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AIRRSHIP: simulating human B cell receptor repertoire sequences

SUMMARY: Adaptive Immune Receptor Repertoire Sequencing is a rapidly developing field that has advanced understanding of the role of the adaptive immune system in health and disease. Numerous tools have been developed to analyse the complex data produced by this technique but work to compare their a...

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Autores principales: Sutherland, Catherine, Cowan, Graeme J M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10272706/
https://www.ncbi.nlm.nih.gov/pubmed/37279738
http://dx.doi.org/10.1093/bioinformatics/btad365
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author Sutherland, Catherine
Cowan, Graeme J M
author_facet Sutherland, Catherine
Cowan, Graeme J M
author_sort Sutherland, Catherine
collection PubMed
description SUMMARY: Adaptive Immune Receptor Repertoire Sequencing is a rapidly developing field that has advanced understanding of the role of the adaptive immune system in health and disease. Numerous tools have been developed to analyse the complex data produced by this technique but work to compare their accuracy and reliability has been limited. Thorough, systematic assessment of their performance is dependent on the ability to produce high quality simulated datasets with known ground truth. We have developed AIRRSHIP, a flexible and fast Python package that produces synthetic human B cell receptor sequences. AIRRSHIP uses a comprehensive set of reference data to replicate key mechanisms in the immunoglobulin recombination process, with a particular focus on junctional complexity. Repertoires generated by AIRRSHIP are highly similar to published data and all steps in the sequence generation process are recorded. These data can be used to not only determine the accuracy of repertoire analysis tools but can also, by tuning of the large number of user-controllable parameters, give insight into factors that contribute to inaccuracies in results. AVAILABILITY AND IMPLEMENTATION: AIRRSHIP is implemented in Python. It is available via https://github.com/Cowanlab/airrship and on PyPI at https://pypi.org/project/airrship/. Documentation can be found at https://airrship.readthedocs.io/.
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spelling pubmed-102727062023-06-17 AIRRSHIP: simulating human B cell receptor repertoire sequences Sutherland, Catherine Cowan, Graeme J M Bioinformatics Applications Note SUMMARY: Adaptive Immune Receptor Repertoire Sequencing is a rapidly developing field that has advanced understanding of the role of the adaptive immune system in health and disease. Numerous tools have been developed to analyse the complex data produced by this technique but work to compare their accuracy and reliability has been limited. Thorough, systematic assessment of their performance is dependent on the ability to produce high quality simulated datasets with known ground truth. We have developed AIRRSHIP, a flexible and fast Python package that produces synthetic human B cell receptor sequences. AIRRSHIP uses a comprehensive set of reference data to replicate key mechanisms in the immunoglobulin recombination process, with a particular focus on junctional complexity. Repertoires generated by AIRRSHIP are highly similar to published data and all steps in the sequence generation process are recorded. These data can be used to not only determine the accuracy of repertoire analysis tools but can also, by tuning of the large number of user-controllable parameters, give insight into factors that contribute to inaccuracies in results. AVAILABILITY AND IMPLEMENTATION: AIRRSHIP is implemented in Python. It is available via https://github.com/Cowanlab/airrship and on PyPI at https://pypi.org/project/airrship/. Documentation can be found at https://airrship.readthedocs.io/. Oxford University Press 2023-06-05 /pmc/articles/PMC10272706/ /pubmed/37279738 http://dx.doi.org/10.1093/bioinformatics/btad365 Text en © The Author(s) 2023. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Note
Sutherland, Catherine
Cowan, Graeme J M
AIRRSHIP: simulating human B cell receptor repertoire sequences
title AIRRSHIP: simulating human B cell receptor repertoire sequences
title_full AIRRSHIP: simulating human B cell receptor repertoire sequences
title_fullStr AIRRSHIP: simulating human B cell receptor repertoire sequences
title_full_unstemmed AIRRSHIP: simulating human B cell receptor repertoire sequences
title_short AIRRSHIP: simulating human B cell receptor repertoire sequences
title_sort airrship: simulating human b cell receptor repertoire sequences
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10272706/
https://www.ncbi.nlm.nih.gov/pubmed/37279738
http://dx.doi.org/10.1093/bioinformatics/btad365
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