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Updated: Nov 5, 2025

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TRUST4: immune repertoire reconstruction from bulk and single-cell RNA-seq data.

Li Song1,2, David Cohen1, Zhangyi Ouyang3

  • 1Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA.

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|May 14, 2021
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Summary

We developed TRUST4, an open-source tool for analyzing immune receptor repertoires from RNA sequencing data. It is faster and more sensitive than other methods for reconstructing T-cell and B-cell receptor sequences.

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Area of Science:

  • Immunoinformatics
  • Computational Biology
  • Genomics

Background:

  • Accurate reconstruction of immune receptor repertoires is crucial for understanding adaptive immunity.
  • Existing methods for repertoire analysis from RNA sequencing data have limitations in speed, sensitivity, and input data compatibility.

Purpose of the Study:

  • To introduce TRUST4, an open-source algorithm for the efficient and sensitive reconstruction of immune receptor repertoires.
  • To enable repertoire analysis from diverse RNA sequencing data types, including single-cell RNA sequencing.

Main Methods:

  • TRUST4 algorithm utilizes RNA sequencing data (FASTQ and BAM formats).
  • Supports reconstruction of αβ T-cell receptor, γδ T-cell receptor, and B-cell receptor repertoires.
  • Compatible with SMART-seq and 10x Genomics single-cell RNA sequencing platforms without V(D)J enrichment.

Main Results:

  • TRUST4 demonstrates superior speed and sensitivity in assembling longer and full-length immune receptor sequences compared to existing methods.
  • Successfully calls repertoire sequences from single-cell RNA sequencing data.

Conclusions:

  • TRUST4 provides a robust, efficient, and versatile solution for immune receptor repertoire reconstruction.
  • Facilitates deeper insights into adaptive immune responses across various experimental settings.