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Commit message:
planemo upload for repository https://github.com/INFRAFRONTIERDIB/tools-iuc/tree/query_impc/tools/query_impc commit 991881b5df5f5228ecf4445ee2cc1431b9602ea8 |
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added:
impc_tool.py impc_tool.xml test-data/test_output_1_1.tabular test-data/test_output_1_2.tabular test-data/test_output_2.tabular test-data/test_output_3.tabular test-data/test_output_9.tabular test-data/test_query_1.txt test-data/test_query_2.txt test-data/test_query_3.txt |
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| diff -r 000000000000 -r d319dc5f3ea8 impc_tool.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/impc_tool.py Wed Oct 11 14:51:02 2023 +0000 |
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| b'@@ -0,0 +1,759 @@\n+import sys\n+\n+import mygene\n+import pandas as pd\n+import requests\n+\n+\n+impc_api_url = "https://www.ebi.ac.uk/mi/impc/bulkdata-api"\n+impc_api_search_url = f"{impc_api_url}/genes"\n+impc_api_gene_bundle_url = f"{impc_api_url}/geneBundles"\n+\n+\n+def stop_err(msg):\n+ sys.exit(msg)\n+\n+\n+def main():\n+ inp = str(sys.argv[1])\n+ query = str(sys.argv[3])\n+\n+ try:\n+ if query == "7":\n+ g_out = str(sys.argv[5])\n+ full_gene_table(g_out)\n+ sys.exit(0)\n+\n+ if str(sys.argv[5]) == "txt":\n+ s = str(sys.argv[6])\n+ if s == "t":\n+ sep = "\\t"\n+ elif s == "s":\n+ sep = " "\n+ elif s in ",;.":\n+ sep = s\n+ else:\n+ sys.exit("Separator not valid, please change it.")\n+ inp = pd.read_csv(inp, header=None, delimiter=sep)\n+ if len(inp.columns) == 1:\n+ inp = inp.to_csv(header=None,\n+ index=False).strip("\\n").split("\\n")\n+ inp = ",".join(inp)\n+ else:\n+ inp = inp.to_csv(header=None,\n+ index=False).strip(sep).split(sep)\n+ inp = ",".join(inp)\n+\n+ if query == "8":\n+ if str(sys.argv[5]) == "txt":\n+ g_out = str(sys.argv[7])\n+ else:\n+ g_out = str(sys.argv[6])\n+ genes_in_pipeline(inp, g_out)\n+ sys.exit(0)\n+ elif query == "9":\n+ if str(sys.argv[5]) == "txt":\n+ g_out = str(sys.argv[7])\n+ else:\n+ g_out = str(sys.argv[6])\n+ sign_mp(inp, g_out)\n+ sys.exit(0)\n+ elif query == "10":\n+ par_pip_ma(inp)\n+ sys.exit(0)\n+ elif query == "11":\n+ par_gen(inp)\n+ sys.exit(0)\n+ elif query == "2" or query == "4":\n+ final_list = pheno_mapping(inp)\n+ else:\n+ final_list = gene_mapping(inp)\n+ inp = ",".join(final_list)\n+\n+ if query == "1":\n+ get_pheno(inp)\n+ sys.exit(0)\n+ elif query == "2":\n+ if str(sys.argv[5]) == "txt":\n+ g_out = str(sys.argv[7])\n+ else:\n+ g_out = str(sys.argv[6])\n+ get_genes(inp, g_out)\n+ sys.exit(0)\n+ elif query == "3":\n+ gene_set(inp)\n+ sys.exit(0)\n+ elif query == "4":\n+ extr_img(inp)\n+ sys.exit(0)\n+ elif query == "5":\n+ parameters(inp)\n+ sys.exit(0)\n+ elif query == "6":\n+ sign_par(inp)\n+ sys.exit(0)\n+ else:\n+ stop_err("Error, non-implemented query selected: " + query)\n+ except Exception as ex:\n+ stop_err("Error running impc_tool.py:\\n" + str(ex))\n+\n+\n+# 1-Given a gene id, retrieve all the phenotypes related to it (id and name)\n+def get_pheno(inp):\n+ head = sys.argv[4]\n+ mgi_accession_id = inp\n+\n+ gene_url = f"{impc_api_search_url}/{mgi_accession_id}"\n+ gene_data = requests.get(gene_url).json()\n+\n+ p_list = []\n+ id_list = []\n+\n+ if gene_data["significantMpTerms"] is None:\n+ stop_err("No significant MP terms found for this gene")\n+ else:\n+ for x in gene_data["significantMpTerms"]:\n+ p_list.append(x["mpTermId"])\n+ id_list.append(x["mpTermName"])\n+\n+ df = pd.DataFrame()\n+ df["MP term name"] = p_list\n+ df["MP term id"] = id_list\n+\n+ if head == "True":\n+ df.to_csv(sys.argv[2], header=True, index=False,\n+ sep="\\t", index_label=False)\n+ else:\n+ df.to_csv(sys.argv[2], header=False, index=False,\n+ sep="\\t", index_label=False)\n+\n+\n+# 3-Extract all genes having a particular phenotype or a set of phenotypes\n+# (e.g. relevant to a disease)\n+def get_genes(inp, g_out):\n+ head = sys.argv[4]\n+ target_mp_terms = in'..b' Values": g[""]}\n+ list_d.append(d)\n+\n+ for i in list_d:\n+ gen.append(i["Genes"])\n+ mes.append(i["Measured Values"])\n+\n+ if g_out == "sym":\n+ list_of_genes = pd.DataFrame(columns=["Gene symbol",\n+ "Measured Values"])\n+ list_of_genes["Gene symbol"] = mgi_sym_map(gen)\n+ else:\n+ list_of_genes = pd.DataFrame(columns=["Gene accession id",\n+ "Measured Values"])\n+ list_of_genes["Gene accession id"] = gen\n+ list_of_genes["Measured Values"] = mes\n+\n+ if head == "True":\n+ list_of_genes.to_csv(sys.argv[2], header=True, index=False,\n+ sep="\\t", index_label=False)\n+ else:\n+ list_of_genes.to_csv(sys.argv[2], header=False, index=False,\n+ sep="\\t", index_label=False)\n+\n+\n+# Function to map gene symbol to MGI ids\n+def gene_mapping(inp):\n+ tmp = inp.split(",")\n+ final_list = []\n+ sym_list = []\n+ for i in tmp:\n+ if "MGI:" in i:\n+ final_list.append(i)\n+ else:\n+ sym_list.append(i)\n+ del i\n+\n+ # symbol for symbols, mgi for MGI :\n+ # https://docs.mygene.info/en/latest/doc/query_service.html#available-fields\n+ if len(sym_list) != 0:\n+ mg = mygene.MyGeneInfo()\n+ ginfo = mg.querymany(sym_list, scopes="symbol", fields="symbol,MGI",\n+ species="mouse")\n+ empty = True\n+ discarded = []\n+ for i in ginfo:\n+ try:\n+ final_list.append(i["MGI"])\n+ empty = False\n+ except KeyError:\n+ discarded.append(i["query"])\n+ if empty and len(final_list) == 0:\n+ stop_err("Error: it was not possible to map the input.")\n+ elif empty:\n+ print("Warning: it was not possible to map any of the symbol ids. "\n+ "Only MGI ids will be used.")\n+ elif len(discarded) != 0:\n+ print("Warning: it was not possible to map these elements: "\n+ "" + ",".join(discarded) + "\\n")\n+\n+ return final_list\n+\n+\n+# Function to map phenotypes ids to names\n+def pheno_mapping(inp):\n+ tmp = inp.split(",")\n+ final_list = []\n+ sym_list = []\n+ for i in tmp:\n+ if "MP:" in i:\n+ final_list.append(i)\n+ else:\n+ sym_list.append(i)\n+ del i\n+ if len(sym_list) != 0:\n+ url = "https://raw.githubusercontent.com/AndreaFurlani/" \\\n+ "hp_mp_mapping_test/main/hp_mp_mapping.csv"\n+ mapper = pd.read_csv(url, header=0, index_col=2)\n+ empty = True\n+ discarded = []\n+ for i in sym_list:\n+ try:\n+ final_list.append(mapper.loc[i]["mpId"])\n+ empty = False\n+ except KeyError:\n+ discarded.append(i)\n+ continue\n+ if empty and len(final_list) == 0:\n+ stop_err("Error: it was not possible to map the input.")\n+ elif empty:\n+ print("Warning: it was not possible to map any of the "\n+ "HP term entries. Only MP entries will be used.")\n+ elif len(discarded) != 0:\n+ print("Warning: it was not possible to "\n+ "map these elements: " + ",".join(discarded) + "\\n")\n+ return final_list\n+\n+\n+# Function to map MGI ids to Gene Symbols\n+def mgi_sym_map(mgi_list):\n+ sym_list = []\n+ mg = mygene.MyGeneInfo()\n+ ginfo = mg.querymany(mgi_list, scopes="MGI", fields="symbol,MGI",\n+ species="mouse")\n+ discarded = []\n+ for i in ginfo:\n+ try:\n+ sym_list.append(i["symbol"])\n+ except KeyError:\n+ sym_list.append(i["query"])\n+ discarded.append(i["query"])\n+ if len(discarded) != 0:\n+ print("It was not possible to map these genes: " + ",".join(discarded))\n+ return sym_list\n+\n+\n+if __name__ == "__main__":\n+ main()\n' |
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| diff -r 000000000000 -r d319dc5f3ea8 impc_tool.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/impc_tool.xml Wed Oct 11 14:51:02 2023 +0000 |
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| b'@@ -0,0 +1,351 @@\n+<tool id="query_impc" name="IMPC" version="0.9.0" profile="22.05">\n+ <description>query tool</description>\n+ <macros>\n+ <xml name="selectSeparator">\n+ <param name="sep" type="select" label="Select the separator used in the file">\n+ <option value="t">tab</option>\n+ <option value="s">single space</option>\n+ <option value=",">Comma</option>\n+ <option value=";">Semicolumn</option>\n+ </param>\n+ </xml>\n+ <xml name="inputType">\n+ <param name="inp_sel" type="select" label="Select the type of input">\n+ <option value="str">Direct input</option>\n+ <option value="txt">Txt file</option>\n+ </param>\n+ </xml>\n+ <xml name="outputType">\n+ <param name="g_out" type="select" label="Select the type of gene ID in the output" help="Select if the genes in the output will use MGI IDs (default option) or Symbol IDs">\n+ <option value="mgi">MGI IDs</option>\n+ <option value="sym">Symbol IDs</option>\n+ </param>\n+ </xml>\n+ <xml name="header">\n+ <param name="head" type="boolean" checked="true" truevalue="True" falsevalue="False" label="Choose if include the header in the output" help="The default value is True"/>\n+ </xml>\n+ </macros>\n+ <creator>\n+ <organization name="INFRAFRONTIER GmbH" url="https://www.infrafrontier.eu/" email="info@infrafrontier.eu" />\n+ <person name="Andrea Furlani" email="andrea.furlani@infrafrontier.eu" />\n+ <person name="Philipp Gormanns" email="philipp.gormanns@infrafrontier.eu" />\n+ </creator>\n+ <requirements>\n+ <requirement type="package" version="2.25.1">requests</requirement>\n+ <requirement type="package" version="1.3.5">pandas</requirement>\n+ <requirement type="package" version="4.9.2">lxml</requirement>\n+ <requirement type="package" version="3.2.2">mygene</requirement>\n+ </requirements>\n+ <command detect_errors="exit_code">\n+ <![CDATA[\n+ python3 \'$__tool_directory__/impc_tool.py\' \n+ #if $query_type.selector == "7"\n+ \'$query_type.input\' \'$output\' \'$query_type.selector\' \'$query_type.head\' \'$query_type.g_out\'\n+ #else\n+ #if $query_type.inp_q.inp_sel == "str"\n+ \'$query_type.inp_q.input\' \'$output\' \'$query_type.selector\' \'$query_type.head\' \'$query_type.inp_q.inp_sel\'\n+ #else\n+ \'$query_type.inp_q.input\' \'$output\' \'$query_type.selector\' \'$query_type.head\' \'$query_type.inp_q.inp_sel\' \'$query_type.inp_q.sep\'\n+ #end if\n+ #end if\n+ #if $query_type.selector in ["2", "8", "9"]\n+ \'$query_type.g_out\'\n+ #end if]]>\n+ </command>\n+ <inputs>\n+ <conditional name="query_type">\n+ <param name="selector" type="select" label="Select a query">\n+ <option value="1">1 - Extract all measured phenotypes related to a gene</option>\n+ <option value="2">2 - Extract all genes having a particular phenotype or a set of phenotypes (e.g. relevant to a disease)</option>\n+ <option value="3">3 - Extract all phenotypes which are present in a particular gene set (e.g. genes together in a pathway)</option>\n+ <option value="4">4 - Extract images with a particular phenotype or a set of phenotypes</option>\n+ <option value="5">5 - Which IMPReSS parameters have been measured for a particular knockout</option>\n+ <option value="6">6 - Which IMPRess parameters Identified a significant finding for a particular knockout</option>\n+ <option value="7">7 - Full table of genes and all Identified phenotypes, no input needed</option>\n+ <option value="8">8 - Extract all genes names and ID measured in a specific IMPReSS pipeline</option>\n+ <option value="9">9 - Extract all genes and corresponding phenotypes related to a particular top level phenotype category</option>\n+ </param>\n+ <when value="1">\n+ <conditional name="inp_q">\n+ <expand macro="inputType" />\n+ <when value="str">\n+ <param name="input" type="text" label="Input gene" help="Enter a single MGI gene ID or gene symbol"/>\n+ </when>\n+ <when value="txt">\n+ <param name="input" type="data" format="tabular,txt" labe'..b'====================================================================+\n+ |Extract all measured phenotypes related to a gene |MP term name, MP term ID |\n+ +---------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------+\n+ |Extract all genes having a particular phenotype or a set of phenotypes |Gene accession ID/Gene symbol, Gene name, Gene bundle url |\n+ +---------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------+\n+ |Extract all phenotypes which are present in a particular gene set |MP term ID, MP term name, genes |\n+ +---------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------+\n+ |Extract images with a particular phenotype or a set of phenotypes |External sample ID, Gene symbol, Biological sample group, Sex, Colony ID, |\n+ | |Zygosity, Parameter name, Download url, Thumbnail url |\n+ +---------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------+\n+ |Which IMPReSS parameters have been measured for a particular knockout |IMPReSS Parameter name |\n+ +---------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------+\n+ |Which IMPRess parameters identified a significant finding for a particular knockout |IMPReSS Parameter name, p-value |\n+ +---------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------+\n+ |Full table of genes and all identified phenotypes |Gene accession ID/Gene symbol, Identified phenotypes |\n+ +---------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------+\n+ |Extract all genes names and ID measured in a specific IMPReSS pipeline |Gene accession ID/Gene symbol, Gene name |\n+ +---------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------+\n+ |Extract all genes and corresponding phenotypes related to a particular top level phenotype category|Gene accession ID/Gene symbol, Significant mp term ID, Significant mp term name |\n+ +---------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------+\n+ \n+ .. _here: https://www.mousephenotype.org/impress/pipelines\n+ ]]></help>\n+ <citations>\n+ <citation type="doi">https://doi.org/10.1093/nar/gku1193</citation>\n+ <citation type="doi">https://doi.org/10.12688/f1000research.25369.1</citation>\n+ <citation type="doi">https://doi.org/10.1038/nature19356</citation>\n+ </citations>\n+ </tool>\n\\ No newline at end of file\n' |
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| diff -r 000000000000 -r d319dc5f3ea8 test-data/test_output_1_1.tabular --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_output_1_1.tabular Wed Oct 11 14:51:02 2023 +0000 |
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| @@ -0,0 +1,10 @@ +MP term name MP term id +MP:0002135 abnormal kidney morphology +MP:0000194 increased circulating calcium level +MP:0002574 increased vertical activity +MP:0005633 increased circulating sodium level +MP:0001303 abnormal lens morphology +MP:0002965 increased circulating serum albumin level +MP:0001304 cataract +MP:0010052 increased grip strength +MP:0001402 decreased locomotor activity |
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| diff -r 000000000000 -r d319dc5f3ea8 test-data/test_output_1_2.tabular --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_output_1_2.tabular Wed Oct 11 14:51:02 2023 +0000 |
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| @@ -0,0 +1,5 @@ +MP term name MP term id +MP:0000194 increased circulating calcium level +MP:0011110 preweaning lethality, incomplete penetrance +MP:0001303 abnormal lens morphology +MP:0010053 decreased grip strength |
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| diff -r 000000000000 -r d319dc5f3ea8 test-data/test_output_2.tabular --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_output_2.tabular Wed Oct 11 14:51:02 2023 +0000 |
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| @@ -0,0 +1,21 @@ +Gene accession id Gene name Gene bundle url +MGI:1345144 sprouty RTK signaling antagonist 4 https://www.ebi.ac.uk/mi/impc/bulkdata-api/geneBundles/MGI:1345144 +MGI:2670964 terminal nucleotidyltransferase 5A https://www.ebi.ac.uk/mi/impc/bulkdata-api/geneBundles/MGI:2670964 +MGI:95490 fibrillin 2 https://www.ebi.ac.uk/mi/impc/bulkdata-api/geneBundles/MGI:95490 +MGI:95689 growth differentiation factor 6 https://www.ebi.ac.uk/mi/impc/bulkdata-api/geneBundles/MGI:95689 +MGI:1341886 ajuba LIM protein https://www.ebi.ac.uk/mi/impc/bulkdata-api/geneBundles/MGI:1341886 +MGI:1347352 hormonally upregulated Neu-associated kinase https://www.ebi.ac.uk/mi/impc/bulkdata-api/geneBundles/MGI:1347352 +MGI:109331 nucleoredoxin https://www.ebi.ac.uk/mi/impc/bulkdata-api/geneBundles/MGI:109331 +MGI:1914061 dual oxidase maturation factor 2 https://www.ebi.ac.uk/mi/impc/bulkdata-api/geneBundles/MGI:1914061 +MGI:1915958 RAB, member RAS oncogene family-like 2 https://www.ebi.ac.uk/mi/impc/bulkdata-api/geneBundles/MGI:1915958 +MGI:1917363 ciliary microtubule associated protein 1B https://www.ebi.ac.uk/mi/impc/bulkdata-api/geneBundles/MGI:1917363 +MGI:1920858 MARVEL (membrane-associating) domain containing 3 https://www.ebi.ac.uk/mi/impc/bulkdata-api/geneBundles/MGI:1920858 +MGI:106576 chondroitin polymerizing factor https://www.ebi.ac.uk/mi/impc/bulkdata-api/geneBundles/MGI:106576 +MGI:107185 chaperonin containing Tcp1, subunit 5 (epsilon) https://www.ebi.ac.uk/mi/impc/bulkdata-api/geneBundles/MGI:107185 +MGI:1931881 DnaJ heat shock protein family (Hsp40) member B12 https://www.ebi.ac.uk/mi/impc/bulkdata-api/geneBundles/MGI:1931881 +MGI:109327 BCL2/adenovirus E1B interacting protein 2 https://www.ebi.ac.uk/mi/impc/bulkdata-api/geneBundles/MGI:109327 +MGI:1913955 deoxyribonuclease 1-like 2 https://www.ebi.ac.uk/mi/impc/bulkdata-api/geneBundles/MGI:1913955 +MGI:107374 paired-like homeodomain transcription factor 1 https://www.ebi.ac.uk/mi/impc/bulkdata-api/geneBundles/MGI:107374 +MGI:1335088 proline-serine-threonine phosphatase-interacting protein 2 https://www.ebi.ac.uk/mi/impc/bulkdata-api/geneBundles/MGI:1335088 +MGI:95688 growth differentiation factor 5 https://www.ebi.ac.uk/mi/impc/bulkdata-api/geneBundles/MGI:95688 +MGI:107474 CD38 antigen https://www.ebi.ac.uk/mi/impc/bulkdata-api/geneBundles/MGI:107474 |
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| diff -r 000000000000 -r d319dc5f3ea8 test-data/test_output_3.tabular --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_output_3.tabular Wed Oct 11 14:51:02 2023 +0000 |
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| @@ -0,0 +1,79 @@ +MP:0002764 short tibia MGI:99960,MGI:108071 +MP:0001785 edema MGI:99960 +MP:0002968 increased circulating alkaline phosphatase level MGI:99960 +MPATH:590 fibro-osseous lesion MGI:99960 +MP:0001399 hyperactivity MGI:99960,MGI:1354170 +MP:0011100 preweaning lethality, complete penetrance MGI:99960,MGI:1344380,MGI:1917473 +MP:0010052 increased grip strength MGI:99960,MGI:96709 +MPATH:134 hyperplasia MGI:99960 +MP:0000218 increased leukocyte cell number MGI:99960,MGI:96709 +MP:0005013 increased lymphocyte cell number MGI:99960 +MP:0001363 increased anxiety-related response MGI:1354170 +MP:0001258 decreased body length MGI:1354170,MGI:108071,MGI:1915775,MGI:2443026 +MP:0003795 abnormal bone structure MGI:1354170 +MP:0001417 decreased exploration in new environment MGI:1354170,MGI:96709 +MP:0002797 increased thigmotaxis MGI:1354170 +MP:0002757 decreased vertical activity MGI:1354170 +MP:0011960 abnormal eye anterior chamber depth MGI:1354170 +MP:0010124 decreased bone mineral content MGI:1354170 +MP:0001402 decreased locomotor activity MGI:1354170 +MP:0004924 abnormal behavior MGI:1354170,MGI:96709 +MP:0013279 increased fasting circulating glucose level MGI:99502,MGI:1860418,MGI:103225 +MP:0005333 decreased heart rate MGI:3616082 +MP:0001406 abnormal gait MGI:96709 +MP:0010053 decreased grip strength MGI:96709,MGI:1924093,MGI:1915775 +MP:0001523 impaired righting response MGI:96709 +MP:0005559 increased circulating glucose level MGI:96709 +MP:0000745 tremors MGI:96709 +MPATH:52 lipid depletion MGI:1913564 +MPATH:42 lipid deposition MGI:1913564 +MP:0005419 decreased circulating serum albumin level MGI:1860418 +MP:0000219 increased neutrophil cell number MGI:1860418 +MP:0005567 decreased circulating total protein level MGI:1860418,MGI:1915775 +MP:0008810 increased circulating iron level MGI:1914361 +MP:0002875 decreased erythrocyte cell number MGI:1914361 +MP:0000208 decreased hematocrit MGI:1914361 +MP:0002874 decreased hemoglobin content MGI:1914361 +MP:0005566 decreased blood urea nitrogen level MGI:103225,MGI:1915775 +MP:0005343 increased circulating aspartate transaminase level MGI:103225 +MP:0011954 shortened PQ interval MGI:103225 +MP:0005344 increased circulating bilirubin level MGI:103225,MGI:95479 +MP:0002644 decreased circulating triglyceride level MGI:103225 +MP:0001415 increased exploration in new environment MGI:103225 +MP:0010511 shortened PR interval MGI:103225 +MP:0002574 increased vertical activity MGI:1915291 +MP:0003917 increased kidney weight MGI:1915291 +MP:0013292 embryonic lethality prior to organogenesis MGI:1344380 +MP:0000221 decreased leukocyte cell number MGI:95479 +MP:0005016 decreased lymphocyte cell number MGI:95479 +MP:0012361 decreased large unstained cell number MGI:95479 +MP:0001146 abnormal testis morphology MGI:2443598 +MP:0002152 abnormal brain morphology MGI:2443598 +MPATH:127 atrophy MGI:2443598 +MPATH:639 hydrocephalus MGI:2443598 +MP:0001925 male infertility MGI:2443598 +MP:0002092 abnormal eye morphology MGI:2443598 +MP:0005238 increased brain size MGI:2443598 +MP:0001147 small testis MGI:2443598 +MP:0000598 abnormal liver morphology MGI:2441730 +MP:0002833 increased heart weight MGI:2441730 +MP:0011110 preweaning lethality, incomplete penetrance MGI:2441730,MGI:1915775,MGI:2443026 +MP:0004738 abnormal auditory brainstem response MGI:2441730 +MP:0000599 enlarged liver MGI:2441730 +MP:0009476 enlarged cecum MGI:2441730 +MP:0005565 increased blood urea nitrogen level MGI:2441730 +MP:0001284 absent vibrissae MGI:2441730 +MP:0004832 enlarged ovary MGI:2441730 +MP:0005084 abnormal gallbladder morphology MGI:1915775 +MP:0000274 enlarged heart MGI:1915775 +MP:0009142 decreased prepulse inhibition MGI:1915775 +MP:0000692 small spleen MGI:1915775 +MP:0030610 absent teeth MGI:1915775 +MP:0001325 abnormal retina morphology MGI:1915775 +MP:0000266 abnormal heart morphology MGI:1915775 +MPATH:64 developmental dysplasia MGI:1915775 +MP:0000494 abnormal cecum morphology MGI:1915775 +MP:0001120 abnormal uterus morphology MGI:1915775 +MP:0000689 abnormal spleen morphology MGI:1915775 +MP:0009709 hydrometra MGI:1915775 +MP:0002060 abnormal skin morphology MGI:1915775 |
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| diff -r 000000000000 -r d319dc5f3ea8 test-data/test_output_9.tabular --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_output_9.tabular Wed Oct 11 14:51:02 2023 +0000 |
| [ |
| @@ -0,0 +1,4 @@ +Gene symbol Significant MP terms Ids Significant MP terms Names +Cacna1s ['MP:0001697', 'MP:0001785', 'MP:0003231', 'MP:0005388', 'MP:0001491', 'MP:0001575', 'MP:0003743', 'MP:0001914', 'MP:0011100', 'MP:0005560'] ['abnormal embryo size', 'edema', 'abnormal placenta vasculature', 'respiratory system phenotype', 'unresponsive to tactile stimuli', 'cyanosis', 'abnormal facial morphology', 'hemorrhage', 'preweaning lethality, complete penetrance', 'decreased circulating glucose level'] +Ndel1 ['MP:0001697', 'MP:0003984', 'MP:0002111', 'MP:0005388', 'MP:0011100'] ['abnormal embryo size', 'embryonic growth retardation', 'abnormal tail morphology', 'respiratory system phenotype', 'preweaning lethality, complete penetrance'] +Zfp536 ['MP:0003019', 'MP:0005564', 'MP:0005388', 'MP:0001575', 'MP:0001399', 'MP:0011100', 'MP:0005641'] ['increased circulating chloride level', 'increased hemoglobin content', 'respiratory system phenotype', 'cyanosis', 'hyperactivity', 'preweaning lethality, complete penetrance', 'increased mean corpuscular hemoglobin concentration'] |
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| diff -r 000000000000 -r d319dc5f3ea8 test-data/test_query_1.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_query_1.txt Wed Oct 11 14:51:02 2023 +0000 |
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| @@ -0,0 +1,1 @@ +MGI:1923523 \ No newline at end of file |
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| diff -r 000000000000 -r d319dc5f3ea8 test-data/test_query_2.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_query_2.txt Wed Oct 11 14:51:02 2023 +0000 |
| b |
| @@ -0,0 +1,1 @@ +MP:0002110 MP:0000559 \ No newline at end of file |
| b |
| diff -r 000000000000 -r d319dc5f3ea8 test-data/test_query_3.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_query_3.txt Wed Oct 11 14:51:02 2023 +0000 |
| b |
| @@ -0,0 +1,1 @@ +MGI:1913564 MGI:1915291 MGI:1914361 MGI:1915775 MGI:1354170 MGI:103225 MGI:2441730 MGI:108071 MGI:2443598 MGI:106643 MGI:1917473 MGI:1338073 MGI:1924093 MGI:99960 MGI:99502 MGI:95479 MGI:1344380 MGI:1860418 MGI:1354721 MGI:3616082 MGI:96709 MGI:2443026 \ No newline at end of file |