Bio Reporting Quarto Reports

Quarto Reports

Basic Document

---
title: "Analysis Report"
author: "Your Name"
date: today
format:
  html:
    toc: true
    code-fold: true
    theme: cosmo
---

Python Document

````markdown --- title: "scRNA-seq Analysis" format: html jupyter: python3 ---

```{python} import scanpy as sc import matplotlib.pyplot as plt

adata = sc.read_h5ad('data.h5ad') sc.pl.umap(adata, color='leiden')

R Document

````markdown --- title: "DE Analysis" format: html ---

```{r} library(DESeq2) dds <- DESeqDataSetFromMatrix(counts, metadata, ~ condition) dds <- DESeq(dds)

Multiple Formats

---
title: "Multi-format Report"
format:
  html:
    toc: true
  pdf:
    documentclass: article
  docx:
    reference-doc: template.docx
---

# Render all formats
quarto render report.qmd

# Render specific format
quarto render report.qmd --to pdf

Parameters

---
title: "Parameterized Report"
params:
  sample: "sample1"
  threshold: 0.05
---

# Render with parameters
quarto render report.qmd -P sample:sample2 -P threshold:0.01

Tabsets

````markdown ::: {.panel-tabset}

PCA

```{r} plotPCA(vsd)

## Heatmap

pheatmap(mat)

:::

Callouts

::: {.callout-note}
This is an important note about the analysis.
:::

::: {.callout-warning}
Check your input data format before proceeding.
:::

::: {.callout-tip}
Use caching for long computations.
:::

Cross-References

````markdown See @fig-volcano for the volcano plot.

```{r} #| label: fig-volcano #| fig-cap: "Volcano plot showing DE genes" ggplot(res, aes(log2FC, -log10(pvalue))) + geom_point()

Results are summarized in @tbl-summary.

#| label: tbl-summary #| tbl-cap: "Summary statistics" knitr::kable(summary_df)

Code Cell Options

```markdown ``{python} #| echo: true #| warning: false #| fig-width: 10 #| fig-height: 6 #| cache: true

import scanpy as sc sc.pl.umap(adata, color='leiden')

Inline Code

We found `{python} len(sig_genes)` significant genes.
We found `{r} nrow(sig)` significant genes.

Presentations

---
title: "Analysis Results"
format: revealjs
---

## Slide 1

Content here

## Slide 2 {.smaller}

More content with smaller text

Quarto Projects

# _quarto.yml
project:
  type: website
  output-dir: docs

website:
  title: "Analysis Portal"
  navbar:
    left:
      - href: index.qmd
        text: Home
      - href: methods.qmd
        text: Methods
      - href: results.qmd
        text: Results

Bibliography

---
bibliography: references.bib
csl: nature.csl
---

Gene expression analysis was performed using DESeq2 [@love2014].

## References

Freeze Computations

# _quarto.yml
execute:
  freeze: auto  # Only re-run when source changes

Include Files

{{< include _methods.qmd >}}

Diagrams with Mermaid

```markdown ``{mermaid} flowchart LR A[Raw Data] --> B[QC] B --> C[Alignment] C --> D[Quantification] D --> E[DE Analysis]

Multi-Language Document

````markdown --- title: "R + Python Analysis" ---

Load in R: ```{r} library(reticulate) counts <- read.csv('counts.csv')

Process in Python:

import pandas as pd counts_py = r.counts # Access R object

Related Skills

• reporting/rmarkdown-reports - R-focused alternative
• data-visualization/ggplot2-fundamentals - R visualizations
• workflow-management/snakemake-workflows - Pipeline integration