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Immune Repertoire Analysis

Immune repertoire analysis is the study of the set of T-cell receptors (TCRs) and B-cell receptors (BCRs) in an individual. This analysis provides insights into the state of the adaptive immune system and can be used to understand immune responses to diseases, vaccinations, and therapies. High-throughput sequencing has enabled deep analysis of immune repertoires, revealing millions of receptor sequences that help in diagnostics, treatment development, and monitoring.


📄️ Gene Usage

The immune repertoire, comprised of a vast array of T-cell and B-cell receptors (TCRs and BCRs), is generated through a process of V(D)J recombination. During this process, different V (Variable), D (Diversity, for heavy chains), and J (Joining) gene segments are randomly selected and joined together, creating a unique receptor sequence. However, this selection is not always purely random; certain gene segments may be preferentially used, a phenomenon known as "gene usage bias."

📄️ Rarefaction

When analyzing immune repertoires, a key goal is to compare the number of unique clonotypes—the clonal richness—across different samples. However, a common challenge is that samples are often sequenced to different depths. A sample with more sequencing reads will, by chance alone, likely reveal more unique clonotypes, making a direct comparison of richness misleading. This is like comparing the variety of colored candies in a small bag versus a large jar; the jar will almost certainly have more colors simply because it contains more candies.

📄️ Clone Tracking

Tracking individual clones over time is crucial for understanding how the immune system responds to stimuli like vaccinations, infections, or therapies. This longitudinal analysis, often called clone tracking, allows researchers to monitor the expansion, contraction, and persistence of specific immune cell populations. By tracking these dynamics, we can identify which clonotypes are driving an immune response, assess the durability of that response, and uncover potential biomarkers for disease or treatment efficacy.