Commit Graph

3 Commits

Author SHA1 Message Date
Eric Coissac
a7ea47624b Optimisation du parsing des grandes séquences
Implémente une optimisation du parsing des grandes séquences en évitant l'allocation de mémoire inutile lors de la fusion des chunks. Ajoute un support pour le parsing direct de la structure rope, ce qui permet de réduire les allocations et d'améliorer les performances lors du traitement de fichiers GenBank/EMBL et FASTA/FASTQ de plusieurs Gbp. Les parseurs sont mis à jour pour utiliser la rope non-packée et le nouveau mécanisme d'écriture in-place pour les séquences GenBank.
2026-03-10 14:20:21 +01:00
Eric Coissac
a016ad5b8a Refactor kmer index to disk-based partitioning with minimizer
Refactor kmer index package to use disk-based partitioning with minimizer

- Replace roaring64 bitmaps with disk-based kmer index
- Implement partitioned kmer sets with delta-varint encoding
- Add support for frequency filtering during construction
- Introduce new builder pattern for index construction
- Add streaming operations for set operations (union, intersect, etc.)
- Add support for super-kmer encoding during construction
- Update command line tool to use new index format
- Remove dependency on roaring bitmap library

This change introduces a new architecture for kmer indexing that is more memory efficient and scalable for large datasets.
2026-02-09 17:52:37 +01:00
Eric Coissac
500144051a Add jj Makefile targets and k-mer encoding utilities
Add new Makefile targets for jj operations (jjnew, jjpush, jjfetch) to streamline commit workflow.

Introduce k-mer encoding utilities in pkg/obikmer:
- EncodeKmers: converts DNA sequences to encoded k-mers
- ReverseComplement: computes reverse complement of k-mers
- NormalizeKmer: returns canonical form of k-mers
- EncodeNormalizedKmers: encodes sequences with normalized k-mers

Add comprehensive tests for k-mer encoding functions including edge cases, buffer reuse, and performance benchmarks.

Document k-mer index design for large genomes, covering:
- Use cases and objectives
- Volume estimations
- Distance metrics (Jaccard, Sørensen-Dice, Bray-Curtis)
- Indexing options (Bloom filters, sorted sets, MPHF)
- Optimization techniques (k-2-mer indexing)
- MinHash for distance acceleration
- Recommended architecture for presence/absence and counting queries
2026-02-04 14:27:10 +01:00