The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: ReadError
Message: invalid compressed data
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/tarfile.py", line 558, in _read
buf = self.cmp.decompress(buf)
zlib.error: Error -3 while decompressing data: invalid code lengths set
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2383, in __iter__
for key, example in self.ex_iterable:
^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 315, in __iter__
for key_example in islice(self.generate_examples_fn(**gen_kwargs), shard_example_idx_start, None):
~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 127, in _generate_examples
for example_idx, example in enumerate(self._get_pipeline_from_tar(tar_path, tar_iterator)):
~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 51, in _get_pipeline_from_tar
current_example[field_name] = f.read()
~~~~~~^^
File "/usr/local/lib/python3.14/tarfile.py", line 705, in read
b = self.fileobj.read(length)
File "/usr/local/lib/python3.14/tarfile.py", line 536, in read
buf = self._read(size)
File "/usr/local/lib/python3.14/tarfile.py", line 560, in _read
raise ReadError("invalid compressed data") from e
tarfile.ReadError: invalid compressed dataNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
xdxtools-genomes
Reference genome index builds for the OTTER bisulfite, RNA-seq, and PDX workflows.
Cloning a reference release here is generally faster than rebuilding it: bismark,
bowtie2, and STAR index generation takes hours on a full mammalian genome, and the
result is identical between machines.
Layout
The dataset mirrors the registry layout that OTTER's reference contract declares — see reference migration — so an extracted release is a working registry entry:
genomes/<id>/<release>/
├── indexes/
│ ├── <id>_<release>_bismark.tar.gz root: indexes/bismark/
│ ├── <id>_<release>_bowtie2.tar.gz root: indexes/bowtie2/
│ └── <id>_<release>_star.tar.gz root: indexes/star/
├── fasta.tar.gz root: fasta/
├── annotations.tar.gz root: annotations/
├── reference.yaml
├── manifest.json
└── checksums.sha256
Each archive's root matches the path reference.yaml records for it — indexes/bismark
for an index, fasta for the sequence — so extracting into the release directory restores
the structure the contract describes.
The three files outside the archives are what make a release resolvable: reference.yaml
declares the assembly, aliases, and per-asset digests along with the tool that built each
index; manifest.json lists every file in the release with its digest; and
checksums.sha256 carries the same set in sha256sum form.
Releases
| id | release | assembly | organism | dataset size |
|---|---|---|---|---|
hg19 |
GRCh37.p13-gencode-v19 |
GRCh37.p13 | Homo sapiens | 41.2 GB |
hg38 |
GRCh38-gencode-v44 |
GRCh38 | Homo sapiens | 40.9 GB |
mm10 |
GRCm38-gencode-M25 |
GRCm38 | Mus musculus | 36.7 GB |
mm39 |
GRCm39-gencode-vM39 |
GRCm39 | Mus musculus | 37.5 GB |
mm9 |
NCBIM37-gencode-M1 |
NCBIM37 | Mus musculus | 35.9 GB |
A release is always named and selected as <id>@<release>; the identifier alone does not
name an immutable artifact. The sizes above are the stored archives; an extracted release is
larger, since the indexes are held uncompressed on disk.
Every release is named <assembly>-gencode-<annotation-version>, and the annotations are
GENCODE primary assemblies throughout.
Fetching
otter-install downloads and extracts a release into a local registry:
otter-install -reference-fetch
Configured through the environment:
| variable | default | purpose |
|---|---|---|
OTTER_REFERENCE_FETCH_RELEASES |
— | comma-separated <id>@<release> selections |
OTTER_REFERENCE_FETCH_ASSETS |
all | restrict to a subset of bismark,bowtie2,star,fasta,annotations |
OTTER_REFERENCE_FETCH_REGISTRY_ROOT |
~/.otter/references |
where genomes/ is written |
OTTER_REFERENCE_FETCH_REPO |
this dataset | the dataset to read |
OTTER_REFERENCE_FETCH_BASE_URL |
https://huggingface.co |
a mirror can be substituted |
OTTER_REFERENCE_FETCH_REVISION |
main |
branch, tag, or commit |
Fetching needs no credentials, because the dataset is public and ungated. That is a requirement rather than an incidental property: a gate would make the anonymous fetch fail even while the dataset still reported itself as public.
Plain curl works too, if you would rather assemble a registry by hand:
base=https://huggingface.co/datasets/fallingstar10/xdxtools-genomes/resolve/main
curl -fL -o mm39.tar.gz \
"$base/genomes/mm39/GRCm39-gencode-vM39/indexes/mm39_GRCm39-gencode-vM39_bowtie2.tar.gz"
Verification
manifest.json lists every file in the release with its digest, and checksums.sha256
carries the same set in sha256sum form. Either can be checked directly:
cd genomes/mm39/GRCm39-gencode-vM39
python3 - <<'PY'
import hashlib, json, pathlib
root = pathlib.Path(".")
entries = json.loads((root / "manifest.json").read_text())
mismatched = 0
for entry in entries:
digest = hashlib.sha256((root / entry["path"]).read_bytes()).hexdigest()
if "sha256:" + digest != entry["sha256"]:
mismatched += 1
print("MISMATCH", entry["path"])
print(f"{len(entries)} files checked, {mismatched} mismatched")
PY
Or, once the archives are extracted, with the provider's own tooling:
sha256sum --check checksums.sha256
A release is worth verifying before use rather than after: an index that disagrees with its recorded digest is one that was corrupted in transit or mixed up with another release.
Provenance
Each release records the tool and parameters that produced every index, so a build is
auditable rather than merely assumed — for example STAR 2.7.11b with sjdbOverhang: 149
for GRCm39-gencode-vM39. Indexes are not portable across STAR major versions, so read
reference.yaml before mixing a fetched index with a differently-pinned pipeline.
Sequences and annotations are redistributed under their providers' terms; the GENCODE FASTA and GTF retain the licences of their respective releases.
Scope
This dataset holds reference data only. Benchmarks, fixtures, and run evidence live in
fallingstar10/otter-data.
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