2141 lines
104 KiB
R
2141 lines
104 KiB
R
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(shinydashboard)
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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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#### reactive values ----
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Dat <- reactiveValues()
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REP <- reactiveValues()
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REPlin <- reactiveValues()
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source("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="logo.png", width=230),
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menuItem("Home", tabName="home", icon=icon("home")),
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menuItem("Data template", 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("EXCEL upload", tabName="Dataupload", icon=icon("magnet", lib="glyphicon")),
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menuItem("4PL simulation", 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("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$footer(HTML(paste(tags$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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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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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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), skin="blue"
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)
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#### server ----
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server <- function(input, output, session) {
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ReportParS <- reactiveValues()
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IPReportParS <- reactiveValues()
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#### renderUIs ----
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output$homePage <- renderUI({
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navbarPage("Home",
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tabPanel("Limit setting",
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tags$img(src="logo.png", class="adv_logo"),
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h4("Introduction to the bioassay software"),
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tags$mark("linear regression"), br(),
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column(3,
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tags$table(id="dose-table",
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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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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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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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))
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),
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tabPanel("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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tabPanel("Configuration",
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verbatimTextOutput("sessioninfo"))
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)
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})
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##### UI XL ----
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output$Dataupload <- renderUI({
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navbarPage(title="Information",
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tabPanel(title = "Real data",
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tabsetPanel(
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tabPanel("Data input",
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column(3,
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#img(src="Screenshot.png", width=200),
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box(title = "Upload", status="warning",solidHeader = T, width=12, "Please upload your EXCEL file here",
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fileInput("iFile",'',accept=".xlsx")),
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uiOutput(outputId = "sheetName"),
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"For data format in the EXCEL file see Data template",
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"If no data are uploaded, the settings to the right are used for calculations.",
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tags$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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#actionLink("selectall","SelectAll"),
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h5("\n\n\n Author: Franz Innerbichler, InnerAnalytics")),
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column(4,
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h4("Suitability tests for 4-parametric logistic regression"),
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checkboxGroupInput("selectedSSTs", "Which suitability tests to be used?", choices= c("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 non-linearity"="6",
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"EQ-test on ratio of asymptote differences"= "7"),
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selected= c("1","4","5","6","7")),
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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("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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selected= c("1","2","3","4","5","6","7","8"))
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),
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column(4,
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h4("Example of EXCEL file "),
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h4("with column of dilutions and at least 2 columns of reference and the same amount of columns with test sample readouts."),
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tags$img(src="ExampleXL.png", class="adv_logo", width="100%"),
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plotOutput("plotSing", width="400px", height="300px"))
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),
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tabPanel("4pl-Analysis",
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tags$style(HTML("pre { color: black; background-color: #FFE1FF;
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font-family: 'Helvetica Neue', Helvetica, Arial, sans-serif;font-size: 12px;} ")),
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wellPanel(
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fluidRow(
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column(4,
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#h5("Diagnostics only shown if EXCEL is uploaded"),
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htmlOutput("PureErrW2"),
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tags$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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tableOutput("VarDiagn")
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),
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column(8,
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plotOutput("XLplot"),
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"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.",
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"Black line is the true slope at EC50 of REF.",
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DTOutput("pottab4plXL"),
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plotOutput("diagnplot"),
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DTOutput("EQtests"),
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DTOutput("pottab4plTransXL"),
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tableOutput("ANOVAXLS")
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)
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))),
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tabPanel("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(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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mainPanel(
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tabsetPanel(id="tabs",
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tabPanel("Plot and models",
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column(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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tabPanel("Tests and ANOVAA",
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column(12,
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h3("Tests for linear PLA:"),
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box(title="Suitability tests", status="primary",solidHeader = T, width=12,
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DTOutput("TESTSlin")),
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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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# 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("parameter estimates",
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htmlOutput("PureErrWParEst"),
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tags$head(tags$style("#PureErrWParEst{color: red;
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font-size: 16px;
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font_style: italic;}")),
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column(3,style = "background: #4FCBD922",
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br(),
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h4("Regression results restricted"),
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tableOutput("coeffs_r"),
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"Bend points restricted",
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tableOutput("bends_r2")),
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column(3,style = "background: #B5C74022",
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br(),
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h4("Regression results unrestricted"),
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tableOutput("coeffs_unr")),
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column(3,style = "background: #F9545422",
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h4("Regression results (ln-transformed)"),
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tableOutput("logcoeffs_r"),
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tableOutput("bends_unr2"),
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tableOutput("logcoeffs_unr"))
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),
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tabPanel("Report",
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h4("Settings for report"),
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downloadButton("downloadXLReport", label="Download 4PL PDF report", class="butt"),
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tags$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(title="4PL+linear reg",
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tabPanel("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(width=12,
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tabsetPanel(id="tabs",
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tabPanel("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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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(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,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,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,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,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,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(8,
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box(title = "Simulated data per log-concentration", status="warning",solidHeader = T, width=12, "incl. mean, sd and CV%",
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DT::dataTableOutput("ConctabMeta")),
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verbatimTextOutput("logdil"))
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#)
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),
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#### 4pl fits ----
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tabPanel("4pl-fit",
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wellPanel(
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fluidRow(
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column(10,
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htmlOutput("PureErrW4plMeta"),
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tags$head(tags$style("#PureErrW4plMeta{color: red;
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font-size: 16px;
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font_style: italic;}")),
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plotOutput("plot4plMeta", width = "80%"),
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DTOutput("pottab4pl"),
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"Footnote: test performed on relative CIs.",
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DTOutput("EQtests4pl"), # SSTs
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h5("*...The estimate for F-test on regression and on non-linearity is the p-value"),
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h5("F-test on regression passes if F-value > F-crit and thus p < 0.05"),
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h5("F-test on non-linearity passes if F-value < F-crit and thus p > 0.05"),
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h5("Test results outcome: 0 ... test passed (for EQ tests: CI within limits);
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1 ... test failed (for EQ tests CI not within limits);
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-1 ... calculations unbound/denominator too close to 0"),
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#plotOutput("CIplot, height=50%")
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),
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column(8,
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"4 PL ANOVA unrestricted",
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box(title = "ANOVA unrestricted", status="warning",solidHeader = T, width=12, "",
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DT::dataTableOutput("ANOVA")),
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h5("Please note that for the CIs of rel. potency the RSS of the restricted model is used"),
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h5("RSS ... 'Residual error' in the SumSquares column"),
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h5("MSE ... 'Residual error' in the MeanSquaress column"),
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h5("SSE ... 'Pure error' in the SumSquares column"),
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h5("RMSE ... Square root of the 'Residual Error' in the MeanSquares column"),
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verbatimTextOutput("RMSE")
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)
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))
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),
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tabPanel("ln-transformed y",
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htmlOutput("PureErrWLogMeta"),
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tags$head(tags$style("#PureErrWLogMeta{color: red;
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font-size: 16px;
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font_style: italic;}")),
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h4("ln-transformed y-axis plots"),
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plotOutput("plot4plTransMeta", width = "80%"),
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DT::dataTableOutput("pottab4plTrans"),
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),
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tabPanel("linear regression",
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htmlOutput("PureErrW3"),
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h4("Evaluations from meta-data"),
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tags$head(tags$style("#PureErrW3{color: red;
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font-size: 16px;
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font_style: italic;}")),
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column(12,
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plotOutput("plotLinMeta"),
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|
"Delta method is used for potency CIs",
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DTOutput("pottabMeta")
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),
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column(5,
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h3("Tests for linear PLA:"),
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box(title="Suitability tests", status="primary",solidHeader = T,collapsible=T, width=12,
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DTOutput("TESTSlinMeta")),
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|
|
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 = T,collapsible=T, width=12,
|
|
tableOutput("SummaryModABuMeta")),
|
|
h4("Restricted linear model (CSSI):"),
|
|
box(title="Restricted linear model (CSSI):", status="primary",solidHeader = T,collapsible=T, width=12,
|
|
tableOutput("SummaryModABMeta"))
|
|
),
|
|
|
|
column(6,
|
|
|
|
h3("ANOVA for parallel line assay"),
|
|
box(title="ANOVA for simultated data", status="primary",solidHeader = T, collapsible=T, 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$style(type="text/css","#downloadXLReport {background-color: orange; color: black;font-family: COurier New}"),
|
|
)
|
|
)
|
|
)
|
|
#)
|
|
)
|
|
)
|
|
})
|
|
|
|
|
|
output$pla <- renderUI({
|
|
navbarPage(title="pla",
|
|
tabPanel("Analysis and Plots",
|
|
|
|
)
|
|
)
|
|
})
|
|
|
|
output$wizard <- renderUI({
|
|
navbarPage(title="Dilution setting",
|
|
tabPanel("Plots",
|
|
sidebarLayout(
|
|
sidebarPanel(
|
|
width=3,
|
|
fluidRow(
|
|
column(6,
|
|
numericInput("Limits",p("limit to be >", bsButton("q4",label="", icon=icon("info"), style="primary", size="extra-small")),
|
|
bsPopover(id="q4", title="", content="The calculated limits ...")))
|
|
)),
|
|
mainPanel(
|
|
tabsetPanel(id="tabs",
|
|
tabPanel("4pl",
|
|
box(title="ANOVA table", status="primary",solidHeader = T, width=12,
|
|
tableOutput("Anovatab")),
|
|
column(4,
|
|
h3("Confidence intervals"),
|
|
tableOutput("CIs"),
|
|
"The confidence interval table is interaactive for changes in: variability slider (%SD), potency of test-slider,
|
|
and 'Adjust the dilutions'-slider",
|
|
tableOutput("optimalDils"),
|
|
selectInput(inputId="scenario", label= "Select an 'optimal' scenario:", choices = c("scenario 2","scenario 3","scenario 6","steep slope"))),
|
|
column(5,
|
|
plotOutput("plotfordilutions"),
|
|
h4("in grey: most extreme bend point lines of theoretical samples with 50% and 200% potency"),
|
|
sliderInput("dilslider", "Adjust the dilutions(+-change in %)", min = -100,max=100, value=0, step=1, round=0),
|
|
checkboxInput("fixupper","Fix highest concentration (if unticked, the center is fixed)",FALSE),
|
|
h5("Dilution factors"),
|
|
tableOutput("adjlogdil"),
|
|
"Short guidance: wider dilution ranges increase the CIs of rel. potency, and decrease the CIs of upper and lower asymptote ratios, as well as Hill's slope ratios", br(),
|
|
"Narrower dilution ranges decrease the CIs of rel. potency, and increase the CIs of upper and lower asymptote ratios, ands Hill's slope ratios",),
|
|
column(3,
|
|
h3("Bend points"),
|
|
tableOutput("bps"),
|
|
tableOutput("extremebps"),
|
|
h4("Explanation of the plots")
|
|
)),
|
|
tabPanel("Report",
|
|
h4("Settings for report")
|
|
))
|
|
)
|
|
)))
|
|
})
|
|
|
|
#output$sessioninfo <- renderPrint(sessioninfo())
|
|
|
|
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$wb)) {
|
|
#browser()
|
|
cnSheets <- Dat$sheets
|
|
cnSheets2 <- c("please choose", cnSheets)
|
|
selectInput(inputId = "sheet", label="Select a sheet:",choices = cnSheets)
|
|
}
|
|
})
|
|
observeEvent(input$sign_out, {
|
|
unlink(input$iFile$datapath)
|
|
reset(id = "") # from shinyjs package
|
|
})
|
|
|
|
|
|
#### process XLSX file ----
|
|
observe({
|
|
if (!is.null(input$iFile)) {
|
|
if (!is.null(input$sheet)) {
|
|
if (input$sheet != "please choose") {
|
|
#browser()
|
|
|
|
Dat$RepIdentifier <- input$RepIdentifier
|
|
Dat$Author <- input$Author
|
|
Dat$NoP <- input$NoP
|
|
Dat$Assay <- input$Assay
|
|
|
|
|
|
XLdat <- Dat$wb[input$sheet][[1]]
|
|
if (is.null(XLdat)) XLdat <- Dat$wb[Dat$sheets[1]][[1]]
|
|
cn <- colnames(XLdat)
|
|
logI <- grep("log", 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("dilu|dose|Dose|Conc|conc",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_textParEst <- reactive({
|
|
ifelse(PureErrFlag, 'Pure Error is selected', '')
|
|
})
|
|
output$PureErrWParEst <- renderText(warning_textParEst())
|
|
|
|
REP$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
|
|
})
|
|
|
|
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$ANOVAXLS <- renderTable({ NULL })
|
|
#)
|
|
|
|
return(NULL)
|
|
}
|
|
}
|
|
|
|
Smr <- FITs[[1]] # summary(mr)
|
|
Smu <- FITs[[2]] # summary(mu)
|
|
coeffsMR <- Smr$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")
|
|
# browser()
|
|
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])
|
|
#browser()
|
|
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 REFr", "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]))
|
|
#browser()
|
|
#VCOVu <- vcov(mu)
|
|
V_Vu <- Smu$cov.unscaled
|
|
#VCOVpure <- V_Vu*meanPureErr
|
|
SEsPureU <- sqrt(diag(V_Vu)*meanPureErr)
|
|
potU_est <- data.frame(estimate=exp(coeffsMU[8]), lowerCI = exp(coeffsMU[8]-qt(0.975,DFsPure)*SEsPureU[8]),
|
|
upperCI = exp(coeffsMU[8]+qt(0.975,DFsPure)*SEsPureU[8]))
|
|
|
|
}
|
|
|
|
|
|
#browser()
|
|
Dat$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$lowerCI)
|
|
MaxPl_ <- MaxPl*1.2
|
|
MinPl_ <- MinPl*0.8
|
|
#browser()
|
|
p_relCI <- ggplot(data=pot_est3, aes(xmin=lowerCI, xmax=upperCI, y=1)) +
|
|
geom_linerange(size=4, col="darkseagreen",alpha=0.5) +
|
|
geom_point(aes(x=estimate, y=1), col="grey15", shape=13, size=10) +
|
|
geom_vline(xintercept = c(input$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
|
|
|
|
#browser()
|
|
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")
|
|
#browser()
|
|
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 = F)
|
|
|
|
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 = F), 3)
|
|
|
|
output$coeffs_unr <- renderTable({
|
|
UnRPLAausw
|
|
})
|
|
|
|
#browser()
|
|
UnRPLAausw2 <- data.frame(Dat$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$UnRPLAausw2 <- UnRPLAausw2
|
|
|
|
# browser()
|
|
coeffs_R <- coeffsMR # pot$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$bends_r2 <- renderTable({ bendsAll }, digits = 3, rownames = T)
|
|
|
|
REP$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
|
|
#browser()
|
|
|
|
|
|
|
|
if (exists("Ind")) {
|
|
Dat$dilution <- XLdat[,Ind]
|
|
} else Dat$dilution <- exp(XLdat[,logI])
|
|
|
|
##### Plot XL 4PL ----
|
|
output$XLplot <- renderPlot({
|
|
XLplot4pl <- plot_f(XLdat2, TransFlag=F)
|
|
REP$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$iFile
|
|
})
|
|
|
|
#### make geomDils reactive ----
|
|
observe({
|
|
#browser()
|
|
if (is.null(input$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$MetaConc
|
|
} else Conc <- CONC()
|
|
logdilu <-log(Conc)
|
|
logdilu
|
|
})
|
|
|
|
|
|
#### reactive dataset sim ----
|
|
|
|
sim <- reactive({
|
|
#browser()
|
|
if(is.null(sigmoid())) return(NULL)
|
|
sd_fac_ <- as.numeric(input$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$MetaConc else Conc <- CONC()
|
|
log_conc <- log(Conc)
|
|
av_test <- as + (ds-as)/(1+exp(bs*(cs - log_conc)))
|
|
av_ref <- at + (dt-at)/(1+exp(bt*(ct - log_conc)))
|
|
#browser()
|
|
if (!is.na(input$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$PureErrW4plMeta <- renderText(warning_text3())
|
|
|
|
sigmoid <- sigmoid()
|
|
det_sig=NULL
|
|
plot_f(sim2(), TransFlag = F)
|
|
})
|
|
|
|
#### Plot 4pl Meta Transformed ----
|
|
output$plot4plTransMeta <- renderPlot({
|
|
PureErrFlag <- input$PureErrMeta
|
|
warning_text3 <- reactive({
|
|
ifelse(PureErrFlag, 'Pure error selected','')
|
|
})
|
|
|
|
output$PureErrWLogMeta <- renderText(warning_text3())
|
|
#browser()
|
|
sigmoid <- sigmoid()
|
|
det_sig=NULL
|
|
plot_f(sim2(), TransFlag = T)
|
|
})
|
|
|
|
|
|
#### Testergebnisse für 4PL Meta ----
|
|
observe({
|
|
if (is.null(sim2())) return(NULL)
|
|
if (is.null(input$PureErrMeta)) return(NULL)
|
|
#observeEvent(input$StartCalc,{
|
|
PureErrFlag <- input$PureErrMeta
|
|
warning_text3 <- reactive({
|
|
ifelse(PureErrFlag, 'Pure error selected','')
|
|
})
|
|
|
|
#browser()
|
|
output$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$limite <- Limite
|
|
#browser()
|
|
|
|
tab <- tests_FUNC(sim2(), Limite, PureErrFlag = PureErrFlag)
|
|
if (length(tab)>1) {
|
|
tab[1,6:7] <- c("-","-")
|
|
Dat$tests_FUNC <- tab
|
|
REP$testsTab <- tab
|
|
tab2 <- tab[1:7,]
|
|
|
|
dat <- datatable(tab2, rownames=F, options = list(
|
|
paging=TRUE,
|
|
dom="t",
|
|
rownames=FALSE
|
|
)) %>% formatStyle("test_results",
|
|
target='row',
|
|
backgroundColor = styleEqual(c(-1,0,1),
|
|
c("pink",'lightgreen','lightgrey')))
|
|
} else { dat <- datatable(data.frame(test_results = "Convergeance failed for the uploaded dataset")) }
|
|
#browser()
|
|
output$EQtests4pl <- renderDT({ dat})
|
|
|
|
}) # observe
|
|
|
|
#### Testergebnisse 4PL für XLSX ----
|
|
observe({
|
|
if (is.null(Dat$EXCEL)) return(NULL)
|
|
if (is.null(input$PureErr)) return(NULL)
|
|
if (!is.null(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$limite <- Limite
|
|
#browser()
|
|
SelTests <- as.numeric(input$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=T,
|
|
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=T,
|
|
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=T,
|
|
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$EXCEL
|
|
|
|
# tab <- sim2()
|
|
if (is.character(tab)) stop(tab)
|
|
#browser()
|
|
log_conc <- tab$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
|
|
#browser()
|
|
sigmoid <- Dat$coeffsMUnr
|
|
|
|
pLin <- PlotLinPLA_FUNC(circle, sigmoid = sigmoid, all_l2, pl_df, indS, indT)
|
|
REPlin$pLin <- pLin
|
|
|
|
pLin
|
|
})
|
|
|
|
#### process metadata, Plot output ----
|
|
output$plotLinMeta <- renderPlot({
|
|
tab <- sim2()
|
|
|
|
if(is.null(tab)) return(NULL)
|
|
if (is.character(tab)) stop(tab)
|
|
#browser()
|
|
if (!is.na(Dils()[4])) noDilSer <- Dils()[4] else noDilSer = (ncol(tab)-1)/2
|
|
Conc <- CONC()
|
|
log_conc <- log(Conc)
|
|
Conctab <- perConcTab(tab, noDilSer)
|
|
if (!is.na(Dils()[3])) noDil <- Dils()[3] else noDil = length(Conc)
|
|
|
|
slopeSt <- slopeTe <- matrix(NA, nrow=noDil-2,ncol=2)
|
|
for (i in 1:(noDil-2)) {
|
|
avs <- Conctab[noDilSer+1,]
|
|
threes <- data.frame(lnC=log(Conc[i:(i+2)]), resp=avs[i:(i+2)])
|
|
lm3St <- lm(resp ~ lnC, data=threes)
|
|
slopeSt[i,] <- lm3St$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()
|
|
#browser()
|
|
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$PureErrW <- renderText(warning_text())
|
|
#browser()
|
|
LIN <- ANOVAlintests(tab,circlesMeta,Limite,PureErrFlag=PureErrFlag)
|
|
df <- LIN[[1]]
|
|
su_modU <- LIN[[2]]
|
|
su_mod2 <- LIN[[4]]
|
|
|
|
output$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=T, dom="t",rownames=F
|
|
)) %>% 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),
|
|
as.numeric(input$lEACratioAdiff), as.numeric(input$uEACratioAdiff))
|
|
|
|
noDil <- nrow(tab)
|
|
noDilSer <- Dat$noDilSeriesXL
|
|
Conctab <- perConcTab(tab, noDilSeries = noDilSer)
|
|
#browser()
|
|
slopeSt <- slopeTe <- matrix(NA, nrow=noDil-2,ncol=2)
|
|
for (i in 1:(noDil-2)) {
|
|
avs <- Conctab[noDilSer+1,]
|
|
threes <- data.frame(lnC=log(Conc[i:(i+2)]), resp=avs[i:(i+2)])
|
|
lm3St <- lm(resp ~ lnC, data=threes)
|
|
slopeSt[i,] <- lm3St$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$PureErrW3 <- renderText(warning_text())
|
|
#browser()
|
|
LIN <- ANOVAlintests(tab,circle,Limite,PureErrFlag=PureErrFlag)
|
|
df <- LIN[[1]]
|
|
su_modU <- LIN[[2]]
|
|
su_mod2 <- LIN[[4]]
|
|
|
|
output$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$ANOVA <- df[,4:length(df)]
|
|
dat <- datatable(df2[,1:3],
|
|
options=list(
|
|
paging=T, dom="t",rownames=F
|
|
)) %>% formatStyle("test_results", target="row",backgroundColor = styleEqual(c(-1,0,1),
|
|
c("pink","lightgreen","lightgrey")))
|
|
output$TESTSlin <- DT::renderDataTable({
|
|
dat
|
|
})
|
|
})
|
|
|
|
#### output 4PL ANOVA tests Meta ----
|
|
output$ANOVA <- DT::renderDataTable({
|
|
sigmoid <- sigmoid()
|
|
tab <- ANOVA4plUnresfunc(sim2()) # ,sigmoid
|
|
dat <- datatable(tab,
|
|
options=list(
|
|
dom="t",rownames=F
|
|
)) %>% formatStyle("p_value", target="row",
|
|
backgroundColor = styleEqual(c("p_value"),
|
|
c("lightgrey")))
|
|
})
|
|
|
|
#### output 4PL ANOVA tests XL ----
|
|
# not needed
|
|
# output$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=F
|
|
)) %>% 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=F
|
|
)) %>% 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=F
|
|
)) %>% 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$upperPot))
|
|
#browser()
|
|
circles <- Dat$circlesMeta
|
|
PureErrFlag <- input$PureErrMeta
|
|
pottab <- LinPotTab(circles,Lim,PureErrFlag = PureErrFlag)
|
|
#browser()
|
|
dat <- datatable(pottab,
|
|
options=list(
|
|
dom="t",rownames=F
|
|
)) %>% formatStyle("test_result", target='row',
|
|
backgroundColor = styleEqual(c(0,1), c("#B5C74055","#F9545488")))
|
|
})
|
|
|
|
#### 4pl potency table Meta ----
|
|
observe({
|
|
#browser()
|
|
if (is.null(sim2()) | is.null(Dils())) return(NULL)
|
|
ro_new <- sim2()
|
|
Dils_ <- Dils()
|
|
if (!is.na(Dils()[4])) noDilSer <- Dils()[4] else noDilSer <- 3
|
|
PureErrFl <- input$PureErrMeta
|
|
pottab4 <- pot4plFUNC(ro_new = ro_new, PureErrFlag = PureErrFl)
|
|
#browser()
|
|
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=T, dom="t",rownames=F
|
|
)) %>% formatStyle("test_result", target="row",backgroundColor = styleEqual(c(0,1),
|
|
c("lightgreen","pink")))
|
|
})
|
|
output$pottab4plTrans <- DT::renderDataTable({
|
|
dat <- datatable(pottab4_[3:4,],
|
|
options=list(digits=3,
|
|
paging=T, dom="t",rownames=F
|
|
)) %>% formatStyle("test_result", target="row",backgroundColor = styleEqual(c(0,1),
|
|
c("lightgreen","pink")))
|
|
})
|
|
})
|
|
|
|
#### 4pl potency table XL ----
|
|
observe({
|
|
#browser()
|
|
if (is.null(Dat$EXCEL)) return(NULL)
|
|
if (!is.null(Dat$FITsFlag)) return(NULL)
|
|
ro_new <- Dat$EXCEL
|
|
|
|
noDilSer <- Dat$noDilSeriesXL
|
|
PureErrFl <- input$PureErr
|
|
pottab4 <- pot4plFUNC(ro_new = ro_new, PureErrFlag = PureErrFl)
|
|
#browser()
|
|
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 <- 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")
|
|
row.names(pottab4_) <- NULL
|
|
REP$pottab4plXL <- pottab4_[1:2,]
|
|
|
|
output$pottab4plXL <- DT::renderDataTable({
|
|
dat <- datatable(pottab4_[1:2,],rownames=F,
|
|
options=list(digits=3,
|
|
paging=T, dom="t"
|
|
)) %>% formatStyle("test_result", target="row",backgroundColor = styleEqual(c(0,1),
|
|
c("#B5C74055","#F9545455")))
|
|
})
|
|
output$pottab4plTransXL <- DT::renderDataTable({
|
|
dat <- datatable(pottab4_[3:4,],rownames=F,
|
|
options=list(digits=3,
|
|
paging=T, dom="t"
|
|
)) %>% formatStyle("test_result", target="row",backgroundColor = styleEqual(c(0,1),
|
|
c("#B5C74055","#F9545455")))
|
|
})
|
|
})
|
|
|
|
|
|
#### Dilutions Simulator ----
|
|
output$plotfordilutions <- renderPlot({
|
|
tab <- sim2()
|
|
#browser()
|
|
tab <- as.data.frame(tab)
|
|
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$newDils <- dils2
|
|
|
|
sigmoid <- sigmoid()
|
|
|
|
#browser()
|
|
BPs <- Dat$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 {
|
|
|
|
#browser()
|
|
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)
|
|
|
|
#browser()
|
|
# scenario2
|
|
eqSpac <- abs((BPs[1]-BPs[2])/5)
|
|
optdils <- c((asyml+BPs[1])/2, BPs[1], BPs[1]+1*eqSpac, BPs[1]+2*eqSpac,BPs[1]+3*eqSpac,BPs[1]+4*eqSpac,BPs[2], (asymu+BPs[2])/2)
|
|
# scenario 3
|
|
eqSpac_3 <- abs((BPs[1]-BPs[2])/3)
|
|
optdils_3 <- c(BPs[1]-2*eqSpac_3, BPs[1]-eqSpac_3, BPs[1], BPs[1]+1*eqSpac_3, BPs[1]+2*eqSpac_3,BPs[2], BPs[2]+eqSpac_3, BPs[2]+2*eqSpac_3)
|
|
# scenario 6
|
|
Einh2 <- abs(((BPs[2]-BPs[1])*0.7)/5)
|
|
eqSpac2 <- (2*0.7/Einh)/3
|
|
optdils2 <- c((asyml+BPs[1])/2, BPs[1], EC50REF-1.5*Einh2, EC50REF-0.5*Einh2,EC50REF+0.5*Einh2,EC50REF+1.5*Einh2, BPs[2], (asymu+BPs[2])/2)
|
|
# steep slope
|
|
eqSpac3 <- (abs(Xbend200-Xbend50))/5
|
|
optdils3 <- c(Xbend200-eqSpac3,Xbend200, Xbend200+1*eqSpac3, Xbend200+2*eqSpac3,Xbend200+3*eqSpac3,Xbend200+4*eqSpac3,Xbend50, Xbend50+eqSpac3)
|
|
|
|
output$extremebps <- renderTable({
|
|
ExtremeBPs <- c(Xbend50,Xbend200)
|
|
DF2 <- data.frame(sample=c("50% sample (right)", "200% sample (left)"), Extreme_BPs=ExtremeBPs)
|
|
DF2
|
|
})
|
|
|
|
optD <- data.frame(cbind(optdils, optdils_3,optdils2, optdils3))
|
|
colnames(optD) <- c("scenario2","scenario3","scenario6","steep slope")
|
|
|
|
output$optimalDils <- renderTable({ optD })
|
|
|
|
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)
|
|
#browser()
|
|
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$heterosked) {
|
|
# heterosc noise
|
|
ro_jit <- matrix(unlist(map(av, function(x) x+rnorm(1,0,x*sd_fac_/100))), nrow=noDil, ncol=noDilSer*2)
|
|
} else {
|
|
# homosc noise
|
|
ro_jit <- matrix(unlist(map(av, function(x) x+rnorm(1,0,sd_fac_*yAxfac/100))), nrow=noDil, ncol=noDilSer*2)
|
|
}
|
|
# browser()
|
|
ro_jit <- abs(ro_jit)
|
|
ro_new <- cbind(ro_jit, log_dose)
|
|
all_l <- melt(data.frame(ro_new), id.vars="log_dose", variable.name = "replname", value.name = "readout")
|
|
all_l$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=F)
|
|
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=F)
|
|
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=F)
|
|
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))
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|
} # withProgress
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|
|
|
})
|
|
end.time2 <- Sys.time()
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|
|
|
Dat$resHist <- resHist
|
|
})
|
|
})
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|
|
|
|
|
#### simulation Histograms output ----
|
|
|
|
output$plotHistuAs <- renderPlot({
|
|
if (!is.null(Dat$resHist)) {
|
|
|
|
resHist <- Dat$resHist
|
|
#browser()
|
|
resHistuAs <- as.data.frame(resHist[,8:10])
|
|
resHistuAs_l <- melt(data.frame(resHistuAs), variable.name="ratio_CIs", value.name = "readout")
|
|
#browser()
|
|
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)
|
|
#browser()
|
|
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----
|
|
|
|
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,"logo.png")
|
|
file.copy("logo.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$nameRep ,".pdf"),
|
|
|
|
content = function(file) {
|
|
tpdr <- tempdir()
|
|
tempReport <- file.path(tpdr,"Doc_BioassayLinReport.Rmd")
|
|
file.copy("Doc_BioassayLinReport.Rmd", tempReport, overwrite = T)
|
|
|
|
tempReportc <- file.path(tpdr,"logo.png")
|
|
file.copy("logo.png", tempReportc, overwrite = T)
|
|
|
|
rmarkdown::render(tempReport, output_file = file,
|
|
params = list(FileName = Dat$FileName,
|
|
author = Dat$Author,
|
|
REP = REP,
|
|
REPlin = REPlin,
|
|
coeffsLin = Dat$coeffs_UN),
|
|
envir = new.env(parent = globalenv()))
|
|
|
|
}
|
|
)
|
|
}
|
|
|
|
shinyApp(ui, server)
|