Skip to main content

orfdata

An evidence layer over PyEnsembl for proteins beyond standard annotations. orfdata tells you which open reading frames (ORFs) have experimental support for producing peptides or proteins.

PyEnsembl supplies reference transcripts and annotated proteins. orfdata adds other ORFs, their sequences, and evidence to those same transcript objects. One RNA can have several ORFs, even when its annotation says it is noncoding. The original transcript's biotype and annotated protein stay intact.

Which ORFs?

The bundled catalogue includes:

  • Upstream ORFs (uORFs): before the main protein-coding region.
  • Overlapping ORFs: extending into or out of the main coding region.
  • Internal ORFs: alternative reading frames within the main coding region.
  • Downstream ORFs (dORFs): after the main coding region.
  • ORFs on noncoding RNAs: including long noncoding RNAs (lncRNAs) and processed transcripts without an annotated protein.

These are additional possible protein sources that standard transcript protein annotations may omit. The catalogue currently contains 7,264 human GRCh38 ORFs, of which 2,186 have reported supporting mass-spectrometry observations. It is a source-backed reference catalogue; it does not discover every possible ORF. Data sources and current limits.

What does the evidence mean?

Evidence What it supports
Ribosome profiling Translation of the ORF.
Protease-digest mass spectrometry (MS) Detection of peptides matching its protein sequence.
MHC/HLA peptidomics Detection of matching peptides presented by MHC molecules.

Peptide matches can be ambiguous, so orfdata keeps their source, mapping and quality information. These observations have different strengths: a translated ORF or detected peptide does not by itself establish a stable, functional protein. Missing evidence also does not establish that an ORF is never translated. Evidence interpretation.

Use with PyEnsembl

With the selected PyEnsembl annotation already downloaded and indexed:

from pyensembl import EnsemblRelease
from orfdata import load_catalog

genome = EnsemblRelease(95, species="human")
catalog = load_catalog()
transcript = genome.transcript_by_id("ENST00000304842")  # TPST1

for orf in catalog.for_transcript(transcript):
    print(orf.model.orf_id, orf.protein_sequence)
    print(orf.evidence.has_evidence("ms"))
    assert orf.transcript is transcript

The same call works for a noncoding parent, such as NUTM2B-AS1 (ENST00000483080). Each returned ReferenceORF keeps its model, evidence and original PyEnsembl transcript together, after checking its coordinates and sequence against that transcript.

Varcode describes changes to this reference ORF; Isovar connects it to observed RNA products. Reference evidence stays separate from evidence for a variant or fusion. See the API and integration guide.

The catalogue API supports other species, with explicit species and assembly checks. Bundled experimental evidence is currently human-only. Offline tests bind real human, mouse, dog and yeast reference slices; those fixtures are not new experimental ORF catalogues. Species and reference identity.

Install with pip install orfdata[pyensembl]. See the measurement API for native units, explicit samples and assays, and DataCache-managed downloads, and the quantitative, multispecies data roadmap for upcoming RNA abundance, ribosome occupancy and protein data releases.

Metadata

Release files for orfdata 0.4.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for orfdata 0.4.0
File Size Uploaded
orfdata-0.4.0.tar.gz 2.0 MB Details

Built distribution (wheel)

Table of built distributions (wheels) for orfdata 0.4.0
File Interpreter ABI Platform
orfdata-0.4.0-py3-none-any.whl Python 3 none any Details

Total release size: 3.9 MB

Release files / orfdata-0.4.0.tar.gz

Download URL orfdata-0.4.0.tar.gz
Size 2.0 MB
Tags Source
SHA-256 checksum
How to use checksums
a53c37f6adb4f350efa0663a0050bc34500373af4f1ba38abdabadd81897a58d
BLAKE2b-256 checksum
How to use checksums
18471adf568341c7c5996f536c5322d1be0b173b65e86ac3d0962b891463502d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.6

Release files / orfdata-0.4.0-py3-none-any.whl

Download URL orfdata-0.4.0-py3-none-any.whl
Size 1.9 MB
Tags Python 3
SHA-256 checksum
How to use checksums
39bd316a28d5ad9a67a5e9f0e2cc62f4ab9a3084f756c843eb8b5bde0db88d14
BLAKE2b-256 checksum
How to use checksums
e8a2abf9bef09ea48c956b7d31ce0bd59432570f36a09e4516781c11a8eaf6e2
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.6

Release history Release notifications | RSS feed

0.27.1

2 release files

0.18.0

2 release files

0.17.0

2 release files

0.16.0

2 release files

0.15.0

2 release files

0.14.0

2 release files

0.13.0

2 release files

0.12.0

2 release files

0.11.0

2 release files

0.10.0

2 release files

0.9.0

2 release files

0.8.0

2 release files

0.7.0

2 release files

0.6.0

2 release files

0.5.0

2 release files

This release

0.4.0 This release

2 release files

0.3.0

2 release files

0.2.0

2 release files

0.1.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page