(input$EACLinupp), # Limits from linear PLA page
|
|
as.numeric(input$lEACratioAdiff), as.numeric(input$uEACratioAdiff)
|
|
)
|
|
|
|
noDil <- nrow(tab)
|
|
noDilSer <- Dat$noDilSeriesXL
|
|
Conctab <- perConcTab(tab, noDilSeries = noDilSer)
|
|
slopeSt <- slopeTe <- matrix(NA, nrow = noDil - 2, ncol = 2)
|
|
for (i in 1:(noDil - 2)) {
|
|
avs <- Conctab[noDilSer + 1, ]
|
|
threes <- data.frame(lnC = log(Conc[i:(i + 2)]), resp = avs[i:(i + 2)])
|
|
lm3St <- lm(resp ~ lnC, data = threes)
|
|
slopeSt[i, ] <- lm3St$coefficients
|
|
avt <- Conctab[noDilSer * 2 + 4, ]
|
|
threet <- data.frame(lnC = log(Conc[i:(i + 2)]), resp = avt[i:(i + 2)])
|
|
lm3Te <- lm(resp ~ lnC, data = threet)
|
|
slopeTe[i, ] <- lm3Te$coefficients
|
|
}
|
|
|
|
indS <- which(abs(slopeSt[, 2]) == max(abs(slopeSt[, 2])))
|
|
indT <- which(abs(slopeTe[, 2]) == max(abs(slopeTe[, 2])))
|
|
|
|
# pl_ <- slopeSt[indS,1]+slopeSt[indS,2]*log_conc
|
|
# pl_T <- slopeTe[indT,1]+slopeTe[indT,2]*log_conc
|
|
# pl_df <- data.frame(lnC=log_conc, plotS=pl_, plotT=pl_T)
|
|
|
|
all_l <- melt(data.frame(tab), id.vars = "log_dose", variable.name = "replname", value.name = "readout")
|
|
isRef <- rep(c(1, 0), 1, each = nrow(all_l) / 2)
|
|
isSample <- rep(c(0, 1), 1, each = nrow(all_l) / 2)
|
|
all_l2 <- cbind(all_l, isRef, isSample)
|
|
all_l2S <- all_l2[all_l2$isRef == 1, ]
|
|
all_l2T <- all_l2[all_l2$isRef == 0, ]
|
|
all_mS <- all_l2S[order(all_l2S$log_dose, decreasing = TRUE), ]
|
|
all_mT <- all_l2T[order(all_l2T$log_dose, decreasing = TRUE), ]
|
|
|
|
circleS <- all_mS[(indS * noDilSer - (noDilSer - 1)):((indS + 2) * noDilSer), ]
|
|
circleT <- all_mT[(indT * noDilSer - (noDilSer - 1)):((indT + 2) * noDilSer), ]
|
|
circle <- rbind(circleS, circleT)
|
|
|
|
PureErrFlag <- input$PureErr
|
|
warning_text <- reactive({
|
|
ifelse(PureErrFlag, "Pure error is selected", "")
|
|
})
|
|
output$PureErrW3 <- renderText(warning_text())
|
|
LIN <- ANOVAlintests(tab, circle, Limite, PureErrFlag = PureErrFlag)
|
|
df <- LIN[[1]]
|
|
su_modU <- LIN[[2]]
|
|
su_mod2 <- LIN[[4]]
|
|
|
|
output$SummaryModABu <- renderTable(
|
|
{
|
|
su_modU
|
|
},
|
|
digits = 5
|
|
)
|
|
output$SummaryModAB <- renderTable(
|
|
{
|
|
su_mod2
|
|
},
|
|
digits = 5
|
|
)
|
|
|
|
REPlin$SuModABu <- su_modU
|
|
REPlin$SuModAB <- su_mod2
|
|
|
|
slopeDiffCI <- t(data.frame(LIN[[3]]))
|
|
colnames(slopeDiffCI) <- c("slope difference", "lower CI", "upper CI")
|
|
output$SlopeDiffCI <- renderTable(
|
|
{
|
|
slopeDiffCI
|
|
},
|
|
digits = 5
|
|
)
|
|
|
|
SelTestsL <- as.numeric(input$selectedSSTsLinear)
|
|
df2 <- df[SelTestsL, ]
|
|
|
|
REPlin$LinTests <- df2
|
|
|
|
Dat$ANOVA <- df[, 4:length(df)]
|
|
dat <- datatable(df2[, 1:3],
|
|
options = list(
|
|
paging = TRUE, dom = "t", rownames = FALSE
|
|
)
|
|
) |> formatStyle("test_results", target = "row", backgroundColor = styleEqual(
|
|
c(-1, 0, 1),
|
|
c("pink", "lightgreen", "lightgrey")
|
|
))
|
|
output$TESTSlin <- DT::renderDataTable({
|
|
dat
|
|
})
|
|
})
|
|
|
|
#### output 4PL ANOVA tests Meta ----
|
|
output$ANOVA <- DT::renderDataTable({
|
|
sigmoid <- sigmoid()
|
|
tab <- ANOVA4plUnresfunc(sim2()) # ,sigmoid
|
|
dat <- datatable(tab,
|
|
options = list(
|
|
dom = "t", rownames = FALSE
|
|
)
|
|
) |> formatStyle("p_value",
|
|
target = "row",
|
|
backgroundColor = styleEqual(
|
|
c("p_value"),
|
|
c("lightgrey")
|
|
)
|
|
)
|
|
})
|
|
|
|
#### output 4PL ANOVA tests XL ----
|
|
# not needed
|
|
# output$ANOVA_XL <- DT::renderDataTable({
|
|
# tab <- Dat$EXCEL
|
|
# tab <- ANOVA4plUnresfunc(sim2()) # ,sigmoid
|
|
# dat <- datatable(tab,
|
|
# options=list(
|
|
# dom="t",rownames=F
|
|
# )) |> formatStyle("p_value", target="row",
|
|
# backgroundColor = styleEqual(c("p_value"),
|
|
# c("lightgrey")))
|
|
# })
|
|
|
|
|
|
#### output RMSEs ----
|
|
output$RMSE <- renderText({
|
|
paste(
|
|
"RMSE (unrestricted model):", Dat$RMSE_unr, "(Use it to compare against RMSE restr. model for non-parallelism)\n",
|
|
"RMSE (restricted model):", Dat$RMSE_r, "\n",
|
|
"Pure RMSE (unrestricted model):", Dat$RMSE_pure, "\n",
|
|
"%SD (unr. model): ", Dat$RMSE_unr * 100 / Dat$up_lowAs, "(calculated as: RMSE/(upper-lower Asymptote)*100\n",
|
|
"RMSE (log restr. model): ", Dat$RMSE_Rlog, "\n",
|
|
"RMSE (log unrestr. model): ", Dat$RMSE_Ulog, "\n",
|
|
"%SDlog (unr model): ", Dat$RMSE_Ulog * 100 / Dat$up_lowAslog
|
|
)
|
|
})
|
|
|
|
output$ANOVAlin <- DT::renderDataTable({
|
|
if (is.null(Dat$ANOVA)) {
|
|
return(NULL)
|
|
}
|
|
ANOVAlin <- Dat$ANOVA
|
|
dat <- datatable(ANOVAlin,
|
|
options = list(
|
|
dom = "t", rownames = FALSE
|
|
)
|
|
) |> formatStyle("p.value",
|
|
target = "cell",
|
|
backgroundColor = styleEqual(
|
|
c("p.value"),
|
|
c("lightgrey")
|
|
)
|
|
)
|
|
})
|
|
|
|
output$ANOVAlinMeta <- DT::renderDataTable({
|
|
ANOVAlin <- Dat$ANOVAMeta
|
|
dat <- datatable(ANOVAlin,
|
|
options = list(
|
|
dom = "t", rownames = FALSE
|
|
)
|
|
) |> formatStyle("p.value",
|
|
target = "cell",
|
|
backgroundColor = styleEqual(
|
|
c("p.value"),
|
|
c("lightgrey")
|
|
)
|
|
)
|
|
})
|
|
#### output Lin pot tab XL ----
|
|
output$pottab <- DT::renderDataTable({
|
|
if (is.null(Dat$circles)) {
|
|
return(NULL)
|
|
}
|
|
Lim <- list(
|
|
as.numeric(input$lEACdiffla), as.numeric(input$uEACdiffla),
|
|
as.numeric(input$lEACratiola), as.numeric(input$uEACratiola),
|
|
as.numeric(input$lEACratioSlope), as.numeric(input$uEACratioSlope),
|
|
as.numeric(input$lEACratioua), as.numeric(input$uEACratioua),
|
|
as.numeric(input$lowerPot), as.numeric(input$upperPot)
|
|
)
|
|
|
|
circles <- Dat$circles
|
|
PureErrFlag <- input$PureErr
|
|
|
|
warning_text2 <- reactive({
|
|
ifelse(PureErrFlag, "Pure Error is selected", "")
|
|
})
|
|
output$PureErrWLinXL <- renderText(warning_text2())
|
|
|
|
LinPotTab <- LinPotTab(circles, Lim, PureErrFlag = PureErrFlag)
|
|
REPlin$LinPotTab <- LinPotTab
|
|
|
|
dat <- datatable(LinPotTab,
|
|
options = list(
|
|
dom = "t", rownames = FALSE
|
|
)
|
|
) |> formatStyle("test_result",
|
|
target = "row",
|
|
backgroundColor = styleEqual(c(0, 1), c("#B5C74055", "#F9545488"))
|
|
)
|
|
})
|
|
|
|
|
|
### output pot tab Meta ----
|
|
output$pottabMeta <- DT::renderDataTable({
|
|
Lim <- list(
|
|
as.numeric(input$lEACdiffla), as.numeric(input$uEACdiffla),
|
|
as.numeric(input$lEACratiola), as.numeric(input$uEACratiola),
|
|
as.numeric(input$lEACratioSlope), as.numeric(input$uEACratioSlope),
|
|
as.numeric(input$lEACratioua), as.numeric(input$uEACratioua),
|
|
as.numeric(input$lowerPot), as.numeric(input$upperPot)
|
|
)
|
|
circles <- Dat$circlesMeta
|
|
PureErrFlag <- input$PureErrMeta
|
|
pottab <- LinPotTab(circles, Lim, PureErrFlag = PureErrFlag)
|
|
dat <- datatable(pottab,
|
|
options = list(
|
|
dom = "t", rownames = FALSE
|
|
)
|
|
) |> formatStyle("test_result",
|
|
target = "row",
|
|
backgroundColor = styleEqual(c(0, 1), c("#B5C74055", "#F9545488"))
|
|
)
|
|
})
|
|
|
|
#### 4pl potency table Meta ----
|
|
observe({
|
|
if (is.null(sim2()) | is.null(Dils())) {
|
|
return(NULL)
|
|
}
|
|
ro_new <- sim2()
|
|
Dils_ <- Dils()
|
|
if (!is.na(Dils()[4])) noDilSer <- Dils()[4] else noDilSer <- 3
|
|
PureErrFl <- input$PureErrMeta
|
|
pottab4 <- pot4plFUNC(ro_new = ro_new, PureErrFlag = PureErrFl)
|
|
Lim <- list(
|
|
as.numeric(input$lEACdiffla), as.numeric(input$uEACdiffla),
|
|
as.numeric(input$lEACratiola), as.numeric(input$uEACratiola),
|
|
as.numeric(input$lEACratioSlope), as.numeric(input$uEACratioSlope),
|
|
as.numeric(input$lEACratioua), as.numeric(input$uEACratioua),
|
|
as.numeric(input$lowerPot), as.numeric(input$upperPot)
|
|
)
|
|
|
|
|
|
pottab4_ <- data.frame(pottab4)
|
|
pottab4_$potency <- round(as.numeric(pottab4[, 2]) * 100, 1)
|
|
pottab4_$`lower95%CI` <- round(as.numeric(pottab4[, 3]) * 100, 2)
|
|
pottab4_$`upper95%CI` <- round(as.numeric(pottab4[, 4]) * 100, 2)
|
|
pottab4_$relative_lowerCL <- round(pottab4_[, 6] / pottab4_[, 5] * 100, 2)
|
|
pottab4_$relative_upperCL <- round(pottab4_[, 7] / pottab4_[, 5] * 100, 2)
|
|
|
|
if (as.numeric(pottab4_$relative_lowerCL[1]) > Lim[[9]] & as.numeric(pottab4_$relative_upperCL[1]) < Lim[[10]]) {
|
|
test_potCI <- 0
|
|
} else {
|
|
test_potCI <- 1
|
|
}
|
|
if (as.numeric(pottab4_$relative_lowerCL[2]) > Lim[[9]] & as.numeric(pottab4_$relative_upperCL[2]) < Lim[[10]]) {
|
|
test_potUCI <- 0
|
|
} else {
|
|
test_potUCI <- 1
|
|
}
|
|
if (as.numeric(pottab4_$relative_lowerCL[3]) > Lim[[9]] & as.numeric(pottab4_$relative_upperCL[3]) < Lim[[10]]) {
|
|
test_potCI_t <- 0
|
|
} else {
|
|
test_potCI_t <- 1
|
|
}
|
|
if (as.numeric(pottab4_$relative_lowerCL[4]) > Lim[[9]] & as.numeric(pottab4_$relative_upperCL[4]) < Lim[[10]]) {
|
|
test_potUCI_t <- 0
|
|
} else {
|
|
test_potUCI_t <- 1
|
|
}
|
|
pottab4_ <- cbind(pottab4_[, -(2:4)], data.frame(tests = c(test_potCI, test_potUCI, test_potCI_t, test_potUCI_t)))
|
|
colnames(pottab4_) <- c("model", "potency", "lower95%CI", "upper95%CI", "relative_lower95%CI", "relative_upper95%CI", "test_result")
|
|
|
|
output$pottab4pl <- DT::renderDataTable({
|
|
dat <- datatable(pottab4_[1:2, ],
|
|
options = list(
|
|
digits = 3,
|
|
paging = TRUE, dom = "t", rownames = FALSE
|
|
)
|
|
) |> formatStyle("test_result", target = "row", backgroundColor = styleEqual(
|
|
c(0, 1),
|
|
c("lightgreen", "pink")
|
|
))
|
|
})
|
|
output$pottab4plTrans <- DT::renderDataTable({
|
|
dat <- datatable(pottab4_[3:4, ],
|
|
options = list(
|
|
digits = 3,
|
|
paging = TRUE, dom = "t", rownames = FALSE
|
|
)
|
|
) |> formatStyle("test_result", target = "row", backgroundColor = styleEqual(
|
|
c(0, 1),
|
|
c("lightgreen", "pink")
|
|
))
|
|
})
|
|
})
|
|
|
|
#### 4pl potency table XL ----
|
|
observe({
|
|
if (is.null(Dat$EXCEL)) {
|
|
return(NULL)
|
|
}
|
|
if (Dat$FITsFlag) {
|
|
return(NULL)
|
|
}
|
|
ro_new <- Dat$EXCEL
|
|
|
|
noDilSer <- Dat$noDilSeriesXL
|
|
PureErrFl <- input$PureErr
|
|
pottab4 <- pot4plFUNC(ro_new = ro_new, PureErrFlag = PureErrFl)
|
|
Lim <- list(
|
|
as.numeric(input$lEACdiffla), as.numeric(input$uEACdiffla),
|
|
as.numeric(input$lEACratiola), as.numeric(input$uEACratiola),
|
|
as.numeric(input$lEACratioSlope), as.numeric(input$uEACratioSlope),
|
|
as.numeric(input$lEACratioua), as.numeric(input$uEACratioua),
|
|
as.numeric(input$lowerPot), as.numeric(input$upperPot)
|
|
)
|
|
REP$Lim <- Lim
|
|
|
|
pottab4_ <- data.frame(pottab4)
|
|
pottab4_$potency <- round(as.numeric(pottab4[, 2]) * 100, 1)
|
|
pottab4_$`lower95%CI` <- round(as.numeric(pottab4[, 3]) * 100, 2)
|
|
pottab4_$`upper95%CI` <- round(as.numeric(pottab4[, 4]) * 100, 2)
|
|
pottab4_$relative_lowerCL <- round(pottab4_[, 6] / pottab4_[, 5] * 100, 2)
|
|
pottab4_$relative_upperCL <- round(pottab4_[, 7] / pottab4_[, 5] * 100, 2)
|
|
|
|
if (as.numeric(pottab4_$relative_lowerCL[1]) > Lim[[9]] & as.numeric(pottab4_$relative_upperCL[1]) < Lim[[10]]) {
|
|
test_potCI <- "passed"
|
|
} else {
|
|
test_potCI <- "failed"
|
|
}
|
|
if (as.numeric(pottab4_$relative_lowerCL[2]) > Lim[[9]] & as.numeric(pottab4_$relative_upperCL[2]) < Lim[[10]]) {
|
|
test_potUCI <- ""
|
|
} else {
|
|
test_potUCI <- ""
|
|
}
|
|
if (as.numeric(pottab4_$relative_lowerCL[3]) > Lim[[9]] & as.numeric(pottab4_$relative_upperCL[3]) < Lim[[10]]) {
|
|
test_potCI_t <- ""
|
|
} else {
|
|
test_potCI_t <- ""
|
|
}
|
|
if (as.numeric(pottab4_$relative_lowerCL[4]) > Lim[[9]] & as.numeric(pottab4_$relative_upperCL[4]) < Lim[[10]]) {
|
|
test_potUCI_t <- ""
|
|
} else {
|
|
test_potUCI_t <- ""
|
|
}
|
|
pottab4_ <- cbind(pottab4_[, -(2:4)], data.frame(tests = c(test_potCI, test_potUCI, test_potCI_t, test_potUCI_t)))
|
|
colnames(pottab4_) <- c("model", "potency", "lower95%CI", "upper95%CI", "relative_lower95%CI", "relative_upper95%CI", "test_result")
|
|
row.names(pottab4_) <- NULL
|
|
REP$pottab4plXL <- pottab4_[1:2, ]
|
|
# browser()
|
|
output$pottab4plXL <- DT::renderDataTable({
|
|
dat <- datatable(pottab4_[1:2, ],
|
|
rownames = FALSE,
|
|
options = list(
|
|
digits = 3,
|
|
paging = TRUE, dom = "t"
|
|
)
|
|
) |> formatStyle("test_result", target = "row", backgroundColor = styleEqual(
|
|
c("passed", "failed"),
|
|
c("#B5C74055", "#F9545455")
|
|
))
|
|
})
|
|
output$pottab4plTransXL <- DT::renderDataTable({
|
|
dat <- datatable(pottab4_[3:4, -ncol(pottab4_)],
|
|
rownames = FALSE,
|
|
options = list(
|
|
digits = 3,
|
|
paging = TRUE, dom = "t"
|
|
)
|
|
)
|
|
})
|
|
})
|
|
|
|
|
|
#### Dilutions Simulator ----
|
|
output$plotfordilutions <- renderPlot({
|
|
if (!is.null(Dat$Mws)) {
|
|
|
|
|
|
AllXL <- Dat$Mws
|
|
AllSheets <- Dat$Msheets
|
|
|
|
URMcoefsL <- RMcoefsL <- potEstL <- list()
|
|
|
|
for (N_WS in 1:length(AllXL)) {
|
|
|
|
datWS <- as.data.frame(AllXL[[N_WS]])
|
|
|
|
cn <- colnames(datWS)
|
|
logI <- grep("log|ln", cn)
|
|
logDoseI <- grep("log_dose", cn)
|
|
if (length(logI) > 0 & length(logDoseI) == 0) {
|
|
datWS$log_dose <- datWS[, logI]
|
|
datWS2 <- datWS[, -logI]
|
|
CORro <- cor(datWS$log_dose, datWS[, 3])
|
|
} else if (length(logI) == 0 & length(logDoseI) == 0) {
|
|
Ind <- grep(".ilution|.ose|.onc", cn)
|
|
datWS$log_dose <- log(datWS[, Ind])
|
|
CORro <- cor(datWS[, Ind], datWS[, 3])
|
|
datWS2 <- datWS[, -Ind]
|
|
} else if (length(logI) > 0 & length(logDoseI) > 0) {
|
|
datWS2 <- datWS
|
|
CORro <- cor(datWS[, logI], datWS[, 3])
|
|
}
|
|
Dat$datWS2 <- datWS2
|
|
|
|
FITs <- Fitting_FUNC(datWS2, TransFlag = F)
|
|
|
|
pot_est <- FITs[[3]]
|
|
potEstL[[N_WS]] <- pot_est
|
|
potU_est <- FITs[[4]]
|
|
# unrestricted
|
|
SU_mu <- FITs[[2]]
|
|
URMcoefs1 <- SU_mu$coefficients
|
|
URMcoefs <- t(matrix(unlist(URMcoefs1[,1])))
|
|
URMcoefs_ <- cbind(AllSheets[[N_WS]], URMcoefs)
|
|
URMcoefsL[[N_WS]] <- URMcoefs_
|
|
|
|
SU_mr <- FITs[[1]]
|
|
RMcoefs1 <- SU_mr$coefficients
|
|
RMcoefs <- t(matrix(unlist(RMcoefs1[,1])))
|
|
RMcoefs_ <- cbind(AllSheets[[N_WS]], RMcoefs)
|
|
RMcoefsL[[N_WS]] <- RMcoefs_
|
|
|
|
|
|
|
|
X <- seq(min(datWS2$log_dose), max(datWS2$log_dose), 0.1)
|
|
sigRef <- URMcoefs[1,1] + (URMcoefs[1,3]-URMcoefs[1,1])/(1+exp(URMcoefs[1,2]*(URMcoefs[1,4]-X)))
|
|
sigTest1 <- URMcoefs[1,5] + (URMcoefs[1,7]-URMcoefs[1,5])/(1+exp(URMcoefs[1,6]*(URMcoefs[1,4] - URMcoefs[1,8]-X)))
|
|
#browser()
|
|
dfPlotsigRef <- data.frame(X=X, sigRef = sigRef, Sheet = AllSheets[[N_WS]])
|
|
dfPlotsigTest <- data.frame(X=X, sigTest = sigTest1, Sheet = AllSheets[[N_WS]])
|
|
|
|
if (!exists("SIGrefDF")) SIGrefDF <- dfPlotsigRef else SIGrefDF <- rbind(SIGrefDF, dfPlotsigRef)
|
|
if (!exists("SIGtestDF")) SIGtestDF <- dfPlotsigTest else SIGtestDF <- rbind(SIGtestDF,dfPlotsigTest)
|
|
|
|
} #for N_WS
|
|
|
|
#browser()
|
|
URMcoefsDF <- t(matrix(unlist(URMcoefsL),nrow=9))
|
|
EC50TEST <- as.numeric(URMcoefsDF[,5]) - as.numeric(URMcoefsDF[,9])
|
|
# EC50TEST <- EC50TEST[!EC50TEST %in% boxplot.stats(EC50TEST)$out]
|
|
EC50REF <- as.numeric(URMcoefsDF[,5])
|
|
# EC50REF <- EC50REF[!EC50REF %in% boxplot.stats(EC50REF)$out]
|
|
UasREF <- as.numeric(URMcoefsDF[,4])
|
|
# UasREF <- UasREF[!UasREF %in% boxplot.stats(UasREF)$out]
|
|
LasREF <- as.numeric(URMcoefsDF[,2])
|
|
# LasREF <- LasREF[!LasREF %in% boxplot.stats(LasREF)$out]
|
|
UasTEST <- as.numeric(URMcoefsDF[,4])
|
|
LasTEST <- as.numeric(URMcoefsDF[,2])
|
|
|
|
RMcoefsDF <- t(matrix(unlist(RMcoefsL),nrow=6))
|
|
|
|
Dat$URMcoefsDF <- URMcoefsDF
|
|
Dat$RestrM <- RMcoefsDF
|
|
|
|
CalcPotDF <- t(matrix(unlist(potEstL),nrow=3))
|
|
Dat$CalcPot <- CalcPotDF
|
|
#
|
|
#### sigmoid plots ----
|
|
|
|
Slope <- as.numeric(URMcoefsDF[1,3])
|
|
if (Slope > 0) {
|
|
x_UA <- max(X); x_LA <- min(X)
|
|
} else { x_UA <- min(X); x_LA <- max(X) }
|
|
|
|
p1 <- ggplot(SIGrefDF, aes(x=X, y=sigRef, col=as.factor(Sheet))) +
|
|
geom_line() +
|
|
annotate("text", label="x", x=x_UA, y=UasREF, alpha=0.2) +
|
|
annotate("text", label="o", x=x_LA, y=LasREF, alpha=0.2) +
|
|
geom_vline(xintercept = EC50REF, alpha = 0.2) +
|
|
xlab("dilutions") +
|
|
ggtitle("Plot of all calculated reference fits (unrestricted model, in gray vertical lines: EC50)") +
|
|
theme_bw() +
|
|
theme(axis.text = element_text(face = "bold", size = 15),
|
|
plot.title = element_text(size = 15, face = "bold"))
|
|
|
|
output$sigPlotREF <- renderPlot({ p1 })
|
|
|
|
Dat$sigPlotREF <- p1
|
|
#
|
|
p2 <- ggplot(SIGtestDF, aes(x=X, y=sigTest, col=as.factor(Sheet))) +
|
|
geom_line() +
|
|
annotate("text", label="x", x=x_UA, y=UasTEST, alpha=0.2) +
|
|
annotate("text", label="o", x=x_LA, y=LasTEST, alpha=0.2) +
|
|
geom_vline(xintercept = EC50TEST, alpha = 0.2) +
|
|
xlab("dilutions") +
|
|
ggtitle("Calculated test sample fits (unrestricted model, in gray vertical lines: EC50)") +
|
|
theme_bw() +
|
|
theme(axis.text = element_text(face = "bold", size = 15),
|
|
plot.title = element_text(size = 15, face = "bold"))
|
|
|
|
output$sigPlotTEST <- renderPlot({ p2 })
|
|
|
|
Dat$sigPlotTEST <- p2
|
|
|
|
#### histograms right panel ----
|
|
|
|
#browser()
|
|
|
|
all_lPot <- data.frame(Cat_potency= c(rep("rel poteny",nrow(CalcPotDF)), rep("lower CI",nrow(CalcPotDF)),rep("upper CI",nrow(CalcPotDF))),
|
|
Potency_and_CI = c(CalcPotDF[,1], CalcPotDF[,2],CalcPotDF[,3]))
|
|
all_lPot[,2][all_lPot[,2] > 5] <- NA
|
|
all_lPot[,2][all_lPot[,2] < 0.1] <- NA
|
|
|
|
P_histCI <- ggplot(all_lPot, aes(x=Potency_and_CI, fill=Cat_potency)) +
|
|
geom_histogram(color="#e9ecef", alpha=0.6, position = "identity") +
|
|
scale_fill_manual(values=c("darkgreen","darkblue","salmon2","tomato3")) +
|
|
ggtitle("Histogram of relative potencies, standard RMSEs") +
|
|
scale_x_continuous(
|
|
breaks=seq(trunc(min(all_lPot$Potency_and_CI, na.rm=T)*10)/10, max(all_lPot$Potency_and_CI, na.rm=T)*1.1, by=0.4),
|
|
) +
|
|
theme_bw() +
|
|
theme(axis.text = element_text(face="bold", size=15),
|
|
axis.text.x = element_text(angle=90),
|
|
plot.title= element_text(size=15, face="bold"))
|
|
|
|
output$histCIs <- renderPlot({ P_histCI })
|
|
|
|
output$histEC50REF <- renderPlot({
|
|
hist(EC50REF, col="steelblue", border="white", main = 'Histogram of EC50REF')
|
|
})
|
|
output$histLasREF <- renderPlot({
|
|
hist(LasREF, col="violet", border="white",main = 'Histogram of lower asymptotes REF')
|
|
})
|
|
output$histUasREF <- renderPlot({
|
|
hist(UasREF, col="darkturquoise", border="white",main = 'Histogram of upper asymptotes REF')
|
|
})
|
|
Dat$histEC50REF <- hist(EC50REF, col="steelblue", border="white", main = 'Histogram of EC50REF')
|
|
Dat$histLasREF <- hist(LasREF, col="violet", border="white", main = 'Histogram of EC50REF')
|
|
Dat$histUasREF <- hist(UasREF, col="darkturquoise", border="white", main = 'Histogram of EC50REF')
|
|
|
|
# dils <- tab$log_dose
|
|
# min_y <- min(tab[, 1:3])
|
|
# max_y <- max(tab[, 1:3])
|
|
#
|
|
# if (input$fixupper) {
|
|
# dils_av <- dils - max(dils)
|
|
# dils_av_ <- dils_av * (input$dilslider / 100 + 1)
|
|
# dils2 <- round(dils_av_ + max(dils), 4)
|
|
# dilfactors <- 1 / exp(dils2 - lag(dils2))
|
|
# } else {
|
|
# if (!is.null(Dat$cfordils)) {
|
|
# av <- Dat$cfordils
|
|
# } else {
|
|
# av <- (min(dils) + max(dils)) / 2
|
|
# }
|
|
# dils_av <- dils - av
|
|
# dils_avsc <- dils_av * (input$dilslider / 100 + 1)
|
|
# dils2 <- dils_avsc + av
|
|
# dilfactors <- 1 / exp(dils2 - lag(dils2))
|
|
# }
|
|
|
|
|
|
|
|
|
|
#Dat$newDils <- dils2
|
|
|
|
|
|
#sigmoid <- sigmoid()
|
|
|
|
# BPs <- Dat$bendpoints
|
|
# EC50REF <- (BPs[2] + BPs[1]) / 2
|
|
# Einh <- abs((BPs[2] - BPs[1]) / 5)
|
|
# asyml <- EC50REF - 2 * (EC50REF - BPs[1])
|
|
# asymu <- EC50REF + 2 * (EC50REF - BPs[1])
|
|
#
|
|
# det_sig <- Dat$coeffs_UN
|
|
#
|
|
# if (is.null(Dat$coeffs_UN)) {
|
|
# SAMPLE50 <- sigmoid[1] + (sigmoid[3] - sigmoid[1]) / (1 + exp(sigmoid[5] * ((sigmoid[7] + 0.693147) - dils2)))
|
|
# SAMPLE200 <- sigmoid[1] + (sigmoid[3] - sigmoid[1]) / (1 + exp(sigmoid[5] * ((sigmoid[7] - 0.693147) - dils2)))
|
|
# Xbend50l <- sigmoid[7] + 0.693147 - 1.5434 / sigmoid[5]
|
|
# Xbend200l <- sigmoid[7] - 0.693147 - 1.5434 / sigmoid[5]
|
|
# Xbend50u <- sigmoid[7] + 0.693147 + 1.5434 / sigmoid[5]
|
|
# Xbend200u <- sigmoid[7] - 0.693147 + 1.5434 / sigmoid[5]
|
|
# Xbend50 <- max(Xbend50l, Xbend50u)
|
|
# Xbend200 <- min(Xbend200l, Xbend200u)
|
|
# dummy <- plot_f(tab)
|
|
# } else {
|
|
# SAMPLE50 <- det_sig[3] + (det_sig[5] - det_sig[3]) / (1 + exp(det_sig[1] * (det_sig[7] + 0.693147 - dils2)))
|
|
# SAMPLE200 <- det_sig[3] + (det_sig[5] - det_sig[3]) / (1 + exp(det_sig[1] * (det_sig[7] - 0.693147 - dils2)))
|
|
# Xbend50l <- det_sig[7] + 0.693147 - 1.5434 / det_sig[1]
|
|
# Xbend200l <- det_sig[7] - 0.693147 - 1.5434 / det_sig[1]
|
|
# Xbend50u <- det_sig[7] + 0.693147 + 1.5434 / det_sig[1]
|
|
# Xbend200u <- det_sig[7] - 0.693147 + 1.5434 / det_sig[1]
|
|
# Xbend50 <- max(Xbend50l, Xbend50u)
|
|
# Xbend200 <- min(Xbend200l, Xbend200u)
|
|
# dummy <- plot_f(tab)
|
|
# }
|
|
#
|
|
#
|
|
# pl_df <- cbind(dils2, SAMPLE50, SAMPLE200)
|
|
#
|
|
#
|
|
# output$adjlogdil <- renderTable({
|
|
# adjlogdilfactors <- round(dilfactors, 3)
|
|
# adjlogdils <- round(dils2, 3)
|
|
# adjdils <- round(exp(dils2), 3)
|
|
# DilsTable <- data.frame(
|
|
# "adjusted ln(dilutions)" = adjlogdils,
|
|
# "adjusted ln_dilution_factors" = adjlogdilfactors,
|
|
# "adjusted dilutions" = adjdils
|
|
# )
|
|
# DilsTable
|
|
# })
|
|
|
|
# if (!is.null(Dat$p2)) {
|
|
# p2 <- Dat$p2
|
|
# p_dil <- p2 +
|
|
# annotate("pointrange", x = dils2, y = rep(min_y, length(dils2)), xmin = min(dils2), xmax = max(dils2)) +
|
|
# annotate("text", x = dils2, y = rep(min_y + (max_y - min_y) * 0.05, length(dils2)), label = as.character(round(dils2, 3))) +
|
|
# annotate("text",
|
|
# x = dils2[-1] + (max(dils2) - min(dils2)) * 0.05,
|
|
# y = rep(min_y + (max_y - min_y) * 0.1, length(dils2[-1])),
|
|
# label = as.character(round(dilfactors[-1], 3))
|
|
# ) +
|
|
# geom_line(
|
|
# data = as.data.frame(pl_df), aes(x = dils2, y = SAMPLE50), color = "grey15", linetype = 2,
|
|
# inherit.aes = F
|
|
# ) +
|
|
# geom_line(
|
|
# data = as.data.frame(pl_df), aes(x = dils2, y = SAMPLE200), color = "grey15", linetype = 2,
|
|
# inherit.aes = F
|
|
# ) +
|
|
# geom_vline(xintercept = c(Xbend50, Xbend200), col = "grey15", linetype = 2) +
|
|
# {
|
|
# if (input$scenario == "scenario 6") {
|
|
# annotate("pointrange",
|
|
# x = optdils2, y = rep(min_y + (max_y - min_y) * 0.2, length(optdils2)),
|
|
# xmin = min(optdils2), xmax = max(optdils2), color = "seagreen"
|
|
# )
|
|
# }
|
|
# } +
|
|
# {
|
|
# if (input$scenario == "scenario 6") {
|
|
# annotate("text",
|
|
# x = optdils2, y = rep(min_y + (max_y - min_y) * 0.25, length(optdils2)),
|
|
# label = as.character(round(optdils2, 3)), color = "seagreen"
|
|
# )
|
|
# }
|
|
# } +
|
|
# {
|
|
# if (input$scenario == "scenario 2") {
|
|
# annotate("pointrange",
|
|
# x = optdils, y = rep(min_y + (max_y - min_y) * 0.2, length(optdils)),
|
|
# xmin = min(optdils), xmax = max(optdils), color = "seagreen"
|
|
# )
|
|
# }
|
|
# } +
|
|
# {
|
|
# if (input$scenario == "scenario 2") {
|
|
# annotate("text",
|
|
# x = optdils, y = rep(min_y + (max_y - min_y) * 0.25, length(optdils)),
|
|
# label = as.character(round(optdils, 3)), color = "seagreen"
|
|
# )
|
|
# }
|
|
# } +
|
|
# {
|
|
# if (input$scenario == "scenario 3") {
|
|
# annotate("pointrange",
|
|
# x = optdils_3, y = rep(min_y + (max_y - min_y) * 0.2, length(optdils_3)),
|
|
# xmin = min(optdils_3), xmax = max(optdils_3), color = "seagreen"
|
|
# )
|
|
# }
|
|
# } +
|
|
# {
|
|
# if (input$scenario == "scenario 3") {
|
|
# annotate("text",
|
|
# x = optdils_3, y = rep(min_y + (max_y - min_y) * 0.25, length(optdils_3)),
|
|
# label = as.character(round(optdils_3, 3)), color = "seagreen"
|
|
# )
|
|
# }
|
|
# } +
|
|
# {
|
|
# if (input$scenario == "steep slope") {
|
|
# annotate("pointrange",
|
|
# x = optdils3, y = rep(min_y + (max_y - min_y) * 0.2, length(optdils3)),
|
|
# xmin = min(optdils3), xmax = max(optdils3), color = "seagreen"
|
|
# )
|
|
# }
|
|
# } +
|
|
# {
|
|
# if (input$scenario == "steep slope") {
|
|
# annotate("text",
|
|
# x = optdils3, y = rep(min_y + (max_y - min_y) * 0.25, length(optdils3)),
|
|
# label = as.character(round(optdils3, 3)), color = "seagreen"
|
|
# )
|
|
# }
|
|
# } +
|
|
# annotate("text",
|
|
# x = optdils[1], y = (max_y + min_y) * 0.5,
|
|
# label = paste("in green: optimal \n dilutions acc. to Whitepaper\n", input$scenario), color = "seagreen",
|
|
# size = 14 / .pt, fontface = "bold"
|
|
# )
|
|
# }
|
|
#print(p_dil)
|
|
# }
|
|
}
|
|
|
|
})
|
|
|
|
#### Dilutions CI table ----
|
|
observe({
|
|
if (is.null(input$potencydiff)) {
|
|
return(NULL)
|
|
}
|
|
output$CIs <- renderTable({
|
|
PureErrFlag <- input$PureErr
|
|
if (is.null(Dat$coeffs_UN)) {
|
|
# checks if an EXCEL was uploaded
|
|
sigmoid <- sigmoid()
|
|
det_sig <- NULL
|
|
|
|
ast <- sigmoid()[1]
|
|
bst <- sigmoid()[5]
|
|
cst <- sigmoid()[7]
|
|
dst <- sigmoid()[3]
|
|
ate <- sigmoid()[2]
|
|
bte <- sigmoid()[6]
|
|
r_ <- sigmoid()[8]
|
|
cte <- cst - r_
|
|
dte <- sigmoid()[4]
|
|
} else {
|
|
sigmoid <- NULL
|
|
det_sig <- Dat$coeffs_UN
|
|
ast <- det_sig[3]
|
|
ate <- det_sig[4]
|
|
bst <- det_sig[1]
|
|
bte <- det_sig[2]
|
|
cst <- det_sig[7]
|
|
cte <- det_sig[7] - log(input$potencydiff / 100)
|
|
dst <- det_sig[5]
|
|
dte <- det_sig[6]
|
|
r_ <- log(input$potencydiff / 100)
|
|
}
|
|
if (!is.na(input$NoDilSer)) {
|
|
noDilSer <- input$NoDilSer
|
|
} else if (!is.null(Dat$NoDilSeriesXL)) noDilSer <- Dat$noDilSeriesXL else noDilSer <- 3
|
|
if (!is.na(input$NoDil)) noDil <- input$NoDil else noDil <- length(Dat$newDils)
|
|
tab <- Calc_DilRes(
|
|
as = ast, at = ate, ds = dst, dt = dte, cs = cst, ct = cte, r = r_, bt = bte, bs = bst,
|
|
sd_fac = input$sdfac, log_conc = Dat$newDils,
|
|
# auslenkU=outlierU,
|
|
# auslenkM=outlierM,
|
|
# auslenkL=outlierL,
|
|
heteroNoise = FALSE, noDilSeries = noDilSer, noDils = noDil
|
|
)
|
|
Limite <- list(
|
|
as.numeric(input$lEACdiffla), as.numeric(input$uEACdiffla),
|
|
as.numeric(input$lEACratiola), as.numeric(input$uEACratiola),
|
|
as.numeric(input$lEACratioSlope), as.numeric(input$uEACratioSlope),
|
|
as.numeric(input$lEACratioua), as.numeric(input$uEACratioua),
|
|
as.numeric(input$lowerPot), as.numeric(input$upperPot),
|
|
as.numeric(input$lEACratioAdiff), as.numeric(input$uEACratioAdiff)
|
|
)
|
|
|
|
CItable <- tests_FUNC(tab, Limite, PureErrFlag = PureErrFlag)
|
|
|
|
CItable_ <- CItable[-c(1, 2, 6, 8, 9), -c(2, 4, 5)]
|
|
potAll <- pot4plFUNC(tab, input$PureErr)
|
|
restrPot <- potAll[1, 1:4]
|
|
restrPot[2:4] <- round(as.numeric(restrPot[2:4]), 5)
|
|
potAll_ <- rbind(CItable_, restrPot)
|
|
potAll_$CIwidth <- as.numeric(potAll_[, 4]) - as.numeric(potAll_[, 3])
|
|
potAll_[, 1] <- c("ratio of lower asymptotes", "ratio of slopes", "ratio of upper asymptotes", "ratio of asympt. differences", "restricted potency")
|
|
|
|
output$bps <- renderTable({
|
|
DF <- data.frame(sample = names(Dat$bendpoints), BPs = Dat$bendpoints)
|
|
DF
|
|
})
|
|
return(potAll_)
|
|
})
|
|
})
|
|
|
|
#### simulations ----
|
|
observe({
|
|
observeEvent(input$goSim, {
|
|
sd_fac_ <- as.numeric(input$sdfac)
|
|
|
|
r_ <- log(as.numeric(input$potencydiff) / 100)
|
|
Conc <- Dat$MetaConc
|
|
as <- sigmoid()[1]
|
|
bs <- sigmoid()[5]
|
|
cs <- sigmoid()[7]
|
|
ds <- sigmoid()[3]
|
|
at <- sigmoid()[2]
|
|
bt <- sigmoid()[6]
|
|
r <- sigmoid()[8]
|
|
ct <- cs - r_
|
|
dt <- sigmoid()[4]
|
|
|
|
if (!is.null(Dat$MetaConc)) {
|
|
Conc <- Dat$MetaConc
|
|
} else {
|
|
Conc <- CONC()
|
|
}
|
|
log_dose <- log(Conc)
|
|
yAxfac <- (ds - as)
|
|
|
|
if (!is.na(input$NoDilSer)) {
|
|
noDilSer <- input$NoDilSer
|
|
} else if (!is.null(Dat$NoDilSeriesXL)) noDilSer <- Dat$noDilSeriesXL else noDilSer <- 3
|
|
if (!is.na(input$NoDil)) noDil <- input$NoDil else noDil <- length(Conc)
|
|
isRef <- rep(c(1, 0), 1, each = noDilSer * noDil)
|
|
isSample <- rep(c(0, 1), 1, each = noDilSer * noDil)
|
|
N <- as.numeric(input$simN)
|
|
|
|
av <- as * isRef + at * isSample + (ds * isRef + dt * isSample - as * isRef - at * isSample) /
|
|
(1 + isRef * exp(bs * (cs - log_dose)) + isSample * exp(bt * (ct - log_dose)))
|
|
|
|
resHist <- matrix(NA, nrow = N, ncol = 13)
|
|
residualsList <- list()
|
|
start.time2 <- Sys.time()
|
|
withProgress(message = "Making plot", value = 0, {
|
|
for (i in 1:N) {
|
|
if (input$heterosked) {
|
|
# heterosc noise
|
|
ro_jit <- matrix(unlist(map(av, function(x) x + rnorm(1, 0, x * sd_fac_ / 100))), nrow = noDil, ncol = noDilSer * 2)
|
|
} else {
|
|
# homosc noise
|
|
ro_jit <- matrix(unlist(map(av, function(x) x + rnorm(1, 0, sd_fac_ * yAxfac / 100))), nrow = noDil, ncol = noDilSer * 2)
|
|
}
|
|
ro_jit <- abs(ro_jit)
|
|
ro_new <- cbind(ro_jit, log_dose)
|
|
all_l <- melt(data.frame(ro_new), id.vars = "log_dose", variable.name = "replname", value.name = "readout")
|
|
all_l$isRef <- isRef
|
|
all_l$isSample <- isSample
|
|
all_l$Conc <- exp(all_l$log_dose)
|
|
pot <- drm(readout ~ Conc, isSample,
|
|
data = all_l, fct = LL.4(names = c("b", "d", "a", "c")),
|
|
pmodels = data.frame(1, 1, 1, isSample)
|
|
)
|
|
potAll <- EDcomp(pot, percVec = c(50, 50), interval = "delta", display = FALSE)
|
|
potAll2 <- potAll[1:3]
|
|
RSS <- sum(pot$predres[, 2]^2)
|
|
dfreed <- nrow(all_l) - 5
|
|
MSE <- RSS / dfreed
|
|
|
|
potU <- drm(readout ~ Conc, isSample,
|
|
data = all_l, fct = LL.4(names = c("b", "d", "a", "c")),
|
|
pmodels = data.frame(isSample, isSample, isSample, isSample)
|
|
)
|
|
DF_U <- nrow(all_l) - 8
|
|
|
|
uAsratio <- compParm(potU, "a", display = FALSE)
|
|
uCIuAs <- uAsratio[1] + qt(0.975, DF_U) * uAsratio[2]
|
|
lCIuAs <- uAsratio[1] - qt(0.975, DF_U) * uAsratio[2]
|
|
lAsratio <- compParm(potU, "d", display = FALSE)
|
|
uCIlAs <- lAsratio[1] + qt(0.975, DF_U) * lAsratio[2]
|
|
lCIlAs <- lAsratio[1] - qt(0.975, DF_U) * lAsratio[2]
|
|
Sloperatio <- compParm(potU, "b", display = FALSE)
|
|
uCISlo <- Sloperatio[1] + qt(0.975, DF_U) * Sloperatio[2]
|
|
lCISlo <- Sloperatio[1] - qt(0.975, DF_U) * Sloperatio[2]
|
|
su <- summary(potU)
|
|
|
|
v <- vcov(potU)[c(5, 6), c(5, 6)]
|
|
Vd <- vcov(potU)[c(3, 4), c(3, 4)]
|
|
Va_d <- v + Vd
|
|
|
|
A_DTEST <- su$coefficients[6, 1] - su$coefficients[4, 1]
|
|
A_DREF <- su$coefficients[5, 1] - su$coefficients[3, 1]
|
|
if (abs(at / (sqrt(Va_d[2, 2] / 3))) > qt(0.95, 2)) {
|
|
try(Fie_ad <- round(FiellerRatio(A_DREF, A_DTEST, Va_d), 5))
|
|
}
|
|
if (!exists("Fie_ad")) Fie_ad <- NA
|
|
|
|
resHist[i, ] <- c(
|
|
potAll2, sqrt(MSE), Sloperatio[1], lCISlo, uCISlo,
|
|
uAsratio[1], lCIuAs, uCIuAs, Fie_ad[1], Fie_ad[2], Fie_ad[3]
|
|
)
|
|
colnames(resHist) <- c(
|
|
"pot4pl", "lCI4pl", "uCI4pl", "RMSE", "estSlope_ratio",
|
|
"lCISlope_ratio", "uCISlope_ratio", "estuAs_ratio",
|
|
"lCIuAs_ratio", "uCIuAs_ratio", "estAsyDiff_ratio",
|
|
"lCIAsyDiff_ratio", "uCIAsyDiff_ratio"
|
|
)
|
|
|
|
incProgress(1 / N, detail = paste("Doing simulations", i))
|
|
} # withProgress
|
|
})
|
|
end.time2 <- Sys.time()
|
|
|
|
Dat$resHist <- resHist
|
|
})
|
|
})
|
|
|
|
|
|
#### simulation Histograms output ----
|
|
|
|
output$plotHistuAs <- renderPlot({
|
|
if (!is.null(Dat$resHist)) {
|
|
resHist <- Dat$resHist
|
|
resHistuAs <- as.data.frame(resHist[, 8:10])
|
|
resHistuAs_l <- melt(data.frame(resHistuAs), variable.name = "ratio_CIs", value.name = "readout")
|
|
lowquant_uAs <- quantile(resHistuAs[, 2], probs = as.numeric(input$lowQuant) / 100)
|
|
upquant_uAs <- quantile(resHistuAs[, 3], probs = as.numeric(input$uppQuant) / 100)
|
|
|
|
p_uAs <- ggplot(resHistuAs_l) +
|
|
geom_histogram(aes(readout, fill = ratio_CIs), alpha = 0.5, position = "identity") +
|
|
labs(title = paste("upper asymptote ratio EACs:", round(lowquant_uAs, 3), " to ", round(upquant_uAs, 3))) +
|
|
geom_vline(xintercept = c(lowquant_uAs, upquant_uAs), color = "black", linetype = "dashed", linewidth = 1) +
|
|
geom_vline(xintercept = c(input$lEACratioua, input$uEACratioua), color = "red", linetype = "dashed", linewidth = 1) +
|
|
theme_bw()
|
|
|
|
# asympt diff ratio
|
|
resHistAsDiff <- as.data.frame(resHist[, 11:13])
|
|
resHistAsDiff_l <- melt(data.frame(resHistAsDiff), variable.name = "ratio_CIs", value.name = "readout")
|
|
|
|
lowquant_AsDiff <- quantile(resHistAsDiff[, 2], probs = as.numeric(input$lowQuant) / 100)
|
|
upquant_AsDiff <- quantile(resHistAsDiff[, 3], probs = as.numeric(input$uppQuant) / 100)
|
|
|
|
p_AsDiff <- ggplot(resHistAsDiff_l, aes(readout, fill = ratio_CIs)) +
|
|
geom_histogram(alpha = 0.5, position = "identity") +
|
|
labs(title = paste("asymptote diff. ratio EACs:", round(lowquant_AsDiff, 3), " to ", round(upquant_AsDiff, 3))) +
|
|
geom_vline(xintercept = c(lowquant_AsDiff, upquant_AsDiff), color = "black", linetype = "dashed", linewidth = 1) +
|
|
geom_vline(xintercept = c(input$lEACratioAdiff, input$uEACratioAdiff), color = "red", linetype = "dashed", linewidth = 1) +
|
|
theme_bw()
|
|
|
|
# Slope ratio
|
|
resHistSlo <- as.data.frame(resHist[, 5:7])
|
|
resHistSlo_l <- melt(data.frame(resHistSlo), variable.name = "ratio_CIs", value.name = "readout")
|
|
|
|
lowquant_Slo <- quantile(resHistSlo[, 2], probs = as.numeric(input$lowQuant) / 100)
|
|
upquant_Slo <- quantile(resHistSlo[, 3], probs = as.numeric(input$uppQuant) / 100)
|
|
|
|
p_Slo <- ggplot(resHistSlo_l, aes(readout, fill = ratio_CIs)) +
|
|
geom_histogram(alpha = 0.5, position = "identity") +
|
|
labs(title = paste("Slope ratio EACs:", round(lowquant_Slo, 3), " to ", round(upquant_Slo, 3))) +
|
|
geom_vline(xintercept = c(lowquant_Slo, upquant_Slo), color = "black", linetype = "dashed", linewidth = 1) +
|
|
geom_vline(xintercept = c(input$lEACratioSlope, input$uEACratioSlope), color = "red", linetype = "dashed", linewidth = 1) +
|
|
theme_bw()
|
|
|
|
# poency ratio
|
|
resHistPot <- as.data.frame(resHist[, 1:3])
|
|
resHistPot_l <- melt(data.frame(resHistPot), variable.name = "ratio_CIs", value.name = "readout")
|
|
|
|
lowquant_Pot <- quantile(resHistPot[, 2], probs = as.numeric(input$lowQuant) / 100)
|
|
upquant_Pot <- quantile(resHistPot[, 3], probs = as.numeric(input$uppQuant) / 100)
|
|
p_Pot <- ggplot(resHistPot_l, aes(readout, fill = ratio_CIs)) +
|
|
geom_histogram(alpha = 0.5, position = "identity") +
|
|
labs(title = paste("Poency ratio EACs:", round(lowquant_Pot, 3), " to ", round(upquant_Pot, 3))) +
|
|
geom_vline(xintercept = c(lowquant_Pot, upquant_Pot), color = "black", linetype = "dashed", linewidth = 1) +
|
|
geom_vline(xintercept = c(input$lowerPot / 100, input$upperPot / 100), color = "red", linetype = "dashed", linewidth = 1) +
|
|
theme_bw()
|
|
|
|
grid.arrange(p_Slo, p_AsDiff, p_uAs, p_Pot, nrow = 1)
|
|
}
|
|
})
|
|
|
|
#### download XL 4PL report----
|
|
|
|
observeEvent(input$btn, {
|
|
if(!Dat$FITsFlag) {
|
|
runjs("$('#downloadXLReport')[0].click();")
|
|
} else {
|
|
showModal(modalDialog(
|
|
title = "No 4PL model to Download",
|
|
"Please select other data before download.",
|
|
easyClose = TRUE,
|
|
footer = NULL
|
|
))
|
|
}
|
|
})
|
|
|
|
output$downloadXLReport <- downloadHandler(
|
|
filename = paste0("Report_4PLEvaluation", Dat$RepIdentifier, ".pdf"),
|
|
content = function(file) {
|
|
tpdr <- tempdir()
|
|
tempReport <- file.path(tpdr, "Doc_BioassayReport.Rmd")
|
|
file.copy("Doc_BioassayReport.Rmd", tempReport, overwrite = T)
|
|
|
|
tempReportc <- file.path(tpdr, "logov2.png")
|
|
file.copy("logov2.png", tempReportc, overwrite = T)
|
|
|
|
rmarkdown::render(tempReport,
|
|
output_file = file,
|
|
params = list(
|
|
FileName = Dat$FileName,
|
|
author = Dat$Author,
|
|
NoP = Dat$NoP,
|
|
Assay = Dat$Assay,
|
|
REP = REP,
|
|
coeffs = Dat$coeffs_UN
|
|
),
|
|
envir = new.env(parent = globalenv())
|
|
)
|
|
}
|
|
)
|
|
|
|
|
|
|
|
#### download XL Lin report----
|
|
|
|
output$downloadXLReportLin <- downloadHandler(
|
|
filename = paste0("Report_linPLA", Dat$nameRep, ".pdf"),
|
|
content = function(file) {
|
|
tpdr <- tempdir()
|
|
tempReport <- file.path(tpdr, "Doc_BioassayLinReport.Rmd")
|
|
file.copy("Doc_BioassayLinReport.Rmd", tempReport, overwrite = TRUE)
|
|
|
|
tempReportc <- file.path(tpdr, "logov2.png")
|
|
file.copy("logov2.png", tempReportc, overwrite = TRUE)
|
|
|
|
rmarkdown::render(tempReport,
|
|
output_file = file,
|
|
params = list(
|
|
FileName = Dat$FileName,
|
|
author = Dat$Author,
|
|
NoP = Dat$NoP,
|
|
Assay = Dat$Assay,
|
|
REP = REP,
|
|
REPlin = REPlin,
|
|
coeffsLin = Dat$coeffs_UN
|
|
),
|
|
envir = new.env(parent = globalenv())
|
|
)
|
|
}
|
|
)
|
|
}
|
|
|
|
shinyApp(ui, server)
|