Immune repertoire sequencing6/27/2023 ![]() We selected the computational tools discussed in this review based on their relevance (i.e., attention or citations received since their publication), continuous maintenance (at least one in the last 5 years), and up to date with the current sequencing platforms available. The measurable features associated with the antibody repertoire discussed in this review are: V(D)J germline assignment, clonal grouping, mutation analysis, evolution and convergence of antibody repertoires. We begin by briefly explaining the pre-processing step and also the measurable features of antibody repertoires and their basic rationale, to then describe the strengths and differences of each pipeline, emphasizing where the computational pipelines may converge and diverge to explore the repertoire biogenesis process. In this review, we focus on the current repertoire of some of the most widely used computational pipelines for Ig-Seq and provide a comparison of all the specific processes they perform. With the large amount of software devoted for a specific (or all) processing step(s), the analysis of antibody repertoires may seem intimidating for newcomer laboratories as the necessary processing steps to fulfill a specific type of analysis, or the reason for using a specific tool may not be as evident. ![]() Whereas, high-throughput sequencing has become more available for most laboratories, there is a lag in the expertise required to plunge into the current computational pipelines developed for immunoglobulin sequencing (or Ig-Seq). Since the study of antibody repertoires can be addressed from many biological aspects, there is a concomitant diverse set of computational algorithms tailored to many purposes. Likewise, computational pipelines have also helped to unveil details previously unknown about the antibody repertoire exhibiting the intertwined relationship that exists between modern antibody repertoire analysis and computational immunology ( 4, 8– 15). As new discoveries arise in the immunology field, novel computational tools have emerged to adapt their algorithms to provide more accurate and statistically robust analyses ( 6, 7). Practically, every maturation step can be followed experimentally by high-throughput sequencing, giving us the opportunity to analyze how the diverse exposure to antigens has a distinctive effect on a myriad of individual B cells, either at transcriptomic, or genomic level ( 3– 5). The study of antibody repertoires by high-throughput sequencing prompted many groups to develop computational pipelines that aid in the processing of large amounts of sequencing data in order to categorize and understand the diversity and dynamics of repertoires in individuals ( 1, 2). ![]() In this review we provide a practical and organized list of the current set of computational tools, focusing on their most attractive features and differences in order to carry out the characterization of antibody repertoires so that the reader better decides a strategic approach for the experimental design, and computational pathways for the analyses of immune repertoires. However, since not all tools function identically, every pipeline has its unique rationale and capabilities, creating a rich blend of useful features that may appear intimidating for newcomer laboratories with the desire to plunge into immune repertoire analysis to expand and improve their research hence, all pipeline strengths and differences may not seem evident. There is an increasing number of computational tools that aid in every step of the immune repertoire characterization. With the advent of high-throughput sequencing of immunoglobulin genes (Ig-Seq), the understanding of antibody repertoires and their dynamics among individuals and populations has become an exciting area of research.
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