Evaluation of T Cell Receptor Construction Methods from scRNA-Seq Data

被引：0

作者：

Tian, Ruonan ^{[1
,2
,3
]}

Yu, Zhejian ^{[1
]}

Xue, Ziwei ^{[1
,2
,3
]}

Wu, Jiaxin ^{[1
]}

Wu, Lize ^{[2
,3
,4
,5
]}

Cai, Shuo ^{[1
]}

Gao, Bing ^{[1
]}

He, Bing ^{[6
]}

Zhao, Yu ^{[6
]}

Yao, Jianhua ^{[6
]}

Lu, Linrong ^{[2
,3
,4
,5
,7
]}

Liu, Wanlu ^{[1
,2
,3
]}

机构：

[1] Zhejiang Univ, Affiliated Hosp 2, Sch Med, Dept Rheumatol & Immunol, Hangzhou 310003, Peoples R China

[2] Zhejiang Univ, Univ Edinburgh Inst, Sch Med, Ctr Biomed Syst & Informat, Hangzhou 310003, Peoples R China

[3] Zhejiang Univ, Innovat Ctr Yangtze River Delta, Future Hlth Lab, Jiaxing 314100, Peoples R China

[4] Zhejiang Univ, Inst Immunol, Sch Med, Hangzhou 310058, Peoples R China

[5] Zhejiang Univ, Sir Run Run Shaw Hosp, Sch Med, Dept Dermatol & Rheumatol, Hangzhou 310058, Peoples R China

[6] AI Lab, Tencent, Shenzhen 518000, Peoples R China

[7] Shanghai Jiao Tong Univ, Affiliated Renji Hosp, Shanghai Immune Therapy Inst, Sch Med, Shanghai 200025, Peoples R China

来源：

GENOMICS PROTEOMICS & BIOINFORMATICS | 2025年 / 22卷 / 06期

基金：

中国国家自然科学基金;

关键词：

T cell receptor; scRNA-seq; Benchmark analysis; TCR construction; Adaptive immunity; CLONALITY INFERENCE; READ ALIGNMENT; REPERTOIRE; SEQUENCES; HEALTH;

D O I：

10.1093/gpbjnl/qzae086

中图分类号：

Q3 [遗传学];

学科分类号：

071007 ; 090102 ;

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 accuracy. 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.

引用

页数：14

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