Related Experiment Video
Updated: Jul 27, 2026
10:12
Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
Published on: January 10, 2019
18.8K
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.
Nature Methods
|May 14, 2021
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.
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.
