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immuneSIM: tunable multi-feature simulation of B- and T-cell receptor repertoires for immunoinformatics benchmarking.
Weber, Cédric R; Akbar, Rahmad; Yermanos, Alexander; Pavlovic, Milena; Snapkov, Igor; Sandve, Geir K; Reddy, Sai T; Greiff, Victor.
Affiliation
  • Weber CR; Department of Biosystems Science and Engineering, ETH Zürich, 4058 Basel, Switzerland.
  • Akbar R; Department of Immunology, University of Oslo, 0372 Oslo, Norway.
  • Yermanos A; Department of Biosystems Science and Engineering, ETH Zürich, 4058 Basel, Switzerland.
  • Pavlovic M; Department of Informatics, University of Oslo, 0373 Oslo, Norway.
  • Snapkov I; Department of Immunology, University of Oslo, 0372 Oslo, Norway.
  • Sandve GK; Department of Informatics, University of Oslo, 0373 Oslo, Norway.
  • Reddy ST; Department of Biosystems Science and Engineering, ETH Zürich, 4058 Basel, Switzerland.
  • Greiff V; Department of Immunology, University of Oslo, 0372 Oslo, Norway.
Bioinformatics ; 36(11): 3594-3596, 2020 06 01.
Article in En | MEDLINE | ID: mdl-32154832
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 by tuning the following immune receptor features (i) species and chain type (BCR, TCR, single and 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 AND IMPLEMENTATION The package is available via https//github.com/GreiffLab/immuneSIM and on CRAN at https//cran.r-project.org/web/packages/immuneSIM. The documentation is hosted at https//immuneSIM.readthedocs.io. CONTACT sai.reddy@ethz.ch or victor.greiff@medisin.uio.no. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software / Benchmarking Type of study: Prognostic_studies Language: En Journal: Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2020 Document type: Article Affiliation country:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software / Benchmarking Type of study: Prognostic_studies Language: En Journal: Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2020 Document type: Article Affiliation country: