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Friedensohn S, Lindner JM, Cornacchione V, et al. Synthetic Standards Combined With Error and Bias Correction Improve the Accuracy and Quantitative Resolution of Antibody Repertoire Sequencing in Human Naïve and Memory B Cells. Front Immunol. 2018;9:1401doi: 10.3389/fimmu.2018.01401.
Friedensohn, S., Lindner, J. M., Cornacchione, V., Iazeolla, M., Miho, E., Zingg, A., Meng, S., Traggiai, E., & Reddy, S. T. (2018). Synthetic Standards Combined With Error and Bias Correction Improve the Accuracy and Quantitative Resolution of Antibody Repertoire Sequencing in Human Naïve and Memory B Cells. Frontiers in immunology, 91401. https://doi.org/10.3389/fimmu.2018.01401
Friedensohn, Simon, et al. "Synthetic Standards Combined With Error and Bias Correction Improve the Accuracy and Quantitative Resolution of Antibody Repertoire Sequencing in Human Naïve and Memory B Cells." Frontiers in immunology vol. 9 (2018): 1401. doi: https://doi.org/10.3389/fimmu.2018.01401
Friedensohn S, Lindner JM, Cornacchione V, Iazeolla M, Miho E, Zingg A, Meng S, Traggiai E, Reddy ST. Synthetic Standards Combined With Error and Bias Correction Improve the Accuracy and Quantitative Resolution of Antibody Repertoire Sequencing in Human Naïve and Memory B Cells. Front Immunol. 2018 Jun 20;9:1401. doi: 10.3389/fimmu.2018.01401. eCollection 2018. PMID: 29973938; PMCID: PMC6019461.
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Front Immunol. 2018 Jun 20;9:1401. doi: 10.3389/fimmu.2018.01401. eCollection 2018.

Synthetic Standards Combined With Error and Bias Correction Improve the Accuracy and Quantitative Resolution of Antibody Repertoire Sequencing in Human Naïve and Memory B Cells.

Frontiers in immunology

Simon Friedensohn, John M Lindner, Vanessa Cornacchione, Mariavittoria Iazeolla, Enkelejda Miho, Andreas Zingg, Simon Meng, Elisabetta Traggiai, Sai T Reddy

Affiliations

  1. Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
  2. Novartis Institutes for BioMedical Research, Basel, Switzerland.

PMID: 29973938 PMCID: PMC6019461 DOI: 10.3389/fimmu.2018.01401

Abstract

High-throughput sequencing of immunoglobulin (Ig) repertoires (Ig-seq) is a powerful method for quantitatively interrogating B cell receptor sequence diversity. When applied to human repertoires, Ig-seq provides insight into fundamental immunological questions, and can be implemented in diagnostic and drug discovery projects. However, a major challenge in Ig-seq is ensuring accuracy, as library preparation protocols and sequencing platforms can introduce substantial errors and bias that compromise immunological interpretation. Here, we have established an approach for performing highly accurate human Ig-seq by combining synthetic standards with a comprehensive error and bias correction pipeline. First, we designed a set of 85 synthetic antibody heavy-chain standards (

Keywords: B cells; antibody repertoire; bioinformatics; next-generation sequencing; systems immunology; unique molecular identifiers

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