From cabb406b9fbeed79e29f5b557d9f43d13f57a8e1 Mon Sep 17 00:00:00 2001 From: Ismail Ugur Bayindir Date: Wed, 1 Nov 2023 13:13:54 +0000 Subject: [PATCH] Changes for MVP-4632 (#56) * Made changes for MVP-4632 * Updated walkthrough.ipynb --- README.md | 4 + pandasaurus_cxg/anndata_analyzer.py | 2 +- .../graph_generator/graph_generator.py | 6 + pandasaurus_cxg/utils/exceptions.py | 12 +- poetry.lock | 1343 +++++++++-------- pyproject.toml | 6 +- test/graph_generator/test_graph_generator.py | 41 +- test/test_anndata_enricher.py | 22 +- walkthrough.ipynb | 350 ++--- 9 files changed, 933 insertions(+), 853 deletions(-) diff --git a/README.md b/README.md index c375095..39e4e12 100644 --- a/README.md +++ b/README.md @@ -71,6 +71,10 @@ More examples and detailed explanation can be found in jupyter notebook given in https://github.com/INCATools/pandasaurus_cxg/blob/main/walkthrough.ipynb +## Library Documentation + +https://incatools.github.io/pandasaurus_cxg/ + ## Roadmap https://github.com/INCATools/pandasaurus_cxg/blob/main/ROADMAP.md diff --git a/pandasaurus_cxg/anndata_analyzer.py b/pandasaurus_cxg/anndata_analyzer.py index 4efd856..10f6a53 100644 --- a/pandasaurus_cxg/anndata_analyzer.py +++ b/pandasaurus_cxg/anndata_analyzer.py @@ -174,7 +174,7 @@ def enriched_co_annotation_report(self, disease: Optional[str] = None): def _enrich_co_annotation(enricher: AnndataEnricher): enriched_df = enricher.enricher.enriched_df if enriched_df.empty: - return pd.DataFrame() + return enriched_df return enriched_df[enriched_df["o"].isin(enricher.seed_list)][["s_label", "o_label"]] def _filter_data_and_drop_duplicates(self, field_name_1, field_name_2, disease): diff --git a/pandasaurus_cxg/graph_generator/graph_generator.py b/pandasaurus_cxg/graph_generator/graph_generator.py index e72e2d5..4aa6599 100644 --- a/pandasaurus_cxg/graph_generator/graph_generator.py +++ b/pandasaurus_cxg/graph_generator/graph_generator.py @@ -10,6 +10,7 @@ from rdflib.plugins.sparql import prepareQuery from pandasaurus_cxg.enrichment_analysis import ( + AnndataAnalyzer, AnndataEnricher, AnndataEnrichmentAnalyzer, ) @@ -29,6 +30,7 @@ ) from pandasaurus_cxg.utils.exceptions import ( InvalidGraphFormat, + MissingAnalysisProcess, MissingEnrichmentProcess, ) from pandasaurus_cxg.utils.logging_config import configure_logger @@ -55,6 +57,10 @@ def __init__( """ # TODO need to think about how to handle the requirement of enrichment and co_annotation_analysis methods self.ea = enrichment_analyzer + if self.ea.analyzer_manager.report_df.empty: + analysis_methods = [i for i in dir(AnndataAnalyzer) if "_report" in i] + analysis_methods.sort() + raise MissingAnalysisProcess(analysis_methods) # TODO need to handle invalid keys. We also need to discuss about keeping the keys param. 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testing = ["pytest (>=7.4.0)"] tooling = ["black (>=23.7.0)", "pyright (>=1.1.325)", "ruff (>=0.0.287)"] tooling-extras = ["pyaml (>=23.7.0)", "pypandoc-binary (>=1.11)", "pytest (>=7.4.0)"] +[[package]] +name = "virtualenv" +version = "20.24.6" +description = "Virtual Python Environment builder" +optional = false +python-versions = ">=3.7" +files = [ + {file = "virtualenv-20.24.6-py3-none-any.whl", hash = "sha256:520d056652454c5098a00c0f073611ccbea4c79089331f60bf9d7ba247bb7381"}, + {file = "virtualenv-20.24.6.tar.gz", hash = "sha256:02ece4f56fbf939dbbc33c0715159951d6bf14aaf5457b092e4548e1382455af"}, +] + +[package.dependencies] +distlib = ">=0.3.7,<1" +filelock = ">=3.12.2,<4" +platformdirs = ">=3.9.1,<4" + +[package.extras] +docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"] +test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.4)", "pytest-env (>=0.8.2)", "pytest-freezer (>=0.4.8)", "pytest-mock (>=3.11.1)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=68)", "time-machine (>=2.10)"] + [[package]] name = "watchdog" version = "3.0.0" @@ -4028,4 +4071,4 @@ docs = ["sphinx", "sphinx-copybutton", "sphinx-rtd-theme"] [metadata] lock-version = "2.0" python-versions = "^3.9" -content-hash = "91353e5ca366e34e70e64396cb7ecd99d5c5d5b9c544718e604c52535800fabb" +content-hash = "ce98ced34046e3442f80b0d7eb6231ded58d18b8a2bbb59a40bc872cd5791c70" diff --git a/pyproject.toml b/pyproject.toml index b45d532..0128345 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "pandasaurus-cxg" -version = "0.1.5" +version = "0.1.6" description = "Ontology enrichment tool for CxG standard AnnData files." authors = ["Ugur Bayindir "] license = "http://www.apache.org/licenses/LICENSE-2.0" @@ -12,9 +12,9 @@ python = "^3.9" pandas = "^2.0.2" anndata = "^0.9.1" rdflib = "^6.3.2" -oaklib = "^0.5.13" +oaklib = "0.5.13" matplotlib = "^3.7.2" -pandasaurus = "^0.3.5" +pandasaurus = "^0.3.6" pygraphviz = "^1.11" sphinx = { version = "^7.2.6", optional = true } sphinx-rtd-theme = { version = "^1.3.0", optional = true } diff --git a/test/graph_generator/test_graph_generator.py b/test/graph_generator/test_graph_generator.py index 0ef93a5..2ceffb5 100644 --- a/test/graph_generator/test_graph_generator.py +++ b/test/graph_generator/test_graph_generator.py @@ -9,6 +9,7 @@ from pandasaurus_cxg.graph_generator.graph_predicates import CONSIST_OF from pandasaurus_cxg.utils.exceptions import ( InvalidGraphFormat, + MissingAnalysisProcess, MissingEnrichmentProcess, ) @@ -53,33 +54,45 @@ def graph_generator_instance_for_kidney(enrichment_analyzer_instance_for_kidney_ return GraphGenerator(ea) -def test_graph_generator_init(enrichment_analyzer_instance_for_immune_data): +def test_graph_generator_init_missing_enrichment_process(enrichment_analyzer_instance_for_immune_data): ea = enrichment_analyzer_instance_for_immune_data + ea.co_annotation_report() + with pytest.raises(MissingEnrichmentProcess) as exc_info: GraphGenerator(ea) exception = exc_info.value expected_message = ( - "Any of the following enrichment methods from AnndataEnricher must be used before using " - "enriched_rdf_graph method: contextual_slim_enrichment, full_slim_enrichment, " - "minimal_slim_enrichment, simple_enrichment" + "Any of the following enrichment methods from AnndataEnricher must be used first; " + "contextual_slim_enrichment, full_slim_enrichment, minimal_slim_enrichment, " + "simple_enrichment" ) assert isinstance(exception, MissingEnrichmentProcess) assert exception.args[0] == expected_message + +def test_graph_generator_init_missing_analysis_process(enrichment_analyzer_instance_for_immune_data): + ea = enrichment_analyzer_instance_for_immune_data ea.enricher_manager.simple_enrichment() - ea.co_annotation_report() - # keys = ["author_cell_type", "cell_type"] - # graph_generator = GraphGenerator(ea, keys) - # - # assert graph_generator.ea == ea - # assert graph_generator.df.equals(ea.analyzer_manager.report_df[keys]) - # assert graph_generator.cell_type_dict == {} - # assert graph_generator.ns == Namespace("http://example.org/") - # assert graph_generator.graph is not None - # assert graph_generator.label_priority is None + with pytest.raises(MissingAnalysisProcess) as exc_info: + GraphGenerator(ea) + + exception = exc_info.value + expected_message = ( + "Any of the following analysis methods from AnndataAnalyser must be used first; " + "co_annotation_report, enriched_co_annotation_report" + ) + + assert isinstance(exception, MissingAnalysisProcess) + assert exception.args[0] == expected_message + + +def test_graph_generator_init_with_valid_input(enrichment_analyzer_instance_for_immune_data): + ea = enrichment_analyzer_instance_for_immune_data + ea.enricher_manager.simple_enrichment() + ea.co_annotation_report() graph_generator = GraphGenerator(ea) diff --git a/test/test_anndata_enricher.py b/test/test_anndata_enricher.py index a7faf01..bfb2f20 100644 --- a/test/test_anndata_enricher.py +++ b/test/test_anndata_enricher.py @@ -268,9 +268,9 @@ def test_filter_anndata_with_enriched_cell_type(sample_immune_data): exception = exc_info.value expected_message = ( - "Any of the following enrichment methods from AnndataEnricher must be used before using " - "enriched_rdf_graph method: contextual_slim_enrichment, full_slim_enrichment, " - "minimal_slim_enrichment, simple_enrichment" + "Any of the following enrichment methods from AnndataEnricher must be used first; " + "contextual_slim_enrichment, full_slim_enrichment, minimal_slim_enrichment, " + "simple_enrichment" ) assert isinstance(exception, MissingEnrichmentProcess) @@ -307,9 +307,9 @@ def test_annotate_anndata_with_cell_type(sample_immune_data): exception = exc_info.value expected_message = ( - "Any of the following enrichment methods from AnndataEnricher must be used before using " - "enriched_rdf_graph method: contextual_slim_enrichment, full_slim_enrichment, " - "minimal_slim_enrichment, simple_enrichment" + "Any of the following enrichment methods from AnndataEnricher must be used first; " + "contextual_slim_enrichment, full_slim_enrichment, minimal_slim_enrichment, " + "simple_enrichment" ) assert isinstance(exception, MissingEnrichmentProcess) @@ -369,10 +369,10 @@ def test_annotate_anndata_with_cell_type(sample_immune_data): def test_set_enricher_property_list(sample_immune_data): enricher = AnndataEnricher(sample_immune_data) - assert enricher.enricher._Query__enrichment_property_list == ["rdfs:subClassOf"] + assert enricher.enricher._enrichment_property_list == ["rdfs:subClassOf"] enricher.set_enricher_property_list(["rdfs:subClassOf", "BFO:0000050"]) - assert enricher.enricher._Query__enrichment_property_list == ["rdfs:subClassOf", "BFO:0000050"] + assert enricher.enricher._enrichment_property_list == ["rdfs:subClassOf", "BFO:0000050"] def test_validate_slim_list(mocker, sample_immune_data, slim_data): @@ -442,9 +442,9 @@ def test_check_subclass_relationships(sample_immune_data): exception = exc_info.value expected_message = ( - "Any of the following enrichment methods from AnndataEnricher must be used before using " - "enriched_rdf_graph method: contextual_slim_enrichment, full_slim_enrichment, " - "minimal_slim_enrichment, simple_enrichment" + "Any of the following enrichment methods from AnndataEnricher must be used first; " + "contextual_slim_enrichment, full_slim_enrichment, minimal_slim_enrichment, " + "simple_enrichment" ) assert isinstance(exception, MissingEnrichmentProcess) diff --git a/walkthrough.ipynb b/walkthrough.ipynb index 19adf08..85c5b69 100644 --- a/walkthrough.ipynb +++ b/walkthrough.ipynb @@ -313,7 +313,7 @@ } ], "source": [ - "ade._anndata.obs[0:5]" + "ade.anndata.obs[0:5]" ] }, { @@ -653,48 +653,48 @@ " CL:0000798\n", " gamma-delta T cell\n", " rdfs:subClassOf\n", - " CL:0000084\n", - " T cell\n", + " CL:0000842\n", + " mononuclear cell\n", " \n", " \n", " 8\n", " CL:0000798\n", " gamma-delta T cell\n", " rdfs:subClassOf\n", - " CL:0000842\n", - " mononuclear cell\n", + " CL:0000084\n", + " T cell\n", " \n", " \n", " 9\n", " CL:0000809\n", " double-positive, alpha-beta thymocyte\n", " rdfs:subClassOf\n", - " CL:0002420\n", - " immature T cell\n", + " CL:0000084\n", + " T cell\n", " \n", " \n", " 10\n", " CL:0000809\n", " double-positive, alpha-beta thymocyte\n", " rdfs:subClassOf\n", - " CL:0000842\n", - " mononuclear cell\n", + " CL:0000789\n", + " alpha-beta T cell\n", " \n", " \n", " 11\n", " CL:0000809\n", " double-positive, alpha-beta thymocyte\n", " rdfs:subClassOf\n", - " CL:0000789\n", - " alpha-beta T cell\n", + " CL:0000842\n", + " mononuclear cell\n", " \n", " \n", " 12\n", " CL:0000809\n", " double-positive, alpha-beta thymocyte\n", " rdfs:subClassOf\n", - " CL:0000084\n", - " T cell\n", + " CL:0002420\n", + " immature T cell\n", " \n", " \n", " 13\n", @@ -733,128 +733,128 @@ " CL:0000895\n", " naive thymus-derived CD4-positive, alpha-beta ...\n", " rdfs:subClassOf\n", - " CL:0000084\n", - " T cell\n", + " CL:0000842\n", + " mononuclear cell\n", " \n", " \n", " 18\n", " CL:0000895\n", " naive thymus-derived CD4-positive, alpha-beta ...\n", " rdfs:subClassOf\n", - " CL:0000789\n", - " alpha-beta T cell\n", + " CL:0000084\n", + " T cell\n", " \n", " \n", " 19\n", " CL:0000895\n", " naive thymus-derived CD4-positive, alpha-beta ...\n", " rdfs:subClassOf\n", - " CL:0000842\n", - " mononuclear cell\n", + " CL:0000789\n", + " alpha-beta T cell\n", " \n", " \n", " 20\n", " CL:0000897\n", " CD4-positive, alpha-beta memory T cell\n", " rdfs:subClassOf\n", - " CL:0000813\n", - " memory T cell\n", + " CL:0000084\n", + " T cell\n", " \n", " \n", " 21\n", " CL:0000897\n", " CD4-positive, alpha-beta memory T cell\n", " rdfs:subClassOf\n", - " CL:0000842\n", - " mononuclear cell\n", + " CL:0000789\n", + " alpha-beta T cell\n", " \n", " \n", " 22\n", " CL:0000897\n", " CD4-positive, alpha-beta memory T cell\n", " rdfs:subClassOf\n", - " CL:0000789\n", - " alpha-beta T cell\n", + " CL:0000813\n", + " memory T cell\n", " \n", " \n", " 23\n", " CL:0000897\n", " CD4-positive, alpha-beta memory T cell\n", " rdfs:subClassOf\n", - " CL:0000084\n", - " T cell\n", + " CL:0000842\n", + " mononuclear cell\n", " \n", " \n", " 24\n", " CL:0000900\n", " naive thymus-derived CD8-positive, alpha-beta ...\n", " rdfs:subClassOf\n", - " CL:0000789\n", - " alpha-beta T cell\n", + " CL:0000084\n", + " T cell\n", " \n", " \n", " 25\n", " CL:0000900\n", " naive thymus-derived CD8-positive, alpha-beta ...\n", " rdfs:subClassOf\n", - " CL:0000842\n", - " mononuclear cell\n", + " CL:0000789\n", + " alpha-beta T cell\n", " \n", " \n", " 26\n", " CL:0000900\n", " naive thymus-derived CD8-positive, alpha-beta ...\n", " rdfs:subClassOf\n", - " CL:0000084\n", - " T cell\n", + " CL:0000842\n", + " mononuclear cell\n", " \n", " \n", " 27\n", " CL:0000909\n", " CD8-positive, alpha-beta memory T cell\n", " rdfs:subClassOf\n", - " CL:0000813\n", - " memory T cell\n", + " CL:0000842\n", + " mononuclear cell\n", " \n", " \n", " 28\n", " CL:0000909\n", " CD8-positive, alpha-beta memory T cell\n", " rdfs:subClassOf\n", - " CL:0000084\n", - " T cell\n", + " CL:0000789\n", + " alpha-beta T cell\n", " \n", " \n", " 29\n", " CL:0000909\n", " CD8-positive, alpha-beta memory T cell\n", " rdfs:subClassOf\n", - " CL:0000842\n", - " mononuclear cell\n", + " CL:0000084\n", + " T cell\n", " \n", " \n", " 30\n", " CL:0000909\n", " CD8-positive, alpha-beta memory T cell\n", " rdfs:subClassOf\n", - " CL:0000789\n", - " alpha-beta T cell\n", + " CL:0000813\n", + " memory T cell\n", " \n", " \n", " 31\n", " CL:0000940\n", " mucosal invariant T cell\n", " rdfs:subClassOf\n", - " CL:0000842\n", - " mononuclear cell\n", + " CL:0000789\n", + " alpha-beta T cell\n", " \n", " \n", " 32\n", " CL:0000940\n", " mucosal invariant T cell\n", " rdfs:subClassOf\n", - " CL:0000789\n", - " alpha-beta T cell\n", + " CL:0000842\n", + " mononuclear cell\n", " \n", " \n", " 33\n", @@ -893,16 +893,16 @@ " CL:0002489\n", " double negative thymocyte\n", " rdfs:subClassOf\n", - " CL:0000842\n", - " mononuclear cell\n", + " CL:0000084\n", + " T cell\n", " \n", " \n", " 38\n", " CL:0002489\n", " double negative thymocyte\n", " rdfs:subClassOf\n", - " CL:0000084\n", - " T cell\n", + " CL:0000842\n", + " mononuclear cell\n", " \n", " \n", " 39\n", @@ -967,38 +967,38 @@ "4 rdfs:subClassOf CL:0000842 mononuclear cell \n", "5 rdfs:subClassOf CL:0000145 professional antigen presenting cell \n", "6 rdfs:subClassOf CL:0000236 B cell \n", - "7 rdfs:subClassOf CL:0000084 T cell \n", - "8 rdfs:subClassOf CL:0000842 mononuclear cell \n", - "9 rdfs:subClassOf CL:0002420 immature T cell \n", - "10 rdfs:subClassOf CL:0000842 mononuclear cell \n", - "11 rdfs:subClassOf CL:0000789 alpha-beta T cell \n", - "12 rdfs:subClassOf CL:0000084 T cell \n", + "7 rdfs:subClassOf CL:0000842 mononuclear cell \n", + "8 rdfs:subClassOf CL:0000084 T cell \n", + "9 rdfs:subClassOf CL:0000084 T cell \n", + "10 rdfs:subClassOf CL:0000789 alpha-beta T cell \n", + "11 rdfs:subClassOf CL:0000842 mononuclear cell \n", + "12 rdfs:subClassOf CL:0002420 immature T cell \n", "13 rdfs:subClassOf CL:0000084 T cell \n", "14 rdfs:subClassOf CL:0000842 mononuclear cell \n", "15 rdfs:subClassOf CL:0000084 T cell \n", "16 rdfs:subClassOf CL:0000842 mononuclear cell \n", - "17 rdfs:subClassOf CL:0000084 T cell \n", - "18 rdfs:subClassOf CL:0000789 alpha-beta T cell \n", - "19 rdfs:subClassOf CL:0000842 mononuclear cell \n", - "20 rdfs:subClassOf CL:0000813 memory T cell \n", - "21 rdfs:subClassOf CL:0000842 mononuclear cell \n", - "22 rdfs:subClassOf CL:0000789 alpha-beta T cell \n", - "23 rdfs:subClassOf CL:0000084 T cell \n", - "24 rdfs:subClassOf CL:0000789 alpha-beta T cell \n", - "25 rdfs:subClassOf CL:0000842 mononuclear cell \n", - "26 rdfs:subClassOf CL:0000084 T cell \n", - "27 rdfs:subClassOf CL:0000813 memory T cell \n", - "28 rdfs:subClassOf CL:0000084 T cell \n", - "29 rdfs:subClassOf CL:0000842 mononuclear cell \n", - "30 rdfs:subClassOf CL:0000789 alpha-beta T cell \n", - "31 rdfs:subClassOf CL:0000842 mononuclear cell \n", - "32 rdfs:subClassOf CL:0000789 alpha-beta T cell \n", + "17 rdfs:subClassOf CL:0000842 mononuclear cell \n", + "18 rdfs:subClassOf CL:0000084 T cell \n", + "19 rdfs:subClassOf CL:0000789 alpha-beta T cell \n", + "20 rdfs:subClassOf CL:0000084 T cell \n", + "21 rdfs:subClassOf CL:0000789 alpha-beta T cell \n", + "22 rdfs:subClassOf CL:0000813 memory T cell \n", + "23 rdfs:subClassOf CL:0000842 mononuclear cell \n", + "24 rdfs:subClassOf CL:0000084 T cell \n", + "25 rdfs:subClassOf CL:0000789 alpha-beta T cell \n", + "26 rdfs:subClassOf CL:0000842 mononuclear cell \n", + "27 rdfs:subClassOf CL:0000842 mononuclear cell \n", + "28 rdfs:subClassOf CL:0000789 alpha-beta T cell \n", + "29 rdfs:subClassOf CL:0000084 T cell \n", + "30 rdfs:subClassOf CL:0000813 memory T cell \n", + "31 rdfs:subClassOf CL:0000789 alpha-beta T cell \n", + "32 rdfs:subClassOf CL:0000842 mononuclear cell \n", "33 rdfs:subClassOf CL:0000084 T cell \n", "34 rdfs:subClassOf CL:0000145 professional antigen presenting cell \n", "35 rdfs:subClassOf CL:0000236 B cell \n", "36 rdfs:subClassOf CL:0000842 mononuclear cell \n", - "37 rdfs:subClassOf CL:0000842 mononuclear cell \n", - "38 rdfs:subClassOf CL:0000084 T cell \n", + "37 rdfs:subClassOf CL:0000084 T cell \n", + "38 rdfs:subClassOf CL:0000842 mononuclear cell \n", "39 rdfs:subClassOf CL:0002420 immature T cell " ] }, @@ -1087,32 +1087,32 @@ " CL:0000084\n", " T cell\n", " rdfs:subClassOf\n", - " CL:0000842\n", - " mononuclear cell\n", + " CL:0000542\n", + " lymphocyte\n", " \n", " \n", " 1\n", " CL:0000084\n", " T cell\n", " rdfs:subClassOf\n", - " CL:0000542\n", - " lymphocyte\n", + " CL:0000842\n", + " mononuclear cell\n", " \n", " \n", " 2\n", " CL:0000787\n", " memory B cell\n", " rdfs:subClassOf\n", - " CL:0000785\n", - " mature B cell\n", + " CL:0000145\n", + " professional antigen presenting cell\n", " \n", " \n", " 3\n", " CL:0000787\n", " memory B cell\n", " rdfs:subClassOf\n", - " CL:0001201\n", - " B cell, CD19-positive\n", + " CL:0001200\n", + " lymphocyte of B lineage, CD19-positive\n", " \n", " \n", " 4\n", @@ -1128,18 +1128,18 @@ ], "text/plain": [ " s s_label p o \\\n", - "0 CL:0000084 T cell rdfs:subClassOf CL:0000842 \n", - "1 CL:0000084 T cell rdfs:subClassOf CL:0000542 \n", - "2 CL:0000787 memory B cell rdfs:subClassOf CL:0000785 \n", - "3 CL:0000787 memory B cell rdfs:subClassOf CL:0001201 \n", + "0 CL:0000084 T cell rdfs:subClassOf CL:0000542 \n", + "1 CL:0000084 T cell rdfs:subClassOf CL:0000842 \n", + "2 CL:0000787 memory B cell rdfs:subClassOf CL:0000145 \n", + "3 CL:0000787 memory B cell rdfs:subClassOf CL:0001200 \n", "4 CL:0000787 memory B cell rdfs:subClassOf CL:0001201 \n", "\n", - " o_label \n", - "0 mononuclear cell \n", - "1 lymphocyte \n", - "2 mature B cell \n", - "3 B cell, CD19-positive \n", - "4 B cell, CD19-positive " + " o_label \n", + "0 lymphocyte \n", + "1 mononuclear cell \n", + "2 professional antigen presenting cell \n", + "3 lymphocyte of B lineage, CD19-positive \n", + "4 B cell, CD19-positive " ] }, "execution_count": 8, @@ -1226,8 +1226,8 @@ " CL:0000653\n", " podocyte\n", " rdfs:subClassOf\n", - " CL:1000510\n", - " kidney glomerular epithelial cell\n", + " CL:1000449\n", + " epithelial cell of nephron\n", " \n", " \n", " 2\n", @@ -1242,16 +1242,16 @@ " CL:0000653\n", " podocyte\n", " rdfs:subClassOf\n", - " CL:1000450\n", - " epithelial cell of glomerular capsule\n", + " CL:1000510\n", + " kidney glomerular epithelial cell\n", " \n", " \n", " 4\n", " CL:0000653\n", " podocyte\n", " rdfs:subClassOf\n", - " CL:1000449\n", - " epithelial cell of nephron\n", + " CL:1000612\n", + " kidney corpuscule cell\n", " \n", " \n", " 5\n", @@ -1266,32 +1266,32 @@ " CL:0000653\n", " podocyte\n", " rdfs:subClassOf\n", - " CL:0002584\n", - " renal cortical epithelial cell\n", + " CL:1000497\n", + " kidney cell\n", " \n", " \n", " 7\n", " CL:0000653\n", " podocyte\n", " rdfs:subClassOf\n", - " CL:1000746\n", - " glomerular cell\n", + " CL:0002518\n", + " kidney epithelial cell\n", " \n", " \n", " 8\n", " CL:0000653\n", " podocyte\n", " rdfs:subClassOf\n", - " CL:1000612\n", - " kidney corpuscule cell\n", + " CL:0002584\n", + " renal cortical epithelial cell\n", " \n", " \n", " 9\n", " CL:0000653\n", " podocyte\n", " rdfs:subClassOf\n", - " CL:1000497\n", - " kidney cell\n", + " CL:1000746\n", + " glomerular cell\n", " \n", " \n", " 10\n", @@ -1306,72 +1306,72 @@ " CL:0000653\n", " podocyte\n", " rdfs:subClassOf\n", - " CL:0002518\n", - " kidney epithelial cell\n", + " CL:1000746\n", + " glomerular cell\n", " \n", " \n", " 12\n", " CL:0000653\n", " podocyte\n", " rdfs:subClassOf\n", - " CL:1000746\n", - " glomerular cell\n", + " CL:1000612\n", + " kidney corpuscule cell\n", " \n", " \n", " 13\n", " CL:0000653\n", " podocyte\n", " rdfs:subClassOf\n", - " CL:1000612\n", - " kidney corpuscule cell\n", + " CL:1000510\n", + " kidney glomerular epithelial cell\n", " \n", " \n", " 14\n", " CL:0000653\n", " podocyte\n", " rdfs:subClassOf\n", - " CL:1000510\n", - " kidney glomerular epithelial cell\n", + " CL:1000450\n", + " epithelial cell of glomerular capsule\n", " \n", " \n", " 15\n", " CL:0002306\n", " epithelial cell of proximal tubule\n", " rdfs:subClassOf\n", - " CL:0002584\n", - " renal cortical epithelial cell\n", + " CL:1000507\n", + " kidney tubule cell\n", " \n", " \n", " 16\n", " CL:0002306\n", " epithelial cell of proximal tubule\n", " rdfs:subClassOf\n", - " CL:1000615\n", - " kidney cortex tubule cell\n", + " CL:1000494\n", + " nephron tubule epithelial cell\n", " \n", " \n", " 17\n", " CL:0002306\n", " epithelial cell of proximal tubule\n", " rdfs:subClassOf\n", - " CL:0002681\n", - " kidney cortical cell\n", + " CL:1000449\n", + " epithelial cell of nephron\n", " \n", " \n", " 18\n", " CL:0002306\n", " epithelial cell of proximal tubule\n", " rdfs:subClassOf\n", - " CL:0002681\n", - " kidney cortical cell\n", + " CL:0002584\n", + " renal cortical epithelial cell\n", " \n", " \n", " 19\n", " CL:0002306\n", " epithelial cell of proximal tubule\n", " rdfs:subClassOf\n", - " CL:0002584\n", - " renal cortical epithelial cell\n", + " CL:0002681\n", + " kidney cortical cell\n", " \n", " \n", "\n", @@ -1402,25 +1402,25 @@ "\n", " o o_label \n", "0 CL:0002584 renal cortical epithelial cell \n", - "1 CL:1000510 kidney glomerular epithelial cell \n", + "1 CL:1000449 epithelial cell of nephron \n", "2 CL:1000450 epithelial cell of glomerular capsule \n", - "3 CL:1000450 epithelial cell of glomerular capsule \n", - "4 CL:1000449 epithelial cell of nephron \n", + "3 CL:1000510 kidney glomerular epithelial cell \n", + "4 CL:1000612 kidney corpuscule cell \n", "5 CL:0002681 kidney cortical cell \n", - "6 CL:0002584 renal cortical epithelial cell \n", - "7 CL:1000746 glomerular cell \n", - "8 CL:1000612 kidney corpuscule cell \n", - "9 CL:1000497 kidney cell \n", + "6 CL:1000497 kidney cell \n", + "7 CL:0002518 kidney epithelial cell \n", + "8 CL:0002584 renal cortical epithelial cell \n", + "9 CL:1000746 glomerular cell \n", "10 CL:0002681 kidney cortical cell \n", - "11 CL:0002518 kidney epithelial cell \n", - "12 CL:1000746 glomerular cell \n", - "13 CL:1000612 kidney corpuscule cell \n", - "14 CL:1000510 kidney glomerular epithelial cell \n", - "15 CL:0002584 renal cortical epithelial cell \n", - "16 CL:1000615 kidney cortex tubule cell \n", - "17 CL:0002681 kidney cortical cell \n", - "18 CL:0002681 kidney cortical cell \n", - "19 CL:0002584 renal cortical epithelial cell " + "11 CL:1000746 glomerular cell \n", + "12 CL:1000612 kidney corpuscule cell \n", + "13 CL:1000510 kidney glomerular epithelial cell \n", + "14 CL:1000450 epithelial cell of glomerular capsule \n", + "15 CL:1000507 kidney tubule cell \n", + "16 CL:1000494 nephron tubule epithelial cell \n", + "17 CL:1000449 epithelial cell of nephron \n", + "18 CL:0002584 renal cortical epithelial cell \n", + "19 CL:0002681 kidney cortical cell " ] }, "execution_count": 10, @@ -2090,7 +2090,8 @@ "metadata": {}, "outputs": [], "source": [ - "aea = AnndataEnrichmentAnalyzer(\"test/data/modified_human_kidney.h5ad\")" + "cell_type_list=['subclass.full', 'subclass.l3', 'subclass.l2', 'subclass.l1', 'class', 'author_cell_type']\n", + "aea = AnndataEnrichmentAnalyzer(\"test/data/human_kidney.h5ad\", author_cell_type_list=cell_type_list)" ] }, { @@ -2143,16 +2144,16 @@ " CL:0000653\n", " podocyte\n", " rdfs:subClassOf\n", - " CL:1000449\n", - " epithelial cell of nephron\n", + " CL:0002518\n", + " kidney epithelial cell\n", " \n", " \n", " 1\n", " CL:0000653\n", " podocyte\n", " rdfs:subClassOf\n", - " CL:1000510\n", - " kidney glomerular epithelial cell\n", + " CL:1000746\n", + " glomerular cell\n", " \n", " \n", " 2\n", @@ -2167,16 +2168,16 @@ " CL:0000653\n", " podocyte\n", " rdfs:subClassOf\n", - " CL:1000746\n", - " glomerular cell\n", + " CL:1000510\n", + " kidney glomerular epithelial cell\n", " \n", " \n", " 4\n", " CL:0000653\n", " podocyte\n", " rdfs:subClassOf\n", - " CL:0002584\n", - " renal cortical epithelial cell\n", + " CL:1000450\n", + " epithelial cell of glomerular capsule\n", " \n", " \n", " ...\n", @@ -2191,24 +2192,24 @@ " CL:1001432\n", " kidney collecting duct intercalated cell\n", " rdfs:subClassOf\n", - " CL:1000449\n", - " epithelial cell of nephron\n", + " CL:1000454\n", + " kidney collecting duct epithelial cell\n", " \n", " \n", " 133\n", " CL:1001432\n", " kidney collecting duct intercalated cell\n", " rdfs:subClassOf\n", - " CL:0005010\n", - " renal intercalated cell\n", + " CL:1000497\n", + " kidney cell\n", " \n", " \n", " 134\n", " CL:1001432\n", " kidney collecting duct intercalated cell\n", " rdfs:subClassOf\n", - " CL:1000497\n", - " kidney cell\n", + " CL:0002518\n", + " kidney epithelial cell\n", " \n", " \n", " 135\n", @@ -2223,8 +2224,8 @@ " CL:1001432\n", " kidney collecting duct intercalated cell\n", " rdfs:subClassOf\n", - " CL:0002518\n", - " kidney epithelial cell\n", + " CL:0005010\n", + " renal intercalated cell\n", " \n", " \n", "\n", @@ -2245,18 +2246,18 @@ "135 CL:1001432 kidney collecting duct intercalated cell rdfs:subClassOf \n", "136 CL:1001432 kidney collecting duct intercalated cell rdfs:subClassOf \n", "\n", - " o o_label \n", - "0 CL:1000449 epithelial cell of nephron \n", - "1 CL:1000510 kidney glomerular epithelial cell \n", - "2 CL:1000612 kidney corpuscule cell \n", - "3 CL:1000746 glomerular cell \n", - "4 CL:0002584 renal cortical epithelial cell \n", - ".. ... ... \n", - "132 CL:1000449 epithelial cell of nephron \n", - "133 CL:0005010 renal intercalated cell \n", - "134 CL:1000497 kidney cell \n", - "135 CL:1001225 kidney collecting duct cell \n", - "136 CL:0002518 kidney epithelial cell \n", + " o o_label \n", + "0 CL:0002518 kidney epithelial cell \n", + "1 CL:1000746 glomerular cell \n", + "2 CL:1000612 kidney corpuscule cell \n", + "3 CL:1000510 kidney glomerular epithelial cell \n", + "4 CL:1000450 epithelial cell of glomerular capsule \n", + ".. ... ... \n", + "132 CL:1000454 kidney collecting duct epithelial cell \n", + "133 CL:1000497 kidney cell \n", + "134 CL:0002518 kidney epithelial cell \n", + "135 CL:1001225 kidney collecting duct cell \n", + "136 CL:0005010 renal intercalated cell \n", "\n", "[137 rows x 5 columns]" ] @@ -2511,7 +2512,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -2522,13 +2523,18 @@ ], "source": [ "gg.visualize_rdf_graph(\n", - " [\n", - " \"http://example.org/dbbb13f3-8c47-4310-89d2-d2fae21f6ff3\",\n", - " ],\n", + " node_selector={\"property\": \"label\", \"value\": \"Cortical Collecting Duct Intercalated Cell Type A\"},\n", " predicate=None,\n", " file_path=\"kidney_new.ttl\",\n", ")" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": {