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HiMaLAYAS Documentation

Annotation Input

himalayas-base/himalayas

Annotation Input¶

Annotations map categorical terms to labels present in your matrix. HiMaLAYAS filters labels to the matrix universe, then applies term-size filters.

Signature¶

Annotations(
    term_to_labels: Dict[str, Iterable[str]],
    matrix: Matrix,
    *,
    min_term_size: int = 2,
    max_term_size: int | None = None,
)

Parameters¶

Parameter	Type	Default	Description
`term_to_labels`	`Dict[str, Iterable[str]]`	required	Mapping from term to labels (genes, sectors, proteins).
`matrix`	`Matrix`	required	Provides the label universe.
`min_term_size`	`int`	`2`	Minimum number of matrix-overlapping labels required for a term to be retained.
`max_term_size`	`int \| None`	`None`	Maximum number of matrix-overlapping labels allowed for a term to be retained.

Expected Mapping Format¶

term_to_labels = {
    "mitochondrion inheritance": ["GEM1", "PTC1", "ARP2", "ADY3"],
    "vacuole inheritance": ["VPS15", "VAC17", "PEP7", "VPS3"],
}

Each key is an annotation term, and each value is a list of matrix label IDs. Labels must match matrix row labels exactly.

Common Attributes¶

Attribute	Type	Description
`annotations.matrix_labels`	`set[str]`	Matrix label universe used to filter incoming annotation labels.
`annotations.term_to_labels`	`Dict[str, set[str]]`	Filtered term-to-label mapping retained on the object after dropping labels not present in the matrix.

Common Methods¶

Annotations.terms -> List[str]
Annotations.rebind(matrix: Matrix) -> Annotations

Method	Description
`annotations.terms`	Returns retained annotation terms after overlap filtering.
`annotations.rebind(matrix)`	Returns a new `Annotations` object aligned to a new matrix label universe (useful for zoom and subset workflows).

`terms`¶

Annotations.terms -> List[str]

Returns retained annotation terms after overlap filtering.

`rebind`¶

Annotations.rebind(matrix: Matrix) -> Annotations

Returns a new Annotations object aligned to a new matrix label universe.

Parameter	Type	Default	Description
`matrix`	`Matrix`	required	New matrix whose label universe will be used to re-filter terms.

Example (GO Biological Process)¶

import json
from himalayas import Annotations

with open("data/go_bp_name_to_orfs.json", "r", encoding="utf-8") as fh:
    go_bp = json.load(fh)

annotations = Annotations(go_bp, matrix)

Example (Country to Sectors)¶

country_to_sectors = {
    "Germany": ["DEU | Manufacturing", "DEU | Transport"],
    "Japan": ["JPN | Manufacturing", "JPN | Finance"],
}

annotations = Annotations(country_to_sectors, matrix)

Common Errors¶

Labels for term ... must be an iterable of labels if a term maps to a string.
No annotation terms overlap matrix labels if none of the labels match the matrix.

Notes¶

Terms are filtered by matrix overlap and term size limits.
Keep min_term_size=2 as the default floor for analysis-ready runs.
min_term_size is independent from Analysis.enrich(min_overlap=...); the two are not kept in sync.