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ui.R
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ui.R
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shinyUI(pageWithSidebar(
titlePanel("easyROC: a web-tool for ROC curve analysis (ver. 1.3.1)"),
# Left-side panel, including options and inputs for each tab.
sidebarPanel(width = 3,
conditionalPanel(condition="input.tabs1=='Introduction'",
tags$p(
tags$img(src = "multi.png", width = 300, height = 300)
),
tags$head(
includeScript("js/google-analytics.js")
)
),
# Tab: Data Upload
conditionalPanel(condition="input.tabs1 == 'Data upload'",
# h4("Input data"),
#radioButtons("dataInput", "", list("Load example data"=1, "Upload a file"=2, "Paste your data"=3), selected=1),
radioButtons("dataInput", "", list("Load example data" = 1, "Upload a file" = 2), selected = 1),
conditionalPanel(condition = "input.dataInput == '1'",
#HTML('<br>'),
h5(tags$b("Datasets:")),
radioButtons("sampleData", "",
list("Mayo data (n=312, p=4)" = 1, "PBC data set (n=418, p=20)" = 2),
selected = 1),
tags$p(tags$b('n:'), ' number of observations'),
HTML('<p><b>p</b>: number of variables</p>')
),
conditionalPanel(condition = "input.dataInput == '2'",
HTML('<br>'),
h5("Upload a delimited text file (max. 30MB): "),
#HTML('<i class="fa fa-beer fa-lg"></i>'),
fileInput("upload", "", multiple = FALSE),
radioButtons("fileSepDF", "Delimiter:",
list("Comma" = 1, "Tab" = 2, "Semicolon" = 3, "Space" = 4),
selected = 2),
conditionalPanel(condition = "input.fileSepDF != '1'",
checkboxInput(inputId = "decimal", label = "Use comma as decimal", value = FALSE)
),
HTML('<br>'),
HTML('<p>You can upload your data separated by comma, tab, semicolon or space.</p>'),
HTML('<p><b>Note</b>: First row must be the header including the variable names.</p>')
),
conditionalPanel(condition = "input.dataInput == '3'",
h5("Paste or enter your data below:"),
tags$textarea(id = "myData", rows = 10, cols = 5, ""),
actionButton('clearText_button','Clear data'),
HTML('<br>'),
HTML('<br>'),
radioButtons("fileSepP", "Separator:",
list("Comma" = 1, "Tab" = 2, "Semicolon" = 3),
selected = 2),
HTML('<p>You can paste or manually enter your data as separated by comma, tab or semicolon.</p>'),
HTML('<p>Note: First row must be header.</p>')
),
HTML('<br>'),
selectizeInput("statusVar", "Select status variable", choices = NULL, multiple = FALSE),
selectizeInput("valueStatus", "Select category for cases", choices = NULL, multiple = FALSE)
), # End for Data Upload tab.
# Tab: ROC Curve
conditionalPanel(condition = "input.tabs1 == 'ROC curve'",
selectizeInput("markerInput", "Select markers (*)", choices = NULL, multiple = TRUE),
checkboxInput("lowhigh", "Higher values indicate risks", TRUE),
HTML('<br>'),
helpText("(*) Multiple markers are allowed."),
HTML('<br>'),
conditionalPanel(condition = "input.navbarROCcurve == 'Multiple Comparisons'",
selectInput(inputId = "MultipleCompMethod", label = "Multiple Comparison Method", selected = "bonferroni",
choices = c("Bonferroni" = "bonferroni", "False discovery rate" = "fdr", "None" = "none")),
HTML('<br>')
),
checkboxInput(inputId = "advanced", label = "Advanced options", value = FALSE),
# Use this to add vertical spaces.
conditionalPanel(condition = "input.advanced",
## Use this code block to add bold label.
tags$style('.bottom-three {
margin-bottom: 1.2em;
font-weight: bold
}'),
tags$p(class = "bottom-three", ""),
radioButtons(inputId = "rocEstimationType", label = "Select a method for curve fitting",
choices = list("Nonparametric" = "nonParametricROC", "Parametric" = "parametricROC"),
selected = "nonParametricROC"),
# Non parametric ROC curve
conditionalPanel(condition = "input.rocEstimationType == 'nonParametricROC'",
radioButtons(inputId = "StdErr", label = "1. Select a method for SE estimation",
choices = list("Mann-Whitney" = "MW", "DeLong(1988)[+]" = "DeLong",
"Under Null Hyp." = "Null", "Binomial" = "Binomial"),
selected = "DeLong"),
radioButtons(inputId = "ConfInt", label = "2. Select a method for Conf. Interval",
choices = list("Mann-Whitney" = "MW", "DeLong(1988)[+]" = "DeLong",
"Under Null Hyp." = "Null", "Binomial Exact" = "Exact"),
selected = "DeLong"),
numericInput(inputId = "alpha", label = "Type I error", value = 0.05, min = 0, max = 1, step = 0.01),
tags$br(),
helpText("[+]: Default options."),
tags$br()
),
# Parametric ROC Curve.
conditionalPanel(condition = "input.rocEstimationType == 'parametricROC'",
radioButtons(inputId = "ConfIntParametric", label = "1. Select a method for Conf. Interval",
choices = list("Asymptotic [+]" = "asymptotic", "Exact" = "Exact"), selected = "asymptotic"),
numericInput(inputId = "alphaParametric", label = "Type I error", value = 0.05, min = 0, max = 1, step = 0.01),
HTML('<br>'),
HTML('<br>'),
helpText("[+]: Default options."),
HTML('<br>')
)
),
checkboxInput(inputId = "ROCplotOpts", label = "Plot options", value = FALSE),
conditionalPanel(condition = "input.ROCplotOpts",
fluidRow(
column(6, sliderInput("myheight", "Plot height:", value = 400, min = 200, max = 1200)),
# column(2),
column(6, sliderInput("mywidth", "Plot width:", value = 400, min = 200, max = 1200 ))
),
HTML('<br>'),
fluidRow(
column(12, selectizeInput("fontfamilyRC", "Font family",
choices = c("Times New Roman" = "serif",
"Arial" = "sans",
"Corier New" = "mono"),
selected = "sans"))
),
HTML('<br>'),
selectizeInput("subGrpsRC", "", choices = c("Edit x-axis" = "xAxis",
"Edit y-axis" = "yAxis",
"Other options" = "others"),
selected = "xAxis"),
conditionalPanel(condition = "input.subGrpsRC == 'others'",
fluidRow(
column(6, textInput("mainRC", "Graph title", "ROC Curve")),
# column(1),
column(6, selectizeInput("font.mainRC", "Title font", choices = c("Regular" = "1",
"Bold" = "2",
"Italic" = "3",
"Bold Italic" = "4"),
selected = "2"))
),
fluidRow(
column(6, textInput("col.mainRC", "Title color", "black")),
# column(1),
column(6, numericInput("cex.mainRC", "Title size", min=0.1, max=5, value = 1.2, step = 0.1))
),
fluidRow(
column(6, textInput("ROCcolRC", "ROC line color", value = "")),
# column(1),
column(6, selectizeInput("ROCltyRC", "ROC line type",
choices = c("\U2500\U2500\U2500\U2500\U2500\U2500\U2500" = "1",
"\U2574 \U2574 \U2574 \U2574 \U2574 \U2574" = "2",
"\U00B7 \U00B7 \U00B7 \U00B7 \U00B7 \U00B7 \U00B7 \U00B7 \U00B7" = "3",
"\U2574 \U00B7 \U2574 \U00B7 \U2574 \U00B7 \U2574" = "4",
"\U2500 \U2500 \U2500 \U2500 \U2500" = "5",
"\U2500 \U2574 \U2500 \U2574 \U2500 \U2574" = "6"),
selected = "1"))
),
textInput(inputId = "legend.namesRC", label = "Legend names", value = "")
),
conditionalPanel(condition = "input.subGrpsRC == 'xAxis'",
h5('X-axis options:'),
## X axis label options
fluidRow(
column(6, textInput("xlabRC", "Axis label", "1-Specificity")),
# column(1),
column(6, selectizeInput("xfont.labRC", "Label font", choices = c("Regular" = "1", "Bold" = "2",
"Italic" = "3", "Bold Italic" = "4"),
selected = "1"))
),
fluidRow(
column(6, textInput("xcol.labRC", "Label color", "black")),
# column(1),
column(6, numericInput("xcex.labRC", "Label size", min = 0.1, max = 5, value = 1, step = 0.1))
),
## X axis annotation options
fluidRow(
column(6, textInput("xcol.axisRC", "Annotation color", "black")),
# column(1),
column(6, numericInput("xcex.axisRC", "Annotation size", min = 0.1, max = 5, value = 1, step = 0.1))
)
#fluidRow(
# column(5, textInput("xcol11", "Axis color", "black")),
# column(1),
# column(5, textInput("xcol.ticks11", "Tickmarks color", "black"))
#),
),
conditionalPanel(condition = "input.subGrpsRC == 'yAxis'",
h5('Y-axis options:'),
## Y axis label options
fluidRow(
column(6, textInput("ylabRC", "Axis label", "Sensitivity")),
# column(1),
column(6, selectizeInput("yfont.labRC", "Label font", choices = c("Regular" = "1", "Bold" = "2",
"Italic" = "3", "Bold Italic" = "4"),
selected = "1"))
),
fluidRow(
column(6, textInput("ycol.labRC", "Label color", "black")),
# column(1),
column(6, numericInput("ycex.labRC", "Label size", min=0.1, max=5, value = 1, step = 0.1))
),
## Y axis annotation options
fluidRow(
column(6, textInput("ycol.axisRC", "Annotation color", "black")),
# column(1),
column(6, numericInput("ycex.axisRC", "Annotation size", min=0.1, max=5, value = 1, step = 0.1))
)
)
),
conditionalPanel(condition = "input.navbarROCcurve == 'Partial AUC'",
checkboxInput(inputId = "partialAUC", label = "Partial AUC", value = TRUE),
conditionalPanel(condition = "input.partialAUC",
fluidRow(
column(6, numericInput("pointA", "Value 1", min=0, max=1, value = 0.5, step = 0.1)),
# column(1),
column(6, numericInput("pointB", "Value 2", min=0, max=1, value = 1, step = 0.1))
),
selectizeInput("sensSpec", "Select a measure", choices = c("Sensitivity", "Specificity"), multiple = FALSE, selected = "Sensitivity")
)
)
), ## End of Roc Curve Tab
conditionalPanel(condition="input.tabs1=='Cut points'",
h5("1. Select a marker"),
selectizeInput("cutoffMarker", "", choices = NULL, multiple = FALSE),
HTML('<br>'),
h5("2. Select a method for optimal cut-off (*)"),
selectizeInput("cutOffMethods", "",
choices = c("Youden", "CB", "MCT", "MinValueSp", "MinValueSe", "ValueSe", "ValueSp", "MinValueSpSe",
"MaxSp", "MaxSe", "MaxSpSe", "MaxProdSpSe", "ROC01", "SpEqualSe", "MaxEfficiency",
"Minimax", "MaxDOR", "MaxKappa", "MinValueNPV", "MinValuePPV", "ValueNPV", "ValuePPV",
"MinValueNPVPPV", "PROC01", "NPVEqualPPV", "MaxNPVPPV", "MaxSumNPVPPV", "MaxProdNPVPPV",
"ValueDLR.Negative", "ValueDLR.Positive", "MinPvalue", "ObservedPrev", "MeanPrev",
"PrevalenceMatching"),
multiple = FALSE),
conditionalPanel(condition="input.cutOffMethods=='Youden'",
HTML('<p><b>Youden:</b> Youden index</p>'),
HTML('<br>'),
numericInput(inputId = "CFP_Youden", label = "Cost of a False Positive", value = 1, min = 0, max = 9999999),
numericInput(inputId = "CFN_Youden", label = "Cost of a False Negative", value = 1, min = 0, max = 9999999),
checkboxInput(inputId = "generalized_Youden", label = "Generalized Youden Index", value = FALSE),
checkboxInput(inputId = "costs_benefits_Youden", label = "Cost-benefit based Youden Index", value = FALSE)
),
conditionalPanel(condition="input.cutOffMethods=='CB'",
HTML('<p><b>CB:</b> cost-benefit method</p>'),
HTML('<br>'),
numericInput(inputId = "costs_ratio", label = "Cost ratio", value = 1, min = 0, max = 99999999)
),
conditionalPanel(condition="input.cutOffMethods=='MCT'",
HTML('<p><b>MCT:</b> minimizes misclassification cost term</p>'),
HTML('<br>'),
numericInput(inputId = "CFP_MCT", label = "Cost of a False Positive", value = 1, min = 0, max = 9999999),
numericInput(inputId = "CFN_MCT", label = "Cost of a False Negative", value = 1, min = 0, max = 9999999)
),
conditionalPanel(condition="input.cutOffMethods=='MinValueSp'",
HTML('<p><b>MinValueSp:</b> a minimum value set for specificity</p>'),
HTML('<br>'),
numericInput(inputId = "valueSp_MVSp", label = "Value of Specificity", value = 0.85, min = 0, max = 1, step = 0.01)
),
conditionalPanel(condition="input.cutOffMethods=='MinValueSe'",
HTML('<p><b>MinValueSe:</b> a minimum value set for sensitivity</p>'),
HTML('<br>'),
numericInput(inputId = "valueSe_MVSe", label = "Value of Sensitivity", value = 0.85, min = 0, max = 1, step = 0.01)
),
conditionalPanel(condition="input.cutOffMethods=='ValueSe'",
HTML('<p><b>ValueSe:</b> a value set for sensitivity</p>'),
HTML('<br>'),
numericInput(inputId = "valueSe_VSe", label = "Value of Sensitivity", value = 0.85, min = 0, max = 1, step = 0.01)
),
conditionalPanel(condition="input.cutOffMethods=='ValueSp'",
HTML('<p><b>ValueSp:</b> a value set for specificity</p>'),
HTML('<br>'),
numericInput(inputId = "valueSp_VSp", label = "Value of Specificity", value = 0.85, min = 0, max = 1, step = 0.01)
),
conditionalPanel(condition="input.cutOffMethods=='MinValueSpSe'",
HTML('<p><b>MinValueSpSe:</b> a minimum value set for specificity and sensitivity</p>'),
HTML('<br>'),
numericInput(inputId = "valueSe_MVSpSe", label = "Value of Sensitivity", value = 0.85, min = 0, max = 1, step = 0.01),
numericInput(inputId = "valueSp_MVSpSe", label = "Value of Specificity", value = 0.85, min = 0, max = 1, step = 0.01),
checkboxInput(inputId = "maxSp_MVSpSe", label = "Maximum specificity", value = TRUE)
),
conditionalPanel(condition="input.cutOffMethods=='MaxSp'",
HTML('<p><b>MaxSp:</b> maximizes specificity</p>')
),
conditionalPanel(condition="input.cutOffMethods=='MaxSe'",
HTML('<p><b>MaxSe:</b> maximizes sensitivity</p>')
),
conditionalPanel(condition="input.cutOffMethods=='MaxSpSe'",
HTML('<p><b>MaxSpSe:</b> maximizes sensitivity and specificity simultaneously</p>')
),
conditionalPanel(condition="input.cutOffMethods=='MaxProdSpSe'",
HTML('<p><b>MaxProdSpSe:</b> maximizes the product of sensitivity and specificity or accuracy area</p>')
),
conditionalPanel(condition="input.cutOffMethods=='ROC01'",
HTML('<p><b>ROC01:</b> minimizes distance between ROC plot and point (0,1)</p>')
),
conditionalPanel(condition="input.cutOffMethods=='SpEqualSe'",
HTML('<p><b>SpEqualSe:</b> sensitivity = specificity</p>')
),
conditionalPanel(condition="input.cutOffMethods=='MaxEfficiency'",
HTML('<p><b>MaxEfficiency:</b> maximizes efficiency or accuracy, similar to minimize error rate </p>'),
HTML('<br>'),
checkboxInput(inputId = "costs_benefits_Efficiency", label = "Cost-benefit based Efficiency", value = FALSE),
checkboxInput(inputId = "standard_deviation_accuracy", label = "Standart deviation accuracy", value = FALSE)
),
conditionalPanel(condition="input.cutOffMethods=='Minimax'",
HTML('<p><b>Minimax:</b> minimizes the most frequent error</p>')
),
conditionalPanel(condition="input.cutOffMethods=='MaxDOR'",
HTML('<p><b>MaxDOR:</b> maximizes diagnostic odds ratio</p>')
),
conditionalPanel(condition="input.cutOffMethods=='MaxKappa'",
HTML('<p><b>MaxKappa:</b> maximizes kappa index</p>'),
HTML('<br>'),
numericInput(inputId = "CFP_MK", label = "Cost of a False Positive", value = 1, min = 0, max = 9999999),
numericInput(inputId = "CFN_MK", label = "Cost of a False Negative", value = 1, min = 0, max = 9999999),
checkboxInput(inputId = "weighted_Kappa", label = "Weighted Kappa", value = FALSE)
),
conditionalPanel(condition="input.cutOffMethods=='MinValueNPV'",
HTML('<p><b>MinValueNPV:</b> a minimum value set for negative predictive value</p>'),
HTML('<br>'),
numericInput(inputId = "valueNPV_MVNPV", label = "Value of NPV", value = 0.85, min = 0, max = 1, step = 0.01)
),
conditionalPanel(condition="input.cutOffMethods=='MinValuePPV'",
HTML('<p><b>MinValuePPV:</b> a minimum value set for positive predictive value</p>'),
HTML('<br>'),
numericInput(inputId = "valuePPV_MVPPV", label = "Value of PPV", value = 0.85, min = 0, max = 1, step = 0.01)
),
conditionalPanel(condition="input.cutOffMethods=='ValueNPV'",
HTML('<p><b>ValueNPV:</b> a value set for negative predictive value</p>'),
HTML('<br>'),
numericInput(inputId = "valueNPV_VNPV", label = "Value of NPV", value = 0.85, min = 0, max = 1, step = 0.01)
),
conditionalPanel(condition="input.cutOffMethods=='ValuePPV'",
HTML('<p><b>ValuePPV:</b> a value set for positive predictive value</p>'),
HTML('<br>'),
numericInput(inputId = "valuePPV_VPPV", label = "Value of PPV", value = 0.85, min = 0, max = 1, step = 0.01)
),
conditionalPanel(condition="input.cutOffMethods=='MinValueNPVPPV'",
HTML('<p><b>MinValueNPVPPV:</b> a minimum value set for predictive values</p>'),
HTML('<br>'),
numericInput(inputId = "valuePPV_MVNPVPPV", label = "Value of PPV", value = 0.85, min = 0, max = 1, step = 0.01),
numericInput(inputId = "valueNPV_MVNPVPPV", label = "Value of NPV", value = 0.85, min = 0, max = 1, step = 0.01),
checkboxInput(inputId = "maxNPV_MVNPVPPV", label = "Maximum NPV", value = TRUE)
),
conditionalPanel(condition="input.cutOffMethods=='PROC01'",
HTML('<p><b>PROC01:</b> minimizes distance between PROC plot and point (0,1)</p>')
),
conditionalPanel(condition="input.cutOffMethods=='NPVEqualPPV'",
HTML('<p><b>NPVEqualPPV:</b> negative predictive value = positive predictive value</p>')
),
conditionalPanel(condition="input.cutOffMethods=='MaxNPVPPV'",
HTML('<p><b>MaxNPVPPV:</b> maximizes positive predictive value and negative predictive value simultaneously</p>')
),
conditionalPanel(condition="input.cutOffMethods=='MaxSumNPVPPV'",
HTML('<p><b>MaxSumNPVPPV:</b> maximizes the sum of the predictive values</p>')
),
conditionalPanel(condition="input.cutOffMethods=='MaxProdNPVPPV'",
HTML('<p><b>MaxProdNPVPPV:</b> maximizes the product of predictive values</p>')
),
conditionalPanel(condition="input.cutOffMethods=='ValueDLR.Negative'",
HTML('<p><b>ValueDLR.Negative:</b> a value set for negative diagnostic likelihood ratio</p>'),
HTML('<br>'),
numericInput(inputId = "valueDLR_Negative", label = "Value of Negative DLR", value = 0.5, min = 0, max = 999999)
),
conditionalPanel(condition="input.cutOffMethods=='ValueDLR.Positive'",
HTML('<p><b>ValueDLR.Positive:</b> a value set for positive diagnostic likelihood ratio</p>'),
HTML('<br>'),
numericInput(inputId = "valueDLR_Positive", label = "Value of Positive DLR", value = 2, min = 0, max = 999999)
),
conditionalPanel(condition="input.cutOffMethods=='MinPvalue'",
HTML('<p><b>MinPvalue:</b> minimizes p-value associated with the statistical Chi-squared test which measures the association between the marker and the binary result obtained on using the cutpoint</p>'),
HTML('<br>'),
selectInput(inputId = "adjusted_pvalue", label = "Adjustment method for p-value",
choices = c("Miller and Siegmund" = "PADJMS", "Altman_5" = "PALT5", "Altman_10" = "PALT10"),
multiple = FALSE, selected = "PADJMS")
),
conditionalPanel(condition="input.cutOffMethods=='ObservedPrev'",
HTML('<p><b>ObservedPrev:</b> the closest value to observed prevalence</p>')
),
conditionalPanel(condition="input.cutOffMethods=='MeanPrev'",
HTML('<p><b>MeanPrev:</b> the closest value to the mean of the diagnostic test values</p>')
),
conditionalPanel(condition="input.cutOffMethods=='PrevalenceMatching'",
HTML('<p><b>PrevalenceMatching:</b> the value for which predicted prevalence is practically equal to observed prevalence</p>')
),
HTML('<br>'),
HTML('<p>(*) See <a href="http://cran.r-project.org/web/packages/OptimalCutpoints/index.html" target="_blank"> OptimalCutpoints</a> package from R</p>'),
HTML('<br>'),
checkboxInput("showPlots", "Include plots.", FALSE),
conditionalPanel(condition="input.showPlots",
fluidRow(
# column(1),
column(6, sliderInput("myheightCutoff", "Plot height:", value=600, min=400, max=1400)),
# column(1),
column(6, sliderInput("mywidthCutoff", "Plot width:", value=800, min=400, max=1400 ))
),
HTML('<br>'),
checkboxInput("cutoffPlotsOpts", "More plot options (See Manual)", FALSE),
HTML('<br>')
),
conditionalPanel(condition="input.cutoffPlotsOpts",
fluidRow(
column(12, selectizeInput("fontfamily", "Font family",
choices = c("Times New Roman" = "serif", "Arial" = "sans",
"Corier New" = "mono"), selected = "sans"))
),
radioButtons("selectedGraph", "", list("Top Left \U2003 \U2003" = 1, "Top Right \U2003 \U2003" = 2,
"Bottom Left \U2002\U2008" = 3, "Bottom Right" = 4), selected = 1),
HTML('<br>'),
selectizeInput("subGrps", "", choices = NULL, selected = NULL),
## First graph options (11)
conditionalPanel(condition = "input.selectedGraph == '1'",
conditionalPanel(condition = "input.subGrps == 'others'",
fluidRow(
column(6, textInput("main11", "Graph title", "ROC Curve")),
# column(1),
column(6, selectizeInput("font.main11", "Title font",
choices = c("Regular" = "1", "Bold" = "2",
"Italic" = "3", "Bold Italic" = "4"),
selected = "2"))
),
fluidRow(
column(6, textInput("col.main11", "Title color", "black")),
# column(1),
column(6, numericInput("cex.main11", "Title size", min=0.1, max=5, value = 1.2, step = 0.1))
),
fluidRow(
column(6, textInput("ROCcol11", "ROC line color", "black")),
# column(1),
column(6, selectizeInput("ROClty11", "ROC line type",
choices = c("\U2500\U2500\U2500\U2500\U2500\U2500\U2500" = "1",
"\U2574 \U2574 \U2574 \U2574 \U2574 \U2574" = "2",
"\U00B7 \U00B7 \U00B7 \U00B7 \U00B7 \U00B7 \U00B7 \U00B7 \U00B7" = "3",
"\U2574 \U00B7 \U2574 \U00B7 \U2574 \U00B7 \U2574" = "4",
"\U2500 \U2500 \U2500 \U2500 \U2500" = "5",
"\U2500 \U2574 \U2500 \U2574 \U2500 \U2574" = "6"),
selected = "1"))
)
),
conditionalPanel(condition = "input.subGrps == 'xAxis'",
h5('X-axis options:'),
## X axis label options
fluidRow(
column(6, textInput("xlab11", "Axis label", "1-Specificity")),
# column(1),
column(6, selectizeInput("xfont.lab11", "Label font",
choices = c("Regular" = "1", "Bold" = "2",
"Italic" = "3", "Bold Italic" = "4"),
selected = "1"))
),
fluidRow(
column(6, textInput("xcol.lab11", "Label color", "black")),
# column(1),
column(6, numericInput("xcex.lab11", "Label size", min=0.1, max=5, value = 1, step = 0.1))
),
## X axis annotation options
fluidRow(
column(6, textInput("xcol.axis11", "Annotation color", "black")),
# column(1),
column(6, numericInput("xcex.axis11", "Annotation size", min=0.1, max=5, value = 1, step = 0.1))
)
#fluidRow(
# column(5, textInput("xcol11", "Axis color", "black")),
# column(1),
# column(5, textInput("xcol.ticks11", "Tickmarks color", "black"))
#),
),
conditionalPanel(condition = "input.subGrps == 'yAxis'",
h5('Y-axis options:'),
## Y axis label options
fluidRow(
column(6, textInput("ylab11", "Axis label", "Sensitivity")),
# column(1),
column(6, selectizeInput("yfont.lab11", "Label font",
choices = c("Regular" = "1", "Bold" = "2",
"Italic" = "3", "Bold Italic" = "4"),
selected = "1"))
),
fluidRow(
column(6, textInput("ycol.lab11", "Label color", "black")),
# column(1),
column(6, numericInput("ycex.lab11", "Label size", min=0.1, max=5, value = 1, step = 0.1))
),
## Y axis annotation options
fluidRow(
column(6, textInput("ycol.axis11", "Annotation color", "black")),
# column(1),
column(6, numericInput("ycex.axis11", "Annotation size", min=0.1, max=5, value = 1, step = 0.1))
)
)
),
## Second graph options (12)
conditionalPanel(condition = "input.selectedGraph == '2'",
conditionalPanel(condition = "input.subGrps == 'others'",
fluidRow(
column(6, textInput("main12", "Graph title", "Sens. & Spec. Curve")),
# column(1),
column(6, selectizeInput("font.main12", "Title font",
choices = c("Regular" = "1", "Bold" = "2",
"Italic" = "3", "Bold Italic" = "4"),
selected = "2"))
),
fluidRow(
column(6, textInput("col.main12", "Title color", "black")),
# column(1),
column(6, numericInput("cex.main12", "Title size", min=0.1, max=5, value = 1.2, step = 0.1))
),
fluidRow(
column(6, textInput("specCol", "Spec. line color", "blue")),
# column(1),
column(6, selectizeInput("specType", "Spec. line type",
choices = c("\U2500\U2500\U2500\U2500\U2500\U2500\U2500" = "1",
"\U2574 \U2574 \U2574 \U2574 \U2574 \U2574" = "2",
"\U00B7 \U00B7 \U00B7 \U00B7 \U00B7 \U00B7 \U00B7 \U00B7 \U00B7" = "3",
"\U2574 \U00B7 \U2574 \U00B7 \U2574 \U00B7 \U2574" = "4",
"\U2500 \U2500 \U2500 \U2500 \U2500" = "5",
"\U2500 \U2574 \U2500 \U2574 \U2500 \U2574" = "6"),
selected = "1"))
),
fluidRow(
column(6, textInput("sensCol", "Sens. line color", "red")),
# column(1),
column(6, selectizeInput("sensType", "Sens. line type",
choices = c("\U2500\U2500\U2500\U2500\U2500\U2500\U2500" = "1",
"\U2574 \U2574 \U2574 \U2574 \U2574 \U2574" = "2",
"\U00B7 \U00B7 \U00B7 \U00B7 \U00B7 \U00B7 \U00B7 \U00B7 \U00B7" = "3",
"\U2574 \U00B7 \U2574 \U00B7 \U2574 \U00B7 \U2574" = "4",
"\U2500 \U2500 \U2500 \U2500 \U2500" = "5",
"\U2500 \U2574 \U2500 \U2574 \U2500 \U2574" = "6"),
selected = "1"))
)
),
conditionalPanel(condition = "input.subGrps == 'Legend'",
fluidRow(
column(6, selectizeInput("legendPos12", "Position",
choices = c("Top right" = "topright", "Top left" = "topleft",
"Bottom right" = "bottomright", "Bottom left" = "bottomleft", "xy coord." = "xy"),
selected = "topright")),
# column(1),
column(3,
conditionalPanel(condition = "input.legendPos12 == 'xy'",
numericInput("legendXpos12", "x", value = 0, step = 0.1)
)
),
# column(1),
column(3,
conditionalPanel(condition = "input.legendPos12 == 'xy'",
numericInput("legendYpos12", "y", value = 0, step = 0.02)
)
)
),
fluidRow(
column(8, textInput("legendNames12", "Legend labels", "Sens.,Spec.")),
# column(1),
column(4, numericInput("cex.legend12", "Leg. size", min = 0.5, max = 5, step = 0.1, value = 1))
),
fluidRow(
column(6, textInput("legendTitle12", "Title", "")),
# column(1),
column(6, textInput("col.legendTitle12", "Title color", "black"))
),
checkboxInput("borderless12", label = "Remove borders.", value = FALSE)
),
conditionalPanel(condition = "input.subGrps == 'xAxis'",
h5('X-axis options:'),
## X axis label options
fluidRow(
column(6, textInput("xlab12", "Axis label", "Marker Name")),
# column(1),
column(6, selectizeInput("xfont.lab12", "Label font",
choices = c("Regular" = "1", "Bold" = "2",
"Italic" = "3", "Bold Italic" = "4"),
selected = "1"))
),
fluidRow(
column(6, textInput("xcol.lab12", "Label color", "black")),
# column(1),
column(6, numericInput("xcex.lab12", "Label size", min=0.1, max=5, value = 1, step = 0.1))
),
## X axis annotation options
fluidRow(
column(6, textInput("xcol.axis12", "Annotation color", "black")),
# column(1),
column(6, numericInput("xcex.axis12", "Annotation size", min=0.1, max=5, value = 1, step = 0.1))
)
),
conditionalPanel(condition = "input.subGrps == 'yAxis'",
h5('Y-axis options:'),
## Y axis label options
fluidRow(
column(6, textInput("ylab12", "Axis label", "Value")),
# column(1),
column(6, selectizeInput("yfont.lab12", "Label font",
choices = c("Regular" = "1", "Bold" = "2",
"Italic" = "3", "Bold Italic" = "4"),
selected = "1"))
),
fluidRow(
column(6, textInput("ycol.lab12", "Label color", "black")),
# column(1),
column(6, numericInput("ycex.lab12", "Label size", min=0.1, max=5, value = 1, step = 0.1))
),
## Y axis annotation options
fluidRow(
column(6, textInput("ycol.axis12", "Annotation color", "black")),
# column(1),
column(6, numericInput("ycex.axis12", "Annotation size", min=0.1, max=5, value = 1, step = 0.1))
)
)
),
## Third graph options (21)
conditionalPanel(condition = "input.selectedGraph == '3'",
conditionalPanel(condition = "input.subGrps == 'others'",
fluidRow(
column(6, textInput("main21", "Graph title", "Distribution Graph")),
# column(1),
column(6, selectizeInput("font.main21", "Title font",
choices = c("Regular" = "1", "Bold" = "2",
"Italic" = "3", "Bold Italic" = "4"),
selected = "2"))
),
fluidRow(
column(6, textInput("col.main21", "Title color", "black")),
# column(1),
column(6, numericInput("cex.main21", "Title size", min=0.1, max=5, value = 1.2, step = 0.1))
),
fluidRow(
column(6, textInput("lineColD", "Line color (Diseased)", "red")),
# column(1),
column(6, selectizeInput("lineTypeD", "Line type",
choices = c("\U2500\U2500\U2500\U2500\U2500\U2500\U2500" = "1",
"\U2574 \U2574 \U2574 \U2574 \U2574 \U2574" = "2",
"\U00B7 \U00B7 \U00B7 \U00B7 \U00B7 \U00B7 \U00B7 \U00B7 \U00B7" = "3",
"\U2574 \U00B7 \U2574 \U00B7 \U2574 \U00B7 \U2574" = "4",
"\U2500 \U2500 \U2500 \U2500 \U2500" = "5",
"\U2500 \U2574 \U2500 \U2574 \U2500 \U2574" = "6"),
selected = "1"))
),
fluidRow(
column(6, textInput("lineColH", "Line color (Healthy)", "blue")),
# column(1),
column(6, selectizeInput("lineTypeH", "Line type",
choices = c("\U2500\U2500\U2500\U2500\U2500\U2500\U2500" = "1",
"\U2574 \U2574 \U2574 \U2574 \U2574 \U2574" = "2",
"\U00B7 \U00B7 \U00B7 \U00B7 \U00B7 \U00B7 \U00B7 \U00B7 \U00B7" = "3",
"\U2574 \U00B7 \U2574 \U00B7 \U2574 \U00B7 \U2574" = "4",
"\U2500 \U2500 \U2500 \U2500 \U2500" = "5",
"\U2500 \U2574 \U2500 \U2574 \U2500 \U2574" = "6"),
selected = "1"))
)
),
conditionalPanel(condition = "input.subGrps == 'Legend'",
fluidRow(
column(6, selectizeInput("legendPos21", "Position",
choices = c("Top right" = "topright", "Top left" = "topleft",
"Bottom right" = "bottomright", "Bottom left" = "bottomleft", "xy coord." = "xy"),
selected = "topright")),
# column(1),
column(3,
conditionalPanel(condition = "input.legendPos21 == 'xy'",
numericInput("legendXpos21", "x", value = 0, step = 0.1)
)
),
# column(1),
column(3,
conditionalPanel(condition = "input.legendPos21 == 'xy'",
numericInput("legendYpos21", "y", value = 0, step = 0.1)
)
)
),
fluidRow(
column(8, textInput("legendNames21", "Legend labels", "Diseased,Healthy")),
# column(1),
column(4, numericInput("cex.legend21", "Leg. Size", min = 0.5, max = 5, step = 0.1, value = 1))
),
fluidRow(
column(6, textInput("legendTitle21", "Title", "")),
# column(1),
column(6, textInput("col.legendTitle21", "Title color", "black"))
),
checkboxInput("borderless21", label = "Remove borders.", value = FALSE)
),
conditionalPanel(condition = "input.subGrps == 'xAxis'",
h5('X-axis options:'),
## X axis label options
fluidRow(
column(6, textInput("xlab21", "Axis label", "Marker Name")),
# column(1),
column(6, selectizeInput("xfont.lab21", "Label font",
choices = c("Regular" = "1", "Bold" = "2",
"Italic" = "3", "Bold Italic" = "4"),
selected = "1"))
),
fluidRow(
column(6, textInput("xcol.lab21", "Label color", "black")),
# column(1),
column(6, numericInput("xcex.lab21", "Label size", min=0.1, max=5, value = 1, step = 0.1))
),
## X axis annotation options
fluidRow(
column(6, textInput("xcol.axis21", "Annotation color", "black")),
# column(1),
column(6, numericInput("xcex.axis21", "Annotation size", min=0.1, max=5, value = 1, step = 0.1))
)
),
conditionalPanel(condition = "input.subGrps == 'yAxis'",
h5('Y-axis options:'),
## Y axis label options
fluidRow(
column(6, textInput("ylab21", "Axis label", "Density")),
# column(1),
column(6, selectizeInput("yfont.lab21", "Label font",
choices = c("Regular" = "1", "Bold" = "2",
"Italic" = "3", "Bold Italic" = "4"),
selected = "1"))
),
fluidRow(
column(6, textInput("ycol.lab21", "Label color", "black")),
# column(1),
column(6, numericInput("ycex.lab21", "Label size", min=0.1, max=5, value = 1, step = 0.1))
),
## Y axis annotation options
fluidRow(
column(6, textInput("ycol.axis21", "Annotation color", "black")),
# column(1),
column(6, numericInput("ycex.axis21", "Annotation size", min=0.1, max=5, value = 1, step = 0.1))
)
)
),
## Fourth graph options (22)
conditionalPanel(condition = "input.selectedGraph == '4'",
conditionalPanel(condition = "input.subGrps == 'others'",
fluidRow(
column(6, textInput("main22", "Graph title", "Distribution Graph")),
# column(1),
column(6, selectizeInput("font.main22", "Title font",
choices = c("Regular" = "1", "Bold" = "2",
"Italic" = "3", "Bold Italic" = "4"),
selected = "2"))
),
fluidRow(
column(6, textInput("col.main22", "Title color", "black")),
# column(1),
column(6, numericInput("cex.main22", "Title size", min=0.1, max=5, value = 1.2, step = 0.1))
),
numericInput("jitterAmount", "Amount of jittering", min=0.01, max = 0.5, value = 0.05, step = 0.01),
## pch options for Healthy and Diseased subjects
fluidRow(
column(8, textInput("colPoints", "Point colors", "black,black")),
# column(1),
column(4, numericInput("pchPoints", "Type", min = 0, max = 25, step = 1, value = 1))
),
fluidRow(
column(4, numericInput("pchSize", "Point size", min = 0.1, max = 5, step = 0.1, value = 1)),
# column(1),
column(8,
conditionalPanel(condition = "input.pchPoints > 20",
textInput("pchFill", "Fill points with color" ,"white,white")
)
)
)
),
conditionalPanel(condition = "input.subGrps == 'xAxis'",
h5('X-axis options:'),
## X axis label options
fluidRow(
column(6, textInput("xlab22", "Axis label", "Disease Status")),
# column(1),
column(6, selectizeInput("xfont.lab22", "Label font",
choices = c("Regular" = "1", "Bold" = "2",
"Italic" = "3", "Bold Italic" = "4"),
selected = "1"))
),
fluidRow(
column(6, textInput("xcol.lab22", "Label color", "black")),
# column(1),
column(6, numericInput("xcex.lab22", "Label size", min=0.1, max=5, value = 1, step = 0.1))
),
## X axis annotation options
fluidRow(
column(12, textInput("xlabels22", "Annotation names (comma seperated)", "Healthy,Diseased"))
),
fluidRow(
column(6, textInput("xcol.axis22", "Annotation color", "black")),
# column(1),
column(6, numericInput("xcex.axis22", "Annotation size", min=0.1, max=5, value = 1, step = 0.1))
)
),
conditionalPanel(condition = "input.subGrps == 'yAxis'",
h5('Y-axis options:'),
## Y axis label options
fluidRow(
column(6, textInput("ylab22", "Axis label", "Marker Name")),
# column(1),
column(6, selectizeInput("yfont.lab22", "Label font",
choices = c("Regular" = "1", "Bold" = "2",
"Italic" = "3", "Bold Italic" = "4"),
selected = "1"))
),
fluidRow(
column(6, textInput("ycol.lab22", "Label color", "black")),
# column(1),
column(6, numericInput("ycex.lab22", "Label size", min=0.1, max=5, value = 1, step = 0.1))
),
## Y axis annotation options
fluidRow(
column(6, textInput("ycol.axis22", "Annotation color", "black")),
# column(1),
column(6, numericInput("ycex.axis22", "Annotation size", min=0.1, max=5, value = 1, step = 0.1))
)
)
)
)
), # End for Cut Points tab.
conditionalPanel(condition="input.tabs1=='Sample size'",
# h5("Choose one of the following methods (*):"),
# HTML('<br>'),
selectInput(inputId = "sampleSizeMethod", label = "Select Method (*)",
choices = c("Single test" = 1, "Comparison of two tests" = 2, "Non-inferiority" = 3),
selected = 1, multiple = FALSE, selectize = TRUE),
HTML('<br>'),
conditionalPanel(condition = "input.sampleSizeMethod == '1'",
numericInput(inputId = "alpha1", label = "Type I error", value = 0.05, min = 0, max = 1, step = 0.01),
numericInput(inputId = "power1", label = "Power", value = 0.80, min = 0, max = 1, step = 0.1),
numericInput(inputId = "auc", label = "Area under the ROC curve", value = 0.60, min = 0.5, max = 1, step = 0.1),
numericInput(inputId = "ratio", label = "Allocation ratio", value = 1, min = 0, step = 0.1)
),
conditionalPanel(condition = "input.sampleSizeMethod == '2'",
numericInput(inputId = "alpha2", label = "Type I error", value = 0.05, min = 0, max = 1, step = 0.01),
numericInput(inputId = "power2", label = "Power", value = 0.80, min = 0, max = 1, step = 0.1),
numericInput(inputId = "auc01", label = "AUC for 1st test under null hypothesis", value = 0.80, min = 0.5, max = 1, step = 0.1),
numericInput(inputId = "auc02", label = "AUC for 2nd test under null hypothesis", value = 0.80, min = 0.5, max = 1, step = 0.1),
numericInput(inputId = "auc11", label = "AUC for 1st test under alternative hypothesis", value = 0.90, min = 0.5, max = 1, step = 0.1),
numericInput(inputId = "auc12", label = "AUC for 2nd test under alternative hypothesis", value = 0.70, min = 0.5, max = 1, step = 0.1),
numericInput(inputId = "ratio2", label = "Allocation ratio", value = 1, min = 0, step = 0.1)
),
conditionalPanel(condition = "input.sampleSizeMethod == '3'",
numericInput(inputId = "alpha3", label = "Type I error", value = 0.05, min = 0, max = 1, step = 0.01),
numericInput(inputId = "power3", label = "Power", value = 0.80, min = 0, max = 1, step = 0.1),
numericInput(inputId = "aucs", label = "AUC for standard test", value = 0.80, min = 0.5, max = 1, step = 0.1),
numericInput(inputId = "aucn", label = "AUC for new test", value = 0.80, min = 0.5, max = 1, step = 0.1),
numericInput(inputId = "sd", label = "Smallest difference", value = 0.1, step = 0.1),
numericInput(inputId = "ratio3", label = "Allocation ratio", value = 1, min = 0, step = 0.1)
),
HTML('<br>'),
HTML('<p>(*) See <a href="http://66.199.228.237/boundary/complex_decision_making_and_ethics/ROC_Analysis.pdf" target="_blank"> Obuchowski, 2005</a> for further details.</p>'),
HTML('<br>')
), ## End for Sample Size tab.
conditionalPanel(condition="input.tabs1=='Manual'",
HTML('<p align="center"><img src="manual.png" width=200 height=200></p>')
),
conditionalPanel(condition="input.tabs1=='Authors & News'",
HTML('<p align="center"> <a href="https://www.erciyes.edu.tr/home/index" target="_blank"><img src="eru_logo.png" width=150 height=150></a> </p>')
)