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app.R
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library(shinydashboard)
library(shinyMobile)
library(RColorBrewer)
library(ggplot2)
library(plotly)
library(dplyr)
library(shinymanager)
library(reshape2)
js <- '.nav-tabs-custom .nav-tabs li.active {
border-top-color: #009900;
}"'
mData <- readRDS('Data/microbiome.rds')
nData <- readRDS('Data/nutriData.rds')
mood_df <- data.frame("happy" = sample(5:10,29,replace = TRUE,
prob = sample(seq(0.5,1,0.1),6,TRUE)),
"sad" = sample(1:4,29,replace = TRUE,
prob = sample(seq(0,0.4,0.1),4,TRUE)),
"tired" = sample(3:10,29,replace = TRUE,
prob = sample(seq(0,0.7,0.1),8,TRUE)),
"dizzy" = sample(1:4,29,replace = TRUE,
prob = sample(seq(0,0.25,0.1),4,TRUE)),
"meh" = sample(2:6,29,replace = TRUE,
prob = sample(seq(0,0.4,0.1),5,TRUE)),
"date" = format(seq(Sys.Date()-29,Sys.Date()-1,1),"%b %d"))
credentials <- data.frame(
user = unique(mData$UserName),
password = paste("innovation",unique(mData$UserName),sep = "_"),
stringsAsFactors = FALSE
)
monthStart <- function(x) {
x <- as.POSIXlt(x)
x$mday <- 1
as.Date(x)
}
messageData = data.frame("from"=c("bioTrac clinic"),
"message"= c("Track your shipment"))
taskData = data.frame("value"=c(100,80,35),
"text"= c("Mood","Calories","Water intake"),
"color" = c("green","yellow","red"))
ui <- dashboardPage(skin = "green",
dashboardHeader(title = "bioTrac - Trust your gut",
dropdownMenuOutput("messageMenu"),
dropdownMenuOutput("taskMenu")
),
dashboardSidebar(
sidebarMenu(
menuItem("Dashboard", tabName = "dashboard", icon = icon("home")),
menuItem("Diet", tabName = "diet", icon = icon("chart-pie")),
menuItem("Microbiome", tabName = "microbiome", icon = icon("chart-area")),
menuItem("Clinical trial", tabName = "population", icon = icon("users")),
menuItem("Mood tracker", tabName = "mood", icon = icon("smile-beam"))
)
),
dashboardBody(
tags$style(js),
tags$script(HTML("
var openTab = function(tabName){
$('a', $('.sidebar')).each(function() {
if(this.getAttribute('data-value') == tabName) {
this.click()
};
});
}
")),
tabItems(
# First tab content
tabItem(tabName = "diet",
fluidRow(
box(h4("Scanner coming soon .."),
background = "olive"),
dateRangeInput('dateRange',label = "Period to analyze : ",
format = "mm/dd/yyyy",
start = Sys.Date()-60,
end=Sys.Date(),
startview = "year",
separator = " - "),
box(plotlyOutput("nplot", height = 350)),
)
),
tabItem(tabName = "microbiome",
fluidRow(
box(h4("Newest results still being analyzed .."),
background = "olive"),
dateRangeInput('dateRange',label = "Period to analyze : ",
format = "mm/dd/yyyy",
start = Sys.Date()-60,
end=Sys.Date(),
startview = "year",
separator = " - "),
box(plotlyOutput("mplot", height = 350)),
)
),
tabItem(tabName = "population",
h3("Contact your clinician to see if you are eligible")
),
tabItem(tabName = "mood",
h3("How are you feeling today?"),
fluidRow(
box(
title = icon("smile-beam","fa-2x"),
sliderInput("s1", "Happy", 1, 10, 10)
),
box(
title = icon("sad-cry","fa-2x"),
sliderInput("s2", "Sad", 1, 10, 10)
),
box(
title = icon("tired","fa-2x"),
sliderInput("s3", "Tired", 1, 10, 10)
),
box(
title = icon("dizzy","fa-2x"),
sliderInput("s4", "Dizzy", 1, 10, 10)
),
box(
title = icon("meh","fa-2x"),
sliderInput("s5", "Meh", 1, 10, 10)
),
box(h3("View results for past days"),
textInput('nDays', 'Number of days', value = 30),
plotlyOutput("moodPlot", height = 650))
)
),
tabItem(tabName = "dashboard",
column(width = 4,
infoBoxOutput("ib1",width = 4),
infoBoxOutput("ib2",width = 4),
infoBoxOutput("ib3",width = 4),
infoBoxOutput("ib4",width = 4),
infoBox("Heart rate", "Sync your wearable",
icon = icon("sync"), color = "olive")
),
box(h4("Experiencing a flare-up?"),
actionButton("s","Schedule a visit",
icon = icon("stethoscope")),
background = "red", width = 3)
)
)
)
)
server <- function(input, output, session) {
result_auth <- secure_server(check_credentials = check_credentials(credentials))
output$auth_output <- renderPrint({
reactiveValuesToList(result_auth)
})
Dates <- reactiveValues()
observe({
Dates$SelectedDates <- c(as.character(format(input$input_var_name[1],
format = "%m/%d/%Y")),
as.character(format(input$dateRange[2],format = "%m/%d/%Y")))
})
output$ib1 <- renderInfoBox({
infoBox("Diet",
a("Scan a food item", onclick = "openTab('diet')", href="#"),
icon = icon("barcode"),
color = "olive")
})
output$ib2 <- renderInfoBox({
infoBox("Microbiome",
a("Check results",onclick = "openTab('microbiome')", href="#"),
icon = icon("chart-area"),
color = "orange")
})
output$ib3 <- renderInfoBox({
infoBox("Clinical trial",
a("Participate",onclick = "openTab('population')", href="#"),
icon = icon("users"), color = "olive")
})
output$ib4 <- renderInfoBox({
infoBox("Mood",
a("Enter your mood",onclick = "openTab('mood')", href="#"),
icon = icon("smile-beam"), color = "orange")
})
output$moodPlot <- renderPlotly({
a = c(seq_len(input$s1),seq_len(input$s2),seq_len(input$s3),
seq_len(input$s4),seq_len(input$s5),format(Sys.Date(),"%b %d"))
mood_df <- rbind(mood_df,a)
mood_df <- tail(mood_df,input$nDays)
mdf <- melt(mood_df,id.vars = 'date')
mdf$date <- as.Date(mdf$date,format = "%b %d")
mdf$value <- as.numeric(mdf$value)
m = ggplot(mdf,aes(x=date, y = value, color = variable, group = variable)) +
geom_point() + geom_line() +
facet_wrap(~variable, ncol = 1) + theme_classic() +
scale_color_brewer(palette = "Set2") +
theme(legend.position = "none",
axis.text.x = element_text(size = 13, angle = 90))
ggplotly(m)
})
output$messageMenu <- renderMenu({
msgs <- apply(messageData, 1, function(row) {
messageItem(from = row[["from"]], message = row[["message"]])
})
dropdownMenu(type = "messages", .list = msgs)
})
output$taskMenu <- renderMenu({
tsks <- apply(taskData, 1, function(row) {
taskItem(text = row[["text"]],
value = row[["value"]],
color = row[["color"]])
})
dropdownMenu(type = "tasks", .list = tsks)
})
output$mplot <- renderPlotly({
df <- mData %>% filter(UserName == reactiveValuesToList(result_auth)$user)
colors_micro <- c("lightgrey", "#afd35a", "#ec9bfa", "#3c3e00", "#aaa4e1", "#f4f4f4", "#a717d9","#f4e909",
"#ffaa00", "#ff0000", "#69ef7b", "#d20000", "#ff5084", "#b04fbc", "#5bc07f",
"#e242a8", "#ffaae8", "#df97ac", "#ffede7", "#0024ff", "#ffa787", "#71619c",
"#668e57", "#3d7600", "#1f72d4", "#12982d", "#dd6c43", "#c25945", "#b6601e",
"#01ceff", "#02531d", "#d7dd4c", "#8f0000", "#4b03a9", "#A0447F")
micro_plot <- ggplot(data = df, aes(x=StudyDayNo, y = newvalue, fill=Species)) +
geom_area(stat = "identity") +
#facet_grid(.~UserName, scales = "free") +
scale_fill_manual(values = colors_micro) +
scale_x_discrete(drop = FALSE) +
theme_classic() +
theme(strip.text.x = element_text(angle = 0, size = 6, face = "italic"),
axis.text.x = element_text(angle = 45, hjust = 1),
axis.text.y = element_text(size = 9),
axis.title = element_text(size = 9),
plot.title = element_text(hjust = 0.5),
axis.title.x = element_blank(),
strip.background = element_rect(color = "grey"),
# legend.position = "bottom", legend.direction = "horizontal",
# legend.text = element_text(size = 7),
# legend.title = element_blank(),
legend.position = "none",
panel.spacing.x=unit(0.05, "lines")) +
guides(fill = guide_legend(reverse = TRUE,
keywidth = 0.5,
keyheight = 0.5,
ncol = 1)) +
ylab("Relative Abundance")
ggplotly(micro_plot)
})
output$nplot = renderPlotly({
df2 = nData %>% filter(UserName == reactiveValuesToList(result_auth)$user)
colors_nutr = sample(c("#bf0000", "#f29d3d", "#a3d9b1", "#bfd9ff", "#f780ff",
"#ff0000", "#ffe1bf", "#00d957", "#0020f2", "#e60099",
"#730f00", "#7f6600", "#336655", "#293aa6", "#a6538a",
"#8c4f46", "#e5c339", "#00ffcc", "#333a66", "#40202d",
"#f29979", "#fbffbf", "#00b3a7", "#8091ff", "#cc335c",
"#594943", "#a3d936", "#003033", "#300059", "#400009",
"#cc5200", "#354020", "#39c3e6", "#cbace6", "#d9a3aa",
"#7f5940", "#6a8040", "#006fa6", "#cc00ff", "#402910",
"#0a4d00", "#566573", "#83008c"))[1:41]
nutr_plot <- ggplot(data = df2, aes(x = StudyDayNo, y = newvalue , fill = Nutrient)) +
geom_area(stat = "identity") +
facet_grid(.~UserName, scales = "free") +
scale_fill_manual(values= colors_nutr) +
scale_x_discrete(drop = FALSE) +
theme_classic() +
theme(strip.text.x = element_blank(),
axis.text.x = element_blank(),
axis.text.y = element_text(size = 9),
axis.title = element_text(size = 9),
plot.title = element_text(hjust = 0.5),
axis.title.x = element_blank(),
strip.background = element_blank(),
#legend.position = "bottom", legend.direction = "horizontal",
#legend.text = element_text(size = 7),
#legend.title = element_blank(),
legend.position = "none",
panel.spacing.x=unit(0.05, "lines")) +
guides(fill = guide_legend(reverse = TRUE,
keywidth = 0.5,
keyheight = 0.5,
ncol = 5)) +
ylab("sqrt(Relative Abundance)")
ggplotly(nutr_plot)
})
}
ui <- secure_app(ui)
shinyApp(ui, server)
## Testing purposes:
#preview_mobile(appPath = system.file("app.R", package = "shinyMobile"), device = "iphoneX")
#preview_mobile(url = "https://noush-joglekar.shinyapps.io/gi_final/", device = "iphoneX")