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A tool for simulation of antigen-experienced adaptive immune receptor repertoire (AIRR) datasets for benchmarking of machine learning (ML) methods.

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KanduriC/simAIRR

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simAIRR

unit_tests docker

simAIRR provides a simulation approach to generate synthetic AIRR datasets that are suitable for benchmarking machine learning (ML) methods, where undesirable access to ground truth signals in training datasets for ML methods is mitigated. Unlike state-of-the-art approaches, simAIRR constructs antigen-experienced-like baseline repertoires and introduces signals by following the empirical relationship between generation probability and sharing pattern of public sequences calibrated from real-world experimental datasets.

Getting started

To get started:

Installation

Install using pip

$ pip install simAIRR 

Manual installation using git

$ pip install git+https://github.com/KanduriC/simAIRR.git

Use simAIRR through Docker

$ docker run -it -v $(pwd):/wd --name my_container kanduric/simairr:latest sim_airr --help

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A tool for simulation of antigen-experienced adaptive immune receptor repertoire (AIRR) datasets for benchmarking of machine learning (ML) methods.

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