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A novel approach to T-cell receptor beta chain (TCRB) repertoire encoding using lossless string compression
Thomas Konstantinovsky1,2, Gur Yaari1,2
1Faculty of Engineering, Bar Ilan University, Ramat Gan 5290002, Israel.
Bioinformatics (Oxford, England)
|July 7, 2023
Summary
This study introduces a novel graph-based method using Lempel-Ziv 76 to represent complex T-cell receptor beta chain (TCRB) repertoires. This approach enables efficient analysis and diverse applications in immune repertoire research.
Area of Science:
- Immunology
- Bioinformatics
- Computational Biology
Background:
- T-cell receptor beta chain (TCRB) repertoires are vital for adaptive immunity.
- The high diversity and complexity of TCRB repertoires pose challenges for analysis and representation.
- Understanding TCRB repertoire dynamics is crucial for immune response studies.
Purpose of the Study:
- To develop a unified and compact representation for TCRB repertoires.
- To enable efficient capture of TCRB repertoire complexity and diversity.
- To facilitate direct inference and analysis of TCRB repertoire data.
Main Methods:
- Leveraged the Lempel-Ziv 76 algorithm for TCRB repertoire encoding.
- Developed a novel graph-like model for TCRB sequence representation.
- Created a new encoding approach for individual TCRB repertoires.
Main Results:
- The proposed representation supports various applications: inference of generation probability, derivation of informative feature vectors, sequence generation, and new measures for diversity and sequence centrality.
- Applied the approach to four large-scale public TCRB sequencing datasets.
- Demonstrated the method's potential for big biological sequencing data analysis.
Conclusions:
- The Lempel-Ziv 76-based approach offers a powerful and versatile tool for TCRB repertoire analysis.
- This novel representation addresses the challenges of TCRB repertoire complexity and diversity.
- The method has broad applicability in immunological and bioinformatics research.
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