Diverse T and B cell repertoires play an important role in mounting effective immune responses against a wide range of pathogens and malignant cells. The number of unique T and B cell clones is characterized by T and B cell receptors (TCRs and BCRs), respectively. Although receptor sequences are generated probabilistically by recombination processes, clinical studies found a high degree of sharing of TCRs and BCRs among different individuals. In this work, we use a general probabilistic model for T/B cell receptor clone abundances to define “publicness” or “privateness” and information-theoretic measures for comparing the frequency of sampled sequences observed across different individuals. We derive mathematical formulae to quantify the mean
Probabilistic modeling is fundamental to the statistical analysis of complex data. In addition to forming a coherent description of the data‐generating process, probabilistic models enable parameter inference about given datasets. This procedure is well developed in the Bayesian perspective, in which one infers probability distributions describing to what extent various possible parameters agree with the data. In this paper, we motivate and review probabilistic modeling for adaptive immune receptor repertoire data then describe progress and prospects for future work, from germline haplotyping to adaptive immune system deployment across tissues. The relevant quantities in immune sequence analysis include not only continuous parameters such as gene use frequency but also discrete objects such as B‐cell clusters and lineages. Throughout this review, we unravel the many opportunities for probabilistic modeling in adaptive immune receptor analysis, including settings for which the Bayesian approach holds substantial promise (especially if one is optimistic about new computational methods). From our perspective, the greatest prospects for progress in probabilistic modeling for repertoires concern ancestral sequence estimation for B‐cell receptor lineages, including uncertainty from germline genotype, rearrangement, and lineage development.
more » « less- PAR ID:
- 10246050
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Immunological Reviews
- Volume:
- 284
- Issue:
- 1
- ISSN:
- 0105-2896
- Page Range / eLocation ID:
- p. 148-166
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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