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Benchmarking immunoinformatic tools for the analysis of antibody repertoire sequences


Smakaj, Erand; Babrak, Lmar; Ohlin, Mats; Shugay, Mikhail; Briney, Bryan; Tosoni, Deniz; Galli, Christopher; Grobelsek, Vendi; D’Angelo, Igor; Olson, Branden; Reddy, Sai; Greiff, Victor; Trück, Johannes; Marquez, Susanna; Lees, William; Miho, Enkelejda (2020). Benchmarking immunoinformatic tools for the analysis of antibody repertoire sequences. Bioinformatics, 36(6):1731-1739.

Abstract

Antibody repertoires reveal insights into the biology of the adaptive immune system and empower diagnostics and therapeutics. There are currently multiple tools available for the annotation of antibody sequences. All downstream analyses such as choosing lead drug candidates depend on the correct annotation of these sequences; however, a thorough comparison of the performance of these tools has not been investigated. Here, we benchmark the performance of commonly used immunoinformatic tools, i.e. IMGT/HighV-QUEST, IgBLAST and MiXCR, in terms of reproducibility of annotation output, accuracy and speed using simulated and experimental high-throughput sequencing datasets.

Abstract

Antibody repertoires reveal insights into the biology of the adaptive immune system and empower diagnostics and therapeutics. There are currently multiple tools available for the annotation of antibody sequences. All downstream analyses such as choosing lead drug candidates depend on the correct annotation of these sequences; however, a thorough comparison of the performance of these tools has not been investigated. Here, we benchmark the performance of commonly used immunoinformatic tools, i.e. IMGT/HighV-QUEST, IgBLAST and MiXCR, in terms of reproducibility of annotation output, accuracy and speed using simulated and experimental high-throughput sequencing datasets.

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Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Children's Hospital Zurich > Medical Clinic
Dewey Decimal Classification:610 Medicine & health
Scopus Subject Areas:Physical Sciences > Statistics and Probability
Life Sciences > Biochemistry
Life Sciences > Molecular Biology
Physical Sciences > Computer Science Applications
Physical Sciences > Computational Theory and Mathematics
Physical Sciences > Computational Mathematics
Uncontrolled Keywords:Statistics and Probability, Computational Theory and Mathematics, Biochemistry, Molecular Biology, Computational Mathematics, Computer Science Applications
Language:English
Date:1 March 2020
Deposited On:06 Feb 2020 11:46
Last Modified:22 Jun 2024 01:40
Publisher:Oxford University Press
ISSN:1367-4803
OA Status:Hybrid
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1093/bioinformatics/btz845
PubMed ID:31873728
  • Content: Published Version
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)