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orfdata

orfdata builds the protein reference for a species: the proteins annotated in a PyEnsembl genome, plus open reading frames (ORFs) that ribosome-profiling studies found translated outside those annotations. Each added ORF stays bound to its PyEnsembl transcript, with its source, category and evidence. Viral proteomes can be added explicitly, but only for a species that is a recorded host of the virus.

Install

Use Python 3.9 or later. Install orfdata and one PyEnsembl annotation:

python -m pip install 'orfdata[pyensembl]'
pyensembl install --release 115 --species human

The second command downloads and indexes Ensembl 115 for human GRCh38. orfdata never downloads or indexes annotation data itself; it reports what is missing.

Build a human proteome

from pyensembl import EnsemblRelease
from orfdata import Proteome

genome = EnsemblRelease(115, species="human")
proteome = Proteome.from_genome(genome).with_extra_orfs(evidence="ms")
proteome.write_fasta("human-e115.fasta")
print(proteome.summary()["kinds"], len(proteome.excluded))

{'annotated': 245535, 'extra_orf': 2181} 5

Proteome.from_genome takes every protein in the Ensembl 115 annotation. with_extra_orfs(evidence="ms") adds the bundled human ORFs that have supporting mass-spectrometry (MS) peptides: 2,181 of the 2,186 are encoded by an Ensembl 115 transcript, which must contain the ORF's exact spliced coding path. The other 5 are listed in proteome.excluded with the reason. Each entry lists every transcript encoding it. Building this human proteome takes under a minute, and proteome.save(path) keeps it as a checksummed snapshot.

The same proteome from the command line:

orfdata proteome --species human --release 115 --output human-e115.fasta

Choose the evidence

evidence= Selects ORFs with Human ORFs Encoded in Ensembl 115
"ribosome" Ribosome profiling (all bundled ORFs) 7,264 7,239
"ms" (default) Any supporting MS peptide 2,186 2,181
"hla" Peptides presented by HLA molecules 1,881 1,879
"shotgun" Peptides from protease-digest MS 73 72

Most MS support in the bundled human catalogue comes from HLA immunopeptidomics. A presented peptide shows that the ORF was translated; it does not establish a stable protein. See building a reference proteome for stricter filters and what each level means.

Look up the ORFs on a transcript

Continue in the same Python session:

from orfdata import extra_orfs

orfs = extra_orfs(genome)
for orf in orfs.for_transcript(genome.transcript_by_id("ENST00000304842")):  # TPST1
    print(orf.model.orf_id, orf.model.orf_type, orf.protein_sequence)
    print(orf.evidence.has_evidence("ms"))

c7riboseqorf56 uORF MPSRRRGGSSLIPDVGYLSEVDCPWPEHFPKIILSKISV
True

extra_orfs(genome) places every catalogue ORF on every transcript of this genome that carries its exact coding path; without evidence=, it includes every catalogue ORF. Each result is a TranscriptORF: the source ORF, its evidence and the original PyEnsembl transcript, with start and end slicing the transcript sequence. One RNA can have several ORFs, even when Ensembl annotates it as noncoding; the transcript's biotype and annotated protein are unchanged. Add include_annotated=True to list the annotated CDSs on that transcript alongside them.

Species

Species Annotated proteins Noncanonical ORFs
Human From PyEnsembl 7,264 GRCh38 ORFs, bundled; lifted to GRCh37 and NCBI36
Mouse From PyEnsembl 2,976 GRCm39 ORFs from OpenProt 2.2, built locally; lifted to GRCm38 and NCBIM37
Dog From PyEnsembl None released; no qualified source yet
Budding yeast From PyEnsembl None released

Other assemblies use a catalogue lifted to them once orfdata chains download has fetched the chain files (with --accept-terms for UCSC's non-commercial mouse chains); see every assembly of a species. with_extra_orfs() raises for a species without a catalogue, or whose catalogue or chains aren't installed yet, rather than returning an annotated-only proteome. Human ORF evidence is never transferred to another species. The same API also serves RNA, ribosome and protein measurements for human, mouse, dog and yeast; see released data and gaps.

Next steps