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Eric Coissac
8c7017a99d
- Update obioptions.Version from "Release 4.4.29" to "/v/ Release v5" - Update version.txt from 4.29 → .30 (automated by Makefile)
38 lines
2.1 KiB
Markdown
38 lines
2.1 KiB
Markdown
# `obiseq` Package: BioSequence Collection Management
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The `obiseq` package provides a high-performance, memory-efficient implementation for managing collections of biological sequences (`BioSequence`) in Go. Its core type is `BioSequenceSlice`, a slice of pointers to `BioSequence` objects, optimized for batch processing in metagenomic pipelines.
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### Key Functionalities
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- **Memory Pooling & Allocation Control**:
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`NewBioSequenceSlice` and `MakeBioSequenceSlice` allow creating slices with optional capacity hints.
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`EnsureCapacity(capacity)` dynamically grows the underlying slice while logging warnings or panicking on persistent allocation failures.
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- **Efficient Element Management**:
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- `Push(sequence)`: Appends a sequence to the end.
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- `Pop()`: Removes and returns the last element (nil-safe).
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- `Pop0()`: Efficiently removes and returns the first element.
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- **Collection Metadata Queries**:
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- `Len()`: Returns number of sequences in the slice.
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- `Size()`: Computes total sequence length (summing all `.Len()`).
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- `NotEmpty()`: Boolean check for non-empty collections.
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- **Attribute Aggregation**:
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`AttributeKeys(skip_map, skip_definition)` aggregates all attribute keys across sequences into a set—useful for schema inference or validation.
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- **Sorting Capabilities**:
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- `SortOnCount(reverse)`: Sorts by read count (descending/ascending).
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- `SortOnLength(reverse)`: Sorts by sequence length.
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- **Taxonomy Integration**:
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`ExtractTaxonomy(taxonomy, seqAsTaxa)` builds or extends a taxonomic tree from sequence paths.
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When `seqAsTaxa=true`, it injects pseudo-taxonomic labels for individual sequences (e.g., `OTU:SEQ0000012345 [seqID]@sequence`), enabling unified taxonomic/rarefaction workflows.
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### Design Highlights
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- Minimal allocations via manual slice management and `slices.Grow`.
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- Explicit niling of popped elements to aid garbage collection.
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- Integrated logging (via `logrus`) for allocation issues—critical in large-scale NGS data processing.
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- Designed to support `BioSequenceBatch`, a higher-level abstraction for streaming or parallelizable sequence batches.
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