AIRRSHIP

AIRRSHIP simulates human B cell receptor (BCR) repertoire sequences to generate synthetic Adaptive Immune Receptor Repertoire Sequencing (AIRR-seq) datasets with known ground truth for benchmarking and evaluation of repertoire analysis methods.

Key Features:

• Synthetic Sequence Generation: Generates synthetic human BCR sequences that reflect the complexity and diversity of real immune repertoires for AIRR-seq datasets.
• Immunoglobulin Recombination and Junctional Diversity: Models immunoglobulin V(D)J recombination mechanisms with explicit emphasis on junctional diversity.
• Comprehensive Reference Data: Uses an extensive set of reference data to ensure synthetic repertoires are representative of published datasets.
• User-Controlled Parameters: Provides adjustable simulation parameters to tailor repertoire characteristics and explore sources of analytical error.
• Python Implementation: Implemented in Python to enable integration with computational analyses and bioinformatics tools.

Scientific Applications:

• Tool Evaluation and Benchmarking: Produces datasets with known ground truth to systematically assess accuracy and reliability of repertoire analysis tools.
• Methodological Research: Enables investigation of methodological biases and error sources by simulating controlled repertoire variability.
• Educational Use: Supplies synthetic datasets for training in immunogenetics and AIRR-seq data analysis.

Methodology:

Simulates BCR sequences using reference data by modeling immunoglobulin V(D)J recombination and junctional diversity with user-adjustable parameters, implemented in Python.