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qPCRTag Analysis - A High Throughput, Real Time PCR Assay for Sc2.0 Genotyping

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Lossless pangenome indexing using tag arrays.

Parsa Eskandar¹, Benedict Paten¹, Jouni Sirén²

¹UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA.

Algorithms for Molecular Biology : AMB

|June 19, 2026

Summary

We developed a scalable indexing framework using tag arrays to efficiently query complex pangenome graphs. This method enables lossless, haplotype-aware analysis of genomic variation, improving bioinformatics tools.

Keywords:

Burrows–Wheeler transform Pangenome indexing Tag arrays

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Area of Science:

Computational Biology
Bioinformatics
Genomics

Background:

Pangenome graphs are essential for representing genomic variation across multiple haplotypes.
Efficient and lossless indexing of large-scale pangenomic data remains a significant computational challenge.

Purpose of the Study:

To present a practical and scalable indexing framework for pangenome graphs.
To enable efficient, lossless, and haplotype-aware querying of genomic variation.

Main Methods:

Developed a tag array indexing framework extending the FM-index with run-length compressed tags.
Introduced a novel construction algorithm combining k-mers, graph extensions, and haplotype traversal.
Utilized multi-string Burrows-Wheeler transform (BWT) and r-index for large genome processing and index merging.

Main Results:

The tag array structure demonstrates effective compression and scalability with increasing haplotypes.
Accurate mapping information is preserved across diverse genomic regions.
The index supports efficient one-to-all coordinate translation between haplotypes.

Conclusions:

The proposed indexing method provides a practical solution for querying complex pangenomes.
Enables the development of scalable aligners and graph-based analysis tools.
Facilitates lossless and haplotype-aware genomic variation analysis.