EchinoML - Echinoderm Codon Usage Analysis

A comprehensive web application for analyzing codon usage patterns across echinoderm species using machine learning and statistical methods.

Features

• Upload and process CDS FASTA files from multiple echinoderm species
• Calculate codon usage statistics and GC content
• Perform dimensionality reduction (PCA, t-SNE)
• Cluster analysis (K-means, Hierarchical)
• Machine learning classification
• Statistical analysis (ANOVA)
• Interactive visualizations

Setup

1. Clone the repository:

git clone https://github.com/yourusername/EchinoML.git
cd EchinoML

2. Create and activate a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install required packages:

pip install -r requirements.txt

Usage

1. Start the Streamlit app:

streamlit run app.py

2. Upload your CDS FASTA files (.fa.gz format) through the web interface
3. Explore the various analysis sections:
   • Basic Statistics
   • GC Content Analysis
   • Codon Usage Analysis
   • Dimensionality Reduction
   • Clustering Analysis
   • Machine Learning Analysis
   • Statistical Analysis

Data Requirements

The app expects CDS (Coding Sequence) FASTA files in gzipped format (.fa.gz) from echinoderm species. Each file should contain protein-coding sequences.

Output

The app provides:

• Interactive visualizations
• Statistical summaries
• Machine learning model performance metrics
• Downloadable results in CSV format

License

[Add your license here]

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.