The advent of high-throughput sequencing technologies revolutionized the analysis of immune repertoires, allowing a much more detailed characterization in both qualitative and quantitative terms. This delved into a better understanding of the complexity of B-cell receptor immunoglobulin (BcR IG) repertoires in a wide range of diseases, such as infections, autoimmune diseases, and B-cell lymphomas. More particularly, growing evidence highlights the role of interactions with (auto)antigens in driving disease onset and evolution through selecting B-cell clones bearing immunogenetically specific BcR IG and continuously transforming the latter through inducing intraclonal diversification (ID). However, the increase in the volume and complexity of high-throughput data necessitated the development of bioinformatics tools enabling a fast and efficient analysis of immune repertoires. Here, we describe an approach to dissect high-throughput BcR IG data, through the application of purpose-built analytical tools. This strategy offers a compartmentalized characterization of BcR IG repertoires starting from raw high-throughput data. First, the T-cell receptor/immunoglobulin profiler (TRIP) tool represents a robust and flexible software framework for the analysis of the clonality and diversity of BcR IG gene repertoires. Subsequently, the Immunoglobulin Intraclonal Diversification Analysis (IgIDivA) tool integrates both traditional and innovative graph-based metrics to determine objectively the level of intraclonal diversification (ID), alongside statistical analysis to compare ID levels and features across various sample groups.