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dc.contributor.author
Weber, Cédric R.
dc.contributor.author
Akbar, Rahmad
dc.contributor.author
Yermanos, Alexander
dc.contributor.author
Pavlović, Milena
dc.contributor.author
Snapkov, Igor
dc.contributor.author
Sandve, Geir K.
dc.contributor.author
Reddy, Sai T.
dc.contributor.author
Greiff, Victor
dc.date.accessioned
2024-05-29T10:36:08Z
dc.date.available
2020-06-11T02:36:51Z
dc.date.available
2020-06-11T08:27:21Z
dc.date.available
2024-05-29T10:36:08Z
dc.date.issued
2020-06
dc.identifier.issn
1367-4803
dc.identifier.issn
1460-2059
dc.identifier.other
10.1093/bioinformatics/btaa158
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/419634
dc.identifier.doi
10.3929/ethz-b-000419634
dc.description.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.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Oxford University Press
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.title
immuneSIM: tunable multi-feature simulation of B- and T-cell receptor repertoires for immunoinformatics benchmarking
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
dc.date.published
2020-04-14
ethz.journal.title
Bioinformatics
ethz.journal.volume
36
en_US
ethz.journal.issue
11
en_US
ethz.journal.abbreviated
Bioinformatics
ethz.pages.start
3594
en_US
ethz.pages.end
3596
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Oxford
en_US
ethz.publication.status
published
en_US
ethz.date.deposited
2020-06-11T02:36:56Z
ethz.source
SCOPUS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2020-06-11T08:27:31Z
ethz.rosetta.lastUpdated
2021-02-15T14:33:05Z
ethz.rosetta.exportRequired
true
ethz.rosetta.versionExported
true
ethz.COinS
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