GO3 documentation

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class go3.PyGOTerm

Bases: object

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go3.ancestors(go_id)

Returns the list of all ancestors in the ontology for the given GO Term.

# Arguments

  • go_id - GO term ID.

# Returns

List of IDs of all the ancestors in the ontology (List of String)

go3.batch_lin(list1, list2, counter)

Compute similarity between two batches of GO terms using Resnik similarity. Both lists must be of the same size.

# Arguments

  • list1 - First list of GO term ID

  • list2 - Second list GO term ID

  • counter - TermCounter with the annotations.

# Returns

List of Resnik similarity scores (float)

go3.batch_resnik(list1, list2, counter)

Compute similarity between two batches of GO terms using Resnik similarity. Both lists must be of the same size.

# Arguments

  • list1 - First list of GO term ID

  • list2 - Second list GO term ID

  • counter - TermCounter with the annotations.

# Returns

List of Resnik similarity scores (float)

go3.build_term_counter(annotations)
go3.common_ancestor(go_id1, go_id2)

Returns the list of all the common ancestors in the ontology for the given GO Terms.

# Arguments

  • go_id1 - GO term ID 1.

  • go_id2 - GO term ID 2.

# Returns

List of IDs of all the common ancestors in the ontology (List of String)

go3.deepest_common_ancestor(go_id1, go_id2)

Returns the deepest common ancestor in the ontology for the given GO Terms.

# Arguments

  • go_id1 - GO term ID 1.

  • go_id2 - GO term ID 2.

# Returns

ID of the deepest common ancestor in the ontology. (String)

go3.get_term_by_id(go_id)

Gets the PyGoTerm object for the given GO Term ID.

# Arguments

  • go_id - GO term ID.

# Returns

PyGOTerm associated with the ID. (PyGOTerm)

go3.lin_similarity(id1, id2, counter)

Compute similarity between two GO terms using Lin.

# Arguments

  • id1 - First GO term ID

  • id2 - Second GO term ID

# Returns

Lin similarity score (float)

go3.load_gaf(path)
go3.load_go_terms(path=None)
go3.resnik_similarity(id1, id2, counter)

Compute similarity between two GO terms using Resnik.

# Arguments

  • id1 - First GO term ID

  • id2 - Second GO term ID

# Returns

Resnik similarity score (float)

go3.term_ic(go_id, counter)

Compute Information Content (IC) for the given GO term using the annotations.

# Arguments

  • go_id - GO term ID.

  • counter - TermCounter with the annotations.

# Returns

Information Content (float)