Database clients (indra.databases)

HGNC client (indra.hgnc_client)

indra.databases.hgnc_client.get_entrez_id(hgnc_id)

Return the Entrez ID corresponding to the given HGNC ID.

Parameters:hgnc_id (str) – The HGNC ID to be converted. Note that the HGNC ID is a number that is passed as a string. It is not the same as the HGNC gene symbol. Returns:entrez_id – The Entrez ID corresponding to the given HGNC ID. Return type:str

indra.databases.hgnc_client.get_hgnc_entry

Return the HGNC entry for the given HGNC ID from the web service.

Parameters:hgnc_id (str) – The HGNC ID to be converted. Returns:xml_tree – The XML ElementTree corresponding to the entry for the given HGNC ID. Return type:ElementTree

indra.databases.hgnc_client.get_hgnc_from_entrez(entrez_id)

Return the HGNC ID corresponding to the given Entrez ID.

Parameters:entrez_id (str) – The EntrezC ID to be converted, a number passed as a strig. Returns:hgnc_id – The HGNC ID corresponding to the given Entrez ID. Return type:str

indra.databases.hgnc_client.get_hgnc_from_mouse(mgi_id)

Return the HGNC ID corresponding to the given MGI mouse gene ID.

Parameters:mgi_id (str) – The MGI ID to be converted. Example: “2444934” Returns:hgnc_id – The HGNC ID corresponding to the given MGI ID. Return type:str

indra.databases.hgnc_client.get_hgnc_from_rat(rgd_id)

Return the HGNC ID corresponding to the given RGD rat gene ID.

Parameters:rgd_id (str) – The RGD ID to be converted. Example: “1564928” Returns:hgnc_id – The HGNC ID corresponding to the given RGD ID. Return type:str

indra.databases.hgnc_client.get_hgnc_id(hgnc_name)

Return the HGNC ID corresponding to the given HGNC symbol.

Parameters:hgnc_name (str) – The HGNC symbol to be converted. Example: BRAF Returns:hgnc_id – The HGNC ID corresponding to the given HGNC symbol. Return type:str

indra.databases.hgnc_client.get_hgnc_name(hgnc_id)

Return the HGNC symbol corresponding to the given HGNC ID.

Parameters:hgnc_id (str) – The HGNC ID to be converted. Returns:hgnc_name – The HGNC symbol corresponding to the given HGNC ID. Return type:str

indra.databases.hgnc_client.get_mouse_id(hgnc_id)

Return the MGI mouse ID corresponding to the given HGNC ID.

Parameters:hgnc_id (str) – The HGNC ID to be converted. Example: “” Returns:mgi_id – The MGI ID corresponding to the given HGNC ID. Return type:str

indra.databases.hgnc_client.get_rat_id(hgnc_id)

Return the RGD rat ID corresponding to the given HGNC ID.

Parameters:hgnc_id (str) – The HGNC ID to be converted. Example: “” Returns:rgd_id – The RGD ID corresponding to the given HGNC ID. Return type:str

indra.databases.hgnc_client.get_uniprot_id(hgnc_id)

Return the UniProt ID corresponding to the given HGNC ID.

Parameters:hgnc_id (str) – The HGNC ID to be converted. Note that the HGNC ID is a number that is passed as a string. It is not the same as the HGNC gene symbol. Returns:uniprot_id – The UniProt ID corresponding to the given HGNC ID. Return type:str

Uniprot client (indra.databases.uniprot_client)

ChEBI client (indra.databases.chebi_client)

indra.databases.chebi_client.get_chebi_id_from_cas(cas_id)

Return a ChEBI ID corresponding to the given CAS ID.

Parameters:cas_id (str) – The CAS ID to be converted. Returns:chebi_id – The ChEBI ID corresponding to the given CAS ID. If the lookup fails, None is returned. Return type:str

indra.databases.chebi_client.get_chebi_id_from_name(chebi_name)

Return a ChEBI ID corresponding to the given ChEBI name.

Parameters:chebi_name (str) – The ChEBI name whose ID is to be returned. Returns:chebi_id – The ID corresponding to the given ChEBI name. If the lookup fails, None is returned. Return type:str

indra.databases.chebi_client.get_chebi_id_from_pubchem(pubchem_id)

Return the ChEBI ID corresponding to a given Pubchem ID.

Parameters:pubchem_id (str) – Pubchem ID to be converted. Returns:chebi_id – ChEBI ID corresponding to the given Pubchem ID. If the lookup fails, None is returned. Return type:str

indra.databases.chebi_client.get_chebi_name_from_id(chebi_id, offline=False)

Return a ChEBI name corresponding to the given ChEBI ID.

Parameters:

• chebi_id (str) – The ChEBI ID whose name is to be returned.
• offline (Optional[bool]) – Choose whether to allow an online lookup if the local lookup fails. If True, the online lookup is not attempted. Default: False.

Returns:

chebi_name – The name corresponding to the given ChEBI ID. If the lookup fails, None is returned.

Return type:

str

indra.databases.chebi_client.get_chebi_name_from_id_web

Return a ChEBI mame corresponding to a given ChEBI ID using a REST API.

Parameters:chebi_id (str) – The ChEBI ID whose name is to be returned. Returns:chebi_name – The name corresponding to the given ChEBI ID. If the lookup fails, None is returned. Return type:str

indra.databases.chebi_client.get_chembl_id(chebi_id)

Return a ChEMBL ID from a given ChEBI ID.

Parameters:chebi_id (str) – ChEBI ID to be converted. Returns:chembl_id – ChEMBL ID corresponding to the given ChEBI ID. If the lookup fails, None is returned. Return type:str

indra.databases.chebi_client.get_pubchem_id(chebi_id)

Return the PubChem ID corresponding to a given ChEBI ID.

Parameters:chebi_id (str) – ChEBI ID to be converted. Returns:pubchem_id – PubChem ID corresponding to the given ChEBI ID. If the lookup fails, None is returned. Return type:str

BioGRID client (indra.databases.biogrid_client)

indra.databases.biogrid_client.get_publications(gene_names, save_json_name=None)

Return evidence publications for interaction between the given genes.

Parameters:

• gene_names (list[str]) – A list of gene names (HGNC symbols) to query interactions between. Currently supports exactly two genes only.
• save_json_name (Optional[str]) – A file name to save the raw BioGRID web service output in. By default, the raw output is not saved.

Returns:

publications – A list of Publication objects that provide evidence for interactions between the given list of genes.

Return type:

list[Publication]

Cell type context client (indra.databases.context_client)

indra.databases.context_client.get_mutations(gene_names, cell_types)

Return protein amino acid changes in given genes and cell types.

Parameters:

• gene_names (list) – HGNC gene symbols for which mutations are queried.
• cell_types (list) –

  List of cell type names in which mutations are queried. The cell type names follow the CCLE database conventions.

  Example: LOXIMVI_SKIN, BT20_BREAST

Returns:

res – A dictionary keyed by cell line, which contains another dictionary that is keyed by gene name, with a list of amino acid substitutions as values.

Return type:

dict[dict[list]]

indra.databases.context_client.get_protein_expression(gene_names, cell_types)

Return the protein expression levels of genes in cell types.

Parameters:

• gene_names (list) – HGNC gene symbols for which expression levels are queried.
• cell_types (list) –

  List of cell type names in which expression levels are queried. The cell type names follow the CCLE database conventions.

  Example: LOXIMVI_SKIN, BT20_BREAST

Returns:

res – A dictionary keyed by cell line, which contains another dictionary that is keyed by gene name, with estimated protein amounts as values.

Return type:

dict[dict[float]]

Network relevance client (indra.databases.relevance_client)

indra.databases.relevance_client.get_heat_kernel(network_id)

Return the identifier of a heat kernel calculated for a given network.

Parameters:network_id (str) – The UUID of the network in NDEx. Returns:kernel_id – The identifier of the heat kernel calculated for the given network. Return type:str

indra.databases.relevance_client.get_relevant_nodes(network_id, query_nodes)

Return a set of network nodes relevant to a given query set.

A heat diffusion algorithm is used on a pre-computed heat kernel for the given network which starts from the given query nodes. The nodes in the network are ranked according to heat score which is a measure of relevance with respect to the query nodes.

Parameters:

• network_id (str) – The UUID of the network in NDEx.
• query_nodes (list[str]) – A list of node names with respect to which relevance is queried.

Returns:

ranked_entities – A list containing pairs of node names and their relevance scores.

Return type:

list[(str, float)]

NDEx client (indra.databases.ndex_client)

indra.databases.ndex_client.create_network(cx_str, ndex_cred=None, private=True)

Creates a new NDEx network of the assembled CX model.

To upload the assembled CX model to NDEx, you need to have a registered account on NDEx (http://ndexbio.org/) and have the ndex python package installed. The uploaded network is private by default.

Parameters:ndex_cred (dict) – A dictionary with the following entries: ‘user’: NDEx user name ‘password’: NDEx password Returns:network_id – The UUID of the NDEx network that was created by uploading the assembled CX model. Return type:str

indra.databases.ndex_client.get_default_ndex_cred(ndex_cred)

Gets the NDEx credentials from the dict, or tries the environment if None

indra.databases.ndex_client.send_request(ndex_service_url, params, is_json=True, use_get=False)

Send a request to the NDEx server.

Parameters:

• ndex_service_url (str) – The URL of the service to use for the request.
• params (dict) – A dictionary of parameters to send with the request. Parameter keys differ based on the type of request.
• is_json (bool) – True if the response is in json format, otherwise it is assumed to be text. Default: False
• use_get (bool) – True if the request needs to use GET instead of POST.

Returns:

res – Depending on the type of service and the is_json parameter, this function either returns a text string or a json dict.

Return type:

str

indra.databases.ndex_client.set_style(network_id, ndex_cred=None, template_id=None)

Set the style of the network to a given template network’s style

Parameters:

• network_id (str) – The UUID of the NDEx network whose style is to be changed.
• ndex_cred (dict) – A dictionary of NDEx credentials.
• template_id (Optional[str]) – The UUID of the NDEx network whose style is used on the network specified in the first argument.

indra.databases.ndex_client.update_network(cx_str, network_id, ndex_cred=None)

Update an existing CX network on NDEx with new CX content.

Parameters:

• cx_str (str) – String containing the CX content.
• network_id (str) – UUID of the network on NDEx.
• ndex_cred (dict) – A dictionary with the following entries: ‘user’: NDEx user name ‘password’: NDEx password

cBio portal client (indra.databases.cbio_client)

indra.databases.cbio_client.get_cancer_studies(study_filter=None)

Return a list of cancer study identifiers, optionally filtered.

There are typically multiple studies for a given type of cancer and a filter can be used to constrain the returned list.

Parameters:study_filter (Optional[str]) – A string used to filter the study IDs to return. Example: “paad” Returns:study_ids – A list of study IDs. For instance “paad” as a filter would result in a list of study IDs with paad in their name like “paad_icgc”, “paad_tcga”, etc. Return type:list[str]

indra.databases.cbio_client.get_cancer_types(cancer_filter=None)

Return a list of cancer types, optionally filtered.

Parameters:cancer_filter (Optional[str]) – A string used to filter cancer types. Its value is the name or part of the name of a type of cancer. Example: “melanoma”, “pancreatic”, “non-small cell lung” Returns:type_ids – A list of cancer types matching the filter. Example: for cancer_filter=”pancreatic”, the result includes “panet” (neuro-endocrine) and “paad” (adenocarcinoma) Return type:list[str]

indra.databases.cbio_client.get_case_lists(study_id)

Return a list of the case set ids for a particular study.

TAKE NOTE the “case_list_id” are the same thing as “case_set_id” Within the data, this string is referred to as a “case_list_id”. Within API calls it is referred to as a ‘case_set_id’. The documentation does not make this explicitly clear.

Parameters:study_id (str) – The ID of the cBio study. Example: ‘cellline_ccle_broad’ or ‘paad_icgc’ Returns:case_set_ids – A dict keyed to cases containing a dict keyed to genes containing int Return type:dict[dict[int]]

indra.databases.cbio_client.get_ccle_cna(gene_list, cell_lines)

Return a dict of CNAs in given genes and cell lines from CCLE.

CNA values correspond to the following alterations

-2 = homozygous deletion

-1 = hemizygous deletion

0 = neutral / no change

1 = gain

2 = high level amplification

Parameters:

• gene_list (list[str]) – A list of HGNC gene symbols to get mutations in
• cell_lines (list[str]) – A list of CCLE cell line names to get mutations for.

Returns:

profile_data – A dict keyed to cases containing a dict keyed to genes containing int

Return type:

dict[dict[int]]

indra.databases.cbio_client.get_ccle_lines_for_mutation(gene, amino_acid_change)

Return cell lines with a given point mutation in a given gene.

Checks which cell lines in CCLE have a particular point mutation in a given gene and return their names in a list.

Parameters:

• gene (str) – The HGNC symbol of the mutated gene in whose product the amino acid change occurs. Example: “BRAF”
• amino_acid_change (str) – The amino acid change of interest. Example: “V600E”

Returns:

cell_lines – A list of CCLE cell lines in which the given mutation occurs.

Return type:

list

indra.databases.cbio_client.get_ccle_mrna(gene_list, cell_lines)

Return a dict of mRNA amounts in given genes and cell lines from CCLE.

Parameters:

• gene_list (list[str]) – A list of HGNC gene symbols to get mRNA amounts for.
• cell_lines (list[str]) – A list of CCLE cell line names to get mRNA amounts for.

Returns:

mrna_amounts – A dict keyed to cell lines containing a dict keyed to genes containing float

Return type:

dict[dict[float]]

indra.databases.cbio_client.get_ccle_mutations(gene_list, cell_lines, mutation_type=None)

Return a dict of mutations in given genes and cell lines from CCLE.

This is a specialized call to get_mutations tailored to CCLE cell lines.

Parameters:

• gene_list (list[str]) – A list of HGNC gene symbols to get mutations in
• cell_lines (list[str]) – A list of CCLE cell line names to get mutations for.
• mutation_type (Optional[str]) – The type of mutation to filter to. mutation_type can be one of: missense, nonsense, frame_shift_ins, frame_shift_del, splice_site

Returns:

mutations – The result from cBioPortal as a dict in the format {cell_line : {gene : [mutation1, mutation2, …] }}

Example: {‘LOXIMVI_SKIN’: {‘BRAF’: [‘V600E’, ‘I208V’]}, ‘SKMEL30_SKIN’: {‘BRAF’: [‘D287H’, ‘E275K’]}}

Return type:

dict

indra.databases.cbio_client.get_genetic_profiles(study_id, profile_filter=None)

Return all the genetic profiles (data sets) for a given study.

Genetic profiles are different types of data for a given study. For instance the study ‘cellline_ccle_broad’ has profiles such as ‘cellline_ccle_broad_mutations’ for mutations, ‘cellline_ccle_broad_CNA’ for copy number alterations, etc.

Parameters:

• study_id (str) – The ID of the cBio study. Example: ‘paad_icgc’
• profile_filter (Optional[str]) – A string used to filter the profiles to return. Will be one of: - MUTATION - MUTATION_EXTENDED - COPY_NUMBER_ALTERATION - MRNA_EXPRESSION - METHYLATION The genetic profiles can include “mutation”, “CNA”, “rppa”, “methylation”, etc.

Returns:

genetic_profiles – A list of genetic profiles available for the given study.

Return type:

list[str]

indra.databases.cbio_client.get_mutations(study_id, gene_list, mutation_type=None, case_id=None)

Return mutations as a list of genes and list of amino acid changes.

Parameters:

• study_id (str) – The ID of the cBio study. Example: ‘cellline_ccle_broad’ or ‘paad_icgc’
• gene_list (list[str]) – A list of genes with their HGNC symbols. Example: [‘BRAF’, ‘KRAS’]
• mutation_type (Optional[str]) – The type of mutation to filter to. mutation_type can be one of: missense, nonsense, frame_shift_ins, frame_shift_del, splice_site
• case_id (Optional[str]) – The case ID within the study to filter to.

Returns:

mutations – A tuple of two lists, the first one containing a list of genes, and the second one a list of amino acid changes in those genes.

Return type:

tuple[list]

indra.databases.cbio_client.get_num_sequenced(study_id)

Return number of sequenced tumors for given study.

This is useful for calculating mutation statistics in terms of the prevalence of certain mutations within a type of cancer.

Parameters:study_id (str) – The ID of the cBio study. Example: ‘paad_icgc’ Returns:num_case – The number of sequenced tumors in the given study Return type:int

indra.databases.cbio_client.get_profile_data(study_id, gene_list, profile_filter, case_set_filter=None)

Return dict of cases and genes and their respective values.

Parameters:

• study_id (str) – The ID of the cBio study. Example: ‘cellline_ccle_broad’ or ‘paad_icgc’
• gene_list (list[str]) – A list of genes with their HGNC symbols. Example: [‘BRAF’, ‘KRAS’]
• profile_filter (str) – A string used to filter the profiles to return. Will be one of: - MUTATION - MUTATION_EXTENDED - COPY_NUMBER_ALTERATION - MRNA_EXPRESSION - METHYLATION
• case_set_filter (Optional[str]) – A string that specifices which case_set_id to use, based on a complete or partial match. If not provided, will look for study_id + ‘_all’

Returns:

profile_data – A dict keyed to cases containing a dict keyed to genes containing int

Return type:

dict[dict[int]]

indra.databases.cbio_client.send_request

Return a data frame from a web service request to cBio portal.

Sends a web service requrest to the cBio portal with arguments given in the dictionary data and returns a Pandas data frame on success.

More information about the service here: http://www.cbioportal.org/web_api.jsp

Parameters:kwargs (dict) – A dict of parameters for the query. Entries map directly to web service calls with the exception of the optional ‘skiprows’ entry, whose value is used as the number of rows to skip when reading the result data frame. Returns:df – Response from cBioPortal as a Pandas DataFrame. Return type:pandas.DataFrame

ChEMBL client (indra.databases.chembl_client)

indra.databases.chembl_client.activities_by_target(activities)

Get back lists of activities in a dict keyed by ChEMBL target id

Parameters:activities (list) – response from a query returning activities for a drug Returns:targ_act_dict – dictionary keyed to ChEMBL target ids with lists of activity ids Return type:dict

indra.databases.chembl_client.get_chembl_id(nlm_mesh)

Get ChEMBL ID from NLM MESH

Parameters:nlm_mesh (str) – Returns:chembl_id Return type:str

indra.databases.chembl_client.get_drug_inhibition_stmts(drug)

Query ChEMBL for kinetics data given drug as Agent get back statements

Parameters:drug (Agent) – Agent representing drug with MESH or CHEBI grounding Returns:stmts – INDRA statements generated by querying ChEMBL for all kinetics data of a drug interacting with protein targets Return type:list of INDRA statements

indra.databases.chembl_client.get_evidence(assay)

Given an activity, return an INDRA Evidence object.

Parameters:assay (dict) – an activity from the activities list returned by a query to the API Returns:ev – an Evidence object containing the kinetics of the Return type:Evidence

indra.databases.chembl_client.get_kinetics(assay)

Given an activity, return its kinetics values.

Parameters:assay (dict) – an activity from the activities list returned by a query to the API Returns:kin – dictionary of values with units keyed to value types ‘IC50’, ‘EC50’, ‘INH’, ‘Potency’, ‘Kd’ Return type:dict

indra.databases.chembl_client.get_mesh_id(nlm_mesh)

Get MESH ID from NLM MESH

Parameters:nlm_mesh (str) – Returns:mesh_id Return type:str

indra.databases.chembl_client.get_pcid(mesh_id)

Get PC ID from MESH ID

Parameters:mesh (str) – Returns:pcid Return type:str

indra.databases.chembl_client.get_pmid(doc_id)

Get PMID from document_chembl_id

Parameters:doc_id (str) – Returns:pmid Return type:str

indra.databases.chembl_client.get_protein_targets_only(target_chembl_ids)

Given list of ChEMBL target ids, return dict of SINGLE PROTEIN targets

Parameters:target_chembl_ids (list) – list of chembl_ids as strings Returns:protein_targets – dictionary keyed to ChEMBL target ids with lists of activity ids Return type:dict

indra.databases.chembl_client.get_target_chemblid(target_upid)

Get ChEMBL ID from UniProt upid

Parameters:target_upid (str) – Returns:target_chembl_id Return type:str

indra.databases.chembl_client.query_target(target_chembl_id)

Query ChEMBL API target by id

Parameters:target_chembl_id (str) – Returns:target – dict parsed from json that is unique for the target Return type:dict

indra.databases.chembl_client.send_query(query_dict)

Query ChEMBL API

Parameters:query_dict (dict) – ‘query’ : string of the endpoint to query ‘params’ : dict of params for the query Returns:js – dict parsed from json that is unique to the submitted query Return type:dict

LINCS client (indra.databases.lincs_client)

indra.databases.lincs_client.get_drug_target_data()

Load the csv into a list of dicts containing the LINCS drug target data.

Returns:data – A list of dicts, each keyed based on the header of the csv, with values as the corresponding column values. Return type:list[dict]

class indra.databases.lincs_client.LincsClient

Client for querying LINCS small molecules and proteins.

get_protein_refs(hms_lincs_id)

Get the refs for a protein from the LINCs protein metadata.

Parameters:hms_lincs_id (str) – The HMS LINCS ID for the protein Returns:A dictionary of protein references. Return type:dict

get_small_molecule_name(hms_lincs_id)

Get the name of a small molecule from the LINCS sm metadata.

Parameters:hms_lincs_id (str) – The HMS LINCS ID of the small molecule. Returns:The name of the small molecule. Return type:str

get_small_molecule_refs(hms_lincs_id)

Get the id refs of a small molecule from the LINCS sm metadata.

Parameters:hms_lincs_id (str) – The HMS LINCS ID of the small molecule. Returns:A dictionary of references. Return type:dict

indra.databases.lincs_client.load_lincs_csv(url)

Helper function to turn csv rows into dicts.

MeSH client (indra.databases.mesh_client)

indra.databases.mesh_client.get_mesh_id_name(mesh_term, offline=False)

Get the MESH ID and name for the given MESH term.

Uses the mappings table in indra/resources; if the MESH term is not listed there, falls back on the NLM REST API.

Parameters:

• mesh_term (str) – MESH Descriptor or Concept name, e.g. ‘Breast Cancer’.
• offline (bool) – Whether to allow queries to the NLM REST API if the given MESH term is not contained in INDRA’s internal MESH mappings file. Default is False (allows REST API queries).

Returns:

Returns a 2-tuple of the form (id, name) with the ID of the descriptor corresponding to the MESH label, and the descriptor name (which may not exactly match the name provided as an argument if it is a Concept name). If the query failed, or no descriptor corresponding to the name was found, returns a tuple of (None, None).

Return type:

tuple of strs

indra.databases.mesh_client.get_mesh_id_name_from_web

Get the MESH ID and name for the given MESH term using the NLM REST API.

Parameters:mesh_term (str) – MESH Descriptor or Concept name, e.g. ‘Breast Cancer’. Returns:Returns a 2-tuple of the form (id, name) with the ID of the descriptor corresponding to the MESH label, and the descriptor name (which may not exactly match the name provided as an argument if it is a Concept name). If the query failed, or no descriptor corresponding to the name was found, returns a tuple of (None, None). Return type:tuple of strs

indra.databases.mesh_client.get_mesh_name(mesh_id, offline=False)

Get the MESH label for the given MESH ID.

Uses the mappings table in indra/resources; if the MESH ID is not listed there, falls back on the NLM REST API.

Parameters:

• mesh_id (str) – MESH Identifier, e.g. ‘D003094’.
• offline (bool) – Whether to allow queries to the NLM REST API if the given MESH ID is not contained in INDRA’s internal MESH mappings file. Default is False (allows REST API queries).

Returns:

Label for the MESH ID, or None if the query failed or no label was found.

Return type:

str

indra.databases.mesh_client.get_mesh_name_from_web

Get the MESH label for the given MESH ID using the NLM REST API.

Parameters:mesh_id (str) – MESH Identifier, e.g. ‘D003094’. Returns:Label for the MESH ID, or None if the query failed or no label was found. Return type:str

GO client (indra.databases.go_client)

indra.databases.go_client.get_go_label(go_id)

Get label corresponding to a given GO identifier.

Parameters:go_id (str) – The GO identifier. Should include the GO: prefix, e.g., GO:1903793 (positive regulation of anion transport). Returns:Label corresponding to the GO ID. Return type:str

indra.databases.go_client.load_go_graph(go_fname)

Load the GO data from an OWL file and parse into an RDF graph.

Parameters:go_fname (str) – Path to the GO OWL file. Can be downloaded from http://geneontology.org/ontology/go.owl. Returns:RDF graph containing GO data. Return type:rdflib.Graph

indra.databases.go_client.update_id_mappings(g)

Compile all ID->label mappings and save to a TSV file.

Parameters:g (rdflib.Graph) – RDF graph containing GO data.