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feat: physical interaction networks #7

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49 changes: 34 additions & 15 deletions stringdb/api.py
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Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
"""api module. Functions to access the STRING API"""
"""api module. Functions to access the STRING API."""
import pandas as pd
import io
import requests
Expand All @@ -12,8 +12,9 @@ def build_request_url(method, output_format='tsv'):
Parameters
----------
method: str
options - get_string_ids, network, interaction_partners, homology, homology_best,
enrichment, functional_annotation, ppi_enrichment, version
options - get_string_ids, network, interaction_partners, homology,
homology_best, enrichment, functional_annotation, ppi_enrichment,
version
output_format: str, optional
options - tsv, tsv-non-header, json, xml

Expand Down Expand Up @@ -73,8 +74,11 @@ def get_string_ids(identifiers, species=9606, limit=1, echo_query=1,
return df


def get_functional_annotation(identifiers, species=9606, caller_identity='https://github.com/gpp-rnd/stringdb',
allow_pubmed=0):
def get_functional_annotation(
identifiers,
species=9606,
caller_identity='https://github.com/gpp-rnd/stringdb',
allow_pubmed=0):
"""Get all pathways for a list of string ids

Parameters
Expand Down Expand Up @@ -111,8 +115,12 @@ def get_functional_annotation(identifiers, species=9606, caller_identity='https:
return pathway_df


def get_network(identifiers, species=9606, required_score=400,
caller_identity='https://github.com/gpp-rnd/stringdb', add_nodes=0):
def get_network(identifiers,
species=9606,
required_score=400,
network_type="physical",
caller_identity='https://github.com/gpp-rnd/stringdb',
add_nodes=0):
"""Get the ppi network for a list of string ids

Parameters
Expand All @@ -122,7 +130,11 @@ def get_network(identifiers, species=9606, required_score=400,
species: int, optional
species NCBI identifier
required_score: int, optional
score cutoff for edges, corresponds to probability of belonging to same kegg pathway
score cutoff for edges, corresponds to probability of belonging
to same kegg pathway
network_type: str, optional
type of interactions in the network.
options - functional (default), physical
caller_identity: str, optional
personal identifier for string
add_nodes: int, optional
Expand All @@ -139,6 +151,7 @@ def get_network(identifiers, species=9606, required_score=400,
"species": species, # species NCBI identifier
"caller_identity": caller_identity,
"required_score": required_score,
"network_type": network_type,
"add_nodes": add_nodes
}
results = requests.post(request_url, data=params)
Expand All @@ -157,7 +170,8 @@ def get_ppi_enrichment(identifiers, species=9606, required_score=400,
species: int, optional
species NCBI identifier
required_score: int, optional
score cutoff for edges, corresponds to probability of belonging to same kegg pathway
score cutoff for edges, corresponds to probability of belonging
to same kegg pathway
caller_identity: str, optional
personal identifier for string

Expand All @@ -178,8 +192,9 @@ def get_ppi_enrichment(identifiers, species=9606, required_score=400,
return df


def get_interaction_partners(identifiers, species=9606, required_score=400,
limit=None, caller_identity='https://github.com/gpp-rnd/stringdb'):
def get_interaction_partners(
identifiers, species=9606, required_score=400, limit=None,
caller_identity='https://github.com/gpp-rnd/stringdb'):
"""Get interactions for identified proteins and all other string proteins

Parameters
Expand All @@ -189,9 +204,11 @@ def get_interaction_partners(identifiers, species=9606, required_score=400,
species: int, optional
species NCBI identifier
required_score: int, optional
score cutoff for edges, corresponds to probability of belonging to same kegg pathway
score cutoff for edges, corresponds to probability of belonging
to same kegg pathway
limit: int, optional
limit the number of interactors returned for each protein, ranked by score
limit the number of interactors returned for each protein,
ranked by score
caller_identity: str, optional
personal identifier for string

Expand All @@ -213,7 +230,8 @@ def get_interaction_partners(identifiers, species=9606, required_score=400,
return df


def get_enrichment(identifiers, background_string_identifiers=None, species=9606,
def get_enrichment(identifiers, background_string_identifiers=None,
species=9606,
caller_identity='https://github.com/gpp-rnd/stringdb'):
"""Get functional enrichment for a list of proteins

Expand All @@ -240,7 +258,8 @@ def get_enrichment(identifiers, background_string_identifiers=None, species=9606
"caller_identity": caller_identity,
}
if background_string_identifiers is not None:
params['background_string_identifiers'] = "\r".join(background_string_identifiers)
params['background_string_identifiers'] = "\r".join(
background_string_identifiers)
results = requests.post(request_url, data=params)
df = handle_results(results)
return df
26 changes: 17 additions & 9 deletions tests/test_stringdb.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,18 +16,23 @@ def mapped_ddr_ids():


def test_string_mapping(mapped_ddr_ids):
assert (mapped_ddr_ids['preferredName'].isin(['TP53', 'BRCA1', 'BRCA2', 'FANCL'])
.sum() / mapped_ddr_ids.shape[0] == 1)
assert (mapped_ddr_ids['preferredName'].isin(
['TP53', 'BRCA1', 'BRCA2', 'FANCL'])
.sum() / mapped_ddr_ids.shape[0] == 1)


def test_functional_annotation(mapped_ddr_ids):
mapped_pathways = stringdb.get_functional_annotation(mapped_ddr_ids.stringId)
assert (mapped_pathways.loc[mapped_pathways.term == 'GO:0006281', 'number_of_genes'].values[0] == 4) # DNA repair
mapped_pathways = stringdb.get_functional_annotation(
mapped_ddr_ids.stringId)
assert (mapped_pathways.loc[
mapped_pathways.term == 'GO:0006281', 'number_of_genes']
.values[0] == 4) # DNA repair


def test_network(mapped_ddr_ids):
network = stringdb.get_network(mapped_ddr_ids.stringId)
assert (network.shape[0] == 5) # edges between everything except TP53 and FANCL
assert (network.shape[0] == 8)
# edges between everything except TP53 and FANCL


def test_ppi_enrichment(mapped_ddr_ids):
Expand All @@ -36,14 +41,17 @@ def test_ppi_enrichment(mapped_ddr_ids):


def test_interaction_partners(mapped_ddr_ids):
interaction_partners = stringdb.get_interaction_partners(mapped_ddr_ids.stringId)
interaction_partners = stringdb.get_interaction_partners(
mapped_ddr_ids.stringId)
n_interactors = interaction_partners.preferredName_A.value_counts()
assert n_interactors['TP53'] > n_interactors['FANCL']


def test_enrichment(mapped_ddr_ids):
enrichment_df = stringdb.get_enrichment(mapped_ddr_ids.stringId)
assert enrichment_df.sort_values('fdr')['term'].values[0] == 'PMID.22918243'
background_enrichment = stringdb.get_enrichment(mapped_ddr_ids.stringId,
background_string_identifiers=mapped_ddr_ids.stringId)
assert enrichment_df.sort_values(
'fdr')['term'].values[0] == 'PMID:31805037'
background_enrichment = stringdb.get_enrichment(
mapped_ddr_ids.stringId,
background_string_identifiers=mapped_ddr_ids.stringId)
assert background_enrichment.shape[0] == 0