library(shiny)
shinyUI(pageWithSidebar(
headerPanel(title="mixADA: Cutpoint selection by mixture models and prediction intervals", windowTitle="mixADAsimple" ),
sidebarPanel(
h3("Data import"),
fileInput(inputId="datafile", label="Upload a csv-file with columns separated by comma (,) and decimal points (.)", multiple=FALSE),
# h3("Normalization"),
h4(textOutput(outputId="plsselect")),
uiOutput("response"),
uiOutput("treatment"),
# uiOutput("tfornormalization"),
uiOutput("tforfitting"),
uiOutput("sampleID"),
# selectInput(inputId="normop", label="Normalization of samples:", choices=c("log-transform data and substract" = "logdiff", "substract" = "diff", "divide by" = "ratio")),
uiOutput("runsnorm"),
checkboxInput(inputId="logtransform", label="Log-transform data before analysis", value=FALSE),
h3("SCP: Random effects mixture model"),
radioButtons(inputId="ranef", label="Random effects in 2-component mixture model:",
choices=c( "Both, equal random effects & equal residual variance" = "bothranres",
"Equal random effects, different residual variance" = "ran",
"Equal residual variance, different random effects" = "res",
"Both, different random effects & different residual variance" = "no")),
# h4("Select variables for model fitting:")
uiOutput("runsmodel"),
selectInput(inputId="design", label="Structure of effects",
choices=c("Runs crossed with samples" = "c1",
# "Repeated runs per sample" = "h1",
"Simplified: pool over runs" = "y")),
numericInput(inputId="level", label="Level of prediction limits or quantiles", value=0.95, min=0, max=1),
selectInput(inputId="aggfun", label="Function for aggregation", choices=c("mean","median")),
checkboxInput(inputId="fitmodel", label="Start model fitting (needs some time)", value=FALSE),
checkboxInput(inputId="showsampleIDNR", label="Show biological samples classified as nonresponders", value=FALSE),
# # # # isolate(submitButton(text = "(Re)start model fitting"))
h3("CCP estimation"),
uiOutput("tspiked"),
radioButtons(inputId="ccpmeasure", label="Compute CCP for", choices=c( "Percent inihibition" = "percinhib", "Ratio spiked/unspiked" = "ratio")),
numericInput(inputId="ccplevel", label="Level of quantiles for CCP", value=0.99, min=0, max=1),
checkboxInput(inputId="computeccp", label="Compute CCP", value=FALSE),
# end of sidebarpanel:
width=3
),
mainPanel(
h4("This is free software and comes with ABSOLUTELY NO WARRANTY!"),
# h3(textOutput(outputId="propplotheader")),
# plotOutput(outputId="propplot"),
# textOutput(outputId="cappropplot"),
h3(textOutput(outputId="normalizationheader")),
plotOutput(outputId="normalizationplot"),
textOutput(outputId="namessage"),
textOutput(outputId="normalizationinfo"),
h3(textOutput(outputId="scpheader")),
h4(textOutput(outputId="classpredintcap")),
plotOutput(outputId="classpredintplot"),
plotOutput(outputId="classpredinthist"),
plotOutput(outputId="classpredinthistpooled"),
h4(textOutput(outputId="diagnosticcap")),
plotOutput(outputId="diagnosticplot"),
textOutput(outputId="notepredintplot"),
h4(textOutput(outputId="flexmixtabcap")),
tableOutput(outputId="flexmixtab"),
textOutput(outputId="sampleIDNR"),
h4(textOutput(outputId="boxcoxheader")),
tableOutput(outputId="boxcoxtab"),
textOutput(outputId="boxcoxtabcap"),
tableOutput(outputId="boxcoxtest"),
textOutput(outputId="boxcoxtestcap"),
h4(textOutput(outputId="predinttabcap")),
tableOutput(outputId="predinttab"),
textOutput(outputId="predinttabsub"),
h3(textOutput(outputId="ccpheader")),
plotOutput(outputId="classCCPplot"),
plotOutput(outputId="classCCPhist"),
plotOutput(outputId="classCCPhistpooled"),
h4(textOutput(outputId="ccptabcap")),
tableOutput(outputId="ccptab"),
textOutput(outputId="ccptabsub")
)))
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