# obikmer

`obikmer` is a Rust toolkit for indexing, querying, and comparing DNA sequences
represented as sets of k-mers. It targets individual genome datasets (tens of
Gbases) with maximum efficiency in computation, memory, and disk usage.

## Key principles

**Compact k-mer encoding.** Each k-mer is stored in a `u64` at 2 bits/base.
k is odd, k ∈ [11, 31], fixed at runtime. The canonical form `min(kmer, revcomp(kmer))`
halves the effective space by collapsing both strands.

**Superkmer-based partitioning.** Sequences are decomposed into superkmers —
maximal runs of k-mers sharing the same minimizer. Superkmers route naturally to
partitions via the minimizer hash, enabling partition-parallel indexing and querying
with no cross-partition communication.

**Layered MPHF index.** Each partition holds a stack of layers. Each layer is a
minimal perfect hash function (MPHF) over the k-mers of one input genome, paired
with a per-genome presence/count matrix. Queries scatter k-mers to their partition,
probe each layer in order, and aggregate results.

**Approximate indexing (Findere).** With `-z Z`, the index stores k-mers of size
`s = k − z + 1` instead of k. At query time, results are produced at size s, then
a per-genome sliding window of size z aggregates z consecutive s-mer hits into one
confirmed k-mer answer. This reduces the false-positive rate from `1/2^b` per s-mer
to `1/2^(b·z)` per k-mer, at the cost of z−1 unconfirmed positions at each sequence
break. The aggregation window spans the full query sequence, not individual superkmers,
to avoid false negatives at superkmer boundaries.

**Multi-genome.** A single index can hold any number of genomes. Each k-mer slot
carries a per-genome count or presence vector. Distance matrices, NJ/UPGMA trees,
and classification are derived from these vectors without rebuilding the index.

## Input formats

    Command              Formats accepted
    ───────────────────  ──────────────────────────────────────────────────────────────
    index, superkmer     FASTA (.fa .fasta), FASTQ (.fq .fastq), GenBank flat file
                         (.gb .gbk .gbff), all optionally gzip-compressed.
                         Directories expanded recursively. Streaming stdin via -.
    query                FASTA, FASTQ, optionally gzip-compressed. Stdin via -.

Non-ACGT characters act as hard breaks between k-mer segments in all formats.

## Commands

    Command    Role
    ─────────  ────────────────────────────────────────────────────────────────────
    index      Build a genome index from sequence files.
               Runs scatter → dereplicate → count → layered MPHF.
               Resumes automatically if interrupted.
    merge      Merge multiple independently built indexes into one.
               Schedules partitions largest-first under a memory budget semaphore
               to avoid OOM on machines with many cores. The worst partition runs
               alone first to calibrate the expansion estimator; subsequent
               partitions run in parallel within the budget.
               --budget-fraction F  fraction of available RAM to use as budget
                                    (default 0.5; reduce if OOM persists).
    filter     Filter and compact an existing index: apply count thresholds,
               drop layers, rewrite as a single-layer index.
    reindex    Convert evidence in-place across all layers:
               exact (evidence.bin) ↔ approximate (fingerprint.bin).
               Does not touch the MPHF or unitigs.
    query      Query an index with FASTA/FASTQ sequences.
               Annotates each sequence with per-genome k-mer match counts
               and optional per-position coverage vectors (--detail).
               Parallel over sequence chunks.
    distance   Compute a pairwise Bray-Curtis or Jaccard distance matrix
               between all indexed genomes.
               Optionally outputs a Newick NJ or UPGMA tree.
    annotate   Add or update genome metadata (taxonomy, etc.) from a CSV
               file; or dump the current metadata as CSV.
    estimate   Dry-run: resolve and print approximate-index parameters
               (z, evidence bits b, FP rates) given any two of (b, z, fp).
               Does not touch any index.
    dump       Dump all indexed k-mers as CSV with per-genome counts or
               presence flags.
    superkmer  Extract superkmers from a sequence file and write to stdout.
               Diagnostic / pipeline use.
    unitig     Dump the unitig sequences stored in a built index. Debug use.
    utils      Miscellaneous utilities.
               --new-label NEW=OLD      rename a genome label in-place.
               --bits-per-kmer          print MPHF / evidence / matrix size breakdown.
               --stats                  per-genome k-mer counts as CSV.
               --partition-stats        partition size distribution across one or more
                                        indexes (markdown report to stdout). Useful to
                                        diagnose minimizer imbalance before a large merge.
               --csv FILE               write per-(partition, source) raw data to FILE
                                        (used with --partition-stats).

## Quick start

```sh
# Build an exact index for each genome independently
obikmer index --kmer-size 31 --label genome_a genome_a.fa --output index_a/
obikmer index --kmer-size 31 --label genome_b genome_b.fa --output index_b/

# Merge into a single multi-genome index
obikmer merge --output index/ index_a/ index_b/

# Convert to approximate index (z=5, 8-bit fingerprints)
obikmer reindex --approx -z 5 --evidence-bits 8 index/

# Query reads
obikmer query index/ reads.fq.gz > annotated.fa

# Pairwise distances
obikmer distance index/ > distances.tsv
```

## Parameter constraints

    Parameter              Constraint
    ─────────────────────  ──────────────
    k  (--kmer-size)       odd, 11 ≤ k ≤ 31
    m  (--minimizer-size)  odd, 3 ≤ m ≤ k−1
    z  (-z, --approx only) 1 ≤ z ≤ k−1

## Documentation

Extended architecture and implementation notes are in `docmd/`. Build with
`make doc` (requires Python + MkDocs Material).
