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I/O, tokenization, caches, evaluation, and security

skills/geniml/references/utilities.md

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I/O, tokenization, caches, evaluation, and security

Research snapshot: 2026-07-23. API claims below use official documentation, PyPI metadata, and the geniml v0.8.4 release source. Where current docs and release code disagree, the discrepancy is stated explicitly.

Release and dependency facts

geniml==0.8.4 was released on 2026-01-14. PyPI metadata:

  • does not set Requires-Python;
  • classifies Python 3.10, 3.11, 3.12, 3.13, and 3.14;
  • provides ml and test extras;
  • ships a pure-Python wheel, but dependencies include native packages;
  • uses Trusted Publishing with a Sigstore provenance link to tag v0.8.4.

Release files:

text
geniml-0.8.4-py3-none-any.whl
sha256 ac0fc520cde6f6461120aee6b40d3cbf20e1e3d8bdb95a3a45345724eee545b5

geniml-0.8.4.tar.gz
sha256 6f429c7c89d06a4c2c378e349d14b3a2d984dc441440ada38473772fce6addb1

The stable release requires gtars>=0.2.5 without an upper bound. The 2026-07-23 verified base smoke resolved gtars==0.9.2 and successfully imported Geniml 0.8.4, geniml.io.RegionSet, and gtars.tokenizers.Tokenizer. Gtars 0.9.2 was released 2026-06-17 and requires Python >=3.10.

Pin both direct packages and retain an uv.lock; upstream transitive requirements are mostly lower bounds.

BED coordinates and validation

BED is normally 0-based, half-open [start, end). A valid BED3 row requires:

  • nonempty contig;
  • integer start >= 0;
  • integer end > start;
  • end no greater than the declared contig length;
  • values within bounded integer limits.

Do not confuse BED with 1-based closed VCF/GFF coordinates. BED columns beyond BED3 have their own constraints; preserve them rather than guessing. BED3 carries no strand. When BED6 strand exists, preserve +, -, or . unless a documented assay conversion says otherwise.

Assembly compatibility requires more than matching chr prefixes. BEDbase describes chromosome-name sensitivity (XS), out-of-bounds regions (OOBR), and sequence fit (SF) as separate criteria. Record a concrete assembly/accession and chromosome-sizes digest. Reject unknown alt/decoy contigs rather than dropping them silently.

Run:

bash
python skills/geniml/scripts/bed_validator.py \
  --input data/peaks.bed \
  --assembly GRCh38 \
  --chrom-sizes refs/GRCh38.chrom.sizes

The script emits aggregate errors and a normalization plan. It never rewrites coordinates or performs liftover.

Region and RegionSet APIs

Gtars API for new workflows

python
from gtars.models import Region, RegionSet

region = Region("chr1", 100, 200, None)
regions = RegionSet("data/peaks.bed")
print(len(regions))
regions.to_bed("work/peaks.copy.bed")

Gtars 0.9.2 exposes operations including sort, reduce, coverage, count_overlaps, jaccard, nearest_neighbors, to_bed, to_bed_gz, and to_bigbed. Do not assume these operations validate assembly or coordinate semantics. Validate before constructing the object and after writing output.

Official Gtars constructors can accept URLs. This skill restricts them to validated local regular files by default.

Legacy Geniml I/O

python
from geniml.io import BedSet, Region, RegionSet

region = Region("chr1", 100, 200)  # third field is named stop
regions = RegionSet("data/peaks.bed", backed=False)

geniml.io.RegionSet(regions, backed=False) accepts a path/URL or a list of legacy Regions. With backed=True, it streams the BED, supports iteration and length, and does not support indexing. Other release classes include BedSet, Maf, SNP, TokenizedRegionSet, and RegionSetCollection, though only Region, RegionSet, and BedSet are exported from geniml.io.

The 0.7.0 changelog says RegionSet use switched toward Gtars. Avoid mixing legacy and Gtars Region objects accidentally: field names and accepted types differ.

Tokenization

Current Gtars tokenizer

python
from gtars.models import RegionSet
from gtars.tokenizers import Tokenizer

tokenizer = Tokenizer.from_bed("refs/universe.bed")
encoded = tokenizer(RegionSet("data/peaks.bed"))
input_ids = encoded["input_ids"]

Gtars also documents Tokenizer.from_config and Tokenizer.from_pretrained. The latter can access Hugging Face; do not call it without explicit network approval, revision pinning, cache bounds, and expected hashes.

With Gtars 0.9.2, a two-region universe produced len(tokenizer) == 9 because seven special tokens are included. Preserve:

  • universe bytes, row order, and assembly;
  • Gtars version;
  • special_tokens_map and every special-token ID;
  • tokenizer length;
  • token-corpus schema and checksum.

Run the local compatibility planner:

bash
python skills/geniml/scripts/tokenizer_compatibility.py \
  --model-dir models/region2vec \
  --universe refs/universe.bed \
  --assembly GRCh38

Legacy hard tokenization

The stable file geniml.tokenization.main defines:

python
hard_tokenization_main(
    src_folder,
    dst_folder,
    universe_file,
    fraction=1e-9,
    file_list=None,
    num_workers=10,
    bedtools_path="bedtools",
)

It invokes an external Bedtools executable and multiprocessing. The fraction is passed to interval intersection logic; it is not a statistical p-value. The package geniml.tokenization.__init__ comments out its public exports, so from geniml.tokenization import hard_tokenization and the installed geniml tokenize dispatcher are unreliable in 0.8.4.

Do not use an arbitrary bedtools found on PATH. If reproducing the legacy path, pin and checksum the binary, pass an explicit absolute path, validate argv, bound workers, use a fresh output directory, and compare synthetic results with the Gtars tokenizer.

The current preferred token corpus is a bounded Parquet file with one list-valued tokens column. Upstream issue #14 proposes deprecating one .gtok file per cell.

BBClient and cache behavior

python
from geniml.bbclient import BBClient

client = BBClient(cache_folder="/absolute/project/.bbcache")

Release defaults:

  • endpoint: BEDBASE_API or https://api.bedbase.org;
  • cache root: BBCLIENT_CACHE or ~/.bbcache;
  • BEDs under bedfiles/;
  • BED sets under bedsets/;
  • token cache in tokens.zarr.

load_bed, load_bedset, add_bed_tokens_to_cache, and corresponding cache-* CLI commands may use the network. add_bed_to_s3 and get_bed_from_s3 accept cloud credentials and endpoints; do not use them without an explicit upload/download request and a separate credential review. Never read or print the environment broadly. Only consult BEDBASE_API and BBCLIENT_CACHE when the user approves those overrides.

Local-oriented CLI:

text
geniml bbclient seek ID --cache-folder CACHE
geniml bbclient inspect-bedfiles --cache-folder CACHE
geniml bbclient inspect-bedsets --cache-folder CACHE
geniml bbclient rm ID --cache-folder CACHE

rm mutates cache state; confirm the exact resolved target first. Inspection can still expose BED IDs and local paths, so redact output in shared logs.

Before an approved download:

  1. approve endpoint and exact IDs;
  2. set a project-scoped cache and byte quota;
  3. reject redirects to unapproved hosts where tooling permits;
  4. verify compressed and expanded size;
  5. checksum downloaded bytes;
  6. validate BED and assembly;
  7. record provenance and retrieval time.

No bundled skill script performs BBClient or Hub downloads.

Model loading and artifact safety

Modern local classes:

python
from geniml.region2vec.main import Region2VecExModel
from geniml.scembed.main import ScEmbed

r2v = Region2VecExModel.from_pretrained("models/region2vec")
sce = ScEmbed.from_pretrained("models/scembed")

These classmethods use local bundle paths. Constructors with model_path="organization/model" call Hugging Face Hub and download checkpoint.pt, universe.bed, and config.yaml.

Geniml's loader uses torch.load(..., weights_only=True) and YAML safe_load. This is safer than unrestricted pickle, but artifacts can still cause resource exhaustion or exploit parser/native-library vulnerabilities. Gensim .model, pickle, joblib, TorchScript, shared libraries, and external binaries require even stronger distrust.

Inspect without importing Torch or deserializing:

bash
python skills/geniml/scripts/model_artifact_inspector.py \
  --model-dir models/region2vec \
  --verify-manifest models/region2vec/SHA256SUMS

The inspector reads bounded metadata formats, hashes bytes, flags risky extensions, rejects URLs/symlinks/traversal, and never loads model objects.

Embedding evaluation

The geniml eval release CLI has:

text
gdst     Genome distance scaling test
npt      Neighborhood preserving test
ctt      Cluster tendency test
rct      Reconstruction test
bin-gen  Generate binary embeddings

Examples:

bash
geniml eval gdst \
  --model-path /absolute/project/model \
  --embed-type region2vec \
  --num-samples 10000 \
  --seed 42

geniml eval npt \
  --model-path /absolute/project/model \
  --embed-type region2vec \
  --K 10 \
  --num-samples 1000 \
  --seed 42 \
  --num-workers 4

The official tutorial's BaseEmbeddings and bin-gen workflows use pickle for binary embedding objects. Generate them locally and never load an untrusted pickle. Bound samples/workers and record random seeds. Evaluate on patients/donors excluded from universe selection and training.

Primary source: Zheng et al. (2024), Methods for evaluating unsupervised vector representations of genomic regions, doi:10.1093/nargab/lqae086.

BEDshift

The integrated Bedshift CLI is:

text
geniml bedshift --help

It can use a local chromosome-length file or resolve a Refgenie genome through refgenconf. Prefer an explicit, checksummed local chromosome-sizes file to avoid implicit lookup/network behavior. Set a seed, output bound, and perturbation policy matching the null hypothesis. Validate randomized coordinates exactly like originals.

Primary source: Gu et al. (2021), Bedshift: perturbation of genomic interval sets, doi:10.1186/s13059-021-02440-w.

Privacy and bounded reporting

Potentially sensitive:

  • BED coordinates and filenames;
  • sample, donor, patient, treatment, diagnosis, and tissue metadata;
  • cell barcodes and rare labels;
  • embeddings that permit membership or nearest-neighbor inference;
  • local cache paths and BEDbase identifiers.

Default reports should contain only aggregate counts, schema names, checksums, software versions, and redacted file IDs. Cap error examples; never dump entire malformed rows or metadata values. Store full provenance manifests in the protected project, not chat output.

Migration and deprecation ledger

  • 0.4.0: tokenizers renamed to TreeTokenizer and AnnDataTokenizer.
  • 0.7.0: RegionSet use moved toward Gtars and encoding changed.
  • 0.8.0: Atacformer added.
  • 0.8.1: BEDspace fixed according to the changelog.
  • 0.8.4: latest stable; release notes contain only the version bump.
  • Current Gtars API: use the unified gtars.tokenizers.Tokenizer.
  • .gtok: proposed for deprecation in upstream issue #14; prefer Parquet.
  • embedding_size: backward-compatible config key; use embedding_dim.
  • Top-level Region2Vec/scEmbed/tokenization exports shown by old docs are absent/commented in the 0.8.4 wheel.
  • Official geniml assess examples are stale; use geniml assess-universe.

Dated authoritative sources

Package and source:

Official API/ecosystem documentation:

Primary papers: