Robust estimates of overall immune-repertoire diversity from high-throughput measurements on samples

Joseph Kaplinsky and Ramy Arnaout ()
Additional contact information
Joseph Kaplinsky: Beth Israel Deaconess Medical Center BIDMC East/Dana 615, 330 Brookline Avenue
Ramy Arnaout: Beth Israel Deaconess Medical Center BIDMC East/Dana 615, 330 Brookline Avenue

Nature Communications, 2016, vol. 7, issue 1, 1-10

Abstract: Abstract The diversity of an organism’s B- and T-cell repertoires is both clinically important and a key measure of immunological complexity. However, diversity is hard to estimate by current methods, because of inherent uncertainty in the number of B- and T-cell clones that will be missing from a blood or tissue sample by chance (the missing-species problem), inevitable sampling bias, and experimental noise. To solve this problem, we developed Recon, a modified maximum-likelihood method that outputs the overall diversity of a repertoire from measurements on a sample. Recon outputs accurate, robust estimates by any of a vast set of complementary diversity measures, including species richness and entropy, at fractional repertoire coverage. It also outputs error bars and power tables, allowing robust comparisons of diversity between individuals and over time. We apply Recon to in silico and experimental immune-repertoire sequencing data sets as proof of principle for measuring diversity in large, complex systems.

Date: 2016
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/ncomms11881 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms11881

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/ncomms11881

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().