For example, the Berger–Parker index (BPI) measures clonality, that is, the dominance of the single largest clone ( Fig. Other diversity measures provide complementary information about the size-frequency distribution of species in the population.
An example of species richness is the number of B-cell clones in an individual (where ‘clone’ denotes cells with a common B- or T-cell progenitor). The most familiar diversity measure is the number of different species in a population: the species richness. However, measuring diversity is more complicated than it may seem, for three reasons.įirst, ‘diversity’ may refer to any of several different measures. Similar requirements also arise in the study of cancer heterogeneity, microbial diversity and high-throughput sequencing, as well as beyond biology 6, 7, 8, 9. The reliability of such observations depends on the ability to measure diversity-and differences in diversity-in overall B- or T-cell populations accurately and with statistical rigour from clinical and experimental samples. This interest follows observations that immune-repertoire diversity correlates with successful responses to infection, immune reconstitution following stem-cell transplant, the presence or absence of leukaemia, and healthy versus unhealthy ageing 2, 3, 4, 5. Of special interest is repertoire diversity, defined as the number of different B- or T-cell receptors on cells present in an individual, tissue (for example, peripheral blood, bone marrow), tumour (for example, tumour-infiltrating lymphocytes) or cell subset (for example, influenza-specific IgG + B cells). Recent technological advances are making it possible to study B- and T-cell repertoires in unprecedented detail 1. We apply Recon to in silico and experimental immune-repertoire sequencing data sets as proof of principle for measuring diversity in large, complex systems. It also outputs error bars and power tables, allowing robust comparisons of diversity between individuals and over time. Recon outputs accurate, robust estimates by any of a vast set of complementary diversity measures, including species richness and entropy, at fractional repertoire coverage. 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. 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. Therefore, partial CDR3 sequences, such as those contained in the output of TRUST v2.1, may be valuable when seeking to gain insights into the frequency of shared specificities.The diversity of an organism’s B- and T-cell repertoires is both clinically important and a key measure of immunological complexity. This is because structural studies indicate that only a small region in the complete CDR3 makes contact with the antigen peptide 5, 6, and the recent GLIPH (grouping of lymphocyte interactions by paratope hotspots) 5 method can cluster TCRs with likely shared specificity from enriched local motifs within many distinct CDR3 molecules. We also point out that partial CDR3 sequences of reasonable length (6–30 amino acids) and perfect match to a subregion of the respective CDR3 molecule are informative for modeling TCR binding specificity. However, we would note that single-chain CDR3 from bulk RNA-seq may also not be ideal to identify a unique clonotype because, for a strict definition of clonotype, generally both chains would be required. We recognize that partial CDR3 sequences or reads that extend beyond the accepted limits of CDR3 cannot be unambiguously counted as unique clonotypes. 1), which were considered “non-canonical unconfirmed” by Bolotin et al.
The output of TRUST v2.1 contains reads with V or J gene motifs and partial CDR3 sequences ( Supplementary Fig. TRUST uses TCR variable (V) and joining (J) gene motifs to search and annotate CDR3-containing reads and performs de novo assembly on the CDR3-overlapping reads.
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