R Markdown Reports
Basic Document Structure
---
title: "RNA-seq Analysis Report"
author: "Your Name"
date: "`r Sys.Date()`"
output:
html_document:
toc: true
toc_float: true
code_folding: hide
theme: cosmo
---
Setup Chunk
```{r setup, include=FALSE}
knitr::opts_chunk$set(
echo = TRUE,
message = FALSE,
warning = FALSE,
fig.width = 10,
fig.height = 6,
fig.align = 'center'
)
library(tidyverse)
library(DESeq2)
library(pheatmap)
```
Code Chunk Options
```{r analysis, echo=TRUE, results='hide'}
# echo: show code
# results: 'hide', 'asis', 'markup'
# include: FALSE hides chunk entirely
# eval: FALSE shows code but doesn't run
# cache: TRUE caches results
```
Parameterized Reports
---
title: "Sample Report"
params:
sample_id: "sample1"
count_file: "counts.csv"
fdr_threshold: 0.05
---
```{r}
counts <- read.csv(params$count_file)
sample <- params$sample_id
fdr <- params$fdr_threshold
```
# Render with parameters
rmarkdown::render('report.Rmd', params = list(sample_id = 'sample2', fdr_threshold = 0.01))
# Batch render
samples <- c('sample1', 'sample2', 'sample3')
for (s in samples) {
rmarkdown::render('report.Rmd', params = list(sample_id = s),
output_file = paste0(s, '_report.html'))
}
Tables
```{r}
# Basic kable table
knitr::kable(head(results), caption = 'Top DE genes')
# Interactive table with DT
library(DT)
datatable(results, filter = 'top', options = list(pageLength = 10))
# Formatted table with kableExtra
library(kableExtra)
results %>%
head(10) %>%
kable() %>%
kable_styling(bootstrap_options = c('striped', 'hover')) %>%
row_spec(which(results$padj < 0.01), bold = TRUE, color = 'red')
```
Figures
```{r volcano-plot, fig.cap="Volcano plot of differential expression"}
ggplot(results, aes(log2FoldChange, -log10(pvalue))) +
geom_point(aes(color = padj < 0.05)) +
theme_minimal()
```
Inline Code
We identified `r sum(res$padj < 0.05, na.rm=TRUE)` significantly
DE genes (FDR < 0.05) out of `r nrow(res)` tested.
Child Documents
---
title: "Main Report"
---
```{r child='methods.Rmd'}
```
```{r child='results.Rmd'}
```
PDF Output
---
output:
pdf_document:
toc: true
number_sections: true
fig_caption: true
latex_engine: xelatex
---
HTML with Tabs
## Results {.tabset}
### PCA Plot
```{r}
plotPCA(vsd, intgroup = 'condition')
```
### Heatmap
```{r}
pheatmap(assay(vsd)[top_genes, ])
```
Caching Long Computations
```{r deseq-analysis, cache=TRUE, cache.extra=tools::md5sum('counts.csv')}
# Cached unless counts.csv changes
dds <- DESeqDataSetFromMatrix(counts, metadata, ~ condition)
dds <- DESeq(dds)
```
```{r downstream, dependson='deseq-analysis'}
# Re-runs when deseq-analysis cache changes
res <- results(dds)
```
Custom CSS
---
output:
html_document:
css: custom.css
---
/* custom.css */
body { font-family: 'Helvetica', sans-serif; }
h1 { color: #2c3e50; }
.figure { margin: 20px auto; }
Complete Report Template
---
title: "RNA-seq Analysis Report"
author: "Bioinformatics Core"
date: "`r Sys.Date()`"
output:
html_document:
toc: true
toc_float: true
code_folding: hide
params:
count_file: "counts.csv"
metadata_file: "metadata.csv"
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE, message = FALSE, warning = FALSE)
library(DESeq2)
library(tidyverse)
library(pheatmap)
library(DT)
```
## Data Overview
```{r load-data}
counts <- read.csv(params$count_file, row.names = 1)
metadata <- read.csv(params$metadata_file, row.names = 1)
```
Loaded `r nrow(counts)` genes across `r ncol(counts)` samples.
## Differential Expression
```{r de-analysis, cache=TRUE}
dds <- DESeqDataSetFromMatrix(counts, metadata, ~ condition)
dds <- DESeq(dds)
res <- results(dds) %>% as.data.frame() %>% arrange(padj)
```
## Results
```{r results-table}
datatable(res %>% filter(padj < 0.05), options = list(pageLength = 10))
```
Related Skills
- reporting/quarto-reports - Modern alternative
- data-visualization/ggplot2-fundamentals - Figure creation
- differential-expression/de-visualization - Analysis plots
FridrichMethod