lobster-ml

Machine learning and deep learning for biological data analysis and framework export.

Installation

# Basic installation
pip install lobster-ml

# With deep learning dependencies (scVI, PyTorch)
pip install lobster-ml[ml]

Agents

Services

Features

ML Readiness Assessment

• Evaluate biological datasets for machine learning suitability
• Check sample size, class balance, and feature quality
• Identify potential data leakage and batch effects
• Recommend preprocessing steps before ML pipeline

Feature Engineering

• Highly variable gene selection for dimensionality reduction
• PCA-based feature extraction with variance thresholds
• Marker gene features from differential expression
• Z-score normalization and scaling

Data Splitting

• Stratified train/test/validation splits
• Configurable split ratios (default: 70/15/15)
• Class balance preservation across splits
• Batch-aware splitting to prevent data leakage

Framework Export

• NumPy arrays for scikit-learn workflows
• CSV export for general ML frameworks
• PyTorch tensor datasets with DataLoader support
• TensorFlow NPZ format for Keras models

Deep Learning Embeddings

• scVI integration for variational autoencoder embeddings
• Latent space visualization and clustering
• Transfer learning from pre-trained models
• GPU acceleration when available

Requirements

• Python 3.12+
• lobster-ai >= 1.0.0
• Optional: torch, scvi-tools (for deep learning features)

Tier Requirement

This is a premium agent. Access is controlled at runtime via Lobster AI's tier system.

Documentation

Full documentation: docs.omics-os.com/docs/agents/ml

License

MIT