Molaop Analyser

C 67 completed
Web App
containerized / python · small
51
Files
12,216
LOC
3
Frameworks
7
Languages

Pipeline State

completed
Run ID
#358256
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Cataloged
Decision
proceed
Novelty
67.67
Framework unique
Isolation
Last stage change
2026-05-10 03:35:24
Deduplication group #51196
Member of a group with 4 similar repo(s) — canonical #27327 view group →
Top concepts (2)
Project DescriptionWeb Backend
Repobility · code-quality intelligence · https://repobility.com

AI Prompt

Create a web application using Flask for Key Event (KE) enrichment analysis related to Molecular Adverse Outcome Pathways (AOPs). The app should allow users to upload gene expression data or use demo datasets. Key features must include auto-detecting gene ID, log2FC, and p-value columns, generating an interactive volcano plot with quick threshold options, and performing KE enrichment analysis using Fisher's exact test with FDR correction. For visualization, it needs an interactive AOP network diagram using Cytoscape.js, and it must generate comprehensive PDF and HTML reports that embed the network visualizations.
python flask web-app bioinformatics data-analysis flask-sqlalchemy cytoscape.js docker
Generated by gemma4:latest

Catalog Information

A web application that performs Key Event enrichment analysis for Molecular Adverse Outcome Pathways using uploaded gene expression data.

Description

The application allows users to upload differential gene expression datasets or select from demo data and automatically detects key columns such as gene identifiers, log2 fold change, and p‑values. It performs KE enrichment using Fisher’s exact test with FDR correction and visualizes results in interactive volcano plots and a Cytoscape‑style AOP network where nodes are color‑coded by event type and expression level. Users can toggle gene nodes, adjust thresholds, and view network statistics. The tool also generates comprehensive PDF and HTML reports that embed the network visualizations and export tables in CSV, Excel, or JSON formats. Designed for researchers in toxicology and computational biology, it streamlines the workflow from raw data to publication‑ready documentation.

الوصف

يتيح التطبيق للمستخدمين رفع مجموعات بيانات التعبير الجيني التفاضلي أو اختيار مجموعات تجريبية مُدمجة، ويكشف تلقائياً عن الأعمدة الأساسية مثل معرفات الجينات، التغير اللوغاريتمي للانبعاث، والقيم الاحتمالية. يُجرى تحليل إثراء الأحداث الرئيسية باستخدام اختبار فشر مع تصحيح FDR، ثم يُعرض النتائج في مخططات فوليومو تفاعلية وشبكة AOP بأسلوب Cytoscape حيث تُرمز العقد حسب نوع الحدث وتُلون حسب مستوى التعبير. يمكن للمستخدم تعديل العتبات، تفعيل أو إلغاء تفعيل العقد الجينية، وعرض إحصائيات الشبكة. كما يُنتج التطبيق تقارير PDF وHTML شاملة تضمّ الشبكة المرئية وتصدّر الجداول بصيغ CSV، Excel أو JSON. يستهدف الباحثين في علم السموم والبيولوجيا الحاسوبية، ويُسهل سير العمل من البيانات الخام إلى وثائق جاهزة للنشر.

Novelty

7/10

Tags

gene-expression-analysis ke-enrichment aop-network-visualization interactive-plots report-generation data-upload

Technologies

flask numpy pandas plotly scipy sqlalchemy

Claude Models

claude-opus-4.6 claude-sonnet-4.6

Quality Score

C
66.6/100
Structure
58
Code Quality
64
Documentation
65
Testing
60
Practices
74
Security
92
Dependencies
60

Strengths

  • Good test coverage (43% test-to-source ratio)
  • Consistent naming conventions (snake_case)
  • Good security practices \u2014 no major issues detected
  • Containerized deployment (Docker)

Weaknesses

  • No LICENSE file \u2014 legal ambiguity for contributors
  • No CI/CD configuration \u2014 manual testing and deployment
  • 441 duplicate lines detected \u2014 consider DRY refactoring
  • 2 'god files' with >500 LOC need decomposition

Recommendations

  • Set up CI/CD (GitHub Actions recommended) to automate testing and deployment
  • Add a linter configuration to enforce code style consistency
  • Add a LICENSE file (MIT recommended for open source)

Security & Health

4.6h
Tech Debt (A)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (1)
Repobility's GitHub App fixes findings like these · https://github.com/apps/repobility-bot
Unknown
License
2.5%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

python
51.3%
html
39.7%
css
8.2%
markdown
0.4%
text
0.2%
ini
0.1%
yaml
0.1%

Frameworks

Flask pytest SQLAlchemy

Concepts (2)

Repobility · code-quality intelligence · https://repobility.com
CategoryNameDescriptionConfidence
Repobility · severity-and-effort ranking · https://repobility.com
auto_descriptionProject DescriptionThis web application allows users to upload or select gene expression datasets and perform Key Event (KE) enrichment analysis in the context of Molecular Adverse Outcome Pathways (AOPs). The results are visualized in interactive tables and network diagrams with comprehensive reporting capabilities.80%
auto_categoryWeb Backendweb-backend70%

Quality Timeline

1 quality score recorded.

View File Metrics

Embed Badge

Add to your README:

![Quality](https://repos.aljefra.com/badge/82395.svg)
Quality BadgeSecurity Badge
Export Quality CSVDownload SBOMExport Findings CSV