Nothing
R/correlation.R
Defines functions correlation_multi
Documented in correlation_multi
#' Run the Shiny App for Correlation Analysis of multiple variables
#'
#' App allows user to import data through excel/.csv files or through clipboard
#' and select the correlation method and download the results with few customization options
#'
#' @details
#' This Shiny app is part of the `visvaR` package and is designed for
#' correlation analysis and user can download the report in word format also has
#' option to download the correlation plot as .png file. To use custom fonts, please install the `extrafont` package and run `extrafont::font_import()` and `extrafont::loadfonts()`.
#'
#' @return
#' This function runs a local instance of the Shiny app in your default web
#' browser. The app interface allows users to upload data, select analysis
#' methods, and download outputs.
#' @usage correlation_multi
#' @aliases cor_multiple
#' @aliases correlation_multi
#' @name correlation_multi
#' @examples
#' # Example 1: Basic usage
#' if(interactive()) {
#' correlation_multi()
#' }
#'
#' # Example 2: Sample workflow with iris dataset
#' if(interactive()) {
#' # Prepare sample data
#' write.csv(iris[, 1:4], "sample_data.csv", row.names = FALSE)
#'
#' # Launch the app
#' correlation_multi()
#'
#' # Instructions for users:
#' # 1. Click "Choose a file" and select sample_data.csv
#' # 2. Select correlation method (e.g., "pearson")
#' # 3. Click "Analyze"
#' # 4. View results in different tabs
#' # 5. Download plot or Word report as needed
#'
#' # Clean up
#' unlink("sample_data.csv")
#' }
#'
#' # Example 3: Using clipboard data
#' if(interactive()) {
#' # Copy this to clipboard:
#' # Var1,Var2,Var3
#' # 1,2,3
#' # 4,5,6
#' # 7,8,9
#'
#' correlation_multi()
#' # Click "Paste from Clipboard" after copying data
#' }
#'
#' @author Ramesh Ramasamy
#' @author Mathiyarsai Kulandaivadivel
#' @author Tamilselvan Arumugam
#' @references Wei, T., & Simko, V. (2021). R package 'corrplot': Visualization of a Correlation Matrix (Version 0.92). Available from https://CRAN.R-project.org/package=corrplot.
#' Friendly, M. (2002). Corrgrams: Exploratory displays for correlation matrices. The American Statistician, 56(4), 316-324.
#' @import DT
#' @import corrplot
#' @import bslib
#' @import corrplot
#' @importFrom readxl read_excel
#' @import officer
#' @import flextable
#' @importFrom tools file_ext
#' @importFrom htmltools HTML
#' @importFrom utils read.delim read.csv
#' @importFrom stats cor
#' @importFrom graphics par
#' @importFrom grDevices png dev.off
NULL
#' @export
correlation_multi<-function(){
default_data <- data.frame(
Var1 = stats::rnorm(10),
Var2 = stats::rnorm(10),
Var3 = stats::rnorm(10),
Var4 = stats::rnorm(10)
)
correlation_multi_ui <- shiny::fluidPage(
theme = bslib::bs_theme(
version = 5,
bootswatch = "simplex",
primary = "#007bff",
"font-size-base" = "0.95rem"
),
shiny::tags$head(
shiny::tags$style(HTML("
h1 {
text-align: center;
}
.btn-info {
margin: 5px;
}
"))
),
shiny::h1("Correlation Analysis (Multiple variables)",
style = "font-family:Times New Roman; font-weight: bold; font-size: 36px; color: #890304;"),
shiny::sidebarLayout(
shiny::sidebarPanel(
position = "right",
fluid = TRUE,
shiny::actionButton("clipboard_input", "Paste from Clipboard",
class = "btn-primary",
style = "margin-bottom: 10px;"),
shiny::fileInput("file", "Or choose a file (CSV or Excel)",
accept = c(".csv", ".xlsx")),
shiny::selectInput("method", "Correlation Method:",
choices = c("pearson", "kendall", "spearman"),
selected = "pearson"), # Default method
shiny::selectInput("plot_method", "Plot Method:",
choices = c('circle', 'square', 'ellipse', 'number', 'shade', 'color', 'pie'),
selected = "circle"), # Default method
shiny::hr(),
shiny::selectInput("font_family", "Choose Font Style:",
choices = c("Times New Roman", "Arial", "Helvetica", "serif", "sans", "mono"),
selected = "Times New Roman"), # Default font
shiny::numericInput("font_size", "Font Size:",
value = 12, min = 8, max = 20),
shiny::selectInput("color_palette", "Choose Color Palette:",
choices = c("RdYlBu", "RdBu", "PuOr", "PRGn", "BrBG", "PiYG"),
selected = "RdYlBu"), # Default palette
shiny::numericInput("plot_width", "Plot Width (inches):",
value = 10, min = 1, max = 20),
shiny::numericInput("plot_height", "Plot Height (inches):",
value = 10, min = 1, max = 20),
shiny::numericInput("plot_dpi", "Plot Resolution(dpi):",
value = 300, min = 72, max = 600),
shiny::actionButton("analyze", "Analyze",
style = "color: green; background-color: #4CAF50; font-size: 20px; margin: 10px 0;"),
shiny::downloadButton("download_plot", "Download Plot",
class = "btn-info"),
shiny::downloadButton("download_word", "Download Word Report",
class = "btn-info"),
shiny::fluidPage(
shiny::fluidRow(
shiny::column(9, offset = 1,
bslib::card(
uiOutput("logo"),
height = "auto",
bslib::card_header(
shiny::div(
class = "text-center",
"visvaR- VISualize VARiance"
),
class = "bg-primary text-white"
),
shiny::HTML("
<p style='text-align: center;'>
<strong>Developed by</strong><br>
<span style='font-size: 24px;'>Ramesh R</span><br>
<span>PhD Scholar</span><br>
<span>Division of Plant Physiology </span><br> ICAR-IARI, New Delhi</span><br>
<span>ramesh.rahu96@gmail.com</span>
</p>
")
)
)
)
)
),
shiny::mainPanel(
shiny::tabsetPanel(
shiny::tabPanel("Data Preview",
shiny::div(
style = "margin-top: 20px;",
DT::DTOutput("data_preview")
)
),
shiny::tabPanel("Correlation Plot",
shiny::div(
style = "margin-top: 20px;",
shiny::plotOutput("correlation_plot", height = "600px")
)
),
shiny::tabPanel("Correlation Matrix",
shiny::div(
style = "margin-top: 20px;",
DT::DTOutput("correlation_matrix")
)
)
)
)
)
)
correlation_multi_server <- function(input, output, session) {
# Initialize reactive values with default data
data_reactive <- shiny::reactiveVal(default_data)
correlation_matrix <- shiny::reactiveVal(cor(default_data))
original_names <- shiny::reactiveVal(colnames(default_data))
session$onSessionEnded(function() {
shiny::stopApp()
})
# Observe event for clipboard input
shiny::observeEvent(input$clipboard_input, {
tryCatch({
df <- read.delim("clipboard", header = TRUE, check.names = FALSE)
data_reactive(df)
original_names(colnames(df))
shiny::showNotification("Data successfully read from clipboard", type = "message")
}, error = function(e) {
shiny::showNotification("Error reading from clipboard. Please try again.", type = "error")
})
})
# Observe event for file input
shiny::observeEvent(input$file, {
shiny::req(input$file)
ext <- tools::file_ext(input$file$name)
tryCatch({
if (ext == "csv") {
df <- read.csv(input$file$datapath, header = TRUE, check.names = FALSE)
} else if (ext == "xlsx") {
df <- readxl::read_excel(input$file$datapath, col_names = TRUE)
} else {
stop("Unsupported file format")
}
data_reactive(df)
original_names(colnames(df))
shiny::showNotification("File successfully uploaded", type = "message")
}, error = function(e) {
shiny::showNotification(paste("Error reading file:", e$message), type = "error")
})
})
# Render data table with improved styling
output$data_preview <- DT::renderDT({
shiny::req(data_reactive())
DT::datatable(
data_reactive(),
options = list(
scrollX = TRUE,
scrollY = "400px",
pageLength = 15,
dom = 'Bfrtip',
buttons = c('copy', 'csv', 'excel')
),
class = 'cell-border stripe'
)
})
# Analyze data for correlation matrix
shiny::observeEvent(input$analyze, {
shiny::req(data_reactive())
M <- cor(data_reactive(), method = input$method)
correlation_matrix(M)
})
# Create the correlation plot with improved styling
create_correlation_plot <- function() {
shiny::req(correlation_matrix())
M <- correlation_matrix()
res1 <- corrplot::cor.mtest(data_reactive(), conf.level = 0.95)
oldpar <- par(no.readonly = TRUE)
on.exit(par(oldpar))
par(mfrow = c(1, 1),
mar = c(5, 4, 4, 2) + 0.1,
family = input$font_family)
corrplot::corrplot(
M,
p.mat = res1$p,
order = "AOE",
method = input$plot_method,
type = "upper",
tl.pos = "lt",
tl.col = "black",
insig = "label_sig",
sig.level = c(0.001, 0.01, 0.05),
pch.cex = 2,
pch.col = "black",
tl.srt = 45,
col = corrplot::COL2(input$color_palette, 10),
tl.offset = 0.5
)
corrplot::corrplot(
M,
add = TRUE,
type = "lower",
method = "number",
col = "black",
number.cex = input$font_size / 12,
order = "AOE",
diag = FALSE,
tl.pos = "n",
cl.pos = "n"
)
}
# Render the correlation plot
output$correlation_plot <- shiny::renderPlot({
create_correlation_plot()
})
# Render the correlation matrix with improved styling
output$correlation_matrix <- DT::renderDT({
shiny::req(correlation_matrix())
matrix_with_names <- correlation_matrix()
colnames(matrix_with_names) <- original_names()
rownames(matrix_with_names) <- original_names()
DT::datatable(
round(matrix_with_names, 2),
options = list(
scrollX = TRUE,
scrollY = "400px",
dom = 'Bfrtip',
buttons = c('copy', 'csv', 'excel')
),
class = 'cell-border stripe'
)
})
# Download handlers remain the same
output$download_plot <- shiny::downloadHandler(
filename = function() {
paste("correlation_plot_", Sys.Date(), ".png", sep = "")
},
content = function(file) {
png(file, width = input$plot_width, height = input$plot_height,
units = "in", res = input$plot_dpi)
create_correlation_plot()
dev.off()
}
)
output$download_word <- shiny::downloadHandler(
filename = function() {
paste("correlation_analysis_report_", Sys.Date(), ".docx", sep = "")
},
content = function(file) {
doc <- officer::read_docx()
fp_bold <- officer::fp_text_lite(bold = TRUE)
fp_refnote <- officer::fp_text_lite(vertical.align = "baseline")
bl <- officer::block_list(
officer::fpar(officer::ftext("Analysis done using visvaR R package ", fp_bold)),
officer::fpar(officer::ftext("Developed by Ramesh R PhD scholar, Division of Plant Physiology, ICAR-IARI, New Delhi", fp_bold))
)
a_par <- officer::fpar(
"visvaR- Visualize Variance ",
officer::run_footnote(x = bl, prop = fp_refnote),
""
)
doc <- officer::body_add_fpar(doc, value = a_par, style = "Normal")
flextable::set_flextable_defaults(
font.size = 12,
font.family = "Times New Roman",
font.color = "#333333",
table.layout = "autofit",
border.color = "black"
)
doc <- doc %>%
officer::body_add_par("Correlation Analysis Report", style = "heading 1")
temp_plot <- tempfile(fileext = ".png")
png(temp_plot, width = input$plot_width, height = input$plot_height,
units = "in", res = input$plot_dpi)
create_correlation_plot()
dev.off()
doc <- doc %>%
officer::body_add_par("Correlation Plot", style = "heading 2") %>%
officer::body_add_img(src = temp_plot, width = 6, height = 6)
doc <- doc %>%
officer::body_add_par("Correlation Matrix", style = "heading 2")
matrix_with_names <- correlation_matrix()
colnames(matrix_with_names) <- original_names()
rownames(matrix_with_names) <- original_names()
matrix_table <- flextable::flextable(round(as.data.frame(matrix_with_names), 2))
matrix_table <- flextable::autofit(matrix_table)
matrix_table <- flextable::add_footer_lines(matrix_table,
paste("Method used:", input$method))
doc <- doc %>%
body_add_flextable(matrix_table)
print(doc, target = file)
}
)
}
shiny::shinyApp(ui = correlation_multi_ui, server = correlation_multi_server)
}
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