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withggplot_v3.17pub.R
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withggplot_v3.17pub.R
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##############################Packages_Needed###################################
library(shiny)
library(readxl)
library(agricolae)
library(markdown)
library(bslib)
library(pastecs)
library(corrplot)
library(GGally)
library(ggplot2)
library(correlation)
library(flextable)
library(fixr)
#####################################UI#########################################
ui <- fluidPage(theme = bs_theme(version = 4, bootswatch = "litera"),
navbarPage(title = div(img(src = "favicon.png", height = 30), "AgriAnalytics@R Ver. 3.17", img(src = "ICAR.png", height = 30)),
tabPanel("Upload",
fluidRow(
column(width = 4,
fileInput("file", "Choose Excel File",
accept = c(".xlsx", ".csv")),
tableOutput("data_preview")
),
column(width = 8)
)
),
tabPanel("Descriptive Statistics",
fluidRow(
column(width = 3,
selectInput("desc_xvar", "Select a Variable",
choices = NULL),
selectInput("desc_grvar", "Select a Group Variable",
choices = NULL)
),
column(width = 9,
plotOutput("boxplot"),
uiOutput("summary")
)
)
),
tabPanel("ANOVA",
tabsetPanel(
id = "anova_tabs",
tabPanel("Anova CRD",
fluidRow(
column(width = 4,
selectInput("xvar_crd", "Select Treatment Variable",
choices = NULL),
selectInput("yvar_crd", "Select Response Variable",
choices = NULL, multiple = TRUE),
actionButton("run_crd", "Run ANOVA")
),
column(width = 8,
div(
verbatimTextOutput("anova_crd"),
style = "max-height: 500px; overflow-y: scroll;"),
downloadButton("download_anova_crd", "Download ANOVA Results as RTF")
)
)
),
tabPanel("Plot CRD",
fluidRow(
column(width = 4,
selectInput("xvar_crd_plot", "Select Treatment Variable",
choices = NULL),
selectInput("yvar_crd_plot", "Select Response Variable",
choices = NULL),
numericInput("plot_crd_width", "Plot Width", 800),
numericInput("plot_crd_height", "Plot Height", 800),
numericInput("plot_crd_resolution", "Plot Resolution", 120),
actionButton("run_crd_plot", "Plot ANOVA")
),
column(width = 8,
plotOutput("plot_crd"),
downloadButton("download_plot_crd", "Download ANOVA PLOT as PNG")
)
)
),
tabPanel("Anova RBD",
fluidRow(
column(width = 4,
selectInput("xvar_rbd", "Select Treatment Variable",
choices = NULL),
selectInput("rep_var_rbd", "Select Replication Variable",
choices = NULL),
selectizeInput("yvar_rbd", "Select Response Variable",
choices = NULL, multiple = TRUE),
actionButton("run_rbd", "Run ANOVA")
),
column(width = 8,
div(
verbatimTextOutput("anova_rbd"),
style = "max-height: 500px; overflow-y: scroll;"),
downloadButton("download_anova_rbd", "Download ANOVA Results as RTF")
)
)
),
tabPanel("Plot RBD",
fluidRow(
column(width = 4,
selectInput("xvar_rbd_plot", "Select Treatment Variable",
choices = NULL),
selectInput("rep_var_rbd_plot", "Select Replication Variable",
choices = NULL),
selectInput("yvar_rbd_plot", "Select Response Variable",
choices = NULL),
numericInput("plot_rbd_width", "Plot Width", 800),
numericInput("plot_rbd_height", "Plot Height", 800),
numericInput("plot_rbd_resolution", "Plot Resolution", 120),
actionButton("run_rbd_plot", "Plot ANOVA"),
),
column(width = 8,
plotOutput("plot_rbd"),
downloadButton("download_plot_rbd", "Download ANOVA PLOT as PNG")
)
)
)
)
),
tabPanel("Correlation",
fluidRow(
column(width = 4,
selectizeInput("xvar_cor", "Select Variables",
choices = NULL, multiple = TRUE
),
uiOutput("cor_output_selector"),
actionButton("run_cor", "Run Correlation")
),
column(width = 8,
conditionalPanel(condition = "input.cor_output=='cor_out'",
verbatimTextOutput("cor_out"),
downloadButton("download_cor", "Download Correlation Results as RTF")
),
conditionalPanel(condition = "input.cor_output=='cor_out_2'",
verbatimTextOutput("cor_out_2"),
downloadButton("download_cor_2", "Download Individual Correlation Results as RTF")
),
conditionalPanel(condition = "input.cor_output=='plot_cor'",
plotOutput("plot_cor"),
downloadButton("download_plot_cor", "Download Correlogram as PNG")
),
conditionalPanel(condition = "input.cor_output=='plot_cor_2'",
plotOutput("plot_cor_2"),
downloadButton("download_plot_cor_2", "Download Scatterplot Matrix as PNG")
)
)
)
),
tabPanel("About",
uiOutput("about_ui")
)
)
)
################################################################################
####################################Server######################################
server <- function(input, output, session) {
df_ori <- reactive({
req(input$file)
file <- input$file
ext <- tools::file_ext(file$datapath)
if (ext %in% c("xlsx", "xls")) {
read_excel(file$datapath)
} else if (ext == "csv") {
read.csv(file$datapath)
} else {
stop("Invalid file type")
}
})
df <- reactive({
fix_column_names(df_ori())
})
###################################UPLOAD#######################################
# Data preview
output$data_preview <- renderTable({
df()
})
############################DESCRIPTIVE STATISTICS##############################
# Descriptive statistics output
observeEvent(df(), {
updateSelectInput(session, "desc_xvar", "Select Response Variable", choices = names(df()))
updateSelectInput(session, "desc_grvar", "Select Group Variable", choices = c("None", names(df())))
})
output$summary <- renderUI({
dat <- data.frame(
Descriptors = c("nbr.val", "nbr.null", "nbr.na", "min", "max", "range", "sum", "median", "mean", "SE.mean", "CI.mean.0.95", "var", "std.dev", "coef.var"),
stat.desc(df()) %>% round(2))
tbl <- flextable(dat)
htmltools_value(tbl)
})
output$boxplot <- renderPlot({
y <- input$desc_xvar
grv <- input$desc_grvar
if (grv == "None") {
boxplot(df()[[y]], main = paste("Boxplot of", y), xlab = "",
ylab = paste(y))
} else {
boxplot(df()[[y]]~df()[[grv]], main = paste("Boxplot of", y), xlab = paste(grv),
ylab = paste(y))
}
})
###################################ANOVA CRD####################################
# ANOVA_crd results output
observeEvent(df(), {
numeric_cols <- sapply(df(), is.numeric)
updateSelectInput(session, "xvar_crd", "Choose the Treatment variable", choices = names(df()))
updateSelectInput(session, "yvar_crd", "Choose the Response variable", choices = names(df())[numeric_cols])
})
observeEvent(input$run_crd, {
if (!is.null(df())) {
x <- input$xvar_crd
y <- input$yvar_crd
if (is.null(y)) {
return()
}
if (length(y) > 1) {
# create a list to store the results for each response variable
anova_list <- list()
for (i in 1:length(y)) {
# fit the ANOVA model for each response variable
model_crd <- lm(paste(y[i], "~", x), data = df())
model_lsd_crd <- LSD.test(model_crd, x, p.adj = "none")
anova_list[[y[i]]] <- list(anova = anova(model_crd), lsd_groups = model_lsd_crd$groups)
}
} else {
# fit the ANOVA model for a single response variable
model_crd <- lm(paste(y, "~", x), data = df())
model_lsd_crd <- LSD.test(model_crd, x, p.adj = "none")
# store the results in a list
anova_list <- list(anova = anova(model_crd), lsd_groups = model_lsd_crd$groups)
}
#Tab ANOVA First row
output$anova_crd <- renderPrint({
anova_list
})
# Download ANOVA results as RTF
filename <- paste0("anova_crd_results_", Sys.Date(), ".rtf")
sink(filename)
print(anova_list)
sink()
output$download_anova_crd <- downloadHandler(
filename = function() {
filename
},
content = function(file) {
file.copy(filename, file)
}
)
#Tab ANOVA Third row
output$plot_crd <- renderPlot({
plot(model_lsd_crd)
})
#Download ANOVA plot as PNG
output$download_plot_crd <- downloadHandler(
filename = function() {
paste("anova_plot", ".png", sep = "")
},
content = function(file) {
png(file, width = 800, height = 800, res = 120)
par(cex.lab = 1.5, cex.main = 1.5, mar = c(2,2,2,2))
plot(model_lsd_crd)
dev.off()
}
)
}
})
###################################ANOVA RBD####################################
# ANOVA_rbd results output
observeEvent(df(), {
numeric_cols <- sapply(df(), is.numeric)
updateSelectInput(session, "xvar_rbd", "Choose the Treatment variable", choices = names(df())[numeric_cols])
updateSelectInput(session, "rep_var_rbd", "Choose the Replication factor", choices = names(df()))
updateSelectInput(session, "yvar_rbd", "Choose the Response variable", choices = names(df())[numeric_cols])
})
observeEvent(input$run_rbd, {
if (!is.null(df())) {
x <- input$xvar_rbd
y <- input$yvar_rbd
r <- input$rep_var_rbd
if (is.null(y)) {
return()
}
if (length(y) > 1) {
# create a list to store the results for each response variable
anova_list <- list()
for (i in 1:length(y)) {
# fit the ANOVA model for each response variable
model_rbd <- lm(paste(y[i], "~", r, "+", x), data = df())
model_lsd_rbd <- LSD.test(model_rbd, x, p.adj = "none")
anova_list[[y[i]]] <- list(anova = anova(model_rbd), lsd_groups = model_lsd_rbd$groups)
}
} else {
# fit the ANOVA model for a single response variable
model_rbd <- lm(paste(y, "~", r, "+", x), data = df())
model_lsd_rbd <- LSD.test(model_rbd, x, p.adj = "none")
# store the results in a list
anova_list <- list(anova = anova(model_rbd), lsd_groups = model_lsd_rbd$groups)
}
#Tab ANOVA First row
output$anova_rbd <- renderPrint({
anova_list
})
#Download ANOVA results as RTF
filename <- paste0("anova_results_", Sys.Date(), ".rtf")
sink(filename)
print(anova_list)
sink()
output$download_anova_rbd <- downloadHandler(
filename = function() {
filename
},
content = function(file) {
file.copy(filename, file)
}
)
}
})
###################################ANOVA CRD PLOT####################################
# ANOVA_crd results plot output
observeEvent(df(), {
numeric_cols <- sapply(df(), is.numeric)
updateSelectInput(session, "xvar_crd_plot", "Choose the Treatment variable", choices = names(df()))
updateSelectInput(session, "yvar_crd_plot", "Choose the Response variable", choices = names(df())[numeric_cols])
})
observeEvent(input$run_crd_plot, {
if (!is.null(df())) {
x <- input$xvar_crd_plot
y <- input$yvar_crd_plot
if (is.null(y)) {
return()
}
# fit the ANOVA model for a single response variable
model_crd_plot <- lm(paste(y, "~", x), data = df())
model_lsd_crd_plot <- LSD.test(model_crd_plot, x, p.adj = "none")
#Tab ANOVA Third row
output$plot_crd <- renderPlot({
plot(model_lsd_crd_plot, xlab = input$xvar_crd_plot, ylab = input$yvar_crd_plot,
width = input$plot_crd_width, height = input$plot_crd_height)
})
#Download ANOVA plot as PNG
output$download_plot_crd <- downloadHandler(
filename = function() {
paste("anova_plot", ".png", sep = "")
},
content = function(file) {
png(file, width = input$plot_crd_width, height = input$plot_crd_height, res = input$plot_crd_resolution)
par(cex.lab = 1.5, cex.main = 1.5, mar = c(2, 2, 2, 2))
plot(model_lsd_crd_plot, xlab = input$xvar_crd_plot, ylab = input$yvar_crd_plot,
width = input$plot_crd_width, height = input$plot_crd_height)
dev.off()
}
)
}
})
###################################ANOVA RBD PLOT####################################
# ANOVA_rbd results plot output
observeEvent(df(), {
numeric_cols <- sapply(df(), is.numeric)
updateSelectInput(session, "xvar_rbd_plot", "Choose the Treatment variable", choices = names(df())[numeric_cols])
updateSelectInput(session, "rep_var_rbd_plot", "Choose the Replication factor", choices = names(df()))
updateSelectInput(session, "yvar_rbd_plot", "Choose the Response variable", choices = names(df())[numeric_cols])
})
observeEvent(input$run_rbd_plot, {
if (!is.null(df())) {
x <- input$xvar_rbd_plot
y <- input$yvar_rbd_plot
r <- input$rep_var_rbd_plot
if (is.null(y)) {
return()
}
# fit the ANOVA model for a single response variable
model_rbd_plot <- lm(paste(y, "~", r, "+", x), data = df())
model_lsd_rbd_plot <- LSD.test(model_rbd_plot, x, p.adj = "none")
# Tab ANOVA Third row
output$plot_rbd <- renderPlot({
plot(model_lsd_rbd_plot, xlab = input$xvar_rbd_plot, ylab = input$yvar_rbd_plot)
})
# Download ANOVA plot as PNG
output$download_plot_rbd <- downloadHandler(
filename = function() {
paste("anova_plot", ".png", sep = "")
},
content = function(file) {
png(file, width = input$plot_rbd_width, height = input$plot_rbd_height, res = input$plot_rbd_resolution)
par(cex.lab = 1.5, cex.main = 1.5, mar = c(5, 4, 4, 2))
plot(model_lsd_rbd_plot, xlab = input$xvar_rbd_plot, ylab = input$yvar_rbd_plot,
width = input$plot_rbd_width, height = input$plot_rbd_height)
dev.off()
}
)
}
})
#################################CORRELATION####################################
# Correlation results output
observeEvent(df(), {
numeric_cols <- sapply(df(), is.numeric)
updateSelectizeInput(session, "xvar_cor", "Choose Variables",
choices = names(df())[numeric_cols])
})
observeEvent(input$run_cor, {
if (!is.null(df())) {
x <- input$xvar_cor
y <- input$yvar_cor
model_cor <- round(cor(df()[, c(x, y = NULL)]), 2)
model_cor_2 <- correlation::correlation((df()[, c(x, y = NULL)]),include_factors = TRUE, method = "auto")
#Tab Correlation First row
output$cor_out <- renderPrint({
model_cor
})
#Download Correlation as RTF
filename <- paste0("Correlation_results_", Sys.Date(), ".rtf")
sink(filename)
print(model_cor)
sink()
output$download_cor <- downloadHandler(
filename = function() {
filename
},
content = function(file) {
file.copy(filename, file)
}
)
#Tab Correlation Second row
output$cor_out_2 <- renderPrint({
model_cor_2
})
#Download Correlation as RTF
filename <- paste0("Correlation_results_withp_", Sys.Date(), ".rtf")
sink(filename)
print(model_cor_2)
sink()
output$download_cor_2 <- downloadHandler(
filename = function() {
filename
},
content = function(file) {
file.copy(filename, file)
}
)
#Tab Correlation Third row
output$plot_cor <- renderPlot({
corrplot(model_cor)
})
#Download corrplot as PNG
output$download_plot_cor <- downloadHandler(
filename = function() {
paste("cor_plot", ".png", sep = "")
},
content = function(file) {
png(file, width = 800, height = 800, res = 120)
par(cex.lab = 1.5, cex.main = 1.5, mar = c(2,2,2,2))
corrplot(model_cor)
dev.off()
}
)
#Tab Correlation Third row
output$plot_cor_2 <- renderPlot({
ggpairs(df()[, x])
})
# Download corrplot as PNG_2
output$download_plot_cor_2 <- downloadHandler(
filename = function() {
paste("scatter_plot", ".png", sep = "")
},
content = function(file) {
ggsave(file, plot = ggpairs(df()[, x]))
}
)
}
})
# Correlation output selector
output$cor_output_selector <- renderUI({
selectInput(
"cor_output",
"Select correlation output",
choices = c("Correlation Matrix" = "cor_out",
"Correlation Matrix with P value" = "cor_out_2",
"Correlogram" = "plot_cor",
"Scatterplot Matrix" = "plot_cor_2")
)
})
# Display selected correlation output
output$selected_cor_output <- renderPrint({
eval(parse(text = input$cor_output))
})
###################################ABOUT########################################
#Read the contents of the README.md file
about_text <- readLines("README.md")
#Render the contents of the README.md file as Markdown
output$about_ui <- renderText({
HTML(renderMarkdown(about_text))
})
}
#################################App_Exec#######################################
shinyApp(ui, server)