From 49345df8df13d08de566932f4894aad27b7133f3 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Max=20H=C3=A4u=C3=9Fler?= <83341109+haeussma@users.noreply.github.com> Date: Thu, 7 Mar 2024 14:06:33 +0100 Subject: [PATCH] Fix incomplete read (#47) * added logging, bumped version * fixed logging in container * implemented new parser for ncbi * added abstract parser ABC * added chunk loading * added examples --- examples/alignments/test_pairwise.ipynb | 72 +- examples/networks/test.ipynb | 5922 ++++++++++++----------- logging.conf | 33 + pyeed/containers/abstract_container.py | 37 +- pyeed/core/proteininfo.py | 18 +- pyeed/ncbi/seq_io.py | 555 ++- pyeed/parsers/__init__.py | 0 pyeed/parsers/abstractparser.py | 287 ++ pyeed/parsers/parser_test.ipynb | 97 + pyproject.toml | 5 +- 10 files changed, 3770 insertions(+), 3256 deletions(-) create mode 100644 logging.conf create mode 100644 pyeed/parsers/__init__.py create mode 100644 pyeed/parsers/abstractparser.py create mode 100644 pyeed/parsers/parser_test.ipynb diff --git a/examples/alignments/test_pairwise.ipynb b/examples/alignments/test_pairwise.ipynb index 6f3edfe0..c3b0bd9a 100644 --- a/examples/alignments/test_pairwise.ipynb +++ b/examples/alignments/test_pairwise.ipynb @@ -16,7 +16,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -28,7 +28,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -36,6 +36,34 @@ "ald2 = ProteinInfo.from_ncbi(\"AAN14384.1\")" ] }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/max/miniconda3/envs/pye/lib/python3.10/site-packages/sdRDM/base/datamodel.py:322: UserWarning: No 'URL' and 'Commit' specified. This model might not be re-usable.\n", + " warnings.warn(\n" + ] + }, + { + "data": { + "text/plain": [ + "'{\\n \"id\": \"proteininfo0\",\\n \"source_id\": \"NP_001287541.1\",\\n \"name\": \"aldolase 1, isoform M\",\\n \"sequence\": \"MTTYFNYPSKELQDELREIAQKIVAPGKGILAADESGPTMGKRLQDIGVENTEDNRRAYRQLLFSTDPKLAENISGVILFHETLYQKADDGTPFAEILKKKGIILGIKVDKGVVPLFGSEDEVTTQGLDDLAARCAQYKKDGCDFAKWRCVLKIGKNTPSYQSILENANVLARYASICQSQRIVPIVEPEVLPDGDHDLDRAQKVTETVLAAVYKALSDHHVYLEGTLLKPNMVTAGQSAKKNTPEEIALATVQALRRTVPAAVTGVTFLSGGQSEEEATVNLSAINNVPLIRPWALTFSYGRALQASVLRAWAGKKENIAAGQNELLKRAKANGDAAQGKYVAGSAGAGSGSLFVANHAY\",\\n \"organism\": {\\n \"id\": \"organism0\",\\n \"name\": \"Drosophila melanogaster\",\\n \"taxonomy_id\": \"taxon:7227\",\\n \"domain\": \"Eukaryota\",\\n \"kingdom\": \"Metazoa\",\\n \"phylum\": \"Arthropoda\",\\n \"tax_class\": \"Insecta\",\\n \"order\": \"Diptera\",\\n \"family\": \"Drosophilidae\",\\n \"genus\": \"Drosophila\",\\n \"species\": \"melanogaster\"\\n },\\n \"regions\": [\\n {\\n \"id\": \"proteinregion0\",\\n \"name\": \"Glycolytic\",\\n \"spans\": [\\n {\\n \"id\": \"span0\",\\n \"start\": 14,\\n \"end\": 361\\n }\\n ],\\n \"note\": \"Fructose-bisphosphate aldolase class-I; pfam00274\",\\n \"cross_reference\": \"CDD:425574\"\\n }\\n ],\\n \"sites\": [\\n {\\n \"id\": \"site0\",\\n \"name\": \"active\",\\n \"type\": \"active\",\\n \"positions\": [\\n 33,\\n 34,\\n 35,\\n 38,\\n 107,\\n 146,\\n 148,\\n 187,\\n 229,\\n 269,\\n 270,\\n 271,\\n 299,\\n 301,\\n 302\\n ],\\n \"cross_ref\": \"CDD:188635\"\\n },\\n {\\n \"id\": \"site1\",\\n \"name\": \"intersubunit interface [polypeptide binding]\",\\n \"type\": \"unannotated\",\\n \"positions\": [\\n 110,\\n 161,\\n 164,\\n 165,\\n 168,\\n 172,\\n 175,\\n 203,\\n 207,\\n 210,\\n 217,\\n 218,\\n 220,\\n 224,\\n 256,\\n 257,\\n 259\\n ],\\n \"cross_ref\": \"CDD:188635\"\\n },\\n {\\n \"id\": \"site2\",\\n \"name\": \"catalytic residue [active]\",\\n \"type\": \"active\",\\n \"positions\": [\\n 229\\n ],\\n \"cross_ref\": \"CDD:188635\"\\n }\\n ],\\n \"coding_sequence_ref\": {\\n \"id\": \"NM_001300612.1\",\\n \"spans\": [\\n {\\n \"id\": \"span1\",\\n \"start\": 278,\\n \"end\": 1363\\n }\\n ],\\n \"type\": \"coding sequence\"\\n },\\n \"ec_number\": \"4.1.2.13\",\\n \"mol_weight\": 38916.0\\n}'" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ald1.json()" + ] + }, { "cell_type": "code", "execution_count": 8, @@ -66,6 +94,44 @@ "source": [ "## BLASTP" ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'TaxId': '9606', 'ScientificName': 'Homo sapiens', 'OtherNames': {'Misnomer': [], 'CommonName': [], 'Synonym': [], 'Misspelling': [], 'EquivalentName': [], 'Anamorph': [], 'GenbankAnamorph': [], 'Name': [{'ClassCDE': 'authority', 'DispName': 'Homo sapiens Linnaeus, 1758'}, {'ClassCDE': 'misspelling', 'DispName': 'Home sapiens'}, {'ClassCDE': 'misspelling', 'DispName': 'Homo sampiens'}, {'ClassCDE': 'misspelling', 'DispName': 'Homo sapeins'}, {'ClassCDE': 'misspelling', 'DispName': 'Homo sapian'}, {'ClassCDE': 'misspelling', 'DispName': 'Homo sapians'}, {'ClassCDE': 'misspelling', 'DispName': 'Homo sapien'}, {'ClassCDE': 'misspelling', 'DispName': 'Homo sapience'}, {'ClassCDE': 'misspelling', 'DispName': 'Homo sapiense'}, {'ClassCDE': 'misspelling', 'DispName': 'Homo sapients'}, {'ClassCDE': 'misspelling', 'DispName': 'Homo sapines'}, {'ClassCDE': 'misspelling', 'DispName': 'Homo spaiens'}, {'ClassCDE': 'misspelling', 'DispName': 'Homo spiens'}, {'ClassCDE': 'misspelling', 'DispName': 'Humo sapiens'}], 'Teleomorph': [], 'GenbankSynonym': [], 'Inpart': [], 'Acronym': [], 'Includes': [], 'GenbankCommonName': 'human'}, 'ParentTaxId': '9605', 'Rank': 'species', 'Division': 'Primates', 'GeneticCode': {'GCId': '1', 'GCName': 'Standard'}, 'MitoGeneticCode': {'MGCId': '2', 'MGCName': 'Vertebrate Mitochondrial'}, 'Lineage': 'cellular organisms; Eukaryota; Opisthokonta; Metazoa; Eumetazoa; Bilateria; Deuterostomia; Chordata; Craniata; Vertebrata; Gnathostomata; Teleostomi; Euteleostomi; Sarcopterygii; Dipnotetrapodomorpha; Tetrapoda; Amniota; Mammalia; Theria; Eutheria; Boreoeutheria; Euarchontoglires; Primates; Haplorrhini; Simiiformes; Catarrhini; Hominoidea; Hominidae; Homininae; Homo', 'LineageEx': [{'TaxId': '131567', 'ScientificName': 'cellular organisms', 'Rank': 'no rank'}, {'TaxId': '2759', 'ScientificName': 'Eukaryota', 'Rank': 'superkingdom'}, {'TaxId': '33154', 'ScientificName': 'Opisthokonta', 'Rank': 'clade'}, {'TaxId': '33208', 'ScientificName': 'Metazoa', 'Rank': 'kingdom'}, {'TaxId': '6072', 'ScientificName': 'Eumetazoa', 'Rank': 'clade'}, {'TaxId': '33213', 'ScientificName': 'Bilateria', 'Rank': 'clade'}, {'TaxId': '33511', 'ScientificName': 'Deuterostomia', 'Rank': 'clade'}, {'TaxId': '7711', 'ScientificName': 'Chordata', 'Rank': 'phylum'}, {'TaxId': '89593', 'ScientificName': 'Craniata', 'Rank': 'subphylum'}, {'TaxId': '7742', 'ScientificName': 'Vertebrata', 'Rank': 'clade'}, {'TaxId': '7776', 'ScientificName': 'Gnathostomata', 'Rank': 'clade'}, {'TaxId': '117570', 'ScientificName': 'Teleostomi', 'Rank': 'clade'}, {'TaxId': '117571', 'ScientificName': 'Euteleostomi', 'Rank': 'clade'}, {'TaxId': '8287', 'ScientificName': 'Sarcopterygii', 'Rank': 'superclass'}, {'TaxId': '1338369', 'ScientificName': 'Dipnotetrapodomorpha', 'Rank': 'clade'}, {'TaxId': '32523', 'ScientificName': 'Tetrapoda', 'Rank': 'clade'}, {'TaxId': '32524', 'ScientificName': 'Amniota', 'Rank': 'clade'}, {'TaxId': '40674', 'ScientificName': 'Mammalia', 'Rank': 'class'}, {'TaxId': '32525', 'ScientificName': 'Theria', 'Rank': 'clade'}, {'TaxId': '9347', 'ScientificName': 'Eutheria', 'Rank': 'clade'}, {'TaxId': '1437010', 'ScientificName': 'Boreoeutheria', 'Rank': 'clade'}, {'TaxId': '314146', 'ScientificName': 'Euarchontoglires', 'Rank': 'superorder'}, {'TaxId': '9443', 'ScientificName': 'Primates', 'Rank': 'order'}, {'TaxId': '376913', 'ScientificName': 'Haplorrhini', 'Rank': 'suborder'}, {'TaxId': '314293', 'ScientificName': 'Simiiformes', 'Rank': 'infraorder'}, {'TaxId': '9526', 'ScientificName': 'Catarrhini', 'Rank': 'parvorder'}, {'TaxId': '314295', 'ScientificName': 'Hominoidea', 'Rank': 'superfamily'}, {'TaxId': '9604', 'ScientificName': 'Hominidae', 'Rank': 'family'}, {'TaxId': '207598', 'ScientificName': 'Homininae', 'Rank': 'subfamily'}, {'TaxId': '9605', 'ScientificName': 'Homo', 'Rank': 'genus'}], 'CreateDate': '1995/02/27 09:24:00', 'UpdateDate': '2021/09/24 13:17:40', 'PubDate': '1992/05/26 01:00:00'}\n" + ] + } + ], + "source": [ + "from Bio import Entrez\n", + "from numpy import rec\n", + "\n", + "# Always provide your email address to NCBI when using the Entrez API\n", + "Entrez.email = \"your.email@example.com\"\n", + "\n", + "\n", + "def get_taxonomy(tax_id):\n", + " handle = Entrez.efetch(db=\"taxonomy\", id=str(tax_id), retmode=\"xml\")\n", + " records = Entrez.read(handle)\n", + "\n", + " # Close the handle after reading the data\n", + " handle.close()\n", + "\n", + " # Process and return the taxonomy information\n", + " return records[0]\n", + "\n", + "\n", + "# Example usage\n", + "tax_id = \"9606\" # Taxonomy ID for Homo sapiens\n", + "taxonomy_info = get_taxonomy(tax_id)\n", + "print(taxonomy_info)" + ] } ], "metadata": { @@ -84,7 +150,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.8" + "version": "3.10.13" } }, "nbformat": 4, diff --git a/examples/networks/test.ipynb b/examples/networks/test.ipynb index c8f05b5d..6a80c74b 100644 --- a/examples/networks/test.ipynb +++ b/examples/networks/test.ipynb @@ -39,27 +39,22 @@ "name": "stdout", "output_type": "stream", "text": [ - "🏃🏼‍♀️ Running PBLAST\n", - "╭── protein name: methionine adenosyltransferase\n", - "├── accession: WP_011249500.1\n", - "├── organism: Thermococcus kodakarensis\n", - "├── e-value: 10.0\n", - "╰── max hits: 200\n" + "🏃 Running BLAST\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "⬇️ Fetching protein sequences: 100%|██████████| 200/200 [00:14<00:00, 13.97it/s]" + "⬇️ Fetching protein sequences: 200it [00:35, 5.69it/s] " ] }, { "name": "stdout", "output_type": "stream", "text": [ - "🎉 Done\n", - "\n" + "2024-03-07 13:59:28,852 - WARNING - abstractparser.py:154 - map_regions() - Incomplete region data found for 7P82_A: {'region_name': ['Domain 1'], 'note': ['NCBI Domains']}, skipping region\n", + "2024-03-07 13:59:28,852 - WARNING - abstractparser.py:154 - map_regions() - Incomplete region data found for 7P82_A: {'region_name': ['Domain 2'], 'note': ['NCBI Domains']}, skipping region\n" ] }, { @@ -72,7 +67,30 @@ ], "source": [ "# Run local blastp search\n", - "blast_results = metTK.ncbi_blastp(n_hits=200)" + "blast_results = metTK.blastp(\n", + " db_path=\"/Users/max/Documents/GitHub/blast-db/data/source\",\n", + " n_hits=200,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "200" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(blast_results)" ] }, { @@ -84,14 +102,14 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "⛓️ Running pairwise alignments: 100%|██████████| 19900/19900 [00:05<00:00, 3893.75it/s]\n" + "⛓️ Running pairwise alignments: 100%|██████████| 19900/19900 [00:05<00:00, 3531.98it/s]\n" ] } ], @@ -104,7 +122,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -119,21 +137,21 @@ [ "methionine adenosyltransferase", null, - "Archaea", - "Euryarchaeota", - "Thermococcales", - "Thermococcus", null, null, null, - "kodakarensis", + null, + null, + null, + null, + null, "2.5.1.6", 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Taxonomy ID: %{customdata[12]}", "marker": { - "color": "rgb(46, 111, 142)", + "color": "rgb(196, 224, 42)", "size": 6, "symbol": "circle" }, "mode": "markers", - "text": "methionine adenosyltransferase", + "text": "S-adenosylmethionine synthetase", "type": "scatter3d", "x": [ - 0.14399751171237338 + 0.12566472167280254 ], "y": [ - -0.03607584055783106 + 0.6130607831166213 ], "z": [ - -0.16701316311277864 + 0.85379894860156 ] }, { @@ -7991,26 +8008,26 @@ [ "methionine adenosyltransferase", null, - "Archaea", - "Euryarchaeota", - "Methanococci", - "Methanocaldococcaceae", null, null, null, - "lauensis", + null, + null, + null, + null, + null, "2.5.1.6", - 45138, - "taxon:2546128", - 0.0008159868029910761, - -0.06488455834952937, - -0.012943066567424088, - 0.08454860316179402 + 42996, + "taxon:1457250", + 0, + -0.6588090678007401, + 0.8031268743617976, + -0.004899041493637145 ] ], "hovertemplate": "%{customdata[0]}
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Taxonomy ID: %{customdata[12]}", "marker": { - "color": "rgb(42, 171, 129)", + "color": "rgb(44, 115, 142)", "size": 6, "symbol": "circle" }, @@ -8018,13 +8035,13 @@ "text": "methionine adenosyltransferase", "type": "scatter3d", "x": [ - -0.06488455834952937 + -0.6588090678007401 ], "y": [ - -0.012943066567424088 + 0.8031268743617976 ], "z": [ - 0.08454860316179402 + -0.004899041493637145 ] }, { @@ -8032,26 +8049,26 @@ [ "methionine adenosyltransferase", null, - "Archaea", - "Euryarchaeota", - "Methanomicrobia", - "Candidatus Methanoperedenaceae", null, null, null, - "Methanoperedenaceae", - "2.5.1.6", null, - "taxon:2072416", - 0.0008213183289618789, - 0.2659913984135081, - 0.0003794116672527822, - -0.16932290948845521 + null, + null, + null, + null, + "2.5.1.6", + 43869, + "taxon:768733", + 0, + -0.4239299153926898, + -0.06498188247234639, + 0.9557667523538388 ] ], "hovertemplate": "%{customdata[0]}
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Taxonomy ID: %{customdata[12]}", "marker": { - "color": "rgb(130, 211, 75)", + "color": "rgb(59, 80, 138)", "size": 6, "symbol": "circle" }, "mode": "markers", - "text": "archaeal S-adenosylmethionine synthetase", + "text": "methionine adenosyltransferase", "type": "scatter3d", "x": [ - -0.11664694739242984 + -0.4151374156704781 ], "y": [ - -0.07152034642915442 + -0.8111481651341976 ], "z": [ - -0.7490223558203997 + -0.6092240344800969 ] }, { @@ -8155,26 +8172,26 @@ [ "methionine adenosyltransferase", null, - "Archaea", - "Euryarchaeota", - "Archaeoglobales", null, null, null, null, - "archaeon", + null, + null, + null, + null, "2.5.1.6", null, - "taxon:2250258", - 0.0033292695842612905, - 0.10249020207848519, - -0.05330460396601036, - -0.12527067399083666 + "taxon:2806419", + 0, + -0.6983953152016034, + -0.6334776672454997, + -0.5625565612318258 ] ], "hovertemplate": "%{customdata[0]}
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Taxonomy ID: %{customdata[12]}", "marker": { - "color": "rgb(71, 42, 121)", + "color": "rgb(34, 146, 139)", "size": 6, "symbol": "circle" }, @@ -8182,13 +8199,13 @@ "text": "methionine adenosyltransferase", "type": "scatter3d", "x": [ - 0.10249020207848519 + -0.6983953152016034 ], "y": [ - -0.05330460396601036 + -0.6334776672454997 ], "z": [ - -0.12527067399083666 + -0.5625565612318258 ] }, { @@ -8196,26 +8213,26 @@ [ "methionine adenosyltransferase", null, - "Archaea", - "Euryarchaeota", - "Methanomicrobia", - "Candidatus Methanoperedenaceae", null, null, null, - "Methanoperedens", + null, + null, + null, + null, + null, "2.5.1.6", null, - "taxon:2032688", - 0.004430203008708208, - 0.23404964130403996, - 0.007522658533011056, - -0.16856593286590946 + "taxon:1906666", + 0, + 0.2755107191106561, + -0.8861482479134809, + -0.242462040006182 ] ], "hovertemplate": "%{customdata[0]}
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Taxonomy ID: %{customdata[12]}", "marker": { - "color": "rgb(69, 190, 112)", + "color": "rgb(38, 132, 142)", "size": 6, "symbol": "circle" }, @@ -8223,13 +8240,13 @@ "text": "methionine adenosyltransferase", "type": "scatter3d", "x": [ - 0.23404964130403996 + 0.2755107191106561 ], "y": [ - 0.007522658533011056 + -0.8861482479134809 ], "z": [ - -0.16856593286590946 + -0.242462040006182 ] }, { @@ -8237,26 +8254,26 @@ [ "methionine adenosyltransferase", null, - "Archaea", - "Euryarchaeota", - "Methanomicrobia", - "Candidatus Methanoperedenaceae", null, null, null, - "Methanoperedens", + null, + null, + null, + null, + null, "2.5.1.6", null, - "taxon:2032688", - 0.0016223123891998593, - 0.24965765667714793, - 0.008920697915647023, - -0.1614269485046464 + "taxon:1906666", + 0, + 0.8389093939289965, + -0.17391739281553426, + 0.4644673256231633 ] ], "hovertemplate": "%{customdata[0]}
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Taxonomy ID: %{customdata[12]}", "marker": { - "color": "rgb(69, 190, 112)", + "color": "rgb(38, 132, 142)", "size": 6, "symbol": "circle" }, @@ -8264,13 +8281,13 @@ "text": "methionine adenosyltransferase", "type": "scatter3d", "x": [ - 0.24965765667714793 + 0.8389093939289965 ], "y": [ - 0.008920697915647023 + -0.17391739281553426 ], "z": [ - -0.1614269485046464 + 0.4644673256231633 ] }, { @@ -8278,26 +8295,26 @@ [ "methionine adenosyltransferase", null, - "Archaea", - "Euryarchaeota", null, null, null, null, null, - "archaeon", + null, + null, + null, "2.5.1.6", null, - "taxon:2250254", + "taxon:90426", 0, - -0.14072907951971342, - -0.03348969445148773, - 0.06062043139626113 + -0.6542358403398179, + -0.6558431159131963, + -0.25175675412504556 ] ], "hovertemplate": "%{customdata[0]}
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Taxonomy ID: %{customdata[12]}", "marker": { - "color": "rgb(33, 150, 138)", + "color": "rgb(90, 198, 100)", "size": 6, "symbol": "circle" }, @@ -8305,13 +8322,13 @@ "text": "methionine adenosyltransferase", "type": "scatter3d", "x": [ - -0.14072907951971342 + -0.6542358403398179 ], "y": [ - -0.03348969445148773 + -0.6558431159131963 ], "z": [ - 0.06062043139626113 + -0.25175675412504556 ] } ], @@ -9177,13 +9194,6 @@ "n.add_target(metTK)\n", "n.visualize()" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { diff --git a/logging.conf b/logging.conf new file mode 100644 index 00000000..15a969cc --- /dev/null +++ b/logging.conf @@ -0,0 +1,33 @@ +[loggers] +keys=root,pyeed + +[handlers] +keys=consoleHandler, fileHandler + +[formatters] +keys=simpleFormatter + +[logger_root] +level=DEBUG +handlers=consoleHandler + +[logger_pyeed] +level=DEBUG +handlers=consoleHandler, fileHandler +qualname=pyeed +propagate=0 + +[handler_consoleHandler] +class=StreamHandler +level=INFO +formatter=simpleFormatter +args=(sys.stdout,) + +[handler_fileHandler] +class=FileHandler +level=DEBUG +formatter=simpleFormatter +args=('pyeed.log',) + +[formatter_simpleFormatter] +format=%(asctime)s - %(levelname)s - %(filename)s:%(lineno)s - %(funcName)s() - %(message)s \ No newline at end of file diff --git a/pyeed/containers/abstract_container.py b/pyeed/containers/abstract_container.py index 1e0795e0..24f15b1e 100644 --- a/pyeed/containers/abstract_container.py +++ b/pyeed/containers/abstract_container.py @@ -1,6 +1,11 @@ import os +import logging +import logging.config import docker import shutil +import random +import string +from pathlib import Path from enum import Enum from typing import Any import tempfile @@ -12,6 +17,10 @@ from docker.models.images import Image from docker.errors import DockerException +path_config = Path(__file__).parent.parent.parent / "logging.conf" +logging.config.fileConfig(path_config) +logger = logging.getLogger("pyeed") + class ToolImage(Enum): CLUSTALO = "biocontainers/clustal-omega:v1.2.1_cv5" @@ -62,21 +71,28 @@ def __init__(self, **kwargs): super().__init__(**kwargs) self._tempdir_path = tempfile.mkdtemp() self._client = self._initialize_docker_client() + logger.debug( + f"Successfully initialized container of type: {self._container_info}, _tempdir_path: {self._tempdir_path}" + ) def _initialize_docker_client(self) -> DockerClient: + + logger.debug("Initializing Docker client") try: client = docker.from_env() client.ping() return client except DockerException as e: - print(f"Docker is not running. Start the Docker application. {e}") + logger.error(f"Docker is not running. Start the Docker application. {e}") def get_image(self) -> Image: """Gets the image from Docker Hub. If the image is not found, it will be pulled.""" try: + logger.debug(f"Getting image {self._container_info.value}") return self._client.images.get(self._container_info.value) except docker.errors.ImageNotFound: - print(f"⬇️ Pulling {self._container_info.name}") + logger.info(f"⬇️ Pulling {self._container_info.name}") + return self._client.images.pull(self._container_info.value) def run_container(self, command: str, data: Any) -> Container: @@ -86,16 +102,18 @@ def run_container(self, command: str, data: Any) -> Container: image = self.get_image() self.create_file(data=data) - print(f"🏃 Running {self._container_info.name}") + logger.info(f"🏃 Running {self._container_info.name}") self._client.containers.run( image=image, command=command, - name=self._container_info.name, + name=self._container_info.name + + "_" + + "".join(random.choices(string.ascii_lowercase, k=5)), auto_remove=True, volumes={self._tempdir_path: {"bind": "/data/", "mode": "rw"}}, ) except Exception as e: - print(f"Error running container: {e}") + logger.error(f"Error running {self._container_info} container: {e}") def _delete_temp_dir(self): """Deletes the temporary directory.""" @@ -173,7 +191,8 @@ def run_container(self, command: str, data: Any) -> Container: self._client.containers.run( image=image, command=command, - name=self._container_info.name, + name=self._container_info.name + + "".join(random.choices(string.ascii_lowercase, k=5)), auto_remove=True, volumes={ self._tempdir_path: {"bind": "/data/", "mode": "rw"}, @@ -186,8 +205,10 @@ def run_container(self, command: str, data: Any) -> Container: def create_file(self, data: str) -> str: """Creates the input data for the container.""" + with open(f"{self._tempdir_path}/input.fasta", "w") as f: f.write(data) + logger.debug(f"Created input file: {self._tempdir_path}/blastp.fasta") return f"{self._tempdir_path}/blastp.fasta" def extract_output_data(self): @@ -196,6 +217,9 @@ def extract_output_data(self): """Extracts the output data from the container.""" search_io = SearchIO.read(f"{self._tempdir_path}/blastp.out", "blast-tab") + logger.debug("Extracted output data") + + # TODO add debug info on how many sequences were discarded due to identity and evalue thresholds return [ result.id @@ -205,6 +229,7 @@ def extract_output_data(self): def setup_command(self) -> str: """Creates the command which is executed in the container.""" + logger.debug(f"Setting up command for {self._container_info}") return ( f"blastp " f"-query /data/input.fasta " diff --git a/pyeed/core/proteininfo.py b/pyeed/core/proteininfo.py index 0d74514f..d4f9e90d 100644 --- a/pyeed/core/proteininfo.py +++ b/pyeed/core/proteininfo.py @@ -4,6 +4,7 @@ from sdRDM.base.listplus import ListPlus from sdRDM.base.utils import forge_signature, IDGenerator from Bio.Blast import NCBIWWW, NCBIXML + from .dnainfo import DNAInfo from .proteinregion import ProteinRegion from .abstractsequence import AbstractSequence @@ -160,7 +161,8 @@ def add_to_substrates( @classmethod def from_ncbi(cls, accession_id: str) -> "ProteinInfo": - from ..ncbi.seq_io import _seqio_to_nucleotide_info, get_ncbi_entry + from ..parsers.abstractparser import NCBIParser + from ..ncbi.seq_io import get_ncbi_entry """ This method creates a 'ProteinInfo' object from a given NCBI ID. @@ -178,19 +180,14 @@ def from_ncbi(cls, accession_id: str) -> "ProteinInfo": return cls.from_accessions(accession_id) seq_record = get_ncbi_entry(accession_id, "protein") - return _seqio_to_nucleotide_info(cls, seq_record) - - @classmethod - def _from_seq_record(cls, seq_record) -> "ProteinInfo": - from ..ncbi.seq_io import _seqio_to_nucleotide_info - - return _seqio_to_nucleotide_info(cls, seq_record) + return NCBIParser(seq_record).map(cls) @classmethod def from_accessions( cls, accession_ids: List[str], email: str = None, api_key: str = None ) -> List["ProteinInfo"]: from ..ncbi.seq_io import get_ncbi_entrys + from ..parsers.abstractparser import NCBIParser seq_entries = get_ncbi_entrys( accession_ids=accession_ids, @@ -199,7 +196,7 @@ def from_accessions( api_key=api_key, ) - return [cls._from_seq_record(record) for record in seq_entries] + return [NCBIParser(seq_entry).map(cls) for seq_entry in seq_entries] def ncbi_blastp( self, @@ -222,7 +219,7 @@ def ncbi_blastp( """ from ..ncbi.seq_io import get_ncbi_entrys - print(f"🏃🏼‍♀️ Running PBLAST") + print("🏃🏼‍♀️ Running PBLAST") print(f"╭── protein name: {self.name}") print(f"├── accession: {self.source_id}") print(f"├── organism: {self.organism.name}") @@ -291,6 +288,7 @@ def get_dna(self): def _nblast(sequence: str, n_hits: int = None) -> List["ProteinInfo"]: result_handle = NCBIWWW.qblast("blastn", "nr", sequence, hitlist_size=n_hits) blast_record = NCBIXML.read(result_handle) + raise NotImplementedError("This method is not implemented yet.") @staticmethod def _get_accessions(blast_record: NCBIXML) -> List[str]: diff --git a/pyeed/ncbi/seq_io.py b/pyeed/ncbi/seq_io.py index 40262ca0..8d67e1b7 100644 --- a/pyeed/ncbi/seq_io.py +++ b/pyeed/ncbi/seq_io.py @@ -1,17 +1,8 @@ -import re import secrets from tqdm import tqdm from typing import List from Bio import SeqIO, Entrez -from pyeed.core.dnaregion import DNARegion -from pyeed.core.dnaregiontype import DNARegionType -from pyeed.core.proteinregion import ProteinRegion -from pyeed.core.proteinsitetype import ProteinSiteType -from pyeed.core.site import Site -from pyeed.core.span import Span - -from ..core.organism import Organism GENEID_PATTERN = r"GeneID:\d+" @@ -19,23 +10,23 @@ def get_ncbi_entry( accession_id: str, database: str, email: str = None, api_key: str = None ) -> SeqIO.SeqRecord: + # generate generic mail if none is given if email is None: email = f"{secrets.token_hex(8)}@gmail.com" databases = {"nucleotide", "protein"} if database not in databases: - raise ValueError(f"database must be one of {databases}") + raise ValueError(f"Database must be one of {databases}") Entrez.email = email Entrez.api_key = api_key - handle = Entrez.efetch( + with Entrez.efetch( db=database, id=accession_id, rettype="gb", retmode="text", api_key=api_key - ) - seq_record = SeqIO.read(handle, "genbank") + ) as handle: + seq_record = SeqIO.read(handle, "genbank") - handle.close() return seq_record @@ -47,277 +38,283 @@ def get_ncbi_entrys( email = f"{secrets.token_hex(8)}@gmail.com" # Concat accession_ids to string - if isinstance(accession_ids, list): - accession_id = ",".join(accession_ids) - else: + if not isinstance(accession_ids, list): raise ValueError("'accession_ids' must be a list") - databases = {"nucleotide", "protein"} - if database not in databases: - raise ValueError(f"database must be one of {databases}") - - # Make request - Entrez.email = email - Entrez.api_key = api_key - - handle = Entrez.efetch( - db=database, id=accession_id, rettype="gb", retmode="text", api_key=api_key - ) + # dissect the list in chunks of 100 + accession_ids = [ + accession_ids[i : i + 100] for i in range(0, len(accession_ids), 100) + ] seq_records = [] - for record in tqdm( - SeqIO.parse(handle, "genbank"), - desc="⬇️ Fetching protein sequences", + with tqdm( total=len(accession_ids), - ): - seq_records.append(record) - - handle.close() + desc="⬇️ Fetching protein sequences", + ) as pbar: + for accession_id_set in accession_ids: + accession_id = ",".join(accession_id_set) + + databases = {"nucleotide", "protein"} + if database not in databases: + raise ValueError(f"database must be one of {databases}") + + # Make request + Entrez.email = email + Entrez.api_key = api_key + + with Entrez.efetch( + db=database, + id=accession_id, + rettype="gb", + retmode="text", + api_key=api_key, + ) as handle: + + for record in SeqIO.parse(handle, "genbank"): + seq_records.append(record) + pbar.update(1) return seq_records -def _seqio_to_dna_info(cls, entry: SeqIO): - regions = [] - for feature in entry.features: - if feature.type == "gene": - regions.append( - DNARegion( - name=feature.qualifiers["gene"][0], - spans=[ - Span( - start=int(feature.location.start), - end=int(feature.location.end), - ) - ], - cross_reference=re.findall( - GENEID_PATTERN, "".join(feature.qualifiers["db_xref"]) - )[0], - note=feature.qualifiers["note"][0], - type=DNARegionType.GENE, - ) - ) - - if feature.type == "CDS": - regions.append( - DNARegion( - name=feature.qualifiers["product"][0], - spans=[ - Span( - start=int(feature.location.start), - end=int(feature.location.end), - ) - ], - cross_reference=feature.qualifiers["protein_id"][0], - note=feature.qualifiers["note"][0], - type=DNARegionType.CODING_SEQUENCE, - ) - ) - - if feature.type == "source": - organism = get_organism(entry.annotations, feature) - - return cls( - source_id=entry.id, - name=entry.description, - sequence=str(entry.seq), - regions=regions, - organism=organism, - ) - - -def get_organism(annotations, feature) -> Organism: - taxonomy = annotations["taxonomy"] - - try: - domain = taxonomy[0] - except IndexError: - domain = None - - try: - kingdom = taxonomy[1] - except IndexError: - kingdom = None - - try: - phylum = taxonomy[3] - except IndexError: - phylum = None - - try: - tax_class = taxonomy[5] - except IndexError: - tax_class = None - - try: - order = taxonomy[9] - except IndexError: - order = None - - try: - family = taxonomy[13] - except IndexError: - family = None - - try: - genus = taxonomy[14] - except IndexError: - genus = None - - try: - species = feature.qualifiers["organism"][0].split(" ")[1] - except IndexError: - species = None - - return Organism( - name=feature.qualifiers["organism"][0], - taxonomy_id=feature.qualifiers["db_xref"][0], - domain=domain, - kingdom=kingdom, - phylum=phylum, - tax_class=tax_class, - order=order, - family=family, - genus=genus, - species=species, - ) - - -# TODO: from Jan Range to Everyone: 1:18 PM .get("note", "") to avoid key error - - -def _seqio_to_nucleotide_info(cls, entry: SeqIO): - """Handel SeqIO entry and return `ProteinSequence`""" - - try: - sites = [] - regions = [] - for feature in entry.features: - # TODO: assert that only one protein is in the file - if feature.type == "Protein": - if "product" in feature.qualifiers: - protein_name = feature.qualifiers["product"][0] - elif "name" in feature.qualifiers: - protein_name = feature.qualifiers["name"][0] - else: - print(f"No name info found in {entry.id}") - protein_name = None - - if "calculated_mol_wt" in feature.qualifiers: - mol_weight = feature.qualifiers["calculated_mol_wt"][0] - else: - mol_weight = None - - if "EC_number" in feature.qualifiers: - ec_number = feature.qualifiers["EC_number"][0] - else: - ec_number = None - - if feature.type == "source": - organism = get_organism(entry.annotations, feature) - - if feature.type == "Region": - if "db_xref" in feature.qualifiers: - cross_reference = feature.qualifiers["db_xref"][0] - else: - cross_reference = None - - if "note" in feature.qualifiers: - if feature.qualifiers["note"]: - note = feature.qualifiers["note"][0] - else: - note = None - else: - note = None - - regions.append( - ProteinRegion( - name=feature.qualifiers["region_name"][0], - spans=[ - Span( - start=int(feature.location.start), - end=int(feature.location.end), - ) - ], - cross_reference=cross_reference, - note=note, - ) - ) - - if feature.type == "Site": - site_type = feature.qualifiers["site_type"][0].lower() - - if "note" in feature.qualifiers: - name = feature.qualifiers["note"][0] - else: - name = site_type - - if "db_xref" in feature.qualifiers: - cross_reference = feature.qualifiers["db_xref"][0] - else: - cross_reference = None - - sites.append( - Site( - name=name, - positions=[loc for loc in feature.location], - cross_ref=cross_reference, - type=ProteinSiteType.match_string(site_type), - ) - ) - - if feature.type == "CDS": - cds_regions = get_cds_regions(feature.qualifiers["coded_by"][0]) - - if "CDS" not in [feature.type for feature in entry.features]: - cds_regions = None - - if "Protein" not in [feature.type for feature in entry.features]: - protein_name = entry.description - ec_number = None - mol_weight = None - - return cls( - source_id=entry.id, - name=protein_name, - sequence=str(entry.seq), - ec_number=ec_number, - mol_weight=mol_weight, - organism=organism, - sites=sites, - regions=regions, - coding_sequence_ref=cds_regions, - ) - except UnboundLocalError: - print(f"❌ Sequence {entry.id} was not added, since mapping failed.") - - -def get_cds_regions(coded_by: dict) -> List[DNARegion]: - """Extract information about the coding sequence from the 'coded_by' qualifier.""" - - cds_pattern = r"\w+\.\d+:\d+\.\.\d+\s?\d+" - - # Extract all regions from the 'coded_by' qualifier - coded_by = coded_by.replace(">", "") - coded_by = coded_by.replace("<", "") - cds_regions = re.findall(cds_pattern, coded_by) - cds_regions = [region.replace(" ", "") for region in cds_regions] - - # Extract the reference id from the first region - reference_ids = [region.split(":")[0] for region in cds_regions] - if not all([reference_id == reference_ids[0] for reference_id in reference_ids]): - print("nucleotide sequence references are not identical.") - - # Extract the start and end position of each region - cds_ranges = [region.split(":")[1] for region in cds_regions] - for region in cds_ranges: - start, end = region.split("..") - span = Span(start=int(start), end=int(end)) - - region = DNARegion( - id=reference_ids[0], - spans=[span], - type=DNARegionType.CODING_SEQUENCE, - ) - - return region +# def _seqio_to_dna_info(cls, entry: SeqIO): +# regions = [] +# for feature in entry.features: +# if feature.type == "gene": +# regions.append( +# DNARegion( +# name=feature.qualifiers["gene"][0], +# spans=[ +# Span( +# start=int(feature.location.start), +# end=int(feature.location.end), +# ) +# ], +# cross_reference=re.findall( +# GENEID_PATTERN, "".join(feature.qualifiers["db_xref"]) +# )[0], +# note=feature.qualifiers["note"][0], +# type=DNARegionType.GENE, +# ) +# ) + +# if feature.type == "CDS": +# regions.append( +# DNARegion( +# name=feature.qualifiers["product"][0], +# spans=[ +# Span( +# start=int(feature.location.start), +# end=int(feature.location.end), +# ) +# ], +# cross_reference=feature.qualifiers["protein_id"][0], +# note=feature.qualifiers["note"][0], +# type=DNARegionType.CODING_SEQUENCE, +# ) +# ) + +# if feature.type == "source": +# organism = get_organism(entry.annotations, feature) + +# return cls( +# source_id=entry.id, +# name=entry.description, +# sequence=str(entry.seq), +# regions=regions, +# organism=organism, +# ) + + +# def get_organism(annotations, feature) -> Organism: +# taxonomy = annotations["taxonomy"] + +# try: +# domain = taxonomy[0] +# except IndexError: +# domain = None + +# try: +# kingdom = taxonomy[1] +# except IndexError: +# kingdom = None + +# try: +# phylum = taxonomy[3] +# except IndexError: +# phylum = None + +# try: +# tax_class = taxonomy[5] +# except IndexError: +# tax_class = None + +# try: +# order = taxonomy[9] +# except IndexError: +# order = None + +# try: +# family = taxonomy[13] +# except IndexError: +# family = None + +# try: +# genus = taxonomy[14] +# except IndexError: +# genus = None + +# try: +# species = feature.qualifiers["organism"][0].split(" ")[1] +# except IndexError: +# species = None + +# return Organism( +# name=feature.qualifiers["organism"][0], +# taxonomy_id=feature.qualifiers["db_xref"][0], +# domain=domain, +# kingdom=kingdom, +# phylum=phylum, +# tax_class=tax_class, +# order=order, +# family=family, +# genus=genus, +# species=species, +# ) + + +# def _seqio_to_nucleotide_info(cls, entry: SeqIO): +# """Handel SeqIO entry and return `ProteinSequence`""" + +# try: +# sites = [] +# regions = [] +# for feature in entry.features: +# # TODO: assert that only one protein is in the file +# if feature.type == "Protein": +# if "product" in feature.qualifiers: +# protein_name = feature.qualifiers["product"][0] +# elif "name" in feature.qualifiers: +# protein_name = feature.qualifiers["name"][0] +# else: +# print(f"No name info found in {entry.id}") +# protein_name = None + +# if "calculated_mol_wt" in feature.qualifiers: +# mol_weight = feature.qualifiers["calculated_mol_wt"][0] +# else: +# mol_weight = None + +# if "EC_number" in feature.qualifiers: +# ec_number = feature.qualifiers["EC_number"][0] +# else: +# ec_number = None + +# if feature.type == "source": +# organism = get_organism(entry.annotations, feature) + +# if feature.type == "Region": +# if "db_xref" in feature.qualifiers: +# cross_reference = feature.qualifiers["db_xref"][0] +# else: +# cross_reference = None + +# if "note" in feature.qualifiers: +# if feature.qualifiers["note"]: +# note = feature.qualifiers["note"][0] +# else: +# note = None +# else: +# note = None + +# regions.append( +# ProteinRegion( +# name=feature.qualifiers["region_name"][0], +# spans=[ +# Span( +# start=int(feature.location.start), +# end=int(feature.location.end), +# ) +# ], +# cross_reference=cross_reference, +# note=note, +# ) +# ) + +# if feature.type == "Site": +# site_type = feature.qualifiers["site_type"][0].lower() + +# if "note" in feature.qualifiers: +# name = feature.qualifiers["note"][0] +# else: +# name = site_type + +# if "db_xref" in feature.qualifiers: +# cross_reference = feature.qualifiers["db_xref"][0] +# else: +# cross_reference = None + +# sites.append( +# Site( +# name=name, +# positions=[loc for loc in feature.location], +# cross_ref=cross_reference, +# type=ProteinSiteType.match_string(site_type), +# ) +# ) + +# if feature.type == "CDS": +# cds_regions = get_cds_regions(feature.qualifiers["coded_by"][0]) + +# if "CDS" not in [feature.type for feature in entry.features]: +# cds_regions = None + +# if "Protein" not in [feature.type for feature in entry.features]: +# protein_name = entry.description +# ec_number = None +# mol_weight = None + +# return cls( +# source_id=entry.id, +# name=protein_name, +# sequence=str(entry.seq), +# ec_number=ec_number, +# mol_weight=mol_weight, +# organism=organism, +# sites=sites, +# regions=regions, +# coding_sequence_ref=cds_regions, +# ) +# except UnboundLocalError: +# print(f"❌ Sequence {entry.id} was not added, since mapping failed.") + + +# def get_cds_regions(coded_by: dict) -> List[DNARegion]: +# """Extract information about the coding sequence from the 'coded_by' qualifier.""" + +# cds_pattern = r"\w+\.\d+:\d+\.\.\d+\s?\d+" + +# # Extract all regions from the 'coded_by' qualifier +# coded_by = coded_by.replace(">", "") +# coded_by = coded_by.replace("<", "") +# cds_regions = re.findall(cds_pattern, coded_by) +# cds_regions = [region.replace(" ", "") for region in cds_regions] + +# # Extract the reference id from the first region +# reference_ids = [region.split(":")[0] for region in cds_regions] +# if not all([reference_id == reference_ids[0] for reference_id in reference_ids]): +# print("nucleotide sequence references are not identical.") + +# # Extract the start and end position of each region +# cds_ranges = [region.split(":")[1] for region in cds_regions] +# for region in cds_ranges: +# start, end = region.split("..") +# span = Span(start=int(start), end=int(end)) + +# region = DNARegion( +# id=reference_ids[0], +# spans=[span], +# type=DNARegionType.CODING_SEQUENCE, +# ) + +# return region diff --git a/pyeed/parsers/__init__.py b/pyeed/parsers/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/pyeed/parsers/abstractparser.py b/pyeed/parsers/abstractparser.py new file mode 100644 index 00000000..21e82c3f --- /dev/null +++ b/pyeed/parsers/abstractparser.py @@ -0,0 +1,287 @@ +import os +import re +import logging +import logging.config +from pathlib import Path +from abc import ABC, abstractmethod +from typing import Any, List + +import Bio +from pyeed.core.dnaregion import DNARegion +from pyeed.core.dnaregiontype import DNARegionType + +from pyeed.core.organism import Organism +from pyeed.core.proteininfo import ProteinInfo +from pyeed.core.proteinregion import ProteinRegion +from pyeed.core.proteinsitetype import ProteinSiteType +from pyeed.core.span import Span + + +path_config = Path(__file__).parent.parent.parent / "logging.conf" +logging.config.fileConfig(path_config) +logger = logging.getLogger("pyeed") + + +class DataParser(ABC): + def __init__(self, source: Any): + self.source = source + + @abstractmethod + def fetch_entry(self): + pass + + @abstractmethod + def parse_organism(self): + pass + + @abstractmethod + def map(self): + pass + + +class NCBIParser(DataParser): + + def map(self, cls: "ProteinInfo"): + + protein_info = cls(source_id=self.source.id, sequence=str(self.source.seq)) + + protein_info.organism = self.parse_organism() + protein_info = self.map_protein(protein_info) + protein_info = self.map_regions(protein_info) + protein_info = self.map_sites(protein_info) + protein_info = self.map_cds(protein_info) + + return protein_info + + def parse_organism(self) -> Organism: + """ + Gets the organism name and taxonomy ID from the source data. + Maps it to an Organism object. + """ + + feature = self.get_feature("source") + if len(feature) != 1: + logger.debug( + f"Multiple features ({len(feature)}) of type `source` found for {self.source.id}: {feature}" + ) + feature = feature[0] + + try: + taxonomy_id = feature.qualifiers["db_xref"] + except KeyError: + logger.debug( + f"No taxonomy ID found for {self.source.id}: {feature[0].qualifiers}" + ) + taxonomy_id = None + + try: + organism_name = feature.qualifiers["organism"] + except KeyError: + logger.debug( + f"No organism name found for {self.source.id}: {feature[0].qualifiers}" + ) + organism_name = None + + return Organism(name=organism_name[0], taxonomy_id=taxonomy_id[0]) + + def map_protein(self, protein_info: ProteinInfo): + + protein = self.get_feature("Protein") + if len(protein) == 0: + logger.debug( + f"No protein feature found for {self.source.id}: {self.source.features}" + ) + + return protein_info + + if len(protein) > 1: + logger.debug( + f"Multiple features ({len(protein)}) of type `Protein` found for {self.source.id}" + ) + + protein = protein[0] + try: + protein_info.name = protein.qualifiers["product"][0] + except KeyError: + logger.debug( + f"No protein name found for {self.source.id}: {protein.qualifiers}" + ) + try: + protein_info.name = protein.qualifiers["name"][0] + except KeyError: + logger.debug( + f"No protein name found for {self.source.id}: {protein.qualifiers}" + ) + protein_info.name = None + + try: + protein_info.mol_weight = protein.qualifiers["calculated_mol_wt"][0] + except KeyError: + logger.debug( + f"No molecular weight found for {self.source.id}: {protein.qualifiers}" + ) + protein_info.mol_weight = None + + try: + protein_info.ec_number = protein.qualifiers["EC_number"][0] + except KeyError: + logger.debug( + f"No EC number found for {self.source.id}: {protein.qualifiers}" + ) + protein_info.ec_number = None + + return protein_info + + def map_regions(self, protein_info: ProteinInfo): + + regions = self.get_feature("region") + for region in regions: + try: + protein_info.regions.append( + ProteinRegion( + name=region.qualifiers["region_name"][0], + spans=[ + Span( + start=int(region.location.start), + end=int(region.location.end), + ) + ], + note=region.qualifiers["note"][0], + cross_reference=region.qualifiers["db_xref"][0], + ) + ) + except KeyError: + logger.debug( + f"Incomplete region data found for {self.source.id}: {region.qualifiers}, skipping region" + ) + + return protein_info + + def map_sites(self, protein_info: ProteinInfo): + + sites = self.get_feature("site") + for site in sites: + try: + protein_info.add_to_sites( + name=site.qualifiers["site_type"][0], + type=ProteinSiteType.match_string( + site.qualifiers["site_type"][0].lower() + ), + positions=[int(part.start) for part in site.location.parts], + cross_ref=site.qualifiers["db_xref"][0], + ) + except KeyError: + logger.warning( + f"Incomplete site data found for {self.source.id}: {site.qualifiers}, skipping site" + ) + + return protein_info + + def map_cds(self, protein_info: ProteinInfo): + + cds = self.get_feature("CDS") + if len(cds) > 1: + logger.info( + f"Multiple features ({len(cds)}) of type `CDS` found for {self.source.id}" + ) + + try: + cds = cds[0] + except IndexError: + logger.debug(f"No CDS found for {self.source.id}: {cds}") + + return protein_info + + try: + protein_info.coding_sequence_ref = self.get_cds_regions( + cds.qualifiers["coded_by"][0] + ) + except IndexError: + logger.debug( + f"No coding sequence reference found for {self.source.id}: {cds.qualifiers}" + ) + + return protein_info + + @staticmethod + def get_cds_regions(coded_by: dict) -> List[DNARegion]: + """Extract information about the coding sequence from the 'coded_by' qualifier.""" + + cds_pattern = r"\w+\.\d+:\d+\.\.\d+\s?\d+" + + # Extract all regions from the 'coded_by' qualifier + coded_by = coded_by.replace(">", "") + coded_by = coded_by.replace("<", "") + cds_regions = re.findall(cds_pattern, coded_by) + cds_regions = [region.replace(" ", "") for region in cds_regions] + + # Extract the reference id from the first region + reference_ids = [region.split(":")[0] for region in cds_regions] + if not all( + [reference_id == reference_ids[0] for reference_id in reference_ids] + ): + logger.warning( + "Nucleotide sequence references are not identical: {reference_ids}" + ) + + # Extract the start and end position of each region + cds_ranges = [region.split(":")[1] for region in cds_regions] + for region in cds_ranges: + start, end = region.split("..") + span = Span(start=int(start), end=int(end)) # noqa: F821 + + region = DNARegion( + id=reference_ids[0], + spans=[span], + type=DNARegionType.CODING_SEQUENCE, + ) + + return region + + def fetch_entry(self, identifier: str): + # Implementation for fetching data from NCBI + logger.debug(f"Fetching NCBI data for {identifier}") + + def parse_data(self, data): + # Implementation for parsing NCBI data + logger.debug("Parsing NCBI data") + + def get_feature(self, feature_type: str) -> "Bio.SeqFeature.SeqFeature": + return [ + feature + for feature in self.source.features + if feature.type.lower() == feature_type.lower() + ] + + +class UniProtParser(DataParser): + + def parse_organism(): + pass + + def fetch_entry(self, identifier: str): + # Implementation for fetching data from UniProt + pass + + def parse_data(self, data): + # Implementation for parsing UniProt data + pass + + +class ParserFactory: + @staticmethod + def get_parser(source: str) -> DataParser: + parsers = {"NCBI": NCBIParser(), "UniProt": UniProtParser()} + parser = parsers.get(source.upper()) + if not parser: + raise ValueError(f"Parser for {source} not found.") + return parser + + +if __name__ == "__main__": + from pyeed.ncbi.seq_io import get_ncbi_entry + + entry = get_ncbi_entry("7P82_A", "protein") + + parser = NCBIParser(entry) + print(parser.map(ProteinInfo)) diff --git a/pyeed/parsers/parser_test.ipynb b/pyeed/parsers/parser_test.ipynb new file mode 100644 index 00000000..24ef0af7 --- /dev/null +++ b/pyeed/parsers/parser_test.ipynb @@ -0,0 +1,97 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "%reload_ext autoreload\n", + "%autoreload 2\n", + "from abstractparser import NCBIParser" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-03-06 16:27:50,249 — abstractparser — WARNING — fetch_entry:36 — Warning\n", + "2024-03-06 16:27:50,249 — abstractparser — WARNING — fetch_entry:36 — Warning\n", + "WARNING:abstractparser:Warning\n" + ] + } + ], + "source": [ + "NCBIParser().fetch_entry(\"some_identifier\")" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-03-06 16:27:50,268 — abstractparser — WARNING — fetch_entry:36 — Warning\n", + "2024-03-06 16:27:50,268 — abstractparser — WARNING — fetch_entry:36 — Warning\n", + "WARNING:abstractparser:Warning\n" + ] + } + ], + "source": [ + "NCBIParser().fetch_entry(\"some_identifier\")" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "ename": "TypeError", + "evalue": "'NoneType' object is not subscriptable", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[12], line 3\u001b[0m\n\u001b[1;32m 1\u001b[0m omg \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mdict\u001b[39m(a\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m, b\u001b[38;5;241m=\u001b[39m[\u001b[38;5;241m2\u001b[39m], c\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m3\u001b[39m)\n\u001b[0;32m----> 3\u001b[0m \u001b[43momg\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mx\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\n", + "\u001b[0;31mTypeError\u001b[0m: 'NoneType' object is not subscriptable" + ] + } + ], + "source": [ + "omg = dict(a=1, b=[2], c=3)\n", + "\n", + "omg.get(\"x\")[0]" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "pye", + "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": "3.10.13" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/pyproject.toml b/pyproject.toml index 1dc8f281..e4fafceb 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "pyeed" -version = "0.1.1" +version = "0.1.2" description = "Enzyme engineering toolkit" authors = ["haeussma <83341109+haeussma@users.noreply.github.com>"] license = "MIT" @@ -11,7 +11,8 @@ packages = [ { include = "pyeed/network" }, { include = "pyeed/aligners" }, { include = "pyeed/containers" }, - { include = "pyeed/utility" } + { include = "pyeed/utility" }, + { include = "pyeed/parsers" } ] [tool.poetry.dependencies]