kazu.utils.download_gilda_contexts

This script does the following things:

1. Query Ensembl to get gene to protein ID maps

2. Query wikidata sparql to get a list of wikidata ids to Ensembl gene or Ensembl protein IDs

3. Query wikidata api to get a list of wikipedia page urls with the wikidata IDs from 2

4. Query Wikipedia API to get page content for each page from 3

5. Join wiki page content to Ensembl gene ids based on above relationships

Functions

create_wiki_mappings(gene_df, protein_df, ...)
divide_chunks(items)
extract_open_targets(path, proxies)
get_biomart_gene_to_protein(proxies)
get_retry()
get_sparql_df(query, proxies)
get_wikipedia_contents_from_urls(urls, proxies)
get_wikipedia_url_from_wikidata_id(df_genes, ...)
retry_wiki_with_maxlag(url, params, proxies)

Classes

WikipediaEnsemblMapping

WikipediaEnsemblMapping(ensembl_gene_id: str, ensembl_protein_ids: set[str] = <factory>, wiki_gene_ids: set[str] = <factory>, wiki_protein_ids: set[str] = <factory>, wiki_gene_urls_to_text: dict[str, typing.Optional[str]] = <factory>, wiki_protein_urls_to_text: dict[str, typing.Optional[str]] = <factory>)

class kazu.utils.download_gilda_contexts.WikipediaEnsemblMapping

Bases: object

WikipediaEnsemblMapping(ensembl_gene_id: str, ensembl_protein_ids: set[str] = <factory>, wiki_gene_ids: set[str] = <factory>, wiki_protein_ids: set[str] = <factory>, wiki_gene_urls_to_text: dict[str, typing.Optional[str]] = <factory>, wiki_protein_urls_to_text: dict[str, typing.Optional[str]] = <factory>)

__init__(ensembl_gene_id, ensembl_protein_ids=<factory>, wiki_gene_ids=<factory>, wiki_protein_ids=<factory>, wiki_gene_urls_to_text=<factory>, wiki_protein_urls_to_text=<factory>)

Parameters:

• ensembl_gene_id (str)

• ensembl_protein_ids (set[str])

• wiki_gene_ids (set[str])

• wiki_protein_ids (set[str])

• wiki_gene_urls_to_text (dict[str, str | None])

• wiki_protein_urls_to_text (dict[str, str | None])

Return type:

None

get_context()

Return type:

str | None

ensembl_gene_id: str

ensembl_protein_ids: set[str]

wiki_gene_ids: set[str]

wiki_gene_urls_to_text: dict[str, str | None]

wiki_protein_ids: set[str]

wiki_protein_urls_to_text: dict[str, str | None]

kazu.utils.download_gilda_contexts.create_wiki_mappings(gene_df, protein_df, ensembl_gene_to_protein_mappings, wikidata_id_to_wikipedia_urls, wikipage_to_text)

Parameters:

• gene_df (DataFrame)

• protein_df (DataFrame)

• ensembl_gene_to_protein_mappings (DataFrame)

• wikidata_id_to_wikipedia_urls (defaultdict[str, set[str]])

• wikipage_to_text (dict[str, str])

Return type:

set[WikipediaEnsemblMapping]

kazu.utils.download_gilda_contexts.divide_chunks(items)

Parameters:

items (list[str])

Return type:

Iterable[list[str]]

kazu.utils.download_gilda_contexts.extract_open_targets(path, proxies)

Parameters:

• path (Path)

• proxies (dict[str, str])

Return type:

None

kazu.utils.download_gilda_contexts.get_biomart_gene_to_protein(proxies)

Parameters:

proxies (dict[str, str])

Return type:

DataFrame

kazu.utils.download_gilda_contexts.get_retry()

Return type:

Retry

kazu.utils.download_gilda_contexts.get_sparql_df(query, proxies)

Parameters:

• query (str)

• proxies (dict[str, str])

Return type:

DataFrame

kazu.utils.download_gilda_contexts.get_wikipedia_contents_from_urls(urls, proxies)

Parameters:

• urls (set[str])

• proxies (dict[str, str])

Return type:

dict[str, str]

kazu.utils.download_gilda_contexts.get_wikipedia_url_from_wikidata_id(df_genes, df_proteins, proxies)

Parameters:

• df_genes (DataFrame)

• df_proteins (DataFrame)

• proxies (dict[str, str])

Return type:

defaultdict[str, set[str]]

kazu.utils.download_gilda_contexts.retry_wiki_with_maxlag(url, params, proxies)

Parameters:

• url (str)

• params (dict[str, str])

• proxies (dict[str, str])

Return type:

dict[str, Any]