diff --git a/.bumpversion.cfg b/.bumpversion.cfg index a722bf1d..9756d38c 100644 --- a/.bumpversion.cfg +++ b/.bumpversion.cfg @@ -1,5 +1,5 @@ [bumpversion] -current_version = 1.3.0 +current_version = 1.3.1-dev commit = True tag = False parse = (?P\d+)\.(?P\d+)\.(?P\d+)(?:-(?P[0-9A-Za-z-]+(?:\.[0-9A-Za-z-]+)*))?(?:\+(?P[0-9A-Za-z-]+(?:\.[0-9A-Za-z-]+)*))? diff --git a/docs/source/conf.py b/docs/source/conf.py index 0247323a..a6ad0d00 100644 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -27,7 +27,7 @@ author = "Tooba Abbassi-Daloii and Yojana Gadiya" # The full version, including alpha/beta/rc tags. -release = "1.3.0" +release = "1.3.1-dev" # The short X.Y version. parsed_version = re.match( diff --git a/examples/02_metabolite_to_graph.ipynb b/examples/02_metabolite_to_graph.ipynb index b27c77df..825c55ea 100644 --- a/examples/02_metabolite_to_graph.ipynb +++ b/examples/02_metabolite_to_graph.ipynb @@ -420,7 +420,17 @@ "cell_type": "code", "execution_count": 9, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Querying AOP_Wiki_RDF for compounds: 100%|██████████| 1/1 [00:00<00:00, 3.83it/s]\n", + "/Users/yojana/Documents/GitHub/pyBiodatafuse/src/pyBiodatafuse/annotators/aopwiki.py:361: UserWarning: The intermediate_df in AOP_Wiki_RDF_compounds annotator should be checked, please create an issue on https://github.com/BioDataFuse/pyBiodatafuse/issues/.\n", + " give_annotator_warning(Cons.AOPWIKI_COMPOUND_COL)\n" + ] + } + ], "source": [ "aopwiki_path = f\"{EXAMPLE_DIR}/aopwiki.pkl\"\n", "aopwiki_metadata_path = f\"{EXAMPLE_DIR}/aopwiki_metadata.pkl\"\n", @@ -620,7 +630,17 @@ "cell_type": "code", "execution_count": 13, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Querying IntAct for compounds: 100%|██████████| 1/1 [00:01<00:00, 1.54s/it]\n", + "/Users/yojana/Documents/GitHub/pyBiodatafuse/src/pyBiodatafuse/annotators/intact.py:424: UserWarning: The intermediate_df in IntAct annotator should be checked, please create an issue on https://github.com/BioDataFuse/pyBiodatafuse/issues/.\n", + " give_annotator_warning(Cons.INTACT)\n" + ] + } + ], "source": [ "intact_path = f\"{EXAMPLE_DIR}/intact.pkl\"\n", "intact_metadata_path = f\"{EXAMPLE_DIR}/intact_metadata.pkl\"\n", @@ -729,7 +749,15 @@ "cell_type": "code", "execution_count": 16, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Processing IntAct column for compounds: IntAct_compound_interactions\n" + ] + } + ], "source": [ "compoundwiki_path = f\"{EXAMPLE_DIR}/compoundwiki.pkl\"\n", "compoundwiki_metadata_path = f\"{EXAMPLE_DIR}/compoundwiki_metadata.pkl\"\n", @@ -1009,7 +1037,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 20, "metadata": {}, "outputs": [], "source": [ @@ -1041,7 +1069,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "Building graph: 100%|██████████| 13/13 [00:00<00:00, 600.02it/s]\n" + "Building graph: 100%|██████████| 13/13 [00:00<00:00, 3236.35it/s]\n" ] } ], @@ -1058,14 +1086,14 @@ "name": "stderr", "output_type": "stream", "text": [ - "Combined DataFrame saved in /home/javi/finalbdfixes/pyBiodatafuse/examples/data/metabolite_workflow/metabolite_workflow_df.pkl\n", - "Metadata saved in /home/javi/finalbdfixes/pyBiodatafuse/examples/data/metabolite_workflow/metabolite_workflow_metadata.pkl\n", - "Building graph: 100%|██████████| 13/13 [00:00<00:00, 919.37it/s]\n", + "Combined DataFrame saved in /Users/yojana/Documents/GitHub/pyBiodatafuse/examples/data/metabolite_workflow/metabolite_workflow_df.pkl\n", + "Metadata saved in /Users/yojana/Documents/GitHub/pyBiodatafuse/examples/data/metabolite_workflow/metabolite_workflow_metadata.pkl\n", + "Building graph: 100%|██████████| 13/13 [00:00<00:00, 5108.30it/s]\n", "Graph is built successfully\n", "Graph saved in: \n", - " /home/javi/finalbdfixes/pyBiodatafuse/examples/data/metabolite_workflow/metabolite_workflow_graph.pkl \n", - " /home/javi/finalbdfixes/pyBiodatafuse/examples/data/metabolite_workflow/metabolite_workflow_graph.gml\n", - "Graph saved in /home/javi/finalbdfixes/pyBiodatafuse/examples/data/metabolite_workflow/metabolite_workflow_graph.edgelist\n" + " /Users/yojana/Documents/GitHub/pyBiodatafuse/examples/data/metabolite_workflow/metabolite_workflow_graph.pkl \n", + " /Users/yojana/Documents/GitHub/pyBiodatafuse/examples/data/metabolite_workflow/metabolite_workflow_graph.gml\n", + "Graph saved in /Users/yojana/Documents/GitHub/pyBiodatafuse/examples/data/metabolite_workflow/metabolite_workflow_graph.edgelist\n" ] } ], @@ -1111,7 +1139,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "{'Unknown', 'Adverse Outcome Pathway', 'Pathway', 'Compound', 'Key Event'}\n" + "{'Compound', 'Adverse Outcome Pathway', 'Unknown', 'Key Event', 'Pathway'}\n" ] } ], @@ -1134,7 +1162,9 @@ "name": "stderr", "output_type": "stream", "text": [ - "Building RDF graph: 100%|██████████| 13/13 [00:00<00:00, 114.33it/s]\n" + "/opt/anaconda3/envs/pybiodatafuse/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", + " from .autonotebook import tqdm as notebook_tqdm\n", + "Building RDF graph: 100%|██████████| 13/13 [00:00<00:00, 649.51it/s]\n" ] } ], @@ -1163,7 +1193,7 @@ { "data": { "text/plain": [ - ")>" + ")>" ] }, "execution_count": 26, @@ -1172,7 +1202,7 @@ } ], "source": [ - "bdf.serialize(EXAMPLE_DIR + \"/metabolite_to_graph.ttl\")" + "bdf.serialize(f\"{EXAMPLE_DIR}/metabolite_to_graph.ttl\")" ] }, { @@ -1215,17 +1245,17 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": null, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", "text/plain": [ "" ] }, - "execution_count": 33, + "execution_count": 28, "metadata": {}, "output_type": "execute_result" } @@ -1233,7 +1263,9 @@ "source": [ "import py4cytoscape as p4c\n", "\n", - "p4c.notebook_export_show_image(\"image_compound.png\")" + "p4c.notebook_export_show_image(\n", + " f\"{EXAMPLE_DIR}/image_compound.png\", resolution=300, overwrite_file=False\n", + ")" ] }, { @@ -2252,7 +2284,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 31, "metadata": {}, "outputs": [ { @@ -3200,11 +3232,18 @@ "source": [ "graph_obj.count_edge_by_data_source(plot=True)" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { "kernelspec": { - "display_name": "pyBiodatafuse", + "display_name": "pybiodatafuse", "language": "python", "name": "python3" }, @@ -3218,7 +3257,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.12" + "version": "3.10.16" } }, "nbformat": 4, diff --git a/examples/03_dea_workflow.ipynb b/examples/03_dea_workflow.ipynb index d23d3cea..5f1b4ae9 100644 --- a/examples/03_dea_workflow.ipynb +++ b/examples/03_dea_workflow.ipynb @@ -43,8 +43,13 @@ "metadata": {}, "outputs": [], "source": [ - "DATA_DIR = \"./data/dea_workflow\"\n", - "os.makedirs(DATA_DIR, exist_ok=True)" + "# Create directories\n", + "base_dir = os.path.abspath(os.getcwd())\n", + "DATA_DIR = os.path.join(base_dir, \"data\")\n", + "EXAMPLE_DIR = os.path.join(DATA_DIR, \"dea_workflow\")\n", + "\n", + "os.makedirs(DATA_DIR, exist_ok=True)\n", + "os.makedirs(EXAMPLE_DIR, exist_ok=True)" ] }, { @@ -166,7 +171,7 @@ } ], "source": [ - "data_input = data_loader.create_df_from_dea(\"data/dea_example.xls\")\n", + "data_input = data_loader.create_df_from_dea(f\"{DATA_DIR}/dea_example.xls\")\n", "data_input.head()" ] }, @@ -200,8 +205,8 @@ "metadata": {}, "outputs": [], "source": [ - "pickle_path = f\"{DATA_DIR}/DEA_gene_list.pkl\"\n", - "metadata_path = f\"{DATA_DIR}/DEA_gene_list_metadata.pkl\"" + "pickle_path = f\"{EXAMPLE_DIR}/DEA_gene_list.pkl\"\n", + "metadata_path = f\"{EXAMPLE_DIR}/DEA_gene_list_metadata.pkl\"" ] }, { @@ -371,8 +376,8 @@ "metadata": {}, "outputs": [], "source": [ - "kegg_df_path = f\"{DATA_DIR}/kegg_df.pkl\"\n", - "kegg_metadata_path = f\"{DATA_DIR}/kegg_metadata.pkl\"" + "kegg_df_path = f\"{EXAMPLE_DIR}/kegg_df.pkl\"\n", + "kegg_metadata_path = f\"{EXAMPLE_DIR}/kegg_metadata.pkl\"" ] }, { @@ -380,6 +385,13 @@ "execution_count": 8, "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Getting KEGG IDs: 100%|██████████| 18/18 [01:54<00:00, 6.38s/it]\n" + ] + }, { "data": { "text/html": [ @@ -427,7 +439,7 @@ " 0.59097\n", " 239599.0\n", " 0.20273\n", - " [{'pathway_id': nan, 'pathway_label': nan, 'ge...\n", + " [{'pathway_id': nan, 'pathway_label': nan, 'pa...\n", " \n", " \n", " 1\n", @@ -455,7 +467,7 @@ " 0.96160\n", " 254376.0\n", " 0.14795\n", - " [{'pathway_id': nan, 'pathway_label': nan, 'ge...\n", + " [{'pathway_id': nan, 'pathway_label': nan, 'pa...\n", " \n", " \n", " 3\n", @@ -505,9 +517,9 @@ "4 0.08899 0.13960 0.50922 304276.0 0.04013 \n", "\n", " KEGG_pathways \n", - "0 [{'pathway_id': nan, 'pathway_label': nan, 'ge... \n", + "0 [{'pathway_id': nan, 'pathway_label': nan, 'pa... \n", "1 [{'pathway_id': 'path:hsa03008', 'pathway_labe... \n", - "2 [{'pathway_id': nan, 'pathway_label': nan, 'ge... \n", + "2 [{'pathway_id': nan, 'pathway_label': nan, 'pa... \n", "3 [{'pathway_id': 'path:hsa04060', 'pathway_labe... \n", "4 [{'pathway_id': 'path:hsa00220', 'pathway_labe... " ] @@ -543,8 +555,8 @@ "metadata": {}, "outputs": [], "source": [ - "inhibitor_df_path = f\"{DATA_DIR}/inhibitor_df.pkl\"\n", - "inhibitor_metadata_path = f\"{DATA_DIR}/inhibitor_metadata.pkl\"" + "inhibitor_df_path = f\"{EXAMPLE_DIR}/inhibitor_df.pkl\"\n", + "inhibitor_metadata_path = f\"{EXAMPLE_DIR}/inhibitor_metadata.pkl\"" ] }, { @@ -554,6 +566,14 @@ "scrolled": true }, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/var/folders/x2/1tdvwk7x2_n98kzwy7rnt3t00000gn/T/ipykernel_28151/3233610423.py:2: UserWarning: The intermediate_df in MolMeDB annotator should be checked, please create an issue on https://github.com/BioDataFuse/pyBiodatafuse/issues/.\n", + " inhibitor_df, inhibitor_metadata = molmedb.get_gene_compound_inhibitor(bridgedb_df=bridgedb_df)\n" + ] + }, { "data": { "text/html": [ @@ -601,7 +621,7 @@ " 0.59097\n", " 239599.0\n", " 0.20273\n", - " [{'compound_name': nan, 'inchikey': nan, 'smil...\n", + " [{'MolMeDB_compound_name': nan, 'MolMeDB_inchi...\n", " \n", " \n", " 1\n", @@ -615,7 +635,7 @@ " 0.70124\n", " 335289.0\n", " 0.01499\n", - " [{'compound_name': nan, 'inchikey': nan, 'smil...\n", + " [{'MolMeDB_compound_name': nan, 'MolMeDB_inchi...\n", " \n", " \n", " 2\n", @@ -629,7 +649,7 @@ " 0.70124\n", " 335289.0\n", " 0.01499\n", - " [{'compound_name': nan, 'inchikey': nan, 'smil...\n", + " [{'MolMeDB_compound_name': nan, 'MolMeDB_inchi...\n", " \n", " \n", " 3\n", @@ -643,7 +663,7 @@ " 0.70124\n", " 335289.0\n", " 0.01499\n", - " [{'compound_name': nan, 'inchikey': nan, 'smil...\n", + " [{'MolMeDB_compound_name': nan, 'MolMeDB_inchi...\n", " \n", " \n", " 4\n", @@ -657,7 +677,7 @@ " 0.70124\n", " 335289.0\n", " 0.01499\n", - " [{'compound_name': nan, 'inchikey': nan, 'smil...\n", + " [{'MolMeDB_compound_name': nan, 'MolMeDB_inchi...\n", " \n", " \n", "\n", @@ -679,11 +699,11 @@ "4 0.02632 0.05167 0.70124 335289.0 0.01499 \n", "\n", " MolMeDB_transporter_inhibitor \n", - "0 [{'compound_name': nan, 'inchikey': nan, 'smil... \n", - "1 [{'compound_name': nan, 'inchikey': nan, 'smil... \n", - "2 [{'compound_name': nan, 'inchikey': nan, 'smil... \n", - "3 [{'compound_name': nan, 'inchikey': nan, 'smil... \n", - "4 [{'compound_name': nan, 'inchikey': nan, 'smil... " + "0 [{'MolMeDB_compound_name': nan, 'MolMeDB_inchi... \n", + "1 [{'MolMeDB_compound_name': nan, 'MolMeDB_inchi... \n", + "2 [{'MolMeDB_compound_name': nan, 'MolMeDB_inchi... \n", + "3 [{'MolMeDB_compound_name': nan, 'MolMeDB_inchi... \n", + "4 [{'MolMeDB_compound_name': nan, 'MolMeDB_inchi... " ] }, "execution_count": 10, @@ -741,22 +761,13 @@ " identifier.source\n", " target\n", " target.source\n", - " F value_dea_x\n", - " Pr(>F)_dea_x\n", - " FDR(>F)_dea_x\n", - " Log2FC_dea_x\n", - " t.ratio_dea_x\n", - " p.value_dea_x\n", - " ...\n", - " t.ratio_dea_y\n", - " p.value_dea_y\n", - " KEGG_pathways\n", " F value_dea\n", " Pr(>F)_dea\n", " FDR(>F)_dea\n", " Log2FC_dea\n", " t.ratio_dea\n", " p.value_dea\n", + " KEGG_pathways\n", " MolMeDB_transporter_inhibitor\n", " \n", " \n", @@ -773,17 +784,8 @@ " 0.59097\n", " 239599.0\n", " 0.20273\n", - " ...\n", - " 239599.0\n", - " 0.20273\n", - " [{'pathway_id': nan, 'pathway_label': nan, 'ge...\n", - " 169738.0\n", - " 0.12886\n", - " 0.18847\n", - " 0.59097\n", - " 239599.0\n", - " 0.20273\n", - " [{'compound_name': nan, 'inchikey': nan, 'smil...\n", + " [{'pathway_id': nan, 'pathway_label': nan, 'pa...\n", + " [{'MolMeDB_compound_name': nan, 'MolMeDB_inchi...\n", " \n", " \n", " 1\n", @@ -797,17 +799,8 @@ " 0.70124\n", " 335289.0\n", " 0.01499\n", - " ...\n", - " 335289.0\n", - " 0.01499\n", " [{'pathway_id': 'path:hsa03008', 'pathway_labe...\n", - " 250342.0\n", - " 0.02632\n", - " 0.05167\n", - " 0.70124\n", - " 335289.0\n", - " 0.01499\n", - " [{'compound_name': nan, 'inchikey': nan, 'smil...\n", + " [{'MolMeDB_compound_name': nan, 'MolMeDB_inchi...\n", " \n", " \n", " 2\n", @@ -821,17 +814,8 @@ " 0.70124\n", " 335289.0\n", " 0.01499\n", - " ...\n", - " 335289.0\n", - " 0.01499\n", " [{'pathway_id': 'path:hsa03008', 'pathway_labe...\n", - " 250342.0\n", - " 0.02632\n", - " 0.05167\n", - " 0.70124\n", - " 335289.0\n", - " 0.01499\n", - " [{'compound_name': nan, 'inchikey': nan, 'smil...\n", + " [{'MolMeDB_compound_name': nan, 'MolMeDB_inchi...\n", " \n", " \n", " 3\n", @@ -845,21 +829,11 @@ " 0.70124\n", " 335289.0\n", " 0.01499\n", - " ...\n", - " 335289.0\n", - " 0.01499\n", " [{'pathway_id': 'path:hsa03008', 'pathway_labe...\n", - " 250342.0\n", - " 0.02632\n", - " 0.05167\n", - " 0.70124\n", - " 335289.0\n", - " 0.01499\n", - " [{'compound_name': nan, 'inchikey': nan, 'smil...\n", + " [{'MolMeDB_compound_name': nan, 'MolMeDB_inchi...\n", " \n", " \n", "\n", - "

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" + ], + "text/plain": [ + " label value\n", + "compound_id \n", + "CID:5793 US 0\n", + "CID:5793 EP 0\n", + "CID:5793 WO 0\n", + "CID:5793 Others 0\n", + "CID:2244 US 31627\n", + "CID:2244 EP 19821\n", + "CID:2244 WO 12931\n", + "CID:2244 Others 46477" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "patent_df" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Select specific entry to plot\n", + "\n", + "Since these plotting functions are at server expensive, we recomment to only looks at 1 entity summary at time." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'No patent data available to plot.'" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "plot_patent_summary(patent_df, compound_id=\"CID:5793\")" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_patent_summary(patent_df, compound_id=\"CID:2244\", interactive=False)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "pybiodatafuse", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.16" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/examples/BDF_example_SHACL.svg b/examples/BDF_example_SHACL.svg deleted file mode 100644 index 7bc4298d..00000000 --- a/examples/BDF_example_SHACL.svg +++ /dev/null @@ -1,2 +0,0 @@ - -ncit:C172573 (ncit:C172573)sio:010038 (sio:010038)sio:001077 (sio:001077)ncit:C16612 (ncit:C16612)ncit:C43531 (ncit:C43531)schema:WebAPI (schema:WebAPI)void:Dataset (void:Dataset)dcat:Dataset (dcat:Dataset)wp:Interaction (wp:Interaction)aopo:KeyEvent (aopo:KeyEvent)aopo:OrganContext : sio:001262 [0..1] sh:BlankNodeOrIRIncit:C25338 (ncit:C25338)rdf:Property (rdf:Property)rdfs:Class (rdfs:Class)pw:0000001 (pw:0000001)sio:000253 : sio:000750 [0..1] sh:BlankNodeOrIRIdcat:DataService (dcat:DataService)aopo:AOP (aopo:AOP)ncit:C17021 (ncit:C17021)iao:0000013 (iao:0000013)dcat:Catalog (dcat:Catalog)dcterms:creator : foaf:Person [0..1] sh:BlankNodeOrIRIsio:000983 (sio:000983)owl:sameAs [0..1]sio:000230 [0..1]sio:001403 [0..1]dcat:servesDataset [0..1]dcat:accessURL [0..1]dcat:endpointURL [0..1]dcterms:source [0..1]pav:retrievedFrom [0..1]dcat:accessURL [0..1]sio:001403sio:001403rdf:type [0..1]rdfs:domain [0..1]rdfs:range [0..1]sio:000068 [0..1]wp:DirectedInteraction [0..1]wp:Interaction [0..1]wp:Stimulation [0..1]owl:sameAs [0..1]pav:importedFrom [0..1]sio:001403 [0..1]sio:000028 [0..1]dcat:servesDataset [0..1]dcat:endpointURL [0..1]sio:000068 [0..1]wp:Conversion [0..1]wp:DirectedInteraction [0..1]wp:Inhibition [0..1]wp:Interaction [0..1]wp:Stimulation [0..1]wp:TranscriptionTranslation [0..1]example:interactionConversion [0..1]example:interactionDirectedInteraction [0..1]example:interactionInhibition [0..1]example:interactionInteraction [0..1]example:interactionStimulation [0..1]example:interactionTranscriptionTranslation [0..1]sio:000216 [0..1]aopo:has_key_event [0..1]sio:000068 [0..1]wp:Conversion [0..1]wp:DirectedInteraction [0..1]wp:Inhibition [0..1]wp:Interaction [0..1]wp:Stimulation [0..1]wp:TranscriptionTranslation [0..1]rdfs:subClassOf [0..1]dcterms:source [0..1]pav:retrievedFrom [0..1]sio:000628 [0..1]dcterms:identifier [0..1]dcterms:source [0..1]prov:wasDerivedFrom [0..1]sio:000628 [0..1]sio:000216 [0..1] diff --git a/examples/bdf_example.shacl b/examples/bdf_example.shacl deleted file mode 100644 index fcd4afc6..00000000 --- a/examples/bdf_example.shacl +++ /dev/null @@ -1,508 +0,0 @@ -# Note: generated with rdfsolve v0.0.1 (https://github.com/jmillanacosta/rdfsolve) -@prefix aopo: . -@prefix dcat: . -@prefix dcterms: . -@prefix example: . -@prefix foaf: . -@prefix iao: . -@prefix ncit: . -@prefix owl: . -@prefix pav: . -@prefix prov: . -@prefix pw: . -@prefix rdf: . -@prefix rdfs: . -@prefix schema: . -@prefix sh: . -@prefix sio: . -@prefix virtrdf: . -@prefix void: . -@prefix wp: . -@prefix xsd: . - -aopo:AOP a sh:NodeShape ; - sh:closed true ; - sh:description "Class representing aopo_AOP" ; - - sh:property [ sh:class aopo:KeyEvent ; - sh:description "Property aopo:has_key_event" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 0 ; - sh:path aopo:has_key_event ] ; - sh:targetClass aopo:AOP . - -iao:0000013 a sh:NodeShape ; - sh:closed true ; - sh:description "Class representing iao_0000013" ; - - sh:property [ sh:class ncit:C16612 ; - sh:description "Property sio:000628" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 0 ; - sh:path sio:000628 ] ; - sh:targetClass iao:0000013 . - -ncit:C17021 a sh:NodeShape ; - sh:closed true ; - sh:description "Class representing ncit_C_17021" ; - - sh:property [ sh:class ncit:C16612 ; - sh:description "Property wp:Stimulation" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 5 ; - sh:path wp:Stimulation ], - [ sh:class ncit:C16612 ; - sh:description "Property wp:TranscriptionTranslation" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 6 ; - sh:path wp:TranscriptionTranslation ], - [ sh:class wp:Interaction ; - sh:description "Property sio:000068" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 0 ; - sh:path sio:000068 ], - [ sh:class ncit:C16612 ; - sh:description "Property wp:Conversion" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 1 ; - sh:path wp:Conversion ], - [ sh:class ncit:C16612 ; - sh:description "Property wp:Interaction" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 4 ; - sh:path wp:Interaction ], - [ sh:class ncit:C16612 ; - sh:description "Property wp:DirectedInteraction" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 2 ; - sh:path wp:DirectedInteraction ], - [ sh:class ncit:C16612 ; - sh:description "Property wp:Inhibition" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 3 ; - sh:path wp:Inhibition ] ; - sh:targetClass ncit:C17021 . - -ncit:C172573 a sh:NodeShape ; - sh:closed true ; - sh:description "Class representing ncit_C_172573" ; - - sh:property [ sh:class sio:010038 ; - sh:description "Property owl:sameAs" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 0 ; - sh:path owl:sameAs ] ; - sh:targetClass ncit:C172573 . - -pw:0000001 a sh:NodeShape ; - sh:closed true ; - sh:description "Class representing pw_0000001" ; - - sh:property [ sh:class ncit:C16612 ; - sh:description "Property sio:000028" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 0 ; - sh:path sio:000028 ], - [ sh:class sio:000750 ; - sh:description "Property sio:000253" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 1 ; - sh:path sio:000253 ] ; - sh:targetClass pw:0000001 . - -sio:000983 a sh:NodeShape ; - sh:closed true ; - sh:description "Class representing sio_000983" ; - - sh:property [ sh:class ncit:C25338 ; - sh:description "Property sio:000216" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 0 ; - sh:path sio:000216 ], - [ sh:class ncit:C16612 ; - sh:description "Property sio:000628" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 1 ; - sh:path sio:000628 ] ; - sh:targetClass sio:000983 . - -sio:001077 a sh:NodeShape ; - sh:closed true ; - sh:description "Class representing sio_001077" ; - - sh:property [ sh:class ncit:C43531 ; - sh:description "Property sio:001403" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 1 ; - sh:path sio:001403 ], - [ sh:class ncit:C16612 ; - sh:description "Property sio:000230" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 0 ; - sh:path sio:000230 ] ; - sh:targetClass sio:001077 . - -rdf:Property a sh:NodeShape ; - sh:closed true ; - sh:description "Class representing rdf_Property" ; - - sh:property [ sh:class rdfs:Class ; - sh:description "Property rdfs:domain" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 1 ; - sh:path rdfs:domain ], - [ sh:class rdfs:Class ; - sh:description "Property rdf:type" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 0 ; - sh:path rdf:type ], - [ sh:class rdfs:Class ; - sh:description "Property rdfs:range" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 2 ; - sh:path rdfs:range ] ; - sh:targetClass rdf:Property . - -dcat:DataService a sh:NodeShape ; - sh:closed true ; - sh:description "Class representing dcat_Data_Service" ; - - sh:property [ sh:class void:Dataset ; - sh:description "Property dcat:servesDataset" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 1 ; - sh:path dcat:servesDataset ], - [ sh:class schema:WebAPI ; - sh:description "Property dcat:endpointURL" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 0 ; - sh:path dcat:endpointURL ] ; - sh:targetClass dcat:DataService . - -dcat:Dataset a sh:NodeShape ; - sh:closed true ; - sh:description "Class representing dcat_Dataset" ; - - sh:property [ sh:class void:Dataset ; - sh:description "Property dcterms:source" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 0 ; - sh:path dcterms:source ], - [ sh:class void:Dataset ; - sh:description "Property pav:retrievedFrom" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 1 ; - sh:path pav:retrievedFrom ], - [ sh:class schema:WebAPI ; - sh:description "Property dcat:accessURL" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 2 ; - sh:path dcat:accessURL ] ; - sh:targetClass dcat:Dataset . - -aopo:KeyEvent a sh:NodeShape ; - sh:closed true ; - sh:description "Class representing aopo_Key_Event" ; - - sh:property [ sh:class sio:001262 ; - sh:description "Property aopo:OrganContext" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 0 ; - sh:path aopo:OrganContext ] ; - sh:property [ - sh:class sio:010038 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:path sio:001403 - ] ; - sh:property [ - sh:class ncit:C16612; ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:path sio:001403 - ] ; - sh:targetClass aopo:KeyEvent . - -sio:000750 a sh:NodeShape ; - sh:closed true ; - sh:description "Class representing sio_000750" ; - - sh:targetClass sio:000750 . - -sio:001262 a sh:NodeShape ; - sh:closed true ; - sh:description "Class representing sio_001262" ; - - sh:targetClass sio:001262 . - - -dcat:Catalog a sh:NodeShape ; - sh:closed true ; - sh:description "Class representing dcat_Catalog" ; - - sh:property [ sh:class void:Dataset ; - sh:description "Property dcterms:source" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 2 ; - sh:path dcterms:source ], - [ sh:class void:Dataset ; - sh:description "Property prov:wasDerivedFrom" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 3 ; - sh:path prov:wasDerivedFrom ], - [ sh:class foaf:Person ; - sh:description "Property dcterms:creator" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 0 ; - sh:path dcterms:creator ], - [ sh:class dcat:Catalog ; - sh:description "Property dcterms:identifier" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 1 ; - sh:path dcterms:identifier ] ; - sh:targetClass dcat:Catalog . - -foaf:Person a sh:NodeShape ; - sh:closed true ; - sh:description "Class representing foaf_Person" ; - - sh:targetClass foaf:Person . - -ncit:C25338 a sh:NodeShape ; - sh:closed true ; - sh:description "Class representing ncit_C_25338" ; - - sh:targetClass ncit:C25338 . - -ncit:C43531 a sh:NodeShape ; - sh:closed true ; - sh:description "Class representing ncit_C_43531" ; - - sh:targetClass ncit:C43531 . - -sio:010038 a sh:NodeShape ; - sh:closed true ; - sh:description "Class representing sio_010038" ; - - sh:property [ sh:class ncit:C16612 ; - sh:description "Property wp:Interaction" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 4 ; - sh:path wp:Interaction ], - [ sh:class wp:Interaction ; - sh:description "Property sio:000068" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 1 ; - sh:path sio:000068 ], - [ sh:class ncit:C16612 ; - sh:description "Property wp:DirectedInteraction" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 3 ; - sh:path wp:DirectedInteraction ], - [ sh:class ncit:C43531 ; - sh:description "Property sio:001403" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 2 ; - sh:path sio:001403 ], - [ sh:class void:Dataset ; - sh:description "Property pav:importedFrom" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 0 ; - sh:path pav:importedFrom ], - [ sh:class ncit:C16612 ; - sh:description "Property wp:Stimulation" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 5 ; - sh:path wp:Stimulation ], - [ sh:class sio:010038 ; - sh:description "Property owl:sameAs" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 6 ; - sh:path owl:sameAs ] ; - sh:targetClass sio:010038 . - - -schema:WebAPI a sh:NodeShape ; - sh:closed true ; - sh:description "Class representing schema_Web_API" ; - - sh:property [ sh:class void:Dataset ; - sh:description "Property dcat:servesDataset" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 1 ; - sh:path dcat:servesDataset ], - [ sh:class schema:WebAPI ; - sh:description "Property dcat:endpointURL" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 0 ; - sh:path dcat:endpointURL ] ; - sh:targetClass schema:WebAPI . - -wp:Interaction a sh:NodeShape ; - sh:closed true ; - sh:description "Class representing wp_Interaction" ; - - sh:targetClass wp:Interaction . - -void:Dataset a sh:NodeShape ; - sh:closed true ; - sh:description "Class representing void_Dataset" ; - - sh:property [ sh:class void:Dataset ; - sh:description "Property pav:retrievedFrom" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 1 ; - sh:path pav:retrievedFrom ], - [ sh:class schema:WebAPI ; - sh:description "Property dcat:accessURL" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 2 ; - sh:path dcat:accessURL ], - [ sh:class void:Dataset ; - sh:description "Property dcterms:source" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 0 ; - sh:path dcterms:source ] ; - sh:targetClass void:Dataset . - -rdfs:Class a sh:NodeShape ; - sh:closed true ; - sh:description "Class representing rdfs_Class" ; - - sh:property [ sh:class rdfs:Class ; - sh:description "Property rdfs:subClassOf" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 0 ; - sh:path rdfs:subClassOf ] ; - sh:targetClass rdfs:Class . - -ncit:C16612 a sh:NodeShape ; - sh:closed true ; - sh:description "Class representing ncit_C_16612" ; - - sh:property [ sh:class ncit:C16612 ; - sh:description "Property example:interactionTranscriptionTranslation" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 13 ; - sh:path example:interactionTranscriptionTranslation ], - [ sh:class ncit:C16612 ; - sh:description "Property example:interactionDirectedInteraction" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 9 ; - sh:path example:interactionDirectedInteraction ], - [ sh:class ncit:C16612 ; - sh:description "Property example:interactionConversion" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 8 ; - sh:path example:interactionConversion ], - [ sh:class ncit:C16612 ; - sh:description "Property example:interactionStimulation" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 12 ; - sh:path example:interactionStimulation ], - [ sh:class ncit:C16612 ; - sh:description "Property example:interactionInteraction" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 11 ; - sh:path example:interactionInteraction ], - [ sh:class ncit:C16612 ; - sh:description "Property wp:DirectedInteraction" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 3 ; - sh:path wp:DirectedInteraction ], - [ sh:class ncit:C16612 ; - sh:description "Property wp:Inhibition" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 4 ; - sh:path wp:Inhibition ], - [ sh:class wp:Interaction ; - sh:description "Property sio:000068" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 0 ; - sh:path sio:000068 ], - [ sh:class ncit:C25338 ; - sh:description "Property sio:000216" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 1 ; - sh:path sio:000216 ], - [ sh:class ncit:C16612 ; - sh:description "Property wp:Stimulation" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 6 ; - sh:path wp:Stimulation ], - [ sh:class ncit:C16612 ; - sh:description "Property example:interactionInhibition" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 10 ; - sh:path example:interactionInhibition ], - [ sh:class ncit:C16612 ; - sh:description "Property wp:TranscriptionTranslation" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 7 ; - sh:path wp:TranscriptionTranslation ], - [ sh:class ncit:C16612 ; - sh:description "Property wp:Conversion" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 2 ; - sh:path wp:Conversion ], - [ sh:class ncit:C16612 ; - sh:description "Property wp:Interaction" ; - sh:maxCount 1 ; - sh:nodeKind sh:BlankNodeOrIRI ; - sh:order 5 ; - sh:path wp:Interaction ] ; - sh:targetClass ncit:C16612 . - diff --git a/examples/image_compound.png b/examples/data/metabolite_workflow/image_compound.png similarity index 100% rename from examples/image_compound.png rename to examples/data/metabolite_workflow/image_compound.png diff --git a/examples/data/metabolite_workflow/metabolite_to_graph.ttl b/examples/data/metabolite_workflow/metabolite_to_graph.ttl new file mode 100644 index 00000000..6d497d08 --- /dev/null +++ b/examples/data/metabolite_workflow/metabolite_to_graph.ttl @@ -0,0 +1,378 @@ +@prefix aop: . +@prefix aop.events: . +@prefix aopo: . +@prefix cheminf: . +@prefix dcat: . +@prefix dcterms: . +@prefix foaf: . +@prefix orcid: . +@prefix owl: . +@prefix pav: . +@prefix prov: . +@prefix pubchem.compound: . +@prefix rdfs: . +@prefix schema: . +@prefix uberon: . +@prefix void: . +@prefix xsd: . + + a dcat:DataService, + schema:WebAPI ; + rdfs:label "AOP_Wiki_RDF API"^^xsd:string ; + dcat:endpointURL ; + dcat:servesDataset . + + a dcat:DataService, + schema:WebAPI ; + rdfs:label "BridgeDB API"^^xsd:string ; + dcat:endpointURL ; + dcat:servesDataset . + + a dcat:DataService, + schema:WebAPI ; + rdfs:label "KEGG API"^^xsd:string ; + dcat:endpointURL ; + dcat:servesDataset . + + a dcat:DataService, + schema:WebAPI ; + rdfs:label "MolMeDB API"^^xsd:string ; + dcat:endpointURL ; + dcat:servesDataset . + + a dcat:Catalog ; + dcterms:created "2026-02-03T10:11:54.725329+00:00"^^xsd:dateTime ; + dcterms:creator orcid:0000-0002-4166-7093 ; + dcterms:description "Test gene graph"^^xsd:string ; + dcterms:identifier ; + dcterms:source , + , + , + ; + dcterms:title "BDFgene"^^xsd:string, + "BioDataFuse Knowledge Graph"^^xsd:string ; + prov:wasDerivedFrom , + , + , + . + +aop.events:1003 a aopo:KeyEvent ; + rdfs:label "Decreased, Triiodothyronine (T3)"^^xsd:string . + +aop.events:1005 a aopo:KeyEvent ; + rdfs:label "Reduced, Swimming performance"^^xsd:string . + +aop.events:1007 a aopo:KeyEvent ; + rdfs:label "Reduced, Anterior swim bladder inflation"^^xsd:string ; + aopo:OrganContext uberon:0006860 . + +aop.events:1101 a aopo:KeyEvent ; + rdfs:label "Altered, Amphibian metamorphosis"^^xsd:string . + +aop.events:1115 a aopo:KeyEvent ; + rdfs:label "Increase, Reactive oxygen species"^^xsd:string ; + aopo:OrganContext uberon:0000062 . + +aop.events:1172 a aopo:KeyEvent ; + rdfs:label "Increased activation, Nuclear factor kappa B (NF-kB)"^^xsd:string ; + aopo:OrganContext uberon:0000479 . + +aop.events:1174 a aopo:KeyEvent ; + rdfs:label "Activation, NADPH Oxidase"^^xsd:string . + +aop.events:1202 a aopo:KeyEvent ; + rdfs:label "Suppression, IL-2 and IL-4 production"^^xsd:string ; + aopo:OrganContext uberon:0002405 . + +aop.events:1283 a aopo:KeyEvent ; + rdfs:label "Activation, TGF-beta pathway"^^xsd:string . + +aop.events:1365 a aopo:KeyEvent ; + rdfs:label "Increase, Apoptosis"^^xsd:string . + +aop.events:1392 a aopo:KeyEvent ; + rdfs:label "Oxidative Stress "^^xsd:string . + +aop.events:1706 a aopo:KeyEvent ; + rdfs:label "Stimulation, TLR7/8"^^xsd:string . + +aop.events:1707 a aopo:KeyEvent ; + rdfs:label "Increase, IL-23 from matured dendritic cells"^^xsd:string ; + aopo:OrganContext uberon:0002405 . + +aop.events:1708 a aopo:KeyEvent ; + rdfs:label "Th17 cell migration and inflammation induction"^^xsd:string ; + aopo:OrganContext uberon:0002405 . + +aop.events:1709 a aopo:KeyEvent ; + rdfs:label "Psoriatic skin disease"^^xsd:string . + +aop.events:177 a aopo:KeyEvent ; + rdfs:label "Mitochondrial dysfunction"^^xsd:string ; + aopo:OrganContext uberon:0000062 . + +aop.events:1822 a aopo:KeyEvent ; + rdfs:label "Maturation of TNF/iNOS-Producing Dendritic Cells"^^xsd:string . + +aop.events:280 a aopo:KeyEvent ; + rdfs:label "Thyroxine (T4) in neuronal tissue, Decreased "^^xsd:string ; + aopo:OrganContext uberon:0000955 . + +aop.events:351 a aopo:KeyEvent ; + rdfs:label "Increased Mortality"^^xsd:string . + +aop.events:360 a aopo:KeyEvent ; + rdfs:label "Decrease, Population growth rate"^^xsd:string . + +aop.events:402 a aopo:KeyEvent ; + rdfs:label "Cognitive function, decreased "^^xsd:string . + +aop.events:756 a aopo:KeyEvent ; + rdfs:label "Hippocampal gene expression, Altered "^^xsd:string ; + aopo:OrganContext uberon:0000955 . + +aop.events:757 a aopo:KeyEvent ; + rdfs:label "Hippocampal anatomy, Altered "^^xsd:string ; + aopo:OrganContext uberon:0000955 . + +aop.events:758 a aopo:KeyEvent ; + rdfs:label "Hippocampal Physiology, Altered"^^xsd:string ; + aopo:OrganContext uberon:0000955 . + +aop.events:759 a aopo:KeyEvent ; + rdfs:label "Increased, Kidney Failure"^^xsd:string . + +aop.events:957 a aopo:KeyEvent ; + rdfs:label "Binding, Transthyretin in serum"^^xsd:string ; + aopo:OrganContext uberon:0001977 . + +aop.events:958 a aopo:KeyEvent ; + rdfs:label "Displacement, Serum thyroxine (T4) from transthyretin"^^xsd:string . + +aop.events:959 a aopo:KeyEvent ; + rdfs:label "Increased, Free serum thyroxine (T4)"^^xsd:string ; + aopo:OrganContext uberon:0000178 . + +aop.events:960 a aopo:KeyEvent ; + rdfs:label "Increased, Uptake of thyroxine into tissue"^^xsd:string . + +aop.events:961 a aopo:KeyEvent ; + rdfs:label "Increased, Clearance of thyroxine from serum"^^xsd:string ; + aopo:OrganContext uberon:0002107 . + +aop.events:979 a aopo:KeyEvent ; + rdfs:label "Interference, nuclear localization of NFAT"^^xsd:string ; + aopo:OrganContext uberon:0002405 . + +aop.events:980 a aopo:KeyEvent ; + rdfs:label "Inhibition, Calcineurin Activity"^^xsd:string . + +aop.events:981 a aopo:KeyEvent ; + rdfs:label "Reduction, NFAT/AP-1 complex formation"^^xsd:string ; + aopo:OrganContext uberon:0002405 . + +aop.events:984 a aopo:KeyEvent ; + rdfs:label "Impairment, T-cell dependent antibody response"^^xsd:string . + +aop:152 a aopo:AOP ; + rdfs:label "Interference with thyroid serum binding protein transthyretin and subsequent adverse human neurodevelopmental toxicity "^^xsd:string ; + aopo:has_key_event aop.events:280, + aop.events:281, + aop.events:402, + aop.events:756, + aop.events:757, + aop.events:758, + aop.events:957, + aop.events:958, + aop.events:959, + aop.events:960, + aop.events:961 . + +aop:154 a aopo:AOP ; + rdfs:label "Inhibition of Calcineurin Activity Leading to Impaired T-Cell Dependent Antibody Response"^^xsd:string ; + aopo:has_key_event aop.events:1202, + aop.events:979, + aop.events:980, + aop.events:981, + aop.events:984 . + +aop:313 a aopo:AOP ; + rdfs:label "Stimulation of TLR7/8 in dendric cells leading to Psoriatic skin disease"^^xsd:string ; + aopo:has_key_event aop.events:1706, + aop.events:1707, + aop.events:1708, + aop.events:1709, + aop.events:1822 . + +aop:622 a aopo:AOP ; + rdfs:label "Calcineurin inhibitor induced nephrotoxicity leading to kidney failure"^^xsd:string ; + aopo:has_key_event aop.events:1115, + aop.events:1172, + aop.events:1174, + aop.events:1283, + aop.events:1365, + aop.events:1392, + aop.events:177, + aop.events:759 . + +orcid:0000-0002-4166-7093 a foaf:Person, + schema:Person ; + foaf:name "Javier Millan Acosta"^^xsd:string . + +pubchem.compound:100208 a cheminf:SIO_010038 ; + rdfs:label "100208"^^xsd:string ; + pav:importedFrom ; + owl:sameAs pubchem.compound:100208 . + +pubchem.compound:10025195 a cheminf:SIO_010038 ; + rdfs:label "10025195"^^xsd:string ; + pav:importedFrom ; + owl:sameAs pubchem.compound:10025195 . + +pubchem.compound:10040286 a cheminf:SIO_010038 ; + rdfs:label "10040286"^^xsd:string ; + pav:importedFrom ; + owl:sameAs pubchem.compound:10040286 . + +pubchem.compound:10041551 a cheminf:SIO_010038 ; + rdfs:label "10041551"^^xsd:string ; + pav:importedFrom ; + owl:sameAs pubchem.compound:10041551 . + +pubchem.compound:1060 a cheminf:SIO_010038 ; + rdfs:label "1060"^^xsd:string ; + pav:importedFrom ; + owl:sameAs pubchem.compound:1060 . + +pubchem.compound:1172 a cheminf:SIO_010038 ; + rdfs:label "1172"^^xsd:string ; + pav:importedFrom ; + owl:sameAs pubchem.compound:1172 . + +pubchem.compound:159603 a cheminf:SIO_010038 ; + rdfs:label "159603"^^xsd:string ; + pav:importedFrom ; + cheminf:SIO_001403 aop:313 ; + owl:sameAs pubchem.compound:159603 . + +pubchem.compound:21831736 a cheminf:SIO_010038 ; + rdfs:label "21831736"^^xsd:string ; + pav:importedFrom ; + cheminf:SIO_001403 aop:159, + aop:175 ; + owl:sameAs pubchem.compound:21831736 . + +pubchem.compound:445643 a cheminf:SIO_010038 ; + rdfs:label "445643"^^xsd:string ; + pav:importedFrom ; + cheminf:SIO_001403 aop:154, + aop:622 ; + owl:sameAs pubchem.compound:445643 . + +pubchem.compound:5291 a cheminf:SIO_010038 ; + rdfs:label "5291"^^xsd:string ; + pav:importedFrom ; + owl:sameAs pubchem.compound:5291 . + +pubchem.compound:6030 a cheminf:SIO_010038 ; + rdfs:label "6030"^^xsd:string ; + pav:importedFrom ; + owl:sameAs pubchem.compound:6030 . + +pubchem.compound:697993 a cheminf:SIO_010038 ; + rdfs:label "697993"^^xsd:string ; + pav:importedFrom ; + cheminf:SIO_001403 aop:159, + aop:175 ; + owl:sameAs pubchem.compound:697993 . + +pubchem.compound:8571 a cheminf:SIO_010038 ; + rdfs:label "8571"^^xsd:string ; + pav:importedFrom ; + cheminf:SIO_001403 aop:152, + aop:175 ; + owl:sameAs pubchem.compound:8571 . + +aop.events:277 a aopo:KeyEvent ; + rdfs:label "Thyroid hormone synthesis, Decreased"^^xsd:string ; + aopo:OrganContext uberon:0002046 . + +aop.events:279 a aopo:KeyEvent ; + rdfs:label "Thyroperoxidase, Inhibition"^^xsd:string ; + aopo:OrganContext uberon:0005305 . + +aop:159 a aopo:AOP ; + rdfs:label "Thyroperoxidase inhibition leading to increased mortality via reduced anterior swim bladder inflation"^^xsd:string ; + aopo:has_key_event aop.events:1003, + aop.events:1005, + aop.events:1007, + aop.events:277, + aop.events:279, + aop.events:281, + aop.events:351, + aop.events:360 . + +aop.events:281 a aopo:KeyEvent ; + rdfs:label " Thyroxine (T4) in serum, Decreased"^^xsd:string ; + aopo:OrganContext uberon:0001977 . + +aop:175 a aopo:AOP ; + rdfs:label "Thyroperoxidase inhibition leading to altered amphibian metamorphosis"^^xsd:string ; + aopo:has_key_event aop.events:1101, + aop.events:277, + aop.events:279, + aop.events:281 . + + a void:Dataset, + dcat:Dataset ; + rdfs:label "BridgeDB"^^xsd:string ; + dcterms:hasVersion "{'java.version': '11.0.16', 'bridgedb.version': '3.0.25', 'webservice.version': '2.1.7'}"^^xsd:string ; + dcterms:source ; + dcterms:title "BridgeDB Dataset"^^xsd:string ; + pav:retrievedFrom ; + pav:retrievedOn "2026-02-03T11:10:35+00:00"^^xsd:dateTime ; + pav:version "{'java.version': '11.0.16', 'bridgedb.version': '3.0.25', 'webservice.version': '2.1.7'}"^^xsd:string ; + dcat:accessURL ; + dcat:landingPage ; + prov:generatedAtTime "2026-02-03T11:10:35+00:00"^^xsd:dateTime ; + schema:url . + + a void:Dataset, + dcat:Dataset ; + rdfs:label "KEGG"^^xsd:string ; + dcterms:hasVersion "117.0+/02-03"^^xsd:string ; + dcterms:source ; + dcterms:title "KEGG Dataset"^^xsd:string ; + pav:retrievedFrom ; + pav:retrievedOn "2026-02-03T11:11:27+00:00"^^xsd:dateTime ; + pav:version "117.0+/02-03"^^xsd:string ; + dcat:accessURL ; + prov:generatedAtTime "2026-02-03T11:11:27+00:00"^^xsd:dateTime . + + a void:Dataset, + dcat:Dataset ; + rdfs:label "MolMeDB"^^xsd:string ; + dcterms:source ; + dcterms:title "MolMeDB Dataset"^^xsd:string ; + pav:retrievedFrom ; + pav:retrievedOn "2026-02-03T11:10:36+00:00"^^xsd:dateTime ; + void:sparqlEndpoint ; + dcat:accessURL ; + dcat:landingPage ; + prov:generatedAtTime "2026-02-03T11:10:36+00:00"^^xsd:dateTime ; + schema:url . + + a void:Dataset, + dcat:Dataset ; + rdfs:label "AOP_Wiki_RDF"^^xsd:string ; + dcterms:license ; + dcterms:source ; + dcterms:title "AOP_Wiki_RDF Dataset"^^xsd:string ; + pav:retrievedFrom ; + pav:retrievedOn "2026-02-03T11:10:36+00:00"^^xsd:dateTime ; + void:sparqlEndpoint ; + dcat:accessURL ; + dcat:landingPage ; + prov:generatedAtTime "2026-02-03T11:10:36+00:00"^^xsd:dateTime ; + schema:url . + diff --git a/examples/image.png b/examples/image.png deleted file mode 100644 index 0808b15f..00000000 Binary files a/examples/image.png and /dev/null differ diff --git a/examples/plotting.ipynb b/examples/plotting.ipynb deleted file mode 100644 index b32429a1..00000000 --- a/examples/plotting.ipynb +++ /dev/null @@ -1,2019 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Import modules" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import pandas as pd\n", - "\n", - "from pyBiodatafuse import id_mapper\n", - "from pyBiodatafuse.viz.patent_data import _process_data_for_plot, get_patent_data\n", - "from pyBiodatafuse.viz.utils import (\n", - " plot_hbarplot_chart,\n", - " plot_pie_chart,\n", - " plotly_barplot_chart,\n", - " plotly_pie_chart,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "chemicals_of_interest = \"\"\"glucose\n", - "Aspirin\"\"\"\n", - "chem_list = chemicals_of_interest.split(\"\\n\")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "pubchem_df, pubchem_metadata = id_mapper.pubchem_xref(\n", - " identifiers=chem_list, indentifier_type=\"name\"\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 2/2 [00:04<00:00, 2.04s/it]\n" - ] - } - ], - "source": [ - "m = get_patent_data(pubchem_df)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Make data in plotting specific template" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "df = _process_data_for_plot(m)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Select specific entry to plot\n", - "\n", - "Since these plotting functions are at server expensive, we recomment to only looks at 1 entity summary at time." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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cid
5793US125
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" - ], - "text/plain": [ - " label value\n", - "cid \n", - "5793 US 125\n", - "5793 EP 42\n", - "5793 WO 25" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "test = df.loc[5793]\n", - "test" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Plot pie chart" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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E21LyX2RlvjNbiOlscrdT0PMfs8uYlzXXLlHvwLX4Ff5VZpdwW0qGvijLJVfTAXK1MTYH3zS7jAWpvtLG3lF1u7qpVujOJd+t9slKSoYeYFWBw1t7w+Dh2NtKTs/N1aZPzvNAWO0gpMo6hQfwPqds6NcVOXv0t8Z9Bt/AZbPLSJl7W86yPZZndhlpJ6FfgLxMnaKAsuWl1UpXkJU9/za7jJTbde4Mm2y8Fr/InUeJV83z7W+mdKoqip03iu8hzq6RN9CSCbNLSYu9zWeotula/M2BKrNLmBWlQ19e4Hbcufj1vItrrNfsMtJGw6D+TDNryDO7lJTyah7W+9fcdps//OEPZGdnE49/cb7F6OgoHo+H2traW7ZtbGxE0zQuXboEQFNTE4888gj5+fn4fD7uuusufvOb35BIzL1xUDpSHpdGeaFzWvvN7ivk935kdhlppxtJvt78MWU2Wou/3r8ar377cai6ujpGR0f58MMPJx87duwYpaWlnDhxgnA4PPl4Q0MDK1euZO3atfz973+npqaGsrIyGhoaaG1t5Qc/+AEvvPAC3/72tzGMud26TOnQA1SXOGNAL18fY1Pf/5hdxqJxJ+I8ce4CJbo9RvW3BKrvuE1VVRVLly6lsbFx8rHGxkYef/xxVq9ezfHjx295vK6ujrGxMZ555hkee+wxXnnlFbZs2UJ5eTlPP/00f/7zn/nb3/7GX/7ylznVqnzo8zN1ltp9nb1hsC/yFlps3OxKFpU3GuHJjy9Zfi3+6ozlFHryZrVtXV0dDQ1frKFoaGigtraWmpqaycdDoRAnTpygrq6Ot956i2AwyI9+9KMpz/Xoo49SWVnJq6++Oqd6lQ89wMal9m7t69yn8A1eMbsMU/jD4+xvvWbptfj3ZG2c9bZ1dXW89957xONxRkZGOHXqFDU1NezevXuyB/D+++8TiUSoq6ujrW3ioqfr16+f9vmqq6snt5ktS4R+Wa7LttN35e5eyrqPmV2GqbLGhtl/sZuABdfil3gKWZlROuvta2trGRsb4+TJkxw7dozKykqWLFlCTU3N5HF9Y2Mja9asYeXKL+b853rcfjuWSdJdy+zX2mdoMXYOvYFm2HN6bi7yhvrZ3z6Az2Jr8bfPoZUHWLdu3eSAXENDAzU1NQAsW7aMFStW0NTURENDA3v27AGgsrISgJaWlmmfr6WlZXKb2bJM6MvyXLa7Nv7DxjFc40Gzy1BGUbCHb1wfx6NZY8am1FNEhW/ui2vq6upobGyksbHxlqm63bt3c+TIET744APq6uoAeOihhygoKODXv/71lOd5/fXX+eSTT3jqqafm9PqWSZGmadyzwlqtwO1sdV8ir/e02WUoZ2lPB493xS2xFr8mZxuaNveFYXV1dbz77rucPn16sqUHqKmp4eWXXyYajU6GPhAI8PLLL/Paa6/xve99j+bmZq5evcof//hHDh48yIEDB/jmN785p9fXjFQeLCyCdy6EuTFk7e5wgT7K1/r/N1osZHYpyrq0ci2HCxMkUXP3rPCt4tGCmjtvOI2rV6+yevVqqqurb+m2t7e3U15eTlVVFa2trbf8zrFjx/jlL3/J+++/TzgcpqKigu9+97s8++yzuFxz+4C0XOgHxpP841xI0V3hzjTD4Jux/0PGULvZpSivZU0VR3LDd95wkbnQ+V/Fj5PntuZdfC3Tvf9cfqbOmiJrHPNNp879kQR+ltZfvsCeMfXm8LcEqi0beLBg6AHuLvPgtmDla9w9LHf49NxcbWn7mJ0KrcX36xncl73J7DIWxILRmbjZ5ZYyaw3qZWgx7h98A81Iml2K5exoOcs2Rdbi35e9WcmbUs6FJUMPUF3iptBCJ+zUJ/+NK9RvdhmWtfvcGe5Kmrskt8Cdy+bMuc2Jq8g6qfkSXdO4v9zLPGZMFt09novk9jWbXYblPXjmDJUm3R5bR+PhvK+ga5aNzCRL/wUFARcbStU+U69QH2FDz1tml2ELGgZfPd1MuZa36K+9I3sTS71LFv1108HSoQfYvNxDdoaazb1mGOwLvYkWV2/ayapcRpJHz3zM8kVci7/UU8SOrLsW7fXSzfKhd+sau9dloCuY+73uD/EOXzO7DNvxJOI8ca6NYj3902Yezc1X83fZolv/OVv8JYUBF1sVO0V3rbubpd3vmV2GbWVEw+w/f4UCPZDW16nL3W7pOfnp2CL0AOtL3CzPVeN8bT9RmZ5bBP7QGPsvdJCj+dPy/Ot8K/mvzIq0PLeZbBN6TdPYuSYDv8f8fn690YgeGjC7DEfIHh1i/6VeAlpGSp83oPvZl3dfSp9TFbYJPYDPo7FrrbnH99vdbWT3nTOvAAfKHwryZPsQGSm6PbaGRn3+Tvy69S7qMRu2Cj1AaY6Le1eZc3xfrA9T3fu2Ka/tdEuC3XyjI5SStfh7c3ewKmNZCqpSk+1CD1BZ7KG6ZHEX5ehGkj2hN9HikUV9XfGFZd0dPNadwLWA3Xp71kY2Bax/1t3t2DL0ANtWelmas3h/3l7XSbzD1xft9cT0VnVc5ZF+17xuj13lK+eB7K1pqEottg29rmnUrPOR40v/AX6Fu5PSnqa0v46YnYr2izw0PLfj8eXeYh7O3zmvK+FYjW1DD+B1azxY5Uvrve4ztQg7Bt5As9a1SGxv46VWasdnN7+e78rhsYJa3JoaU77pZuvQA2Rl6Oyr9uFL01Tew4kG9PBQWp5bLMzWC+e4P3L703X9uo9vFO617Uj9dGwfeoAcn86+Kh/eFH+Q73C3kh08n9onFSl1//lmtsbzpv2ZR3PzeEGd7c64uxNHhB4mLrP1YJUvZXfBLXYNUdnzTmqeTKRVzdkzbPzSWnyv5uHJggdZZpOVc3PhmNADFGW5eDAFLb5Okr1jb6IloqkpTKSVBuxrPkPFZ2vxMzQvBwr3sTyj2NzCTGK5q+GmwsB4krcvhAnH5venP6y/T0n3+ymuSqRbwuXifzZvYVvRDoo9hWaXYxpHtfSfy8/UqV/vI2seo/rV7g6Ku4/feUOhHJcnwCPZ9zo68ODQ0MPE4F79Bh+5/tkHP6CF2dZ/BM2yV913sKwi+Mp3J747nGNDDxNX1a1f76d0lmfu1Sf+hR4ZTnNVIuXyV8D9B8GvzqW0zeTIY/ovSxoGH34apbU7PuM297tbqOg8sohViZRYtR027APdGSfezIZ1bxWTQrqmce+qDPL9OifaoyS/9DFYqg+yrueoOcWJ+dHdcNfXoMzaN6ZIBwn9TSqKPeT6dRovRiZH9l0kqBs/ItNzVpKZD/ccgJxSsytRknTvpxGKJnn3coTO4ST1epOM1lvJknVw9xPgSc8ltOxAQj8DwzBo7xxg1Zk/oCWtfWtsR9B0qNgF63ZhiTugmEhCfydDnXD6/8Jon9mViJnklMKmRyFXuvOzIaGfjUQcWo/C1Q/MrkTcTHdBxW5Y8xXQHT37PCcS+rkY7IBzRyZaf2GuvOUTrXu28xbMLJSEfq4MA66dggsNEB03uxrncXmgshZW75Bj93mS0M9XLAQXGuHT/0x8EIj00jQo2wKVNeBz1vr3VJPQL9RwF5x7EwbknnVpU1IF1XvkvPkUkdCnSs9FuPiuhD+VClZC9V7ILzO7EluR0KdasH0i/H2Xza7EunJKJ7rxJfa+/rxZJPTpMngDLh6D7jazK7EGTYOSalh970QLL9JGQp9uw93Q/iHc+Bjk7jdTeXyw4m4o3w7+21+5VqSGhH6xJGLQ2QLXz0DwqtnVmC+7GFZtm1gF50rNjSfF7EjozTA+MBH+680QctA187OKYOmGiS85qcY0EnozGQb0fwo9n0DvJRjpMbui1AsUwrLPg+7Mq8+qRkKvktDwRPh7PoHgFYhbcA2/xzdxeaqCVbBkDeSUmF2R+BIJvaqSiYk5//5rE+f6D3epeSiQkQUFn4W8YOVEay6nxypNQm8l0RAMd8JQ18SHwFAXhAYnPiDSzeOHrMKJ7vrn37OLIVCQ/tcWKSWht4PIGIRHIDx86/fI6MSsQTIBRnLi+83/bRgTI+du72dfGeD1gzcA3syJ74GCiZB7M83+K0WKSOiFcBi58oAQDiOhF8JhJPRiWgcPHkTTtClf9fX1AJSXl08+FggE2Lp1K3/9619NrlrMhoRezKi+vp7Ozs5bvl599dXJnz///PN0dnZy6tQptm/fzre+9S2amppMrFjMhoRezCgjI4PS0tJbvvLz8yd/np2dTWlpKZWVlfzud7/D7/dz+PBhEysWsyGhFynhdrvxeDxEoxY8i9BhJPRiRv/4xz/Iysq65etXv/rVlO2i0SgvvvgiQ0ND7Nmzx4RKxVzIPL2Y1sGDB+no6OD3v//9LY8XFBRQUFBAeXk5nZ2deDwewuEwWVlZPPfccxw6dMikisVsyQ0sxYwCgQDr1q2b8ec//vGPOXjwIFlZWZSUlKDJOfeWIKEX81ZUVHTbDwWhJgm9mFEkEqGrq+uWx9xuN0VFcilqK5PQixm9+eabLF269JbHqqqqaG1tNakikQoykCeEw8iUnRAOI6EXwmEk9EI4jIReCIeR0AvhMBJ6IRxGQi+Ew0johXAYCb0QDiOhF8JhJPRCOIyEXgiHkdAL4TASeiEcRkIvhMNI6IVwGAm9EA4joRfCYST0QjjM/wfKnyjZjCyiswAAAABJRU5ErkJggg==", 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"anchor": "y", - "domain": [ - 0, - 1 - ], - "title": { - "text": "Label" - } - }, - "yaxis": { - "anchor": "x", - "domain": [ - 0, - 1 - ], - "title": { - "text": "Value" - } - } - } - } - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plotly_barplot_chart(test, fig_size=(8, 5))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "biodatafuse", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.12" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/setup.cfg b/setup.cfg index 00d8afee..eb94c2f6 100644 --- a/setup.cfg +++ b/setup.cfg @@ -3,7 +3,7 @@ ########################## [metadata] name = pybiodatafuse -version = 1.3.0 +version = 1.3.1-dev description = A python package for integrating data from multiple resources long_description = file: README.md long_description_content_type = text/markdown diff --git a/src/pyBiodatafuse/analyzer/explorer/patent.py b/src/pyBiodatafuse/analyzer/explorer/patent.py index 3f25bb14..3b5fc82e 100644 --- a/src/pyBiodatafuse/analyzer/explorer/patent.py +++ b/src/pyBiodatafuse/analyzer/explorer/patent.py @@ -6,16 +6,47 @@ """ import time +from typing import Literal, Union import pandas as pd import requests from tqdm import tqdm - +import plotly.express as px +import matplotlib.pyplot as plt +from pyBiodatafuse.analyzer.utils import ( + plot_hbarplot_chart, + plot_pie_chart, + plotly_barplot_chart, + plotly_pie_chart, +) from pyBiodatafuse.constants import PATENT_INPUT_ID from pyBiodatafuse.utils import get_identifier_of_interest -def get_patent_from_pubchem(bridgedb_df: pd.DataFrame) -> dict: +def process_patent_data(patent_dict: dict) -> pd.DataFrame: + """Process patent data into a DataFrame. + + :param patent_dict: A dictionary with the patent data + :returns: A DataFrame with the processed patent data + """ + data_df = [] + + for cmpd_id, patent_set in patent_dict.items(): + for patent_country, patents in patent_set.items(): + data_df.append( + { + "compound_id": cmpd_id, + "label": patent_country, + "value": len(patents), + } + ) + + data_df = pd.DataFrame(data_df) + data_df.set_index("compound_id", inplace=True) + return data_df + + +def get_patent_from_pubchem(bridgedb_df: pd.DataFrame) -> pd.DataFrame: """Get patent data summary from PubChem compounds. The output is the following: {CID: ["US: X", "EP: X", "WO: X", "Others: X"]} @@ -27,7 +58,7 @@ def get_patent_from_pubchem(bridgedb_df: pd.DataFrame) -> dict: cid_pat_dict = {} - # Neeed some pre-processing: + # TODO: Neeed some pre-processing: # 1. Remove duplicates (WO-03078408-A1 against WO03078408A1, Not classic Patent offices such as AR, AU againts WO) # 2. Adding Granted, non-granted patent counts @@ -37,36 +68,106 @@ def get_patent_from_pubchem(bridgedb_df: pd.DataFrame) -> dict: patent_detail_dict = {"US": set(), "EP": set(), "WO": set(), "Others": set()} # type: ignore[var-annotated] try: - patent_dict = requests.get( - f"https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/cid/{cid}/xrefs/PatentID/JSON" - ).json() + url = f"https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/cid/{cid.split(':')[1]}/xrefs/PatentID/TXT" + patent_list = requests.get(url) except requests.exceptions.ConnectionError: - cid_pat_dict[cid] = "" + cid_pat_dict[cid] = patent_detail_dict + continue + + if patent_list.status_code != 200 or patent_list.text.strip() == "": + cid_pat_dict[cid] = patent_detail_dict continue - if "Fault" in patent_dict.keys(): # No patents found - cid_pat_dict[cid] = "" - else: - patents = patent_dict["InformationList"]["Information"][0]["PatentID"] - - for patent in patents: - p = patent.replace("-", "") - if p.startswith("US"): - patent_detail_dict["US"].add(p) - elif p.startswith("EP"): - patent_detail_dict["EP"].add(p) - elif p.startswith("WO"): - patent_detail_dict["WO"].add(p) - else: - patent_detail_dict["Others"].add(p) + patent_df = pd.DataFrame(patent_list.text.splitlines(), columns=["PatentID"]) + for patent in patent_df["PatentID"].tolist(): + p = patent.replace("-", "") + if p.startswith("US"): + patent_detail_dict["US"].add(p) + elif p.startswith("EP"): + patent_detail_dict["EP"].add(p) + elif p.startswith("WO"): + patent_detail_dict["WO"].add(p) + else: + patent_detail_dict["Others"].add(p) c += 1 if c == 100: time.sleep(3) c = 0 - - # cid_pat_dict[cid] = [ - # f"{k}: {len(v)}" for k, v in patent_detail_dict.items() if len(v) > 0 - # ] # type: ignore[assignment] - - return cid_pat_dict + cid_pat_dict[cid] = patent_detail_dict + + return process_patent_data(cid_pat_dict) + + +def plot_patent_summary( + data_df: pd.DataFrame, + compound_id: str = "", + fig_size: tuple = (10, 5), + interactive: bool = True, + plot_style: Literal["bar", "pie"] = "bar", +) -> Union[px.Figure, plt.Figure, str]: + """Plot patent summary data. + + :param data_df: A dataframe with two columns: "label" and "value" + :param compound_id: The compound identifier for the title + :param fig_size: A tuple with the size of the figure + :param interactive: Whether to create an interactive plotly plot or a static matplotlib plot + :param plot_style: The style of the plot, either "bar" or "pie" + :returns: A plotly or matplotlib plot depending on the interactive parameter + """ + if compound_id == "": + return "Please provide a compound identifier for the title." + + if compound_id not in data_df.index: + return f"{compound_id} not found in the patent data." + + patent_df = data_df.loc[compound_id] + + # Drop entries with zero values + patent_df = patent_df[patent_df["value"] > 0] + + if patent_df.empty: + return "No patent data available to plot." + + if plot_style not in ["bar", "pie"]: + return f"Plot style {plot_style} not recognized. Please use 'bar' or 'pie'." + + if plot_style == "pie" and interactive: + fig = plotly_pie_chart( + template_df=patent_df, + fig_size=fig_size, + fig_title=f"Patent summary for {compound_id}", + ) + fig.update_layout(title_text=f"Patent summary for {compound_id}", showlegend=True) + + return fig + + elif plot_style == "bar" and interactive: + fig = plotly_barplot_chart( + template_df=patent_df, + x_label="Number of Patents", + y_label="Patent Offices", + fig_size=fig_size, + fig_title=f"Patent summary for {compound_id}", + ) + fig.update_layout(title_text=f"Patent summary for {compound_id}", showlegend=False) + + return fig + + elif plot_style == "pie" and not interactive: + return plot_pie_chart( + template_df=patent_df, + fig_size=fig_size, + fig_title=f"Patent summary for {compound_id}", + ) + + elif plot_style == "bar" and not interactive: + return plot_hbarplot_chart( + template_df=patent_df, + x_label="Number of Patents", + y_label="Patent Offices", + fig_size=fig_size, + fig_title=f"Patent summary for {compound_id}", + ) + + return "No patent data available to plot." diff --git a/src/pyBiodatafuse/analyzer/utils.py b/src/pyBiodatafuse/analyzer/utils.py index b37110fa..37495c72 100644 --- a/src/pyBiodatafuse/analyzer/utils.py +++ b/src/pyBiodatafuse/analyzer/utils.py @@ -13,16 +13,19 @@ def plot_pie_chart( template_df: pd.DataFrame, fig_size: tuple = (10, 10), + fig_title: str = "Pie plot", ) -> plt: """Plot a pie chart. :param template_df: A dataframe with two columns: "label" and "value" :param fig_size: A tuple with the size of the figure + :param fig_title: The title of the figure :returns: A pie chart """ plt.figure(figsize=fig_size) colors = sns.color_palette("pastel")[: len(template_df)] plt.pie(template_df["value"], labels=template_df["label"], colors=colors) + plt.title(fig_title, size=14) return plt.show() @@ -31,6 +34,7 @@ def plot_hbarplot_chart( x_label: str = "Label", y_label: str = "Value", fig_size: tuple = (10, 10), + fig_title: str = "Bar plot", ) -> plt: """Plot a bar plot. @@ -38,6 +42,7 @@ def plot_hbarplot_chart( :param x_label: The x-axis label :param y_label: The y-axis label :param fig_size: A tuple with the size of the figure + :param fig_title: The title of the figure :returns: A bar plot """ plt.figure(figsize=fig_size) @@ -56,6 +61,7 @@ def plot_hbarplot_chart( plt.ylabel(y_label, size=12) plt.xticks(fontsize=10) plt.yticks(fontsize=10) + plt.title(fig_title, size=14) plt.tight_layout() @@ -68,15 +74,18 @@ def plot_hbarplot_chart( def plotly_pie_chart( template_df: pd.DataFrame, fig_size: tuple = (10, 10), + fig_title: str = "Pie plot", ) -> px: """Plot a pie chart using Plotly. :param template_df: A dataframe with two columns: "label" and "value" :param fig_size: A tuple with the size of the figure + :param fig_title: The title of the figure :returns: A plotly pie chart """ fig = px.pie(template_df, values="value", names="label", width=fig_size[0], height=fig_size[1]) - return fig.show() + fig.update_layout(title_text=fig_title) + return fig def plotly_barplot_chart( @@ -84,6 +93,7 @@ def plotly_barplot_chart( x_label: str = "Label", y_label: str = "Value", fig_size: tuple = (10, 10), + fig_title: str = "Bar plot", ) -> px: """Plot a bar plot using Plotly. @@ -91,10 +101,12 @@ def plotly_barplot_chart( :param x_label: The x-axis label :param y_label: The y-axis label :param fig_size: A tuple with the size of the figure + :param fig_title: The title of the figure :returns: A bar plot """ fig = px.bar(template_df, x="value", y="label").update_layout( xaxis_title=x_label, yaxis_title=y_label, width=fig_size[0], height=fig_size[1] ) + fig.update_layout(title_text=fig_title) - return fig.show() + return fig diff --git a/src/pyBiodatafuse/graph/rdf/graphdb.py b/src/pyBiodatafuse/graph/rdf/graphdb.py index 1f717e6e..6d47ff5a 100644 --- a/src/pyBiodatafuse/graph/rdf/graphdb.py +++ b/src/pyBiodatafuse/graph/rdf/graphdb.py @@ -83,7 +83,9 @@ def create_repository( graphdb:enable-literal-index "true" ; ] ]. - """.format(repository_name=repository_name) + """.format( + repository_name=repository_name + ) # Save the configuration content to a temporary file with tempfile.NamedTemporaryFile(delete=False, suffix=".ttl") as temp_file: temp_file.write(config_content.encode("utf-8")) diff --git a/src/pyBiodatafuse/graph/rdf/nodes/protein_protein.py b/src/pyBiodatafuse/graph/rdf/nodes/protein_protein.py index 70f7733c..3f65e0c2 100644 --- a/src/pyBiodatafuse/graph/rdf/nodes/protein_protein.py +++ b/src/pyBiodatafuse/graph/rdf/nodes/protein_protein.py @@ -12,12 +12,7 @@ from rdflib.namespace import XSD import pyBiodatafuse.constants as Cons -from pyBiodatafuse.graph.rdf.nodes.base import ( - add_triples, - add_type, - create_node, - safe_get, -) +from pyBiodatafuse.graph.rdf.nodes.base import add_triples, add_type, create_node, safe_get def add_ppi_data(g: Graph, gene_node: URIRef, entry: dict) -> Optional[URIRef]: diff --git a/src/pyBiodatafuse/version.py b/src/pyBiodatafuse/version.py index 1a1325b0..40e64d46 100644 --- a/src/pyBiodatafuse/version.py +++ b/src/pyBiodatafuse/version.py @@ -14,7 +14,7 @@ "get_git_hash", ] -VERSION = "1.3.0" +VERSION = "1.3.1-dev" def get_git_hash() -> str: