Ontology

The Ontology class provides Gene Ontology (GO) utilities: fetching gene sets from GO accessions and mapping phenotypic categories to network nodes.

Import

from neko._annotations.gene_ontology import Ontology

Quick example

from neko._annotations.gene_ontology import Ontology

onto = Ontology()

# Fetch all genes annotated to a specific GO term
genes = onto.fetch_genes_from_go_id("GO:0007165")  # signal transduction

# Map nodes in a network to tissue expression data
onto.add_tissue_expression(net, tissue="liver")

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Helper function

fetch_nodes_from_url

fetch_nodes_from_url(url)

fetch the nodes in a list from the given geneontology url

Source code in neko/_annotations/gene_ontology.py

def fetch_nodes_from_url(url):

    """
    fetch the nodes in a list from the given geneontology url
    """
    print("Start requesting genes from Gene Ontology")
    print("Fetching from: ", url)
    response = requests.get(url)
    print("Done")
    if not response:
        print("Error fetching the genes, no entry found, please check the id accession code")
        return
    genes = response.text.split("\n")
    genes = genes[:-1]
    genes_unique = list(set(genes))
    return genes_unique

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Class reference

Ontology

Ontology()

class that stores some functionalities to connect phenotypes to nodes and to associate information for each node at tissue level

Source code in neko/_annotations/gene_ontology.py

def __init__(self):
    self.gene_ontology_url = "https://golr-aux.geneontology.io/solr/select?defType=edismax&qt=standard&indent=on&wt=csv&rows=100000&start=0&fl=bioentity_label&facet=true&facet.mincount=1&facet.sort=count&json.nl=arrarr&facet.limit=25&hl=true&hl.simple.pre=%3Cem%20class=%22hilite%22%3E&hl.snippets=1000&csv.encapsulator=&csv.separator=%09&csv.header=false&csv.mv.separator=%7C&fq=document_category:%22annotation%22&fq=isa_partof_closure:%22GO:0007049%22&fq=taxon_subset_closure_label:%22Homo%20sapiens%22&fq=type:%22protein%22&fq=annotation_class_label:%22G1/S%20transition%20of%20mitotic%20cell%20cycle%22&facet.field=aspect&facet.field=taxon_subset_closure_label&facet.field=type&facet.field=evidence_subset_closure_label&facet.field=regulates_closure_label&facet.field=isa_partof_closure_label&facet.field=annotation_class_label&facet.field=qualifier&facet.field=annotation_extension_class_closure_label&facet.field=assigned_by&facet.field=panther_family_label&q=*:*"
    self.accession_to_phenotype_dict = {"GO:0010718": "positive regulation of epithelial to mesenchymal transition"}
    return

Functions

modify_url_ontology

modify_url_ontology(new_go_code, new_description)

Modifies a given URL by replacing a GO code and a descriptive string in very specific locations identified by prefixes.

Parameters: - url (str): The original URL to be modified. - new_go_code (str): The new GO code to insert into the URL. - new_description (str): The new descriptive string to insert into the URL.

Returns: - str: The modified URL.

Source code in neko/_annotations/gene_ontology.py

def modify_url_ontology(self, new_go_code, new_description):
    """
    Modifies a given URL by replacing a GO code and a descriptive string
    in very specific locations identified by prefixes.

    Parameters:
    - url (str): The original URL to be modified.
    - new_go_code (str): The new GO code to insert into the URL.
    - new_description (str): The new descriptive string to insert into the URL.

    Returns:
    - str: The modified URL.
    """
    # Ensure we work with plain strings
    if not isinstance(new_go_code, str):
        new_go_code = str(new_go_code)
    # Define the prefixes that identify where the replacements should occur,
    go_code_prefix = "isa_partof_closure:%22"
    description_prefix = "annotation_class_label:%22"

    # Patterns to find the exact locations for replacements
    go_code_pattern = re.escape(go_code_prefix) + r"GO:\d{7}"
    description_pattern = re.escape(description_prefix) + r".+?%22"

    # Perform the replacements
    url = re.sub(go_code_pattern, go_code_prefix + new_go_code, self.gene_ontology_url, 1)
    # URL-encode the new description
    new_description_encoded = re.sub(r" ", "%20", new_description)
    url = re.sub(description_pattern, description_prefix + new_description_encoded + "%22", url, 1)

    return url

check_tissue_annotations

check_tissue_annotations(genes_df, tissue)

Check if tissue annotations for each gene symbol contain the specified tissue.

Args: genes_df (DataFrame): DataFrame containing gene symbols. tissue (str): Tissue to check for in annotations.

Returns: DataFrame: DataFrame with results indicating whether each gene symbol has tissue annotations containing the specified tissue.

Source code in neko/_annotations/gene_ontology.py

def check_tissue_annotations(self, genes_df, tissue):
    """
    Check if tissue annotations for each gene symbol contain the specified tissue.

    Args:
    genes_df (DataFrame): DataFrame containing gene symbols.
    tissue (str): Tissue to check for in annotations.

    Returns:
    DataFrame: DataFrame with results indicating whether each gene symbol has tissue annotations containing the specified tissue.
    """

    results = []

    # Iterate over each gene symbol
    for genesymbol in genes_df['Genesymbol']:
        # Fetch annotations for the gene symbol
        annotations_df = op.requests.Annotations.get([genesymbol], force_full_download=True)

        # Filter annotations for tissue annotations
        tissue_annotations = annotations_df[annotations_df['label'] == 'tissue']

        # Test if any tissue annotation contains the specified tissue
        in_tissue = any(tissue.lower() in value.lower() for value in tissue_annotations['value'])

        # Append result to list
        results.append({'Genesymbol': genesymbol, 'in_tissue': in_tissue})

    # Create DataFrame from results
    results_df = pd.DataFrame(results)

    return results_df