Jupyter reports

Skill BioTender-max/awesome-bio-agent-skills/skills/bioskills/jupyter-reports

A curated collection of AI agent skills for biomedical research, covering genomics, proteomics, single-cell analysis, clinical AI, and protein design.

Install

npx -y skills add BioTender-max/awesome-bio-agent-skills --skill jupyter-reports

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One thing to look at

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What its author says it does

Copied from the file, not written here

Creates reproducible Jupyter notebooks for bioinformatics analysis with parameterization using papermill. Use when generating automated analysis reports, running notebook-based pipelines, or creating shareable computational notebooks.

SKILL.md

2.5 KB, as published. Nobody here has run it

Version Compatibility

Reference examples tested with: jupyter 1.0+, papermill 2.5+

Before using code patterns, verify installed versions match. If versions differ:

Python: pip show <package> then help(module.function) to check signatures
CLI: <tool> --version then <tool> --help to confirm flags

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

Jupyter Reports with Papermill

"Generate reproducible analysis reports" → Execute parameterized Jupyter notebooks programmatically and export as HTML/PDF reports.

Python: papermill.execute_notebook(input, output, parameters={...})
CLI: jupyter nbconvert --to html notebook.ipynb

Parameterized Notebooks

import papermill as pm

# Execute notebook with parameters
pm.execute_notebook(
    'analysis_template.ipynb',
    'output_report.ipynb',
    parameters={
        'input_file': 'data/counts.csv',
        'condition_col': 'treatment',
        'fdr_threshold': 0.05
    }
)

Creating Parameterized Templates

Mark a cell with the parameters tag in Jupyter:

# Parameters (tag this cell as "parameters")
input_file = 'default.csv'
output_dir = 'results/'
fdr_threshold = 0.05

Batch Processing

import papermill as pm
from pathlib import Path

samples = ['sample1', 'sample2', 'sample3']

for sample in samples:
    pm.execute_notebook(
        'qc_template.ipynb',
        f'reports/{sample}_qc.ipynb',
        parameters={'sample_id': sample}
    )

Converting to HTML/PDF

# Single notebook
jupyter nbconvert --to html report.ipynb

# With execution
jupyter nbconvert --execute --to html report.ipynb

# PDF (requires pandoc + LaTeX)
jupyter nbconvert --to pdf report.ipynb

Best Practices

Keep analysis code in cells, explanatory text in markdown
Use parameters for all configurable values
Include version information and timestamps
Clear outputs before committing to version control

Related Skills

reporting/quarto-reports - Alternative report format
reporting/rmarkdown-reports - R-based reports
workflows/rnaseq-to-de - Embed in workflows