Add a new boolean option 'keep-shorter' to preserve fragments shorter than kmer-size during split/extract mode.
This change introduces a new flag _lowmaskKeepShorter that controls whether fragments
shorter than the kmer size should be kept during split/extract operations.
The implementation:
1. Adds the new boolean variable _lowmaskKeepShorter
2. Registers the command-line option "keep-shorter"
3. Updates the lowMaskWorker function signature to accept the keepShorter parameter
4. Modifies the fragment selection logic to check the keepShorter flag
5. Updates the worker creation to pass the global flag value
This allows users to control the behavior when dealing with short sequences in
split/extract modes, providing more flexibility in low-complexity masking.
This commit introduces max frequency filtering to limit k-mer occurrences and adds functionality to save the N most frequent k-mers per set to CSV files. It also includes the ability to output k-mer frequency spectra as CSV and updates the CLI options accordingly.
This commit refactors the k-mer index management tools to use a unified subcommand structure with obik, adds support for per-set metadata and ID management, enhances the k-mer set group builder to support appending to existing groups, and improves command-line option handling with a new global options registration system.
Key changes:
- Introduce obik command with subcommands (index, ls, summary, cp, mv, rm, super, lowmask)
- Add support for per-set metadata and ID management in kmer set groups
- Implement ability to append to existing kmer index groups
- Refactor option parsing to use a global options registration system
- Add new commands for listing, copying, moving, and removing sets
- Enhance low-complexity masking with new options and output formats
- Improve kmer index summary with Jaccard distance matrix support
- Remove deprecated obikindex and obisuperkmer commands
- Update build process to use the new subcommand structure
Refactor k-mer index building to use the new disk-based KmerSetGroupBuilder instead of the old KmerSet and FrequencyFilter approaches. This change introduces a more efficient and scalable approach to building k-mer indices by using partitioned disk storage with streaming operations.
- Replace BuildKmerIndex and BuildFrequencyFilterIndex with KmerSetGroupBuilder
- Add support for frequency filtering via WithMinFrequency option
- Remove deprecated k-mer set persistence methods
- Update CLI to use new builder approach
- Add new disk-based k-mer operations (union, intersect, difference, quorum)
- Introduce KDI (K-mer Delta Index) file format for efficient storage
- Add K-way merge operations for combining sorted k-mer streams
- Update documentation and examples to reflect new API
This refactoring provides better memory usage, faster operations on large datasets, and more flexible k-mer set operations.
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.
This commit optimizes the low-complexity masking algorithm by:
1. Precomputing logarithm values and normalization tables to avoid repeated calculations
2. Replacing the MinMultiset-based sliding minimum with a more efficient deque-based implementation
3. Improving entropy calculation by using precomputed n*log(n) values
4. Simplifying the circular normalization process with precomputed tables
5. Removing unused imports and log statements
The changes significantly improve performance while maintaining the same masking behavior.
This commit introduces a new configuration module `obidefault` to manage progress bar settings, allowing users to disable progress bars via a `--no-progressbar` option. It updates various packages to conditionally display progress bars based on this new configuration, improving user experience by providing control over progress bar output. The changes also include improvements to progress bar handling in several packages, ensuring they are only displayed when appropriate (e.g., when stderr is a terminal and stdout is not piped).
This commit fixes an issue in the chunk processing logic where the wrong classifier instance was being reset and used for code generation. A local clone of the classifier is now created and used to ensure correct behavior during dereplication.
Modify CLIProgressBar function to check if stdout is a named pipe and disable the progress bar accordingly. This prevents the progress bar from being displayed when the output is redirected or piped to another command.
This commit addresses a bug in the super k-mer implementation where the minimizer bijection property was not properly enforced. The fix ensures that:
1. All k-mers within a super k-mer share the same minimizer
2. Identical super k-mer sequences have the same minimizer
The changes include:
- Fixing the super k-mer iteration logic to properly validate the minimizer bijection property
- Adding a comprehensive test suite (TestSuperKmerMinimizerBijection) that validates the intrinsic property of super k-mers
- Updating the .gitignore file to properly track relevant files
This resolves issues where the same sequence could be associated with different minimizers, violating the super k-mer definition.
This commit adds the implementation of the obisuperkmer command, including:
- The main command in cmd/obitools/obisuperkmer/
- The package implementation in pkg/obitools/obisuperkmer/
- Automated tests in obitests/obitools/obisuperkmer/
- Documentation for the implementation and tests
The obisuperkmer command extracts super k-mers from DNA sequences, following the standard OBITools architecture. It includes proper CLI option handling, validation of parameters, and integration with the OBITools pipeline system.
Tests cover basic functionality, parameter validation, output format, metadata preservation, and file I/O operations.
This commit refactors the SuperKmer extraction functionality to use Go's new iterator pattern. The ExtractSuperKmers function is now implemented as a wrapper around a new IterSuperKmers iterator function, which yields results one at a time instead of building a complete slice. This change provides better memory efficiency and more flexible consumption of super k-mers. The functionality remains the same, but the interface is now more idiomatic and efficient for large datasets.
Add Jaccard distance and similarity computations for KmerSet and KmerSetGroup
This commit introduces Jaccard distance and similarity methods for KmerSet and KmerSetGroup.
For KmerSet:
- Added JaccardDistance method to compute the Jaccard distance between two KmerSets
- Added JaccardSimilarity method to compute the Jaccard similarity between two KmerSets
For KmerSetGroup:
- Added JaccardDistanceMatrix method to compute a pairwise Jaccard distance matrix
- Added JaccardSimilarityMatrix method to compute a pairwise Jaccard similarity matrix
Also includes:
- New DistMatrix implementation in pkg/obidist for storing and computing distance/similarity matrices
- Updated version handling with bump-version target in Makefile
- Added tests for all new methods
This commit refactors the k-mer normalization functions, renaming them from 'NormalizeKmer' to 'CanonicalKmer' to better reflect their purpose of returning canonical k-mers. It also introduces new quorum operations (AtLeast, AtMost, Exactly) for k-mer set groups, along with comprehensive tests and benchmarks. The version commit hash has also been updated.
This commit translates all French comments in the kmer filtering and set management code to English, improving code readability and maintainability for international collaborators.
Ajout de la fonctionnalité de sauvegarde et de chargement pour FrequencyFilter en utilisant le KmerSetGroup sous-jacent.
- Nouvelle méthode Save() pour enregistrer le filtre dans un répertoire avec formatage des métadonnées
- Nouvelle méthode LoadFrequencyFilter() pour charger un filtre depuis un répertoire
- Initialisation des métadonnées lors de la création du filtre
- Optimisation des méthodes Union() et Intersect() du KmerSetGroup
- Mise à jour du commit hash
This commit refactors all k-mer encoding and normalization functions to consistently use 'canonical' instead of 'normalized' terminology. This includes renaming functions like EncodeNormalizedKmer to EncodeCanonicalKmer, IterNormalizedKmers to IterCanonicalKmers, and NormalizeKmer to CanonicalKmer. The change aligns the API with biological conventions where 'canonical' refers to the lexicographically smallest representation of a k-mer and its reverse complement. All related documentation and examples have been updated accordingly. The commit also updates the version file with a new commit hash.
This commit introduces new functions for encoding and decoding k-mers, including support for normalized k-mers. It also updates the frequency filter and k-mer set implementations to use the new encoding functions, providing zero-allocation encoding for better performance. The commit hash has been updated to reflect the latest changes.
This commit refactors the KmerSet and related structures to use an immutable K parameter and introduces consistent Copy methods instead of Clone. It also adds attribute API support for KmerSet and KmerSetGroup, and updates persistence logic to handle IDs and metadata correctly.
Cette modification ajoute la capacité de stocker et de persister des métadonnées utilisateur dans les structures KmerSet et KmerSetGroup. Les changements incluent l'ajout d'un champ Metadata dans KmerSet et KmerSetGroup, ainsi que la mise à jour des méthodes de clonage et de persistance pour gérer ces métadonnées. Cela permet de conserver des informations supplémentaires liées aux ensembles de k-mers tout en maintenant la compatibilité avec les opérations existantes.
This commit adds support for saving and loading KmerSet and KmerSetGroup structures using TOML, YAML, and JSON formats for metadata. It includes:
- Added github.com/pelletier/go-toml/v2 dependency
- Implemented Save and Load methods for KmerSet and KmerSetGroup
- Added metadata persistence with support for multiple formats (TOML, YAML, JSON)
- Added helper functions for format detection and metadata handling
- Updated version commit hash
Refactor FrequencyFilter to inherit from KmerSetGroup for better code organization and maintainability. This change replaces the direct bitmap management with a group-based approach, simplifying the implementation and improving readability.
This commit refactors the k-mer encoding logic to handle ambiguous bases more consistently and introduces a KmerSet type for better management of k-mer collections. The frequency filter now works with KmerSet instead of roaring bitmaps directly, and the API has been updated to support level-based frequency queries. Additionally, the commit updates the version and commit hash.
This commit introduces error handling for ambiguous DNA bases (N, R, Y, W, S, K, M, B, D, H, V) in k-mer encoding. It adds new functions IterNormalizedKmersWithErrors and EncodeNormalizedKmersWithErrors that track and encode the number of ambiguous bases in each k-mer using error markers in the top 2 bits. The commit also updates the version string to reflect the latest changes.
Implémentation complète du filtre de fréquence utilisant v niveaux de Roaring Bitmaps pour éliminer efficacement les erreurs de séquençage.
- Ajout de la logique de filtrage par fréquence avec v niveaux
- Intégration des bibliothèques RoaringBitmap et bitset
- Ajout d'exemples d'utilisation et de documentation
- Implémentation de l'itérateur de k-mers pour une utilisation mémoire efficace
- Optimisation pour les distributions skewed typiques du séquençage
Ce changement permet de filtrer les k-mers par fréquence minimale avec une utilisation mémoire optimale et une seule passe sur les données.
This commit introduces error marker functionality for k-mers with odd lengths up to 31. The top 2 bits of each k-mer are now reserved for error coding (0-3), allowing for error detection and correction capabilities. Key changes include:
- Added constants KmerErrorMask and KmerSequenceMask for bit manipulation
- Implemented SetKmerError, GetKmerError, and ClearKmerError functions
- Updated EncodeKmers, ExtractSuperKmers, EncodeNormalizedKmers functions to enforce k ≤ 31
- Enhanced ReverseComplement to preserve error bits during reverse complement operations
- Added comprehensive tests for error marker functionality including edge cases and integration tests
The maximum k-mer size is now capped at 31 to accommodate the error bits, ensuring that k-mers with odd lengths ≤ 31 utilize only 62 bits of the 64-bit uint64, leaving the top 2 bits available for error coding.
This commit introduces the ExtractSuperKmers function which identifies maximal subsequences where all consecutive k-mers share the same minimizer. It includes:
- SuperKmer struct to represent the maximal subsequences
- dequeItem struct for tracking minimizers in a sliding window
- Efficient algorithm using monotone deque for O(1) amortized minimizer tracking
- Comprehensive parameter validation
- Support for buffer reuse for performance optimization
- Extensive test cases covering basic functionality, edge cases, and performance benchmarks
The implementation uses simultaneous forward/reverse m-mer encoding for O(1) canonical m-mer computation and maintains a monotone deque to track minimizers efficiently.
Ajout d'une fonctionnalité pour le filtrage unique qui prend en compte à la fois la séquence et les catégories.
- Modification de la fonction ISequenceChunk pour accepter un classifieur unique optionnel
- Implémentation du traitement unique sur disque en utilisant un classifieur composite
- Mise à jour du classifieur utilisé pour le tri sur disque
- Correction de la gestion des clés de unicité en utilisant le code et la valeur du classifieur
- Mise à jour du numéro de commit
