The accuracy of these results is essential for high-level studies and for the subsequent qualitative and quantitative analysis of TCR Rep-Seq data. V(D) J assignment decodes the fundamental information for somatic recombination, and the CDR3 sequence determines the binding specificity for a particular TCR. While a thorough investigation of these high-level analyses is helpful for the community, the authors did not explicitly compare the performance of these tools in low-level or fundamental analyses. In addition to the general properties such as ease of usage, customizability, Linux installation, and dependency on external tools, their study focused on comparisons of clonotype detection (i.e., the identification of unique V(D) J combinations), CDR3 identification, and error correction accuracy. reported a systematic comparison of ten TCR Rep-Seq tools. While the availability of these tools is helpful, there is no clear consensus of which one yields better results during analyses.Īfzal et al. Several tools have been developed to unravel the complex information contained within TCR repertoires. High-level analyses examine repertoire diversity, shared and private clones, and antigen specificity. Low-level analyses investigate raw data processing, error correction, V (D) J assignments, and third complementary determining region (CDR3) extraction. TCR Rep-Seq analyses can be classified as either low-level or high-level analyses. However, while capturing millions of distinct TCRs via HTS technology is straightforward, accurately and effectively extrapolating biological and/or clinical information from these data represents a significant challenge. TCR Rep-Seq may also have the potential to trace an individual’s immune history and evaluate his or her ability to resist distinct pathogens. To date, this versatile approach has been applied for studies of cancer, inflammation, autoimmune disease, hematopoietic stem cell transplantation, infection, and rare diseases. Indeed, high-throughput TCR repertoire sequencing (TCR Rep-Seq) and profiling has emerged as an important tool in fundamental research and clinical applications, such as vaccine design and monitoring therapeutic responses. High-throughput sequencing (HTS) technology can capture hundreds to thousands of millions of sequencing reads and thus enables researchers to characterize TCR repertoires with unprecedented depth. However, studies of the TCR repertoire are complicated by the number of molecules involved, because traditional methods, such as spectratyping, Sanger sequencing, and flow cytometry, can only characterize a limited number of TCRs. Thus, the TCR repertoire plays a critical role in adaptive immunity, and analysis of TCR repertoires stands to improve our understanding of immune responses and may have broad implications for health and well-being. This diversity underlies the immune system’s ability to raise specific responses against a vast array of antigens, including pathogens, auto-antigens, toxins, allergens, and tumor neoantigens. Theoretically, the number of distinct TCRs in an individual is estimated to be as high as 10 13~10 15. The TCR repertoire is characterized by incredible diversity, because each TCR is generated through consecutive biological processes consisting of somatic rearrangement, non-template insertion and deletion, and heterogeneous chain pairing. The set of all T cell receptors in an individual is known as his or her TCR repertoire. Our results shed light on the detailed functions of TCR repertoire analysis tools and may therefore help researchers in the field to choose the right tools for their particular experimental design. Here, we present a systematic analysis of 12 available TCR repertoire analysis tools using simulated data, with an emphasis on fundamental analysis functions. Although these tools claim to be able to perform the full range of fundamental TCR repertoire analyses, there is no clear consensus of which tool is best suited to particular projects. In the past decade, several high-throughput sequencing-based tools have been developed to assign TCRs to germline genes and to extract complementarity-determining region 3 (CDR3) sequences using different algorithms. Defining TCR repertoires under physiological conditions and in response to a disease or vaccine may lead to a better understanding of adaptive immunity and thus has great biological and clinical value. The full set of T cell receptors (TCRs) in an individual is known as his or her TCR repertoire.
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