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updates
now with a shiny app
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@ -1,7 +1,7 @@
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Package: daDoctoR
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Type: Package
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Title: FUNCTIONS FOR HEALTH RESEARCH
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Version: 0.1.0.9022
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Version: 0.1.0.9023
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Author@R: c(person("Andreas", "Gammelgaard Damsbo", email = "agdamsbo@pm.me", role = c("cre", "aut")))
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Maintainer: Andreas Gammelgaard Damsbo <agdamsbo@pm.me>
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Description: I am a Danish medical doctor involved in neuropsychiatric research.
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@ -12,6 +12,7 @@ Imports: broom,
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epiR,
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ggplot2,
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MASS
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Suggest: shiny
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License: GPL (>= 2)
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Encoding: UTF-8
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LazyData: true
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92
inst/hwe_calc/server.R
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92
inst/hwe_calc/server.R
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#'
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#' This is a Shiny web application. You can run the application by clicking
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#' the 'Run App' button above.
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#'
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#' Find out more about building applications with Shiny here:
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#'
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#' http://shiny.rstudio.com/
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#'
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#'
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#' User requests:
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#'
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#' - Proper labelling of chart
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library(shiny)
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library(ggplot2)
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source("https://raw.githubusercontent.com/agdamsbo/daDoctoR/master/R/hwe_geno.R")
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# Define server logic required to draw a histogram
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server <- function(input, output, session) {
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cale <- reactive({
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as.numeric(input$ale)
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})
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dat<-reactive({
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df<-data.frame(lbls=c("MM","MN","NN","MO","NO","OO"),
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value=rbind(input$mm,input$mn,input$nn,input$mo,input$no,input$oo),
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stringsAsFactors = FALSE)
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print(df)
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df
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})
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cmm <- reactive({
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as.numeric(input$mm)
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})
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cmn <- reactive({
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as.numeric(input$mn)
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})
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cnn <- reactive({
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as.numeric(input$nn)
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})
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cmo <- reactive({
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as.numeric(input$mo)
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})
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cno <- reactive({
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as.numeric(input$no)
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})
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coo <- reactive({
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as.numeric(input$oo)
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})
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hwe_p <- function() ({ hwe_geno(cmm(),cmn(),cnn(),cmo(),cno(),coo(),alleles=cale()) })
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output$allele.tbl <- renderTable({ hwe_p()$allele.dist })
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output$obs.tbl <- renderTable({ hwe_p()$observed.dist })
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output$exp.tbl <- renderTable({ hwe_p()$expected.dist })
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output$chi.val <- renderTable({ hwe_p()$chi.value })
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output$p.val <- renderTable({ hwe_p()$p.value })
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output$allele.dist <- renderText({"Allele distribution"})
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output$obs.dist <- renderText({"Observed distribution"})
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output$exp.dist <- renderText({"Expected distribution"})
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output$chi <- renderText({"Chi square value"})
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output$p <- renderText({"P value"})
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output$geno.pie.plt<- renderPlot({
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ggplot(dat(), aes(x="", y=value, fill=lbls))+
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geom_bar(width = 1, stat = "identity")+
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coord_polar("y", start=0)+
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scale_fill_brewer(palette="Dark2")
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})
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output$geno.pie.ttl <- renderText({"Genotype distribution"})
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}
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# Run the application
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shinyApp(ui = ui, server = server)
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97
inst/hwe_calc/ui.R
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97
inst/hwe_calc/ui.R
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#'
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#' This is a Shiny web application. You can run the application by clicking
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#' the 'Run App' button above.
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#'
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#' Find out more about building applications with Shiny here:
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#'
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#' http://shiny.rstudio.com/
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#'
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#'
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#' User requests:
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#'
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#' - Proper labelling of chart
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library(shiny)
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library(ggplot2)
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source("https://raw.githubusercontent.com/agdamsbo/daDoctoR/master/R/hwe_geno.R")
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ui <- fluidPage(
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# Application title
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titlePanel("Chi square test of HWE for bi- or triallelic systems"),
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sidebarLayout(
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sidebarPanel(
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# Input: Numeric entry for number of alleles ----
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radioButtons(inputId = "ale",
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label = "Number of alleles:",
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inline = FALSE,
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choiceNames=c("Two alleles (M, N)",
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"Three alleles (M, N, O)"),
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choiceValues=c(2,3)),
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h4("Observed genotype distribution"),
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numericInput(inputId = "mm",
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label = "MM:",
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value=NA),
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numericInput(inputId = "mn",
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label = "MN:",
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value=NA),
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numericInput(inputId = "nn",
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label = "NN:",
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value=NA),
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conditionalPanel(condition = "input.ale==3",
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numericInput(inputId = "mo",
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label = "MO:",
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value=NA),
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numericInput(inputId = "no",
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label = "NO:",
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value=NA),
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numericInput(inputId = "oo",
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label = "OO:",
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value=NA))
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),
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mainPanel(
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tabsetPanel(
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tabPanel("Summary",
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h3(textOutput("obs.dist", container = span)),
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htmlOutput("obs.tbl", container = span),
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h3(textOutput("exp.dist", container = span)),
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htmlOutput("exp.tbl", container = span),
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h3(textOutput("allele.dist", container = span)),
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htmlOutput("allele.tbl", container = span),
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value=1),
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tabPanel("Calculations",
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h3(textOutput("chi", container = span)),
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htmlOutput("chi.val", container = span),
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h3(textOutput("p", container = span)),
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htmlOutput("p.val", container = span),
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value=2),
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tabPanel("Plots",
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h3(textOutput("geno.pie.ttl", container = span)),
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plotOutput("geno.pie.plt"),
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value=3),
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selected= 2, type = "tabs")
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)
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)
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)
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