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Updated: Feb 28, 2026
09:10
A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes
Published on: May 22, 2018
10.1K
Adaptive Tracepoints for Pangenome Alignment Compression
Hasitha Kaushan1, Santiago Marco-Sola2,3, Erik Garrison4
1Department of Electrical Engineering, University of Moratuwa, Bandaranayake Mawatha, Moratuwa 10400, Sri Lanka.
Biorxiv : the Preprint Server for Biology
|February 27, 2026
Summary
Adaptive tracepoints offer superior compression for genomic sequence alignments by intelligently segmenting data based on complexity. This method significantly improves storage efficiency for large-scale genomic comparisons compared to traditional fixed-size encodings.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- Storing large-scale genomic comparison data requires efficient compression.
- Fixed-size alignment encodings lack adaptability to variable sequence complexity, limiting compression.
- Conserved regions in genomic sequences present missed compression opportunities.
Purpose of the Study:
- To develop a complexity-aware alignment encoding method.
- To improve compression efficiency for sequence alignments.
- To ensure alignment reconstruction maintains or improves alignment scores.
Main Methods:
- Introduced adaptive tracepoints, an alignment encoding method.
- Segmented alignments using configurable complexity metrics like edit distance or diagonal distance.
- Bounded segments by differences or deviation from the main diagonal to adapt to local characteristics.
Main Results:
- Diagonal-bounded tracepoints achieved 10.5-13.7x better compression on simulated long sequences.
- Edit-bounded tracepoints offered tunable trade-offs between compression and reconstruction cost.
- Real pangenome data showed 23-139x compression with no score degradation and linear reconstruction time.
Conclusions:
- Adaptive tracepoints provide significant compression gains for genomic sequence alignments.
- The method adapts to local alignment characteristics, outperforming fixed-size methods.
- The approach is validated on simulated and real pangenome data, ensuring efficiency and accuracy.
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