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Updated: Feb 7, 2026
07:44
Identifying Protein-protein Interaction Sites Using Peptide Arrays
Published on: November 18, 2014
18.6K
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.
Research Square
|February 6, 2026
Summary
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.
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.
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