protlabel 4.8.0

Embedding Annotation Transfer (EAT): nearest-neighbour label transfer in protein-language-model embedding space

protlabel

Embedding Annotation Transfer (EAT) engine — nearest-neighbour label transfer in protein-language-model (pLM) embedding space, with the goPredSim reliability index.

protlabel is a small, dependency-light library (numpy only). It is ProtSpace-agnostic by design — it imports nothing from protspace — so it is independently testable and reusable from notebooks, protspace_uniprot, or any other project. The protspace transfer CLI is a thin consumer of this engine.

Install

pip install protlabel

Use

import numpy as np
from protlabel import eat, Lookup

preds = eat(
    query_emb=np.random.rand(3, 1024).astype("float32"),
    query_ids=["Q1", "Q2", "Q3"],
    ref_emb=np.random.rand(100, 1024).astype("float32"),
    ref_ids=[f"R{i}" for i in range(100)],
    ref_labels=["toxin", "enzyme"] * 50,
    k=1,
    metric="cosine",          # or "euclidean" (the goPredSim default)
)
for p in preds:
    print(p.query_id, p.label, round(p.reliability, 3))

Lookup builds and serialises a reusable reference set (.npz sidecar) so the reference matrix can be rebuilt on demand rather than shipped.

Method

Nearest-neighbour transfer in the original pLM embedding space (not a 2-D/3-D projection), with the goPredSim reliability index — see Littmann et al., Sci Rep 2021 (Eq. 5) and Heinzinger et al., NAR Genom Bioinform 2022.

Distances are computed with an exact, chunked brute-force search (numpy BLAS GEMM

• argpartition); queries are processed in batches. No approximate-nearest-neighbour index is needed at Swiss-Prot scale.

License

MIT — part of the ProtSpace project.