Bio reporting jupyter reports

Skill bg-szy/TOP-SKILLS/skills/awesome-skills/bio-reporting-jupyter-reports

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Install

npx -y skills add bg-szy/TOP-SKILLS --skill bio-reporting-jupyter-reports

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What its author says it does

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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

2.3 KB, as published. Nobody here has run it

Jupyter Reports with Papermill

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