RepSeq Data Representativeness and Robustness Assessment by Shannon Entropy
High-throughput sequencing (HTS) has the potential to decipher the diversity of T cell repertoires and their dynamics during immune responses. Applied to T cell subsets such as T effector and T regulatory cells, it should help identify novel biomarkers of diseases. However, given the extreme diversi...
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Published in | Frontiers in immunology Vol. 9; p. 1038 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
Switzerland
Frontiers
15.05.2018
Frontiers Media S.A |
Subjects | |
Online Access | Get full text |
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Summary: | High-throughput sequencing (HTS) has the potential to decipher the diversity of T cell repertoires and their dynamics during immune responses. Applied to T cell subsets such as T effector and T regulatory cells, it should help identify novel biomarkers of diseases. However, given the extreme diversity of TCR repertoires, understanding how the sequencing conditions, including cell numbers, biological and technical sampling and sequencing depth, impact the experimental outcome is critical to proper use of these data. Here, we assessed the representativeness and robustness of TCR repertoire diversity assessment according to experimental conditions. By comparative analyses of experimental datasets and computer simulations, we found that (i) for small samples, the number of clonotypes recovered is often higher than the number of cells per sample, even after removing the singletons; (ii) high-sequencing depth for small samples alters the clonotype distributions, which can be corrected by filtering the datasets using Shannon entropy as a threshold; and (iii) a single sequencing run at high depth does not ensure a good coverage of the clonotype richness in highly polyclonal populations, which can be better covered using multiple sequencing. Altogether, our results warrant better understanding and awareness of the limitation of TCR diversity analyses by HTS and justify the development of novel computational tools for improved modeling of the highly complex nature of TCR repertoires. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Specialty section: This article was submitted to T Cell Biology, a section of the journal Frontiers in Immunology Edited by: Benny Chain, University College London, United Kingdom These authors have contributed equally to this work. Reviewed by: Sol Efroni, Bar-Ilan University, Israel; Haopeng Wang, ShanghaiTech University, China; Dmitriy M. Chudakov, M. M. Shemyakin and Yu. A. Ovchinnikov Institute of Bioorganic Chemistry of the Russian Academy of Sciences, Russia |
ISSN: | 1664-3224 1664-3224 |
DOI: | 10.3389/fimmu.2018.01038 |