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Updated: Jun 5, 2025

Streamlined Single Cell TCR Isolation and Generation of Retroviral Vectors for In Vitro and In Vivo Expression of Human TCRs

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

Ruonan Tian^1,2, Zhejian Yu¹, Ziwei Xue^1,2

¹Department 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.

Genomics, Proteomics & Bioinformatics

|December 12, 2024

Summary

This study benchmarks T cell receptor (TCR) reconstruction methods from single-cell RNA sequencing (scRNA-seq) data. TRUST4 and MiXCR showed superior performance, highlighting sequencing depth as a critical factor for accurate TCR construction.

Keywords:

Adaptive immunity Benchmark analysis T cell receptor TCR construction scRNA-seq

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T and B Cell Receptor Immune Repertoire Analysis using Next-generation Sequencing

T and B Cell Receptor Immune Repertoire Analysis using Next-generation Sequencing

Published on: January 12, 2021

Area of Science:

Immunology
Bioinformatics
Genomics

Background:

T cell receptors (TCRs) are crucial for adaptive immunity, recognizing pathogens and abnormal cells.
Accurate TCR reconstruction from single-cell RNA sequencing (scRNA-seq) data is vital for immunological studies.
Existing TCR construction methods lack comprehensive performance evaluations across diverse conditions.

Purpose of the Study:

To benchmark and compare the performance of various TCR reconstruction algorithms using experimental scRNA-seq datasets.
To introduce YASIM-scTCR, a novel simulator for generating synthetic scTCR-seq data.
To identify key factors influencing TCR construction accuracy, such as sequencing depth.

Main Methods:

Utilized experimental single-cell immune profiling datasets for benchmarking.
Developed YASIM-scTCR to simulate scTCR-seq reads with variable sequencing depths and lengths.
Evaluated multiple TCR reconstruction tools including TRUST4, MiXCR, and DeRR.

Main Results:

TRUST4 and MiXCR consistently outperformed other methods across multiple datasets.
DeRR demonstrated notable accuracy in TCR reconstruction.
Sequencing depth was identified as a critical constraint affecting successful TCR construction.

Conclusions:

Provides a benchmark analysis to guide researchers in selecting optimal TCR reconstruction methods.
Highlights the superior performance of TRUST4 and MiXCR for TCR construction from scRNA-seq data.
Emphasizes the significant impact of sequencing depth on the reliability of TCR reconstruction.