Evidence map›Paper›PMID 39666949›Full record

ArticleGenomics, proteomics & bioinformatics2025

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

Ruonan Tian, Zhejian Yu, Ziwei Xue, Jiaxin Wu, Lize Wu, Shuo Cai, Bing Gao, Bing He, Yu Zhao, Jianhua Yao and 2 more

Abstract readEvaluation Study
In one paragraph

Article in Genomics, proteomics & bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Ruonan TianDepartment of Rheumatology and Immunology of the Second Affiliated Hospital, and Centre of Biomedical Systems and Informatics of Zhejiang University-University of Edinburgh Institute, Zhejiang University School of Medicine, Hangzhou 310003, China.ORCID 0009-0003-6018-397X
Zhejian YuDepartment of Rheumatology and Immunology of the Second Affiliated Hospital, and Centre of Biomedical Systems and Informatics of Zhejiang University-University of Edinburgh Institute, Zhejiang University School of Medicine, Hangzhou 310003, China.ORCID 0009-0005-0208-5452
Ziwei XueDepartment of Rheumatology and Immunology of the Second Affiliated Hospital, and Centre of Biomedical Systems and Informatics of Zhejiang University-University of Edinburgh Institute, Zhejiang University School of Medicine, Hangzhou 310003, China.ORCID 0000-0002-3491-2433
Jiaxin WuDepartment of Rheumatology and Immunology of the Second Affiliated Hospital, and Centre of Biomedical Systems and Informatics of Zhejiang University-University of Edinburgh Institute, Zhejiang University School of Medicine, Hangzhou 310003, China.ORCID 0009-0005-4648-1609
Lize WuFuture Health Laboratory, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing 314100, China.ORCID 0009-0007-0590-8375
Shuo CaiDepartment of Rheumatology and Immunology of the Second Affiliated Hospital, and Centre of Biomedical Systems and Informatics of Zhejiang University-University of Edinburgh Institute, Zhejiang University School of Medicine, Hangzhou 310003, China.ORCID 0009-0000-9542-2596
Bing GaoDepartment of Rheumatology and Immunology of the Second Affiliated Hospital, and Centre of Biomedical Systems and Informatics of Zhejiang University-University of Edinburgh Institute, Zhejiang University School of Medicine, Hangzhou 310003, China.ORCID 0009-0007-9748-6367
Bing HeAI Lab, Tencent, Shenzhen 518000, China.ORCID 0000-0003-1719-9290
Yu ZhaoAI Lab, Tencent, Shenzhen 518000, China.ORCID 0000-0001-8179-4903
Jianhua YaoAI Lab, Tencent, Shenzhen 518000, China.ORCID 0000-0001-9157-9596
Linrong LuFuture Health Laboratory, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing 314100, China.ORCID 0000-0002-0171-4115
Wanlu LiuDepartment of Rheumatology and Immunology of the Second Affiliated Hospital, and Centre of Biomedical Systems and Informatics of Zhejiang University-University of Edinburgh Institute, Zhejiang University School of Medicine, Hangzhou 310003, China.ORCID 0000-0001-5963-2908

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Receptors, Antigen, T-CellRNA-SeqSequence Analysis, RNASingle-Cell AnalysisHumansSingle-Cell Gene Expression AnalysisSoftwareReceptors, Antigen, T-CellAdaptive immunityBenchmark analysisscRNA-seqT cell receptorTCR construction

Identifiers

PMID39666949
PMCPMC11846667

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.