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immuneSIM: tunable multi-feature simulation of B- and T-cell receptor repertoires for immunoinformatics benchmarking

View ORCID ProfileCédric R. Weber, View ORCID ProfileRahmad Akbar, Alexander Yermanos, View ORCID ProfileMilena Pavlović, View ORCID ProfileIgor Snapkov, View ORCID ProfileGeir Kjetil Sandve, View ORCID ProfileSai T. Reddy, View ORCID ProfileVictor Greiff
doi: https://doi.org/10.1101/759795
Cédric R. Weber
1Department of Biosystems Science and Engineering, ETH Zürich, 4058 Basel, Switzerland
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Rahmad Akbar
2Department of Immunology, University of Oslo, 0372 Oslo, Norway
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Alexander Yermanos
1Department of Biosystems Science and Engineering, ETH Zürich, 4058 Basel, Switzerland
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Milena Pavlović
3Department of Informatics, University of Oslo, 0373 Oslo, Norway
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Igor Snapkov
2Department of Immunology, University of Oslo, 0372 Oslo, Norway
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Geir Kjetil Sandve
3Department of Informatics, University of Oslo, 0373 Oslo, Norway
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Sai T. Reddy
1Department of Biosystems Science and Engineering, ETH Zürich, 4058 Basel, Switzerland
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  • For correspondence: victor.greiff@medisin.uio.no
Victor Greiff
2Department of Immunology, University of Oslo, 0372 Oslo, Norway
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  • For correspondence: victor.greiff@medisin.uio.no
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Abstract

Summary B- and T-cell receptor repertoires of the adaptive immune system have become a key target for diagnostics and therapeutics research. Consequently, there is a rapidly growing number of bioinformatics tools for immune repertoire analysis. Benchmarking of such tools is crucial for ensuring reproducible and generalizable computational analyses. Currently, however, it remains challenging to create standardized ground truth immune receptor repertoires for immunoinformatics tool benchmarking. Therefore, we developed immuneSIM, an R package that allows the simulation of native-like and aberrant synthetic full length variable region immune receptor sequences. ImmuneSIM enables the tuning of the immune receptor features: (i) species and chain type (BCR, TCR, single, paired), (ii) germline gene usage, (iii) occurrence of insertions and deletions, (iv) clonal abundance, (v) somatic hypermutation, and (vi) sequence motifs. Each simulated sequence is annotated by the complete set of simulation events that contributed to its in silico generation. immuneSIM permits the benchmarking of key computational tools for immune receptor analysis such as germline gene annotation, diversity and overlap estimation, sequence similarity, network architecture, clustering analysis, and machine learning methods for motif detection.

Availability The package is available via https://github.com/GreiffLab/immuneSIM and will also be available at CRAN (submitted). The documentation is hosted at https://immuneSIM.readthedocs.io.

Contact victor.greiff{at}medisin.uio, sai.reddy{at}ethz.ch

Footnotes

  • https://github.com/GreiffLab/immuneSIM

  • https://immuneSIM.readthedocs.io

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted September 06, 2019.
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immuneSIM: tunable multi-feature simulation of B- and T-cell receptor repertoires for immunoinformatics benchmarking
Cédric R. Weber, Rahmad Akbar, Alexander Yermanos, Milena Pavlović, Igor Snapkov, Geir Kjetil Sandve, Sai T. Reddy, Victor Greiff
bioRxiv 759795; doi: https://doi.org/10.1101/759795
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immuneSIM: tunable multi-feature simulation of B- and T-cell receptor repertoires for immunoinformatics benchmarking
Cédric R. Weber, Rahmad Akbar, Alexander Yermanos, Milena Pavlović, Igor Snapkov, Geir Kjetil Sandve, Sai T. Reddy, Victor Greiff
bioRxiv 759795; doi: https://doi.org/10.1101/759795

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