A Macro-scale Comparison Algorithm for Analysis of TCR Repertoire Completeness

Recent advances in biotechnology are beginning to generate whole immunome datasets, which will enable the comparison of immune repertoires between individuals, e.g., to assess immunocompetence. Existing algorithms cluster cell types based on the relative expression abundance of about 20 000 genes, but such algorithms have limited utility when comparing immunome datasets with many higher orders of magnitude (>1012) of variation, such as occurs in immunoreceptor sequences in highly polyclonal naive repertoires. In this paper we present a method for comparing immune repertoires by identifying macro-level features that are conserved between similar individuals. Our method allows us to detect some blind spots in naive populations and to assess whether a repertoire is likely complete by examining only a sample of its sequences. Author SummaryIn this paper we present a method for comparing the immune repertoire of different individuals. Repertoires are represented by a sample of genetic sequences. Our technique coarse grains each individuals data into groups, matches groups between individuals and finds significant differences.