hashrope-bio

Computational biology applications of hashrope — Exact byte comparison for gene-level change detection, genomic region comparison, mutation localization, drug resistance screening, and tandem repeat compression.

Exact comparison in 0.3.3

This release requires Hashrope 0.3.3 or later in the 0.3 series. Fingerprint values/defaults are unchanged; equality, mutation and conservation decisions now verify actual bytes. Report hash fields are metadata, and gene/exon reports carry separate verified change flags. Manually constructing these reports requires those flags rather than deriving them from hashes.

Exact verification can scan an entire independent region and uses a per-call comparison cache where needed. Shared ranges and periodic structure can be skipped after proof. Historical speedups and datasets below describe the earlier fingerprint experiments; they do not establish current exact-comparison performance or universal collision resistance. Historical result files have been preserved.

The exact-path optimization report reruns the full stored HIV comparison workload against archived preoptimization and optimized cores. It includes verification costs and construction exclusions; it does not revalidate the older chromosome-scale fingerprint speedups below.

Install

pip install "hashrope-bio==0.3.3"

For optional backends:

pip install -e ".[genomics]"   # pysam + biopython for FASTA I/O

Features

Gene-level change detection (genomics.gene_diff)

Compare gene bodies and exons exactly, with shortcuts for shared and repeated structure. Independent equal regions may require reading every byte.

from hashrope_bio.genomics import load_fasta_to_rope, load_gene_regions, diff_genes

ref_rope, h, _ = load_fasta_to_rope("reference.fa")
sample_rope, _, _ = load_fasta_to_rope("patient.fa", h=h)
genes = load_gene_regions("chr22_genes.tsv")
report = diff_genes(ref_rope, sample_rope, genes, h)
print(report.summary())
# Gene diff: 12/643 genes changed, 47/5127 exons changed
#   LARGE1 (650,315 bp): body changed, 3/14 exons differ
#   ...

Validated on GRCh38 chr22 with 643 real genes (UCSC refGene): 5,770/5,770 queries correct. Speedups: 25× for typical genes (10–50 Kbp), 411× for large genes (>500 Kbp).

Drug resistance screening (cheminformatics.resistance)

Check N known resistance mutation sites by comparing actual codon bytes.

from hashrope_bio.cheminformatics.resistance import check_resistance_panel, HIV_RT_NNRTI_PANEL

results = check_resistance_panel(ref_rope, sample_rope, HIV_RT_NNRTI_PANEL, h)
for r in results:
    if r.is_mutant:
        print(f"  {r.site.annotation}")

Validated on 100 real clinical HIV-1 sequences against Stanford HIVDB: 103/103 drug resistance mutations detected (100% sensitivity).

Region identity queries (genomics.region_query)

Exact byte comparison for arbitrary genomic regions; fingerprint queries remain available separately.

from hashrope_bio.genomics import region_hash, regions_identical

identical = regions_identical(ref_rope, sample_rope, start=10000, length=50000, h=h)

Mutation localization (genomics.mutation)

Exact prefix comparison localizes the first divergent byte. Matching fingerprints do not prune mutations.

Validated on 3,422 ClinVar pathogenic SNVs on chr22: 3,422/3,422 correct (100%).

Tandem repeat compression (genomics.repeats)

RepeatNode gives O(log q) hash computation for q-repeat motifs vs O(q·d) naive. 610× speedup at q=10,000 for clinical trinucleotide repeats (HTT, FMR1).

Project structure

src/hashrope_bio/
├── genomics/          # FASTA loading, region queries, mutation search, gene diff, repeats
├── proteomics/        # MD trajectory frame comparison (stub)
└── cheminformatics/   # Resistance panels, compound lookup with retained verification bytes
benchmarks/            # Experiment scripts
scripts/               # Dataset download helpers
data/                  # Downloaded datasets (gitignored)
tests/                 # Unit tests (28 passing)

Depends on

• hashrope — core rope data structure
• pysam / biopython (optional) — FASTA I/O

Citation

If you use hashrope-bio in published research, please cite:

• Repository: https://github.com/jemsbhai/hashrope-bio
• Core data structure: https://github.com/jemsbhai/hashrope

License

MIT

Compound lookup compatibility

build_compound_index retains every candidate and its canonical encoding bytes. lookup_compound checks those bytes inside the matching hash bucket; collisions and duplicate input rows are retained. Legacy plain dictionaries containing only hashes/row IDs are rejected because they cannot verify identity; rebuild them from the source file. Canonicalization remains the caller's responsibility.

Run consumer tests from this directory with local Hashrope installed (or add ../../../packages/python and src to PYTHONPATH): python -m pytest tests.