Article (Scientific journals)
Quantification of HTLV-1 Clonality and TCR Diversity.
Laydon, Daniel J.; Melamed, Anat; Sim, Aaron et al.
2014In PLoS Computational Biology, 10 (6), p. 1003646
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Abstract :
[en] Estimation of immunological and microbiological diversity is vital to our understanding of infection and the immune response. For instance, what is the diversity of the T cell repertoire? These questions are partially addressed by high-throughput sequencing techniques that enable identification of immunological and microbiological "species" in a sample. Estimators of the number of unseen species are needed to estimate population diversity from sample diversity. Here we test five widely used non-parametric estimators, and develop and validate a novel method, DivE, to estimate species richness and distribution. We used three independent datasets: (i) viral populations from subjects infected with human T-lymphotropic virus type 1; (ii) T cell antigen receptor clonotype repertoires; and (iii) microbial data from infant faecal samples. When applied to datasets with rarefaction curves that did not plateau, existing estimators systematically increased with sample size. In contrast, DivE consistently and accurately estimated diversity for all datasets. We identify conditions that limit the application of DivE. We also show that DivE can be used to accurately estimate the underlying population frequency distribution. We have developed a novel method that is significantly more accurate than commonly used biodiversity estimators in microbiological and immunological populations.
Disciplines :
Immunology & infectious disease
Author, co-author :
Laydon, Daniel J.
Melamed, Anat
Sim, Aaron
Gillet, Nicolas ;  Université de Liège - ULiège > Chimie et bio-industries > Biologie cell. et moléc.
Sim, Kathleen
Darko, Sam
Kroll, J. Simon
Douek, Daniel C.
Price, David A.
Bangham, Charles R. M.
Asquith, Becca
Language :
English
Title :
Quantification of HTLV-1 Clonality and TCR Diversity.
Publication date :
2014
Journal title :
PLoS Computational Biology
ISSN :
1553-734X
eISSN :
1553-7358
Publisher :
Public Library of Science, United States - California
Volume :
10
Issue :
6
Pages :
e1003646
Peer reviewed :
Peer Reviewed verified by ORBi
Available on ORBi :
since 24 June 2014

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