Computational strategies for dissecting the high-dimensional complexity of adaptive immune repertoires
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Authors
Yermanos, Alexander
Weber, Cédric R.
Berger, Christoph T.
Reddy, Sai T.
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Publication date
2018
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01A - Journal article
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Frontiers in Immunology
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9
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Frontiers Research Foundation
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Abstract
The adaptive immune system recognizes antigens via an immense array of antigen binding antibodies and T-cell receptors, the immune repertoire. The interrogation of immune repertoires is of high relevance for understanding the adaptive immune response in disease and infection (e.g., autoimmunity, cancer, HIV). Adaptive immune receptor repertoire sequencing (AIRR-seq) has driven the quantitative and molecular-level profiling of immune repertoires, thereby revealing the high-dimensional complexity of the immune receptor sequence landscape. Several methods for the computational and statistical analysis of large-scale AIRR-seq data have been developed to resolve immune repertoire complexity and to understand the dynamics of adaptive immunity. Here, we review the current research on (i) diversity, (ii) clustering and network, (iii) phylogenetic, and (iv) machine learning methods applied to dissect, quantify, and compare the architecture, evolution, and specificity of immune repertoires. We summarize outstanding questions in computational immunology and propose future directions for systems immunology toward coupling AIRR-seq with the computational discovery of immunotherapeutics, vaccines, and immunodiagnostics.
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600 - Technik, Medizin, angewandte Wissenschaften
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1664-3224
Language
English
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No
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Published
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Gold
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Citation
MIHO, Enkelejda, Alexander YERMANOS, Cédric R. WEBER, Christoph T. BERGER, Sai T. REDDY und Victor GREIFF, 2018. Computational strategies for dissecting the high-dimensional complexity of adaptive immune repertoires. Frontiers in Immunology. 2018. Bd. 9. DOI 10.3389/fimmu.2018.00224. Verfügbar unter: https://doi.org/10.26041/fhnw-9936