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rmd template
---
title: "<title>"
author: "<name>"
date: 'Compiled: `r format(Sys.Date(), "%B %d, %Y")`'
editor_options:
chunk_output_type: console
output:
html_document:
keep_md: true
engine: knitr
---
```{r setup, include=FALSE}
# Set global R options for efficient output
options(
max.print = 500, # Reduced limit for printing
scipen = 10 # Moderate scientific notation suppression
)
# Set knitr chunk options for compact output
knitr::opts_chunk$set(
echo = TRUE, # Show code
message = FALSE, # Suppress package messages
warning = FALSE, # Suppress warnings
collapse = TRUE, # Combine code and output
comment = "#>", # Standard comment for output
dpi = 300, # Balanced resolution for web
out.width = "100%" # Full-width plots
)
# Set seed for reproducibility
set.seed(123)
```
```{r load-libraries, message=TRUE, warning=TRUE}
library(here) # File path management
library(this.path) # Retrieve its own path without the explicit need to write it elsewhere
library(tinytable) # For saving tables as images
library(tidyverse) # Data manipulation, CSV reading, and plotting (includes dplyr, tidyr, readr, ggplot2)
library(ggrepel) # Non-overlapping labels
library(scales) # Label formatting
library(patchwork) # Combine multiple plots
```
```{r configuration}
# File Paths
# Define the output directory for results
output_dir <- here("analysis_results", gsub(
"\\.([^\\.]+)$", # change .<ext>
"_\\1", # to _<ext>
basename(this.path())
))
# Define the path to the directory containing the processed Excel files
data_dir <- here("raw_data")
# Visualization (optimized for google slides)
plot_width <- 8.2 # Inches
plot_height <- 4.8 # Inches
plot_units <- "in"
plot_res <- 300 # dpi
padj_threshold <- 0.05 # Significance threshold
```
# --- Start working ---
```{r}
```
```{r}
plot_file <- file.path(output_dir, "plot_ggplot.png")
# <ggplot2 script>
# ggsave(
# plot_file,
# plot = plot_gg,
# width = plot_width,
# height = plot_height,
# units = plot_units,
# dpi = plot_res,
# bg = 'white'
# )
```
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