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Identifying Protein-protein Interaction Sites Using Peptide Arrays
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Lossless Pangenome Indexing Using Tag Arrays.

Parsa Eskandar1, Benedict Paten1, Jouni Sirén1

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

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|February 6, 2026
PubMed
Summary
This summary is machine-generated.

We developed a novel tag array indexing framework for pangenome graphs, enabling efficient and lossless querying of genomic variations across multiple haplotypes. This method enhances scalability for complex pangenomic data analysis.

Keywords:
Burrows–Wheeler transformpangenome indexingtag arrays

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • 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 complex pangenomic data.

Main Methods:

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

Main Results:

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

Conclusions:

  • The proposed indexing method provides a practical solution for lossless and haplotype-aware querying in complex pangenomes.
  • This framework serves as a scalable indexing layer for developing advanced graph-based analysis tools and aligners.