omicscheck 1.0.2

A lightweight tool to inspect GEO series matrices online before downloading.

OmicsCheck: Intelligent Quality Assessment for Gene Expression Data

OmicsCheck is a cutting-edge, automated tool designed to evaluate the quality of gene expression datasets from GEO (Gene Expression Omnibus). It intelligently analyzes raw expression matrices and generates professional PDF reports, visual summaries, and interpretable quality metrics – enabling researchers to screen studies before conducting downstream analysis.

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Features

• Download and parse GEO Series Matrix files automatically.
• Auto-orientation of matrices (genes × samples vs. samples × genes).
• Log2 transformation suggestions based on data distribution.
• Data filtering for the most variable genes (top-N).
• QA Score Evaluation using multi-criteria assessment.
• PCA and Heatmap visualization of gene-level variability.
• PDF report generation with visual plots and summary stats.
• Exports analysis files in .json and .csv formats.

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Installation

pip install omicscheck

Requires Python 3.8+

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Usage

omicscheck run GSE12345

This will:

1. Download the matrix file for GSE12345
2. Parse and analyze the data
3. Evaluate quality and suggest improvements
4. Generate visual plots
5. Create a full PDF report at: ~/Desktop/OmicsCheck/GSE12345/report.pdf

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Quality Evaluation Logic

OmicsCheck uses a composite QA Score based on:

• Matrix completeness
• Distribution characteristics
• Gene variance
• Sample PCA spread

Each dataset receives a final Rating: Excellent, Good, Moderate, or Poor

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Output Files

• report.pdf: Professional scientific report
• analysis.json: Full results in machine-readable format
• analysis.csv: Simplified metrics table
• boxplot.png, heatmap.png, pca_plot.png: Generated plots

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Example Output

Example report: docs/report_example.pdf

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OmicsCheck

A smart pre-download screening tool for high-quality omics datasets.

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Citation

Ahmed Yassin. OmicsCheck Enables Improved Selection of High-Quality Gene Expression Datasets: A Pre-download Screening Tool with Biological Impact Assessment.
Research Square (2025).
https://doi.org/10.21203/rs.3.rs-7297713/v1

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Contributing

We welcome contributions! Fork the repo and submit a pull request.

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Contact

Lead Developer: [AHMED YASSIN || Computational Biologist]
Email: [[e-mail]]
Project Page: [https://github.com/AHMEDY3DGENOME/OmicsCheck]

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© 2025 OmicsCheck Team. All rights reserved.