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