Aligned#

class Aligned(data: AlignedDataView, moltype: MolType, name: str | None = None, annotation_db: SupportsFeatures | None = None)#

A single sequence in an alignment.

Attributes:

annotation_db
data
gapped_seq: Returns Sequence object, including gaps.
map
moltype
name
seq: the ungapped sequence.

Methods

`annotate_matches_to`(pattern, biotype, name)	Adds an annotation at sequence positions matching pattern.
`gap_vector`()	Returns gap_vector of positions.
`make_feature`(feature, alignment)	returns a feature, not written into annotation_db
`parent_coordinates`([seq_coords])	returns seqid, start, stop, strand on the parent sequence

slice_with_map

Notes

This is a wrapper around a AlignedDataView. This class performs any complenting needed. It can be cast directly to a string or numpy array, e.g. numpy.array(<aligned instance>) returns a numpy unsigned 8-bit integer array.

annotate_matches_to(pattern: str, biotype: str, name: str, allow_multiple: bool = False)#

Adds an annotation at sequence positions matching pattern.

Parameters:

pattern: The search string for which annotations are made. IUPAC ambiguities are converted to regex on sequences with the appropriate MolType.
biotype: The type of the annotation (e.g. “domain”).
name: The name of the annotation.
allow_multiple: If True, allows multiple occurrences of the input pattern. Otherwise, only the first match is used.

Returns:

Returns a list of Feature instances.

property annotation_db#

property data: AlignedDataView#

gap_vector() → list[bool]#: Returns gap_vector of positions.

property gapped_seq: Sequence#: Returns Sequence object, including gaps.

make_feature(feature: FeatureDataType, alignment: Alignment) → Feature#: returns a feature, not written into annotation_db

property map: IndelMap#

property moltype: MolType#

property name: str#

parent_coordinates(seq_coords=False)#

returns seqid, start, stop, strand on the parent sequence

Parameters:

seq_coords: if True, the coordinates for the unaligned sequence

property seq: Sequence#: the ungapped sequence.

slice_with_map(span: FeatureMap) → tuple[ndarray, ndarray]#