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How-To Guides

Task-oriented guides for specific LZGraphs operations. Each guide focuses on a single task and gives you the recipe to accomplish it.

Available Guides

Prepare Your Data

Load sequences from CSV/TSV, clean input, and handle AIRR-format files

Save & Load Graphs

Persist graphs to disk in the fast .lzg binary format

Generate Sequences

Create new sequences with gene constraints, filtering, and reproducibility

Compare Repertoires

Measure similarity with JSD, diversity profiles, and cross-scoring

Personalize Graphs

Adapt a population graph to an individual using Bayesian posteriors

Distribution Analytics

Validate distributions, measure diversity, and predict occupancy

Graph Algebra

Union, intersection, difference — combine and decompose repertoires

Feature Extraction for ML

Extract fixed-size feature vectors for classifiers and pipelines

Quick Reference

Task Guide Key Functions
Load from CSV/TSV Data Preparation csv.DictReader + LZGraph()
Save a graph Serialization graph.save()
Load a graph Serialization LZGraph.load()
Generate sequences Sequence Generation graph.simulate()
Compare repertoires Comparison jensen_shannon_divergence()
Personalize a graph Posterior graph.posterior()
Measure diversity Distribution Analytics graph.hill_number(), graph.predicted_richness()
Combine repertoires Graph Algebra graph \| other, graph & other, graph - other
ML features Feature Extraction ref.feature_aligned(query), graph.feature_stats()

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