Bioinformatic and Statistical Analysis of Adaptive Immune Repertoires

High-throughput sequencing (HTS) of immune repertoires has enabled the quantitative analysis of adaptive immune responses and offers the potential to revolutionize research in lymphocyte biology, vaccine profiling, and monoclonal antibody engineering. Advances in sequencing technology coupled to an exponential decline in sequencing costs have fueled the recent overwhelming interest in immune repertoire sequencing. This, in turn, has sparked the development of numerous methods for bioinformatic and statistics-driven interpretation and visualization of immune repertoires. Here, we review the current literature on bioinformatic and statistical analysis of immune repertoire HTS data and discuss underlying assumptions, applicability, and scope. We further highlight important directions for future research, which could propel immune repertoire HTS to becoming a standard method for measuring adaptive immune responses.

TrendsHigh-throughput immune repertoire sequencing is becoming a core technology for advancing basic, applied, and clinical immunology.Specialized bioinformatic and statistical methods for repertoire diversity and overlap analysis as well as for performing network and phylogenetic clustering enable the investigation of immune repertoire expansion, dynamics, architecture and evolution at an unprecedented level of detail.There is a divergence of the underlying assumptions, applicability, and scope of bioinformatic and statistical methods, thus compromising the consistency of data analyses within and across studies that needs to (will) be addressed in the (near) future.