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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.
Afiliación
  • Smakaj E; Institute of Biomedical Engineering and Medical Informatics, School of Life Sciences, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Muttenz 4132, Switzerland.
  • Babrak L; Institute of Biomedical Engineering and Medical Informatics, School of Life Sciences, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Muttenz 4132, Switzerland.
  • Ohlin M; Department of Immunotechnology, Lund University, Lund 223, Sweden.
  • Shugay M; Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow 121205, Russia.
  • Briney B; Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037, USA.
  • Tosoni D; Institute of Biomedical Engineering and Medical Informatics, School of Life Sciences, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Muttenz 4132, Switzerland.
  • Galli C; Institute of Biomedical Engineering and Medical Informatics, School of Life Sciences, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Muttenz 4132, Switzerland.
  • Grobelsek V; Department of Biosystems Science and Engineering, ETH Zurich, Basel 4058, Switzerland.
  • D'Angelo I; One Amgen Center Drive, Amgen, Inc., Therapeutic Discovery/Molecular Engineering, Thousand Oaks, CA 91320, USA.
  • Olson B; Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
  • Reddy S; Department of Statistics, University of Washington, Seattle, WA 98195, USA.
  • Greiff V; Department of Biosystems Science and Engineering, ETH Zurich, Basel 4058, Switzerland.
  • Trück J; Department of Immunology, University of Oslo, Oslo 0372, Norway.
  • Marquez S; Paediatric Immunology, Children's Research Center, University Children's Hospital, University of Zurich, Zurich 8032, Switzerland.
  • Lees W; Department of Pathology, Yale School of Medicine, New Haven, CT 06511, USA.
  • Miho E; Department of Biological Sciences and Institute of Structural and Molecular Biology, Birkbeck College, University of London, London WC1E 7HX, UK.
Bioinformatics ; 36(6): 1731-1739, 2020 03 01.
Article en En | MEDLINE | ID: mdl-31873728
SUMMARY: 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.We analyzed changes in IMGT reference germline database in the last 10 years in order to assess the reproducibility of the annotation output. We found that only 73/183 (40%) V, D and J human genes were shared between the reference germline sets used by the tools. We found that the annotation results differed between tools. In terms of alignment accuracy, MiXCR had the highest average frequency of gene mishits, 0.02 mishit frequency and IgBLAST the lowest, 0.004 mishit frequency. Reproducibility in the output of complementarity determining three regions (CDR3 amino acids) ranged from 4.3% to 77.6% with preprocessed data. In addition, run time of the tools was assessed: MiXCR was the fastest tool for number of sequences processed per unit of time. These results indicate that immunoinformatic analyses greatly depend on the choice of bioinformatics tool. Our results support informed decision-making to immunoinformaticians based on repertoire composition and sequencing platforms. AVAILABILITY AND IMPLEMENTATION: All tools utilized in the paper are free for academic use. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Benchmarking / Secuenciación de Nucleótidos de Alto Rendimiento Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2020 Tipo del documento: Article País de afiliación: Suiza Pais de publicación: Reino Unido
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Benchmarking / Secuenciación de Nucleótidos de Alto Rendimiento Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2020 Tipo del documento: Article País de afiliación: Suiza Pais de publicación: Reino Unido