コード例 #1
0
ファイル: test_ddot.py プロジェクト: cthoyt/ddot
    def test_from_sim(self):
        """Test that the run_clixo function can run."""
        sim, genes = self.ont.flatten()

        genes = list(genes)
        print(genes)

        sim = pd.DataFrame(sim, columns=genes, index=genes)

        ddo = Ontology.run_clixo(
            sim,
            'test_df_output.txt',
            'test_clixo_output.txt',
            'test_output.txt',
            square=True,
            square_names=genes,
        )
        print('ddo:\n', ddo)
コード例 #2
0
ファイル: onto.py プロジェクト: priya-gitTest/FHIR-PIT
    #    print(x)
    return x


cooc_df = cooc_df.apply(normalize, axis=1)

# print(cooc_df)

namemap_df = pd.read_csv(nnm, sep="|", header=None).set_index(0)
namemap_df.columns = ["Label"]

# print(namemap_df)

ont = Ontology.run_clixo(
    cooc_df,
    alpha,
    beta,
    verbose=False,
)

ont.update_node_attr(namemap_df)

# print(ont.to_table(output, clixo_format=True))
# nwx = ont.to_networkx()
# nx.write_graphml(nwx, 'clixotable.graphml')

grph = ont.to_igraph(include_genes=True)
grph.write_graphml(output + '.graphml')

if upload:
    ndex_url, ont_ndexgraph = ont.to_ndex(
        name="Pitch 15 Asthma Ontology",
コード例 #3
0
    def infer_hierarchical_model(
        self,
        method='clixo-api',
        method_kwargs=None,
        edge_attr='has_edge',
        ddot_api_location=None,
        get_ontology_object=False,
    ):
        if method_kwargs is None:
            method_kwargs = {}

        if method == 'clixo-api':
            cols = self.edge_table.columns
            table = self.edge_table[[cols[0], cols[1], edge_attr]]
            self.ddot_client = DDOT_Client.from_dataframe(
                table, ddot_api_location=ddot_api_location)
            (self.ddot_client.call(**method_kwargs).wait_for_hiview_url())

            self.hiview_url = self.ddot_client.hiview_url

            if get_ontology_object:
                self.ddot_client.get_output_file(create_object=True)
                self.ontology = self.ddot_client.ontology

        elif method == 'clixo':
            from ddot import Ontology

            self.ontology = Ontology.run_clixo(
                self.edge_table,
                method_kwargs['alpha'],
                method_kwargs['beta'],
                clixo_cmd=method_kwargs['clixo_path'],
                clixo_version=method_kwargs['clixo_version'],
            )

            if len(self.edge_table.columns) != 3:
                #TODO
                print("future warning about edge table columns")

            if method_kwargs.get("upload_to_ndex", True):
                self.upload_ontology_to_ndex(
                    method_kwargs['ndex_username'],
                    method_kwargs['ndex_password'],
                    ndex_server=method_kwargs.get('ndex_server',
                                                  "http://test.ndexbio.org"),
                    main_network=self.edge_table,
                    main_feature=self.edge_table.columns[-1])

                ndex_url, _ = self.ontology.to_ndex(
                    method_kwargs['ndex_username'],
                    method_kwargs['ndex_password'],
                    method_kwargs.get('ndex_server',
                                      'http://test.ndexbio.org'),
                    network=self.edge_table,
                    main_feature=self.edge_table.columns[-1])

                uuid = ndex_url.split('/')[-1]
                self.hiview_url = f"http://hiview-test.ucsd.edu/{uuid}?type=test&server=http://dev2.ndexbio.org"

        else:
            raise ValueError("Invalid method!")

        return self
コード例 #4
0
    concept1 = x[0]
    concept2 = x[1]
    x[0] = x[0].replace(' ', '_')
    x[1] = x[1].replace(' ', '_')
    x[2] = float(x[2]) / (frequency_dict[concept1] * frequency_dict[concept2])
    #    print(x)
    return x


cooc_df = cooc_df.apply(normalize, axis=1)

print(cooc_df)

print(isinstance(cooc_df, pd.DataFrame))

ont = Ontology.run_clixo(cooc_df, alpha, beta)

print(ont.to_table(output, clixo_format=True))
# nwx = ont.to_networkx()
# nx.write_graphml(nwx, 'clixotable.graphml')

grph = ont.to_igraph(include_genes=True)
grph.write_graphml(output + '.graphml')

if upload:
    ndex_url, ont_ndexgraph = ont.to_ndex(
        name="Pitch 15 Asthma Ontology",
        ndex_server="http://test.ndexbio.org",
        ndex_pass='******',
        ndex_user='******',
        layout='bubble-collect',
コード例 #5
0
    def StreamElements(self, element_iterator, context):
        try:
            params = {
                'similarity' : 'Similarity',
                'name' : 'Data-Driven Ontology',
                'min_dt' : -100000,
                'features' : '',
                'all_features' : False,
                'input_fmt' : 'cx',
                'timeout' : 100,
                'ndex_uuid' : None
            }
            params.update(default_params)
            G, params, errors = self.read_element_stream(element_iterator, params)
            self.format_params(params)

            if verbose:
                print('Parameters', params)

            input_fmt = params['input_fmt'].replace('ndex', 'cx')

            G_df, nodes_attr = ndex_to_sim_matrix(
                params['ndex_uuid'],
                params['ndex_server'],
                params['ndex_user'],
                params['ndex_pass'],
                similarity=params['similarity'],
                input_fmt=input_fmt,
                output_fmt='sparse')
            
            print 'Similarity'
            print G_df.head()

            features = [params['similarity']]
            if params['all_features']:
                features.extend(G_df.columns.values.tolist())

            gene_names = np.unique(np.append(
                G_df['Gene1'].values,
                G_df['Gene2'].values))
            if verbose:
                print 'Gene names:', gene_names

            if params['features']:
                to_concat = []

                for f in params['features']:
                    if f in G_df.columns:
                        in_G.append(f)
                    else:
                        tmp = ndex_to_sim_matrix(
                            params['ndex_uuid'],
                            params['ndex_server'],
                            params['ndex_user'],
                            params['ndex_pass'],
                            similarity=params['similarity'],
                            input_fmt=input_fmt,
                            output_fmt='sparse',
                            subset=None)
                        tmp.set_index(['Gene1', 'Gene2'], inplace=True)
                        to_concat.append(tmp)
                to_concat.append(G_df)
                G_df = pd.concat(to_concat, axis=1)

            if verbose:
                print 'Features:', features

            errors = [e for e in errors if e.message != "Error decoding token from stream, EOF"]
            if len(errors) == 0:

                ## Run CLIXO
                graph = G_df[['Gene1', 'Gene2', params['similarity']]]
                ont = Ontology.run_clixo(
                    graph,
                    params['alpha'],
                    params['beta'],
                    min_dt=params['min_dt'],
                    timeout=params['timeout']
                )                

                # Create an NDEX network for every term's subnetwork
                term_2_uuid = ont.upload_subnets_ndex(
                    G_df,
                    features,
                    params['ndex_server'],
                    params['ndex_user'],
                    params['ndex_pass'],
                    params['name'],
                    propagate=True
                )

                if params['output_fmt']=='cx':
                    # Use CXmate to stream to NDEX
                    for elt in self.stream_ontology(ont, term_sizes, term_2_uuid, tree_edges):
                        yield elt

                elif params['output_fmt']=='ndex':
                    description = (
                        'Data-driven ontology created by CLIXO '
                        '(parameters: alpha={alpha}, beta={beta}). '
                        'Created from similarity network '
                        'at {ndex_server}/{ndex_uuid}').format(**params)

                    # nx_nodes_to_pandas(G)

                    ont_ndex = ont.to_NdexGraph(
                        name=params['name'],
                        description=description,
                        term_2_uuid=term_2_uuid,
                        gene_attr=nodes_attr)

                    ont_url = ont_ndex.upload_to(
                        params['ndex_server'],
                        params['ndex_user'],
                        params['ndex_pass'])
                    print 'ontology_url:', ont_url

                    for elt in yield_ndex(ont_url):
                        yield elt
            else:
                for caught_error in errors:
                    error = self.create_internal_crash_error(caught_error.message, 500)
                    log_error(error)
                    yield error
        except Exception as e:
            message = "Unexpected error: " + str(e)
            error = self.create_internal_crash_error(message, 500)
            log_error(error)
        
            import traceback
            print traceback.print_exc()

            yield error
コード例 #6
0
import networkx as nx
import pandas as pd
import ddot
from ddot import Ontology

net = nx.read_edgelist('/home/hsher/secM/string_subnetwork_secM')
df = nx.convert_matrix.to_pandas_dataframe(net, weight='combined_score')

print(df.sum(axis=1))
print(df.shape)

ont = Ontology.run_clixo(df,
                         alpha=0.2,
                         beta=0.9,
                         output='/home/hsher/secM/secM_ontology',
                         square=True,
                         square_names=df.index.tolist())

# put to ndex
ndex_server = 'http://public.ndexbio.org'
ndex_user, ndex_pass = '******', '5mY87$747l'

url, _ = ont.to_ndex(ndex_server=ndex_server,
                     ndex_user=ndex_user,
                     ndex_pass=ndex_pass)
print(url)