摘要T cell receptors(TCRs)serve key roles in the adaptive immune system by enabling recognition and response to pathogens and irregular cells.Various methods have been developed for TCR construction from single-cell RNA sequencing(scRNA-seq)datasets,each with its unique characteristics.Yet,a comprehensive evaluation of their relative performance under different conditions remains elusive.In this study,we conducted a benchmark analysis utilizing experimental single-cell immune profiling datasets.Additionally,we introduced a novel simulator,YASIM-scTCR(Yet Another SIMulator for single-cell TCR),capable of generating scTCR-seq reads containing diverse TCR-derived sequences with different sequencing depths and read lengths.Our results consistently showed that TRUST4 and MiXCR outperformed others across multiple datasets,while DeRR demonstrated considerable accu-racy.We also discovered that the sequencing depth inherently imposes a critical constraint on successful TCR construction from scRNA-seq data.In summary,we present a benchmark study to aid researchers in choosing the appropriate method for reconstructing TCRs from scRNA-seq data.