Change-O: a toolkit for analyzing large-scale B cell immunoglobulin repertoire sequencing data

Area of Science:

• Immunology
• Bioinformatics
• Computational Biology

Background:

• High-throughput sequencing enables large-scale characterization of B cell immunoglobulin (Ig) repertoires.
• The inherent diversity of Ig repertoires poses significant challenges for biological analysis.
• Specialized computational methods are essential for meaningful interpretation of Ig repertoire data.

Purpose of the Study:

• To introduce Change-O, a suite of computational utilities designed for advanced analysis of large-scale Ig repertoire sequencing data.
• To provide tools for comprehensive characterization of Ig repertoire features, including germline alleles, clonal structure, and somatic hypermutation.
• To facilitate integrated analysis workflows through a common data format.

Main Methods:

• Development of a suite of utilities named Change-O.
• Implementation of tools for Ig variable region gene segment allele determination (including novel alleles).
• Inclusion of functions for partitioning sequences into clonal populations, constructing lineage trees, and inferring somatic hypermutation targeting models.
• Features for measuring repertoire diversity, quantifying selection pressure, and calculating sequence chemical properties.
• Standardization of a common data format for seamless integration of multiple analyses.

Main Results:

• Change-O provides tools for comprehensive analysis of Ig repertoire sequencing data.
• The software enables detailed characterization of Ig alleles, clonal populations, and evolutionary dynamics.
• Integrated workflows are facilitated by a unified data format, simplifying complex analyses.

Conclusions:

• Change-O offers a powerful and integrated computational solution for analyzing large-scale Ig repertoire data.
• The toolkit addresses key challenges in Ig repertoire analysis, enabling deeper biological insights.
• Availability for non-commercial use promotes wider adoption in immunological research.