Nothing
source("R/global.R")
ui <- dashboardPage(
title="shinygap",
skin="purple",
dashboardHeader(
title = tags$a(href='https://github.com/jinghuazhao/', target = '_blank',
tags$img(src=paste0("bees.svg"), height = "70%", width = "auto", align = "middle")
),
dropdownMenu(type = "messages",
tags$li(HTML('<li><a href="https://github.com/jinghuazhao/ShinyApps" target="_blank"><i class="fa fa-code-branch"></i><h4>GitHub</h4></a></li>')),
tags$li(HTML('<li><a href="mailto:jinghuazhao@hotmail.com" target="_blank"><i class="fa fa-question"></i><h4>email</h4></a></li>'))
)
),
dashboardSidebar(
sidebarMenu(
menuItem("Home", tabName = "landing", icon = icon("home")),
menuItem("fbDesign", tabName = "fbDesign", icon = icon("upload")),
menuItem("pbDesign", tabName = "pbDesign", icon = icon("download")),
menuItem("ccDesign", tabName = "ccDesign", icon = icon("th")),
menuItem("tsccDesign", tabName = "tsccDesign", icon = icon("th"))
)
),
dashboardBody(
tabItems(
tabItem(tabName = "landing",
div(class = "jumbotron", HTML("<center><h1>Shiny for genetic analysis package (gap) designs</h1></center>")),
fluidRow(div(class = "col-sm-12",
div(class = "box box-primary", style = "padding-right: 5%; padding-left: 5%; font-size:100%", NULL,
div(class = "box-body", shiny::includeMarkdown("README.md"))
)
),
withMathJax()
)
),
tabItem(tabName = "fbDesign",
h2("Family-based design"),
fluidRow(
sidebarLayout(
sidebarPanel(
radioButtons("fb_var", "Variable (x axis of the plot):",
c("Genotype relative risk (gamma)"="fb_gamma",
"frequency of disease allele (p)"="fb_p",
"type I error (alpha)"="fb_alpha",
"type II error (beta)"="fb_beta"
)
),
sliderInput("fb_gamma", "gamma:", min = 1, max = 30, value = 4),
sliderInput("fb_p", "p:", min = 0.001, max = 0.8, value = 0.01),
sliderInput("fb_alpha", "alpha:", min = 1e-8, max = 0.05, value = 1e-6),
sliderInput("fb_beta", "beta:", min = 0.01, max = 0.4, value = 0.2)
),
mainPanel(
h3(verbatimTextOutput("fb_caption")),
plotlyOutput("fb"),
h3("Header of data:"),
tableOutput("fb_preview"),
radioButtons('fb_downloadFormat', 'Download file format:', c('bz2', 'gz', 'tsv', 'xz'), inline = TRUE),
downloadButton("fb_download", "Download data")
)
)
)
),
tabItem(tabName = "pbDesign",
h2("Population-based design"),
fluidRow(
sidebarLayout(
sidebarPanel(
radioButtons("pb_var", "Variable (x axis of the plot):",
c("Prevalence of disease (Kp)"="pb_kp",
"Genotype relative risk (gamma)"="pb_gamma",
"Frequency of disease allele (p)"="pb_p",
"type I error (alpha)"="pb_alpha",
"type II error (beta)"="pb_beta"
)
),
sliderInput("pb_kp", "kp:", min = 1e-5, max = 0.4, value = 0.1),
sliderInput("pb_gamma", "gamma:", min = 1, max = 30, value = 4.5),
sliderInput("pb_p", "p:", min = 1e-3, max = 0.8, value = 0.1),
sliderInput("pb_alpha", "alpha:", min = 5e-8, max = 0.05, value = 5e-8),
sliderInput("pb_beta", "beta:", min = 0.01, max = 0.4, value = 0.2)
),
mainPanel(
h3(verbatimTextOutput("pb_caption")),
plotlyOutput("pb"),
h3("Header of data:"),
tableOutput("pb_preview"),
radioButtons('pb_downloadFormat', 'Download file format:', c('bz2', 'bz', 'tsv', 'xz'), inline = TRUE),
downloadButton("pb_download", "Download data")
)
)
)
),
tabItem(tabName = "ccDesign",
h2("Case-cohort design"),
fluidRow(
sidebarLayout(
sidebarPanel(
checkboxInput("cc_power", "Power/Sample size:", TRUE),
radioButtons("cc_var", "Variable (x axis of the plot):",
c("Cohort size (n)"="cc_n",
"Fraction for subcohort (q)"="cc_q",
"Proportion of failure (pD)"="cc_pD",
"Proportion of group 1 (p1)"="cc_p1",
"log(HR) for two groups (theta)"="cc_theta",
"type I error (alpha)"="cc_alpha",
"type II error (beta)"="cc_beta"
)
),
sliderInput("cc_n", "n:", min = 100, max = 500000, value = 25000),
sliderInput("cc_q", "q:", min = 0.01, max = 0.5, value = 0.01),
sliderInput("cc_pD", "pD:", min = 1e-5, max = 0.8, value = 0.05),
sliderInput("cc_p1", "p1:", min = 1e-5, max = 0.8, value = 0.05),
sliderInput("cc_theta", "log(HR):", min = 0.01, max = 2.3, value = 0.3),
sliderInput("cc_alpha", "alpha:", min = 5e-8, max = 0.05, value = 0.05),
sliderInput("cc_beta", "beta:", min = 0.01, max = 0.4, value = 0.2)
),
mainPanel(
h3(verbatimTextOutput("cc_caption")),
plotlyOutput("cc"),
h3("Header of data:"),
tableOutput("cc_preview"),
radioButtons('cc_downloadFormat', 'Download file format:', c('bz2', 'gz', 'tsv', 'xz'), inline = TRUE),
downloadButton("cc_download", "Download data")
)
)
)
),
tabItem(tabName = "tsccDesign",
h2("Two-stage case-control design"),
fluidRow(
sidebarLayout(
sidebarPanel(
radioButtons("tscc_model", "Model:", c("multiplicative","additive","dominant","recessive")),
radioButtons("tscc_var", "Variable (x axis of the plot):",
c("Genotype relative risk (GRR)"="tscc_GRR",
"The estimated risk allele frequency in cases (p1)"="tscc_p1",
"Total number of cases (n1)"="tscc_n1",
"Total number of controls (n2)"="tscc_n2",
"Total number of markers (M)"="tscc_M",
"False positive rate at genome level (alpha.genome)"="tscc_alpha_genome",
"Sample percentage genotyped at stage 1 (pi.samples)"="tscc_pi_samples",
"Marker percentage to be selected (pi.markers)"="tscc_pi_markers",
"The population prevalence (K)"="tscc_K"
)
),
sliderInput("tscc_GRR", "GRR:", min = 1, max = 30, value = 1.4),
sliderInput("tscc_p1", "p1:", min = 1e-3, max = 0.8, value = 0.4),
sliderInput("tscc_n1", "n1:", min = 400, max = 500000, value = 1000),
sliderInput("tscc_n2", "n2:", min = 400, max = 500000, value = 1000),
sliderInput("tscc_M", "M:", min = 400, max = 10000000, value = 300000),
sliderInput("tscc_alpha_genome", "alpha:", min = 5e-8, max = 0.05, value = 0.05),
sliderInput("tscc_pi_samples", "pi.samples:", min = 0.01, max = 1, value = 0.2),
sliderInput("tscc_pi_markers", "pi.markers:", min = 0.01, max = 1, value = 0.1),
sliderInput("tscc_K", "K:", min = 1e-5, max = 0.4, value = 0.1)
),
mainPanel(
h3(verbatimTextOutput("tscc_caption")),
plotlyOutput("tscc"),
h3("Header of data:"),
tableOutput("tscc_preview"),
radioButtons('tscc_downloadFormat', 'Download file format:', c('bz2', 'bz', 'tsv', 'xz'), inline = TRUE),
downloadButton("tscc_download", "Download data")
)
) # siderbarLayout
) # fluidRow
) # tabitem
) # tabItems
) # dashbarBody
)
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