diff --git a/case_studies/CLDN16/CLDN16_genotype_phenotype_corr.ipynb b/case_studies/CLDN16/CLDN16_genotype_phenotype_corr.ipynb deleted file mode 100644 index 607da972..00000000 --- a/case_studies/CLDN16/CLDN16_genotype_phenotype_corr.ipynb +++ /dev/null @@ -1,852 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "bad892fb-a892-44b0-99a1-c4a9a921f5af", - "metadata": {}, - "source": [ - "# CLDN16 gpc" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "3441db9f-ed83-422e-ba15-e78b525f0359", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using gpsea version 0.1.1dev\n" - ] - } - ], - "source": [ - "import gpsea\n", - "from gpsea.preprocessing import configure_caching_cohort_creator, load_phenopacket_folder\n", - "from gpsea.preprocessing import UniprotProteinMetadataService, VVMultiCoordinateService\n", - "from gpsea.analysis import configure_cohort_analysis, CohortAnalysisConfiguration\n", - "from gpsea.model import VariantEffect\n", - "from gpsea.model.genome import GRCh38\n", - "from gpsea.analysis.predicate import PatientCategories\n", - "from gpsea.view import CohortViewable, ProteinVisualizable, ProteinVisualizer, ProteinViewable\n", - "from IPython.display import HTML, display\n", - "import hpotk\n", - "\n", - "print(f\"Using gpsea version {gpsea.__version__}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "48ac323f-38f2-4d9d-9b88-f3b80bc8bb89", - "metadata": {}, - "outputs": [], - "source": [ - "import hpotk\n", - "hpotk.util.setup_logging()" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "70abc6eb-9fd3-4ee0-ba9a-40b24dfc4c00", - "metadata": {}, - "outputs": [], - "source": [ - "fpath_hpo = 'https://github.com/obophenotype/human-phenotype-ontology/releases/download/v2023-10-09/hp.json'\n", - "hpo = hpotk.load_minimal_ontology(fpath_hpo)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "4c099b9b-76ef-4a18-9b35-2b01ae14aa02", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Patients Created: 100%|██████████| 46/46 [00:38<00:00, 1.19it/s]\n", - "Validated under none policy\n", - "No errors or warnings were found\n" - ] - } - ], - "source": [ - "from gpsea.preprocessing import configure_caching_cohort_creator, load_phenopackets\n", - "from ppktstore.registry import configure_phenopacket_registry\n", - "\n", - "cohort_creator = configure_caching_cohort_creator(hpo)\n", - "\n", - "cohort_name = 'CLDN16'\n", - "phenopacket_store_release = '0.1.19'\n", - "\n", - "registry = configure_phenopacket_registry()\n", - "with registry.open_phenopacket_store(phenopacket_store_release) as ps:\n", - " phenopackets = tuple(ps.iter_cohort_phenopackets(cohort_name))\n", - "\n", - "cohort, validation = load_phenopackets(\n", - " phenopackets=phenopackets, \n", - " cohort_creator=cohort_creator,\n", - ")\n", - "del phenopackets\n", - "validation.summarize()" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "ca31b6e5-760c-4de4-af04-038e87f46a5e", - "metadata": {}, - "outputs": [], - "source": [ - "CLDN16_transcript = 'NM_006580.4' # version number important, nucleotide numbering changed compared to version 3" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "fe5344f4-3cf4-49c5-8bf8-810c0bb17c18", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - " \n", - " Cohort\n", - " \n", - "\n", - "\n", - "\n", - "

GPSEA cohort analysis

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Successfully loaded 46 individuals.

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No errors encountered.

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\n", - "

Top 10 HPO Terms

\n", - " A total of 79 HPO terms were used to annotated the cohort.\n", - "
HPO TermIDSeen in n individuals
NephrocalcinosisHP:000012146
HypercalciuriaHP:000215041
HypermagnesiuriaHP:001260832
Renal insufficiencyHP:000008332
Renal magnesium wastingHP:000556730
Elevated circulating parathyroid hormone levelHP:000316529
PolyuriaHP:000010323
PolydipsiaHP:000195922
HypomagnesemiaHP:000291720
Recurrent urinary tract infectionsHP:000001016
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Top 10 Variants

\n", - " Variants are shown according to NM_006580.4. A total of 60 unique variants were identified in the cohort.\n", - "
CountVariant keyVariant NameProtein VariantVariant Class
173_190404787_190404787_G_Tc.243G>Tp.Leu81PheMISSENSE_VARIANT
63_190408368_190408368_G_Ac.437G>Ap.Arg146HisMISSENSE_VARIANT
53_190402342_190402342_C_Gc.120C>Gp.Ser40ArgMISSENSE_VARIANT
43_190408423_190408423_G_Tc.492G>Tp.Trp164CysMISSENSE_VARIANT
33_190404768_190404768_T_Cc.224T>Cp.Leu75ProMISSENSE_VARIANT
3SO:1000029_HGNC:2037_CLDN161000029_HGNCNoneTRANSCRIPT_ABLATION
23_190402370_190402370_T_Cc.148T>Cp.Cys50ArgMISSENSE_VARIANT
23_190409982_190409982_C_Gc.654C>Gp.Tyr218TerSTOP_GAINED
23_190404908_190404923_--16bp--_--23bp--c.364_379delinsTACCGGTCTGGCTGGACTAGCAAp.Ala122TyrfsTer22FRAMESHIFT_VARIANT
23_190409949_190409949_T_Gc.621T>Gp.Tyr207TerSTOP_GAINED
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Diseases

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Disease NameDisease IDAnnotation Count
Hypomagnesemia 3, renalOMIM:24825046
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Variant categories for NM_006580.4

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Variant effectAnnotation Count
STOP_GAINED6
TRANSCRIPT_ABLATION3
MISSENSE_VARIANT45
FRAMESHIFT_VARIANT3
SPLICE_DONOR_VARIANT2
SPLICE_DONOR_5TH_BASE_VARIANT1
INTRON_VARIANT1
\n", - " \n", - "\n", - "\n", - "\n", - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from gpsea.view import CohortViewable\n", - "viewer = CohortViewable(hpo)\n", - "display(HTML(viewer.process(cohort=cohort, transcript_id=CLDN16_transcript)))" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "c79a33b1-53a8-4f78-aeb8-9939d245e73d", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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jtHTp0lTbPXz4cJbHCtiKvb29TIXzKSaXq5xvRaW9QxrOtqypIs9UyYLIAADIPHt7e1Vr0lBXK5XTX1VLyeFIiAr9/Ke8T12Uy/VImXR3Cqabfnl1pVZ5XQ2uqEKVyys4oPITPx1TkhM7dsv/u02Z3t/OMJRv8z+61KSeChQunIWRAQAAABlDIuIxNWzYMMvPFy9e1NGjRxUQEKC33347B6OyjRYtWqhFixaW53FxdxfZ/e9//5ti/XvPzf22b9+uCxcuqFy5clkaI2BrJepU1/FODVTpyzUP1U6ck4Ou1quk8vnyZVFkAAA8HN/8+eXbsY0iIiJ0pd1zOnQqRDGRt3XTlKA89k7yKlxAviWKq7yv71N1V39cXJwiT4bI++yVh2rHb+UO7Xmxlgq0JxEBAACAnEMi4gng6uqq+fPna+XKlU9kIuJexYrdnZ7G3d1drq6uKdYJCAjQkiVLUtzWvn17LV26VN7eTEuDx0u+AgV0ulkN3fxlt7xCrma6nf2DX1K5xvWeqgs5AIDHg4eHhzwqlJcqlJckbdu2TbXq1s3hqHJOWFiY8m/a99DtOIdHKeFimBITE5+akSQAAAB49PAv0SdArly5JEkJCQk5HEnWql+/vkwmk9zc3JQ3b17Z2dkpJCREknT69Okcjg7IXiaTSQFNn9W+kV0VkyvlJFxazjQLlPm5mspXsGAWRwcAALJabEyMnC9ey5K2nMKjLKOKAQAAgJzAiIgnhKenp8LDw7VixQq1atUqp8PJErVr19bvv/+uqKgoRUXdnRff1dVVhw8flo+PTw5HB2Q/FxcXVWvfUjsNQ1XHLFCuc2Hp2s8wScc61ld492YKbFjPxlHicXP79m2d+mufbl26LCM+QSaznTx886hEjUB5eHjkdHgA8NRKjE+QQ3xilrRlSkhUYmLWtAUAAABkBomIJ0TSF4vWrVvLZDLJ2dlZZrPZqo7JZFJ4eHhOhJcpEyZM0IQJE3I6DOCR4unpqaCu7bQ3t5c81+xUqcW/ySkyJsW6hqTrpQro0MCWKlC/pp6pXJEpmWBx/do1Hdm0VeZjISrx3SZVPHpeJuNu4uqGX34d6dZId8oVV5n6teVbIH9OhwsATx1HVxfd8XbPkrbi3J3l6OiYJW0BAAAAmUEi4gkRGRlp+dkwDEVHR+dgNABsycXFRbVav6CL1QP013PPyO7sJXnvOynPI+dkFxevWC933XimtG6WLSKvksUVWPOZB66pgqdT6MnTOv3jr3pm7CI534qy2mYypNynLin3mIWKdXPSnvfP6XbrJipesXwORQsATydvb2/tr1dZJdbueah2EuzNisvrnewmJQAAACA7kYh4QowdOzanQwCQjUwmkwoWKaKCRYooNjZWN27cUMTVMJ0NPS9//5Iq7usjDw8PFqVEMlcuXNTZH1ar9ohvZZeQ+jQdjrfvKOij+frrTqzsezmrsH+JbIoSAODq6iqjdBFF53KTy63bmW7nfL0KKly1UhZGBgAAAGQciYgnxLBhw3I6BAA5xNHRUfny5VO+fPl06eYNFS/pn9Mh4RGVmJioQ79uUt1R36WZhEhiMqTAj5fo9yK+yl+sqOzt+acDAGQXv9rVdbpNbZWfuz7TbZxtG6xaZUplYVQAAABAxnGrLAAAT4kLISEq+Otfso+Nz9B+dgmJ8luyTWePHLNRZACAlOQrUEBXG1dTpG+uTO1/rn4leZUrKQcHhyyODAAAAMgYEhFPkO7du8vOzk4mk+mBDwDA0+vMzj0qvnpXpvYt/PsBnd97QIZhZHFUAIAHMZlMeual5/XXuJ6K9nLL0L6Xq/gpZFBrVaxfx0bRAQAAAOnH/ApPiLp16+qPP/5ItQ6JCAB4eiUkJMh04aoco+5kan9zXIJcT15QdHQ0i58DQDZyc3NTtY4v6U97syqNX6Q8Jy6mWj/RzqQzzZ7Rpd4tFPRCM9aLAgAAwCOBRMQTIikJsWnTJl25ckWdOnVSzZo1tWPHDrVo0UJr1qxRpUosUgcAT6vY2Fg5hUc9VBtO1yMUGxtLIgLA/2vvz8PzLOu88f99J2maNG3TFbrQ0rK1pQVaoCy17CIwiH5lEUZwGbefDogz6qPiMs4wgit+dR7G5WFGdIRHK3XGBURERZG1UBZZWsvWvQW6r0mz3N8/+msktkALvXon4fU6jhxHc57ndeVz3zmbXHfe93md7GH9+/fPMX97dubsMzyPPTE/o396V0b9/k+pbmnrGLO5sSHPnD0tzx1/SEYcenCOmXyoEAIAgC5DENGD9O3bNyeddFJuuummJElLS0uS5KabbkptbW3+9Kc/VbI8ACqoVCql/Cr/IFWurrK6DqBC6urqMuXUk9J6UmsWnnhM7n7osaSpOWlrT7mmJjX9GzL22CMzYfhwP6sBAOhyBBE9SO/evZMkb3jDG5Iky5cv7+jr379/Vq5cWZG6Xq3zzjsvM2fO7NTWv3//rF27tkIVAXQ/tbW1aRrY91WdY/PeA1JXV7ebKgLglaipqcl+B0/IfgdPSJLMnj07RxxxRIWrAgCAlyaI6EG2/WG+V69eSZIlS5Z09HXXEOKII47IAw88kCTp169famtrs27dumzevLnClQF0L1VVVakdtXc2DumfhhXrdvn45oa6tI4d0RF6A9A1uC4GAKA7cNPQHqK2tjatra1ZsWJFkmTvvfdOsvVWHNuWZne3e3rfdtttHSHExo0bs27duqxYsSJbtmzJli1bKlwdQPez3+uOztNvPe4VHTv/jUdl7DHecQsAAADsOisiurF3v/vd+e53v5skmT9/fu66666OsGH58uUZOXJkli5dmmRrMPHCWzV1B+ecc06S5AMf+ED69OmT++67LxMnTux2gQqQrF69Ok/dNSublz2ftLYlNdWpHz40+087KgMHDqx0ea8ZQ4YMyeOvm5RNM25Pn5Xrd/q45n71WXbG1Bw/alSB1UFllMvlLF2yNI/f9Xia1jal3FZOVV1VRhwwIhOOmJD6+vpKl1gR5XI5zy1fnqfvui+tq9Zu3Yegd68MGDsq+089PA0NDZUukd2opaUlC+b8OcsefjzZ1JRSknLf+uxz+CEZdeABqanxspHda926dXlq7j1Zv3ZxStmSpCa964dm/wnTM2jQoC65z8mWLVuy4JnHsmzRoymVNyUppVTdN/uMOSKj9j0g1dXVlS4RALo0V5Td2LXXXptrr702DQ0Nufzyy/ORj3ykU/8Lb83UHa1evTrJ1vvevvBCtKqqKo8//njGjRtXqdKAndTc3Jz7f/Gr9Jn1eA66/rb0X7qqo2/dyEF56m0n5fGjDs6RZ53ulj97QKlUyhFvOiOzNmzKMf/rP1O3btPLHrOlvjb3XvHOTH7T6al6lZtdQ1ezevXq3PmLO7P+1vXZ8LMNKa8vd/Q9N+m5zL9ofkYeOTJTT5r6mpr/69evzwM/uzlDfv9wJv/kjtSv2ZgkKSdZOW5kHr3olNQceXAmn3qSP7z1AM88+ngW3X5vxtxwe6b98bFUt7UnSVp71WTRyYfmjre8LgecPD37HLh/hSulJ2htbc3se25KddP92b/PdRk4aH5H34aWoXn64fPzeF6XI499c5cKgp/884NZNv/OjK3/UaYPuCdVpbYkSWt77yxc9Pr8cd6bc9CkUzNinzGVLRQAujBBRDfWq1evtLS0ZOPGjfnoRz+aj370oxk6dGiuv/76nHrqqZUub7e57777Ul1dnTFjxmT+/Plpa2vLhAkT0t7eXunSgJewZcuW3D3zZznss9/PwGee3a6//5JVmfKVn2T12Dtyd3Nzpp33/6S2trYClb629O3bN1PO/39yT01Nxv/bT7P3n55Jqbz9uHKSFeP3yWP/+JYccvaZGWDlCj3M6tWr8/vrf58Vl61IecP2/wlaH23Nik+uyMbTNqa5uTnHnXFcl3yH7u62fv36zP7hf+foT16b+tUbOvWVkgz585IM+ex/Zcn0ibm3qTnHvOmM11RI09M88eDD2fBfv8hx3/jpdr8LalpaM/aWB7Lvbx7K7E8+l7YL35R9J3gjEK9ca2tr7vrDf2dC3b9m6MBHt+vv2+v5HNp4ddZvmZl7bm/KMcef3yXCiLmP3Zsty7+X6YO/nb/+NVBT1Zz9+t6UfRtuyX2Pfzbt7Rdmn9FCOwDYEa8aurEtW7akXC7nDW94Q8e70Z5//vm84Q1vSKlUygEHHJCFCxdWuMpXr6qqKq2trXnyySfT2tqaqqqqlMvlfOxjH6t0acBLeOhXv80h/3LdDkOIFxr4zLM59J+vy0O/+u0eqozGxsYce+G5WfnNj+UP1/xD5r31uKzaf1jWjRiUVfsNy5NvPia3f+fSLP/2x3L029+awUOGVLpk2K3a29tzx8/uyIpP7jiEeKHNt2zOou8vyrxH5+2h6iqnXC7ngZ/dvMMQ4q+NvOOxDP/OzzPvvtl7qDp2t9WrV2fljb/P5K9vH0K8UFVbe4648sdZ9MvbsmHDS88LeCmPPvT7HFj7lQyt2z6EeKF+tctzRP9P54F7btxDlb24Fc8/n/VLf55DGrcPIV6outSaowZdnqcfv8kG8gDwIqyI6AFuueWWJMmmTZsyffr0PPTQQymXy3nqqaey7777plQq5eijj87dd99d4UpfmenTp2/3+e23357rr78+X/3qV7cb/9BDD+WKK67Y4bnuuuuuJH+57RNQjM2bN6dt7jMZ/MTSnRo/6MmlaZv7TDafurlLvPPttaB3796ZOO3otB8zNctef3yWLVyS1s2b81zz5ow/eEKmj9nXLVfosRYvWJx1N61LeeNLhxDbbPzJxjxx5hM5aNJBPXpVxHPPPpvBt//pZUOIbcbcMjt/OPe4HDT1CKsiuqEn77w3B3/rpuzMjK4qlzPh2zflqSkTctjJJxReGz1PS0tL1q/8cyYPuX+nxvevXZreGx/KunWnpX///gVX9+KenHtHDun3nZcMIbapKrVlXMN/5Ol5R2TiYa8rvjgA6GYEET1Inz598sADDyRJnnrqqZx66ql55plnUi6Xc88996RUKqVc3rkX3F3J5MmTO31+yCGH5Pbbb8+mTTu+t/kVV1yRmTNnvuQ558yZs7vKA3bgmQf/lP2u/90uHbPf9b/L09OPyMRpRxdUFTtSVVWVkfuOzsh9RydJ7rjjjozaf78KVwXFmnPvnGz65cvvkdKhLdl498Y8f/rz2WuvvYorrMKeueu+HDbzjp0eXyonw3/zYJadenxGjh5dYGXsblu2bEnzU4vSf9mqlx/8/zfoyWV59In5aTthuqCaXbZw/p+zb91Lv0b7awf0uT5Pzj0+hx91WkFVvbSmpqa0b34yDX1W7vQxe9U/kjnL56T9kGMFtADwVwQRPdT++++fBx98MMcee2y3/aP7tj0wZs2a1al99uyttwB4sXfGfPrTn37Rc951111ZunRpJkyYsPsKBbazevHSjH9s124NN/SxhXly8c6toAB4NZpWN6W8adfenLHxjo15fnHPDiJaVq3d6dUQ2+x179wseWaRIKKbWbduXQb96ZldOqaUpPHJpdm4cWNF36FO97R6xdOZWPfwLh0zoPeCbFzzXEEVvby1a9dmSK+dW8GxTamU9K1ZmKampvTp06egygCgexJE9EAnnHBC7rjjjk6bOZdKpRxyyCEVrGrXnX322ZkxY0buvffeTu3bPv/kJz+5w+MmT56cG264YYd95513XmbOnJmBNl2FQrW3taXUtmsbypfa2tPe1lZQRQB/UW7b9RWi5ZZyWppbCqim6yi9gp/BVVta07alZz8vPVF7e3uqNzXv8nHVm7ekze9qXoG2ttZUV2/Z9QPLu3Y9uTu1tbWlurRxl4+rTpP/JwCwA9YK9hBve9vbUltbm1KplNtvv70jhBg5cmRmzZqV9vb2PPzwrr0DpdJ+9KMfddxOqqqqKgMHDuzYqLpXr165+OKLK10i8CJ69e6dLQ11u3RMS0Pv9Ordu6CKAP6iqveuXwJXNValvn/P3sOmvXdtdjWiaW7sk9p+DYXUQ3Fqa2vTtPeAXT6ueXC/1NbW7v6C6PFqa/ukqW3XVtK0latTqqrcfKutrU1T+/BdPq65faD/JwCwA4KIbuwzn/lM6uvrUyqV8sMf/jAtLVvfjda/f/9cd911KZfLWbx4caZOnVrhSl+5JUuWpK6uLuVyOWvWrEm5XE6/fv2yZcsreDcNsMeMnDwxC087fJeOWXDaERk5eWJBFQH8xeBRg1M1atcugxvPbszo/Xr27YcG7jc6Kybss0vHLDx7ekYePK6giihKY2NjVh+2f9p3YfP11l412XjgPm43wysycszhWbj5rF06ZunG12XYyIMLqujlDRo0KM+3HJ1d2Waxpb0+LVVj0tubawBgO4KIbuyKK65IU1NTkqSuri4f//jHUy6Xs3bt2lx44YUVrm73GD58eDZv3pxyudzxsW7dukqXBbyMkWPGZMnpU3f6nbXlJEvPmJqRY8YUWBXAVpOOnZQBFw3Y6fGlgaU0HtCY+vqevSJi/yOn5KmLTtnp8Vv69E7TxDH2C+iGSqVShk0an2VHHbjTxyw+6dCMOvzQlHYhvIBthg4dmhWt09JW3vmNzuc3n5t996tcEFFVVZWhw8bnuc07f4vjBRtPy5gDjiqwKgDovgQR3Vh1dXXe+MY3plwuZ/PmzfnSl75U6ZIAkmx94TZq6mF5/D2n7dT4x997WvY58rBUVfm1BBSvsbExQ44dktrDd+LWGdXJ4E8NzpQTpxRfWIX16dMntUcenMXHT3rZseVS8sBlb82446ftgcoown6HTcoT/78z09T48iscNg7tn/kXnZLRBx2wByqjJyqVSjlg/LQ8vOYfdmqFwZPr35JBww5Pr169ii/uJew/7sjM2XRpmtv6vuzY9VuGZ0nLeRmxz5jiCwOAbshm1d1Ya2trpUsAeFH7Tz40j7xjff5UW5OJ//GrVLdsv2lfW6/qPPbe01O64A3Zf/KhFagSeK2afsb0tGxpybKrl6Xp9007HFPqV8rgzw7OkWcfmUGDB+3hCitj8utPyr2bm7OlX33G/vK+lHbwB8MtDb3zwCffmuHnnJ6hI3b9/ul0DbW1tTn8nLNyT1t7pvzLdWlcvHKH41btNyx/+uzbMvXsN6amxstHXrl9Rh+YTRvPzwNLqnNo4zfSq2r7DdPby9WZt/6CbOzz9hx+SOWDzrq6ukw+6pzcfW9bjmj8l/SrXbbDcSuaxuXRjZ/O0ce9JdXVO7/qAwBeS1xJAlCYQ45/XRbuPTR3HHtwBtz354y85f702tSclj69s+S0I7Nm6riMPWpKRo87qNKlAq8xNTU1OeUtp+Th4Q9n0eOLsv7X69M0uynllnKqBlal8dzG9BvXL4efdHiGDB1S6XL3mKqqqhx91ul5Yvje+cPZ0zPsdw9lr3vmpHpLa5r698nCs6en+eAxGXfCtAwdPqzS5fIq9e/fP0e97Zw8Nmxomp9alH1n/jH9Fj2fckpZt9+wLDx7evocMDrHnDg9dXV1lS6XHuCgCVOztP/Q3D3n0PTNwxlVd2Nqq9entb0uy5pPyorW12XU2Ck5/IBDusxtwAYMHJipx12Uxx4alpaVT2Xf3jekb6+lKacqa1sOyMKmt6TfwAMy7cQTbVINAC9BEAFAoUaPOyijDjowq/5mVZ694Mm0btqc55o3ZcoxR+fQQYO6zItM4LWnqqoqU6ZNyWHHHJbFr1+c5xc+n+dWP5d9Ru6TsePHpm/fl78VR09UVVWVcUcdkQOPnJLlpx6fZfMXZcmqlRk9fHjGjT/InhA9TJ8+fTL1jaenubk5i095XRY9vyLL1q/LAQfsn2MOPKDit8ah5xkxckxGjByT1av/JsuXvCUtzRvz7MqmHHrYkZm4195d8tqwoaEhR73uzWlubs6i+a/P6o0rsuz5jTnwgAMzbd8DrBYCgJ3gtyUAhSuVShk8eHAGTxucJLnjjjsyePDgClcFsFVVVVVGjxmd0WNG54477sghR+78xqQ9WVVVVUaMGpURo0Zl9R13ZPxRR1a6JArUu3fv7D9p68bAa++4I/sdPKHCFdHTDRw4MAMHHptk67Xh3nt3/VVWvXv3zgHjtt5OdO0dd2Ts/uMrXBEAdB92BQUAAAAAAAojiAAAAAAAAAojiOgh7rvvvlRVVeWSSy6pdCkAAAAAANBBENFDLFy4MOVyObNnz06S3HbbbSmVSrngggsqXNkr9773vS+lUmm7j4MPPrjSpQEAAAAAsJNsVt2NbfvDfL9+/TJ69OgkWzcVTJJVq1YlSRYsWFCx+l6te+65J0lSV1eXhoaGtLS0ZN26dZkzZ06GDBmSFStWVLhCAAAAAABejiCiG+vXr182bNiQdevW5dFHH02S3HXXXamvr8+YMWOS/CWY6I4eeeSR7drWrl2bAQMGZOXKlRWoCAAAAACAXdV9/0pN1q1bl/b29pTL5bz3ve/taG9qasrcuXOTbA0mamtrM3HixPzkJz+pVKm7TWNjY6VLAAAAAABgFwgiurGPfexjHf8+/fTTkyTHHHNMyuVy/uEf/qGjr6WlJY8//njOPffcPV3ibnHfffdlxowZueyyy9K/f/8kW29LBQAAAABA1yeI6Mauuuqqjn0i/vZv/zbJ1tAhSaZPn57kL8HE3Llzc+qpp1as1lfjmGOOyQUXXJAvfvGLWb9+fZLkF7/4RYWrAgAAAABgZwgiurG3v/3tGTx4cEqlUkcAMXv27JRKpVxwwQVJ/hJMjBs3Lr/+9a8rVuur8cEPfjBTp07NsGHDOtqeffbZClYEAAAAAMDOsll1N/Zf//VfHf+eMWNGLrjggtTW1qa9vT2tra1J/hJMVFVVZeTIkVm4cGGlyn3Frr766k6fl0qlvOc978nb3/729OrVa7vxDz30UK644oodnuuuu+5KkqxevXr3FwoAAAAAwHYEET1ETc3Wb+Xhhx+eu+++uyOYqKurS7lcTnNzcxYtWlThKnePwYMHZ+XKlfnYxz6Wb3zjG9v1X3HFFZk5c+ZLnmPOnDlFlQcAAAAAwAsIInqIPn36JEnHZs7bgonJkyfn7rvvTpJs2rSpMsXtZttuN/X000/vsP/Tn/70ix571113ZenSpZkwYUIhtQEAAAAA0Jkgooc444wzUi6XOz4fNGhQkmTfffftaNsWVnQX3//+9/POd76zU9uyZcuybt26JC8eOEyePDk33HDDDvvOO++8zJw5MwMHDty9xQIAAAAAsEOCiB7qpJNO6hRMdEfvete78q53vSt1dXXp27dvNmzYkKampiRJ3759c8wxx1S4QgAAAAAAXo4ggi5r9OjRWbhwYZqamjoCiCQZP368PR5eo9ra2vLnWbPz/J+fTFVza3oNHZhxJ03fpRUuK557LvP+cFfaVq1Nua42e08clwMPn5yqqqoCK+/6Vq9alT8/+vu0ND2f9vTOXiPG56AJU1NdXV3p0qBili9anCfvnJXymvUpN9Rln8mTMnbSwSmVSpUuDaBb+uvrsGGTxueAKYcVeh228JmFefzux7Nl3ZbU9K3JuCPHZb9x+/lZXrByuZwn5z2cZQv/lFI2papmUA6ceFz22mt4pUsDACpEEEGXtWDBgkqXQBdSLpdzz89uyuj/9yeZcOdjKZWTTYP6ZvZnl2XiRWdn0JAhL3uOZxcvyVPX/TSHf2FG6tZtSnuplAWnHZ77Ln5Ljn7j6XvgUXRNK1c+n8fvvy5HDPjX9GlYnXK5lMUrj8s9f/xwpp3wFi/UeU1aOHdell/38xz1//5Pajc1p626Kk+cd1z+9L435bCTT6h0eQDdzrOLFuWp636Ww7/4463XYVWlzD/9iNz/wbfkqDeeVsjXnPvw3Pzpv/6UNd9ckzQl6ZWsffvarH332hz+usML+Zps9cCsW9K4+TuZPvAXqSq1pbmtbx586ONpPfiijNhnbKXLAwAq4LX9FmCg23h22bIM/MXdGXXH1hAiSfqs2pCp//SDzPndH3fqHH/+/Z056p+vS926rRu3V5XLGfur2an9/QNZvXp1UaV3eXP+9LscNfCf0qdm63NQKpUzqu/tGdB+c557dnmFq4M9r729PU/fdV+OvHJGajc1J0mq29oz/kd/yOZ7H8mmTZsqXCFA91IulzP3D3d3vg5rL2e/X96fmtsfLOQ6rK2tLX++589Z87U1W0OIJGlJ1n93fRbctyDNzc27/Wuy1bp169K+/s4c0O+nqSq1JUl6V2/I1EH/kicev73b30IYAHhlBBFAt7D80bkZeesD27XXrd+c9udWvewLmi1btqR28fOpaW7Zrm+fm2Zl+dwndlut3Um5XE55y7PpXb1hu7596m7J8sWPVqAqqKwNGzZkwOMLUrWDnysjf3FPnl2ytAJVAXRfW7ZsSe9Fz6VmS+t2ffvceG+enffUbv+aa9asyeb7N++wb/2v12fFihW7/Wuy1bPLnsk+tTdu115daktD1dPZvHnH3xcAoGcTRADdQk1d77TW1+6wr73m5fcxqKqqSlvvXjvsa2moS3Vd71dVX3fWnhd5Xsr1qe5Vt4ergcqrrq5Oa8OO535LY0Nqanf8fwaAHXup67DWht6prtvxNd6rUV1dnaq+O365W9NYYx+sAlVX16a13HeHfa3les89ALxGCSKAbmHUYZPy1IUnb9e+euzeaRg94mX3MaipqUnVvsOyYe8BndrLSZ654MTsM+7A3Vht91EqldKn/+isbt53u76nNl2Y0WMPq0BVUFkNDQ3ZNG5UmvvVd2pvrypl0ZuOzbARIypUGUD31KtXr1TtOzwbhjZ2ai8nefpvT8o+B+3+67DGxsb0mdInqf+rjpqk4ZSGDB06dLd/TbYaOWq/PLP5vJTLna/PN7UOTFvNfund+7X7BiAAeC0TRADdQmNjY/q+YVru/+R5WTdiULY09M6CUybn4cvfmUknH79T5zj0tFNy/xffnUXTJ2ZLfW3WjBqSWf98YfY+5dj06dOn4EfQdR0y5ZQ8vOFfs2DDKdnS1pB1W0bk/lWXpf/wU9O/f/9KlwcVcejfnJq7r3pflh1xQFrqa7Nq/2G5+0vvzn6nTE+vXlZEAOyqQ08/Jfd/6T1ZNP3grddho4fm3n+5KMNPPjb19X+dFrx6pVIpR59xdPa6aq/UHFqT1CfV46oz9CtDc8QbjvCu/AL17t07ow88OfesuiKrm8dkS1t9lmw8NrPWfCWHHnlGpcsDACqkptIFAOysg6cdnVXjD8yTxx+e5RvWZdyECZk+/qDU1Ozcj7KGhoa87sLzMv+wSXngmQVZW1XO0ScenwEDBhRbeBdXV1eX6Sf/bRbMn5IHl83L6vWlHHXMCRk0aFClS4OKGTBgQI59x/l55rCDs2DRsqzrlRx70onp169fpUsD6JYaGhoy7cJzs2DynrsOGzp0aE5712n58+Q/Z+XSldlSuyXHn3x8GhoaCvuabDVm/0kZNHR0nnliapYsW539998v0/Y/JLW1u/82XABA92BFBNCtDBo0KIefcWr6D987+086eKdDiG169eqVA6ccmmPOPisNQwa95kOIbWpqarL/AZNy9HFnp2//oUIIyNZ3dI4/6sgcc85Z6TNooBAC4FWqra3d49dh9fX1mXzs5JxyzinpN7CfEGIP6t+/fw474vXpP2B4xk04QggBAK9xgggAAAAAAKAwggi6tKeeeiq1tbUplUodH0ceeWSlywIAAAAAYCcJIujSDjzwwLS0tKSmpiaDBw9OksyePTsnn3xyhSsDAAAAAGBnCCLoss4666yUy+U0NDSkpaUlK1asyNy5c5Mkt912W4WrAwAAAABgZwgi6LJuueWWJMkvfvGLjrZx48alvr4+SfKVr3ylInUBAAAAALDzBBF0WS0tLUmSk046qVP7IYcckiS59tpr93hNAAAAAADsGkEE3c5hhx2WJHn22WcrXAkAAAAAAC9HEEG3s9deeyX5y4oJAAAAAAC6rppKFwC76rnnnkuS9OrVa4f9Dz30UK644ood9t11111JktWrVxdTHAAAAAAAnQgi6HYefvjhJMnee++9w/4rrrgiM2fOfMlzzJkzZ7fXBQAAAADA9gQRdFk1NTVpbW3Nbbfd1mnD6kceeSRJ8nd/93c7PO7Tn/70i55zzZo1efzxx3PVVVft3mIBAAAAANghQQRd1hve8Ib88pe/zFlnnZUNGzYkSZ566qls3rw5SfK//tf/2uFxkydPzg033LDH6gQAAAAA4MUJIuiybrrpplRVVWXjxo2pra1N//79s3LlyiTJ8ccfX+HqAAAA4LVt4cKFWbFixYv2DxkyJKNHj96DFQHQVQki6NLmzJmTSZMmpaWlpSOEmDJlSv7whz9UuDIAAAB47Vq4cGHGjx/fcdeCHamvr8/cuXOFEQAIIujaxo0bl5aWlkqXAQAAALzAihUrsnnz5lxyySUZOXLkdv1LlizJ1VdfnRUrVggiABBEAAAAAPDKjBw5Mvvtt1+lywCgi6uqdAEAAAAAAEDPJYgAAAAAAAAKI4gAAAAAAAAKI4gAAAAAAAAKI4gAAAAAAAAKUyqXy+VKFwE91a233pqmpqZKl9EjNTc3p3fv3hU/R1fTXZ6Xnvjc9xRFf2+66/e+u9bNrvO93rFKPC++FzuniOepp14LmFOVsTPPe3f83nTHmne3p556Kv/4j/+YK664IuVyOQceeGCn/qeffjqXXXZZ/v3f/z1///d/X6EqAegqaipdAPRkTU1N2bx5c6XL6LF2x3PbE78/3eV56YnPfU9R9Pemu37vu2vd7Drf6x2rxPPie7Fzinieeuq1gDlVGTvzvHfH7013rHl32vamu6qqqnzrW9/KV77ylR2O27Jly54sC4Auyq2ZAAAAAHjFhg8fnuXLl1e6DAC6MCsiAAAAAHjFNmzYkI9//OMZN25cxy2rNm3aVOGqAOhKBBEAAAAAvGInnHBCTjjhhE5tzz33XB577LEKVQRAVyOIAAAAAOAV2xZCtLS0pFevXkm2blY9c+bMSpYFQBdijwgAAAAAXrGFCxfmox/9aC699NIkW0OIm2++ucJVAdCVCCIAAAAAeMWuvfbavO9970v//v2TJGPHjs3cuXMrXBUAXYkgAgAAAIBXrKmpKePHj+/4vFQqpbq6uoIVAdDVCCIAAAAAeMWqqqrS2tra8fmKFStSVeVPTgD8hd8KAAAAALxip59+er761a9m/fr1+dGPfpR//ud/zvHHH1/psgDoQmoqXQAAAAAA3ddxxx2XvfbaK/fff39aW1tzySWXpLa2Nj/84Q8rXRoAXYQgAgAAAIBX7LbbbstJJ52UcePGdbT9+Mc/rmBFAHQ1bs0EAAAAwCv2q1/9aru2u+++uwKVANBVWREBAAAAwCty5513Zv369bn55ps72jZt2pS2trYKVgVAV2NFBAAAAACvyLJly9Lc3Jxnnnmm42P9+vU599xzK10aAF2IFREAAAAAvCLnnntu1q5dmylTpnRqf/rppytUEQBdkSACAAAAgFdsypQpeeKJJ/Lss8923JLp+eefr3BVAHQlgggAAAAAXrH/+I//yMMPP5x99903VVVb7wK+adOmClcFQFciiAAAAADgFXvkkUdy1VVXpba2tqPt6aefzmWXXVbBqgDoSmxWDQAAAMArNmDAgPTq1avSZQDQhVkRAQAAAMArduCBB+ZrX/tapk2b1hFILF++vMJVAdCVCCIAAAAAeMWeeuqpJMmvf/3rjrampqZKlQNAFySIAAAAAOAVWbZsWd71rndt17548eL827/9254vCIAuSRABBaqrq6t0CQAAALDbbXu9+4Mf/GC7/SHK5XJaW1uTpNMG1gC8dgkioECnnnpqpUsAAACA3e6BBx5Iknz84x/Pfvvtt13/008/ncsuuyzHHHPMni4NgC6oqtIFAAAAAAAAPZcgAgAAAAAAKIwgAgAAAAAAKIwgAgAAAAAAKIwgAgAAAAAAKIwgAgAAAAAAKExNpQsAAAAAoHtasmTJLrUD8NpUKpfL5UoXAQAAAED3sXDhwowfPz6bN29+0TH19fWZO3duRo8evQcrA6ArEkQAAAAAsMsWLlyYFStWvGj/kCFDhBAAJBFEAAAAAAAABbJZNQAAAAAAUBhBBAAAAAAAUBhBBAAAAAAAUBhBBAAAAAAAUBhBBAAAAAAAUBhBBAAAAAAAUBhBBAAAAAAAUBhBBAAAAAAAUBhBBAAAAAAAUBhBBAAAAAAAUBhBBAAAAAAAUBhBBAAAAAAAUBhBBAAAAAAAUBhBBAAAAAAAUJiaShcAPdmKFStyyy23ZMyYMamvr690ObzGbN68OfPnzzf/6DLMSboac5KuxpykqzEneTW2zZ/TTjstQ4YMqXQ5AFSYIAIKdMstt+Siiy6qdBkAAABQEdddd10uvPDCSpcBQIUJIqBAY8aMSbL1wmvChAmVLYbXnDlz5uSiiy4y/+gyzEm6GnOSrsacpKsxJ3k1ts2fba+LAXhtE0RAgbYtX54wYUIOP/zwClfDa5X5R1djTtLVmJN0NeYkXY05yavhtl4AJDarBgAAAAAACiSIAAAAAAAACiOIAAAAAAAACiOIAAAAAAAACiOIAAAAAAAACiOIAOihxo8fn9mzZ2f8+PGVLgWSmJN0PeYkXY05SVdjTgIAu0tNpQsAoBh9+vTJ4YcfXukyoIM5SVdjTtLVmJN0NeYkALC7WBEBAAAAAAAURhABAAAAAAAURhABAAAAAAAURhABAAAAAAAURhAB0INcccUVKZVKmTRp0nZ9d911V6ZPn54+ffpk2LBhufTSS7Nhw4YKVElP9sQTT+SCCy7IPvvskz59+mT8+PG5/PLLs2nTpk7jzEd2tw0bNuRzn/tcTj/99AwaNCilUinf+973Oo1pb2/P9773vbzpTW/KqFGj0tDQkEmTJuXzn/98mpqadnje//zP/8yECRNSV1eXAw88MP/7f//vPfBo6Al2Zk5u097enm9961uZPHly6uvrM3jw4Jx88sl5+OGHtxv35S9/OWPHjk1dXV0OPfTQ/PCHP9wDj4bu7r777ssll1ySiRMnpqGhIaNHj85b3/rWzJs3b7uxc+bMyemnn56+fftm0KBBefvb357nn39+u3HmIwCwK2oqXQAAu8fixYtz5ZVXpqGhYbu+hx56KKecckomTJiQr33ta1m8eHG++tWv5oknnsjNN99cgWrpiRYtWpSjjjoqjY2NueSSSzJo0KDcfffd+dznPpfZs2fnZz/7WRLzkWKsWLEil19+eUaPHp3DDjssv//977cbs2nTpvzd3/1djjnmmHzgAx/IXnvt1TFHf/vb3+Z3v/tdSqVSx/jvfOc7+cAHPpBzzjknH/nIR/LHP/4xl156aTZt2pRPfOITe/DR0R3tzJzc5t3vfneuv/76vOMd78gll1ySjRs35sEHH8xzzz3XadynP/3pfPGLX8z73ve+TJ06NT/72c/ytre9LaVSKRdccEHBj4ju7Etf+lLuvPPOnHfeeTn00EOzfPnyXH311Tn88MNzzz33dLyJZfHixTn++OPT2NiYK6+8Mhs2bMhXv/rVPPLII5k1a1Zqa2s7zmk+AgC7pAwUZvbs2eUk5dmzZ1e6FF4Dzj///PLJJ59cPuGEE8oTJ07s1HfGGWeUhw8fXl67dm1H2zXXXFNOUr7lllv2dKn0UFdccUU5SfnRRx/t1P6Od7yjnKS8atWqcrlsPlKMpqam8rJly8rlcrl83333lZOUr7322k5jmpuby3feeed2x/7Lv/xLOUn51ltv7WjbtGlTefDgweUzzzyz09gLL7yw3NDQ0DGf4cXszJwsl8vlGTNmlJOU//u///slz7d48eJyr169yhdffHFHW3t7e/m4444r77PPPuXW1tbdWj89y5133llubm7u1DZv3rxy7969yxdeeGFH2wc/+MFyfX19ecGCBR1tt956azlJ+Tvf+U5Hm/nIzvB6GIAXcmsmgB7g9ttvz8yZM/P1r399u75169bl1ltvzUUXXZT+/ft3tL/jHe9I37598+Mf/3gPVkpPtm7duiTJ3nvv3al9+PDhqaqqSm1trflIYXr37p1hw4a95Jja2tpMmzZtu/a3vOUtSbbejmSb2267LStXrszf//3fdxp78cUXZ+PGjbnpppt2Q9X0ZDszJ5Pka1/7Wo466qi85S1vSXt7ezZu3LjDcT/72c/S0tLSaU6WSqV88IMfzOLFi3P33XfvttrpeaZNm9ZpNUOSHHjggZk4cWKnn30/+clP8sY3vjGjR4/uaHv961+fgw46qNPvaPMRANhVggiAbq6trS0f+tCH8t73vjeHHHLIdv2PPPJIWltbc+SRR3Zqr62tzeTJk/Pggw/uqVLp4U488cQkyXve85489NBDWbRoUWbMmJFvfetbufTSS9PQ0GA+0iUtX748STJkyJCOtm1z8a/n6hFHHJGqqipzld1i3bp1mTVrVqZOnZpPfepTaWxsTN++fbPffvttF8w++OCDaWhoyIQJEzq1H3XUUR39sCvK5XKeffbZjp99S5YsyXPPPbfdz71k6zx74RwzHwGAXWWPCIBu7tvf/nYWLFiQ3/zmNzvsX7ZsWZKt70r/a8OHD88f//jHQuvjteP000/Pv/7rv+bKK6/Mz3/+8472T3/60/n85z+fxHyka/ryl7+c/v3754wzzuhoW7ZsWaqrq7PXXnt1GltbW5vBgwdn6dKle7pMeqCnnnoq5XI5P/rRj1JTU5Mvf/nLaWxszDe+8Y1ccMEF6d+/f04//fQkW+fk3nvv3Wkfk+QvP0/NSXbV9ddfnyVLluTyyy9P8vK/o1etWpXm5ub07t3bfAQAdpkgAqAbW7lyZf7pn/4pn/3sZzN06NAdjtm8eXOSrbeI+Gt1dXUd/bA7jBkzJscff3zOOeecDB48ODfddFOuvPLKDBs2LJdccon5SJdz5ZVX5je/+U2++c1vZsCAAR3tmzdv3u42JtuYq+wuGzZsSLL19/k999yTo48+Oknypje9KWPHjs3nP//5jiBi8+bNL/qzc1s/7Ky5c+fm4osvzrHHHpt3vvOdSV7+mnHbmN69e5uPAMAuE0QAdGOf+cxnMmjQoHzoQx960TH19fVJkubm5u36mpqaOvrh1frRj36U97///Zk3b1722WefJMnZZ5+d9vb2fOITn8jf/u3fmo90KTNmzMhnPvOZvOc978kHP/jBTn319fXZsmXLDo8zV9ldts2jsWPHdoQQSdK3b9+cddZZue6669La2pqamprU19e/6M/OF54LXs7y5ctz5plnprGxMTNnzkx1dXWSl79mfOEY8xEA2FX2iIACjR8/PrNnz8748eMrXQo90BNPPJH/83/+Ty699NIsXbo08+fPz/z589PU1JSWlpbMnz8/q1at6lgiv225/QstW7YsI0aM2NOl00N985vfzJQpUzpCiG3e9KY3ZdOmTXnwwQfNR7qMW2+9Ne94xzty5pln5tvf/vZ2/cOHD09bW1uee+65Tu1btmzJypUrzVV2i23zaO+9996ub6+99kpLS0vH5tXDhw/P8uXLUy6XO43b9vPUnGRnrF27NmeccUbWrFmTX/3qV53mzcv9jh40aFDHKgjzkZ3h9TAALySIgAL16dMnhx9+ePr06VPpUuiBlixZkvb29lx66aUZO3Zsx8e9996befPmZezYsbn88sszadKk1NTU5P777+90/JYtW/LQQw9l8uTJlXkA9DjPPvts2tratmtvaWlJkrS2tpqPdAn33ntv3vKWt+TII4/Mj3/849TUbL9IeNtc/Ou5ev/996e9vd1cZbcYMWJEhg0bliVLlmzXt3Tp0tTV1aVfv35Jts7JTZs2Zc6cOZ3G3XvvvR398FKamppy1llnZd68ebnxxhtz8MEHd+ofOXJkhg4dut3PvSSZNWtWpzlmPrIzvB4G4IUEEQDd1KRJk/I///M/231MnDgxo0ePzv/8z//kPe95TxobG/P6178+1113XdavX99x/A9+8INs2LAh5513XgUfBT3JQQcdlAcffDDz5s3r1P7DH/4wVVVVOfTQQ81HKm7OnDk588wzM2bMmNx4440vevuQk08+OYMGDcq3vvWtTu3f+ta30qdPn5x55pl7olxeA84///wsWrQot956a0fbihUr8rOf/Swnn3xyqqq2vmR785vfnF69euWb3/xmx7hyuZxvf/vbGTlyZKZNm7bHa6f7aGtry/nnn5+77747N9xwQ4499tgdjjvnnHNy4403ZtGiRR1tv/3tbzNv3rxOv6PNRwBgV5XKf72WEoBu7cQTT8yKFSvy6KOPdrQ98MADmTZtWg4++OC8//3vz+LFi3PVVVfl+OOPzy233FLBaulJbr/99px88skZPHhwLrnkkgwePDg33nhjbr755rz3ve/NNddck8R8pDhXX3111qxZk6VLl+Zb3/pWzj777EyZMiVJ8qEPfShVVVWZOHFilixZkiuvvDIjR47sdPz+++/f6Y9z3/zmN3PxxRfn3HPPzWmnnZY//vGP+a//+q9cccUV+dSnPrVHHxvd08vNycbGxjz77LOZMmVKNmzYkI985CNpbGzMt7/97SxatCh33313DjvssI7zffzjH89XvvKVvP/978/UqVPz05/+NDfddFOuv/76vO1tb6vUw6Qb+Id/+Id84xvfyFlnnZW3vvWt2/VfdNFFSZJFixZlypQpGTBgQD784Q9nw4YN+cpXvpJ99tkn9913X6cNqs1HAGBXCCIAepgdBRFJcscdd+QTn/hEHnjggfTr1y9vfetb84UvfKHjlg+wO8yaNSv//M//nAcffDArV67M2LFj8853vjMf//jHO93+xnykCGPGjMmCBQt22PfMM88k2bop8It55zvfme9973ud2q655ppcddVVeeaZZzJq1Khccskl+fCHP5xSqbTb6qbnerk5OWbMmCTJ008/nY997GP57W9/m5aWlhx77LH54he/mKlTp3Y6pr29PV/60pfyne98J8uWLcuBBx6Yyy67LBdeeGHRD4Vu7sQTT8wf/vCHF+1/4Z8FHnvssXzkIx/JHXfckdra2px55pm56qqrttvLxHwEAHaFIAJ2s23vGrr33nsza9asrF69Otdee23e9a53Vbo0AAAA2CX33Xdfvv/97+e2227L/PnzM3jw4BxzzDH5/Oc/n4MOOqhj3DXXXJPrrrsuc+fOzZo1azJixIiceOKJ+dznPtcRvG7zYoH+F77whXzyk58s8uEAUCGCCNjN5s+fn7Fjx2b06NHZb7/98vvf/14QAQAAQLd07rnn5s4778x5552XQw89NMuXL8/VV1+dDRs25J577smkSZOSJH//93+fTZs25ZBDDsnAgQPzzDPP5JprrklbW1sefvjhjBgxouOcpVIpp556at7xjnd0+lpTpkzJxIkT9+jjA2DPEETAbtbc3JzVq1dn2LBhuf/++zN16lRBBAAAAN3SXXfdlSOPPDK1tbUdbU888UQOOeSQnHvuubnuuute9NjZs2fnyCOP3G6lQ6lUysUXX5yrr7660NoB6DpqXn4IsCt69+6dYcOGVboMAAAAeNWmTZu2XduBBx6YiRMnZs6cOS957LZbMq1Zs2aH/Zs3b06pVEpdXd2rLROALq6q0gUAAAAA0H2Uy+U8++yzGTJkyHZ9K1euzHPPPZf7778/f/d3f5ckOeWUU7Yb973vfS8NDQ2pr6/PwQcfnP/7f/9v4XUDUDlWRAAAAACw066//vosWbIkl19++XZ9I0eOTHNzc5Jk8ODB+bd/+7eceuqpncZMmzYtb33rWzN27NgsXbo0//7v/54LL7wwa9euzQc/+ME98hgA2LMEEQAAAADslLlz5+biiy/Osccem3e+853b9d98881pamrKnDlzct1112Xjxo3bjbnzzjs7ff7ud787RxxxRD71qU/lXe96V+rr6wurH4DKEEQAAAAA8LKWL1+eM888M42NjZk5c2aqq6u3G3PSSSclSc4444y8+c1vzqRJk9K3b99ccsklL3re2traXHL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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from gpsea.preprocessing import UniprotProteinMetadataService\n", - "from gpsea.model.genome import GRCh38\n", - "from gpsea.preprocessing import VVMultiCoordinateService\n", - "pms = UniprotProteinMetadataService()\n", - "protein_meta = pms.annotate('NP_006571.1')\n", - "txc_service = VVMultiCoordinateService(genome_build=GRCh38)\n", - "tx_coordinates = txc_service.fetch(CLDN16_transcript)\n", - "from gpsea.view import ProteinVisualizable, ProteinVisualizer\n", - "pvis = ProteinVisualizable(tx_coordinates=tx_coordinates, protein_meta=protein_meta, cohort=cohort)\n", - "drawer = ProteinVisualizer()\n", - "drawer.draw_fig(pvis=pvis)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "6bba515c", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - " \n", - " Cohort\n", - " \n", - "\n", - "\n", - "\n", - "

GPSEA protein analysis

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The UniProt API successfully returned protein information for ID: NP_006571.1

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Protein Name: Claudin-16

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Protein Features

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Feature NameFeature TypeFeature CoordinatesVariants in Feature
Interaction with TJP1motif233 - 2350
\n", - "\n", - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "viewer = ProteinViewable()\n", - "html_prot = viewer.process(cohort, pvis)\n", - "display(HTML(html_prot))" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "fd352277-9cab-494d-aad2-0e528a2d0e73", - "metadata": {}, - "outputs": [], - "source": [ - "from gpsea.analysis import configure_cohort_analysis, CohortAnalysisConfiguration\n", - "from gpsea.analysis.predicate import PatientCategories\n", - "from gpsea.model.genome import Region\n", - "\n", - "analysis_config = CohortAnalysisConfiguration()\n", - "analysis_config.missing_implies_excluded = False\n", - "analysis_config.hpo_mtc_strategy()\n", - "analysis = configure_cohort_analysis(cohort, hpo, config=analysis_config)" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "e3b7bfd7-c4b1-4a4f-ba91-62ffc359350e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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MISSENSE_VARIANT on NM_006580.4YesNo
CountPercentCountPercentp valueCorrected p value
Stage 5 chronic kidney disease [HP:0003774]2/356%3/838%0.0372180.446616
Hypocalcemia [HP:0002901]8/989%2/633%0.0889111.000000
Nephrolithiasis [HP:0000787]7/3023%1/1100%0.2580651.000000
Failure to thrive [HP:0001508]7/2429%1/1100%0.3200001.000000
Recurrent urinary tract infections [HP:0000010]13/2650%3/475%0.6015331.000000
Polyuria [HP:0000103]20/2580%3/3100%1.0000001.000000
Hypermagnesiuria [HP:0012608]25/2793%7/7100%1.0000001.000000
Hypomagnesemia [HP:0002917]11/1292%7/7100%1.0000001.000000
Hypocalcemic seizures [HP:0002199]2/540%1/520%1.0000001.000000
Polydipsia [HP:0001959]19/2479%3/3100%1.0000001.000000
Hypercalciuria [HP:0002150]32/3689%7/7100%1.0000001.000000
Elevated circulating parathyroid hormone level [HP:0003165]25/2696%3/3100%1.0000001.000000
\n", - "
" - ], - "text/plain": [ - "MISSENSE_VARIANT on NM_006580.4 Yes No \\\n", - " Count Percent Count \n", - "Stage 5 chronic kidney disease [HP:0003774] 2/35 6% 3/8 \n", - "Hypocalcemia [HP:0002901] 8/9 89% 2/6 \n", - "Nephrolithiasis [HP:0000787] 7/30 23% 1/1 \n", - "Failure to thrive [HP:0001508] 7/24 29% 1/1 \n", - "Recurrent urinary tract infections [HP:0000010] 13/26 50% 3/4 \n", - "Polyuria [HP:0000103] 20/25 80% 3/3 \n", - "Hypermagnesiuria [HP:0012608] 25/27 93% 7/7 \n", - "Hypomagnesemia [HP:0002917] 11/12 92% 7/7 \n", - "Hypocalcemic seizures [HP:0002199] 2/5 40% 1/5 \n", - "Polydipsia [HP:0001959] 19/24 79% 3/3 \n", - "Hypercalciuria [HP:0002150] 32/36 89% 7/7 \n", - "Elevated circulating parathyroid hormone level ... 25/26 96% 3/3 \n", - "\n", - "MISSENSE_VARIANT on NM_006580.4 \\\n", - " Percent p value \n", - "Stage 5 chronic kidney disease [HP:0003774] 38% 0.037218 \n", - "Hypocalcemia [HP:0002901] 33% 0.088911 \n", - "Nephrolithiasis [HP:0000787] 100% 0.258065 \n", - "Failure to thrive [HP:0001508] 100% 0.320000 \n", - "Recurrent urinary tract infections [HP:0000010] 75% 0.601533 \n", - "Polyuria [HP:0000103] 100% 1.000000 \n", - "Hypermagnesiuria [HP:0012608] 100% 1.000000 \n", - "Hypomagnesemia [HP:0002917] 100% 1.000000 \n", - "Hypocalcemic seizures [HP:0002199] 20% 1.000000 \n", - "Polydipsia [HP:0001959] 100% 1.000000 \n", - "Hypercalciuria [HP:0002150] 100% 1.000000 \n", - "Elevated circulating parathyroid hormone level ... 100% 1.000000 \n", - "\n", - "MISSENSE_VARIANT on NM_006580.4 \n", - " Corrected p value \n", - "Stage 5 chronic kidney disease [HP:0003774] 0.446616 \n", - "Hypocalcemia [HP:0002901] 1.000000 \n", - "Nephrolithiasis [HP:0000787] 1.000000 \n", - "Failure to thrive [HP:0001508] 1.000000 \n", - "Recurrent urinary tract infections [HP:0000010] 1.000000 \n", - "Polyuria [HP:0000103] 1.000000 \n", - "Hypermagnesiuria [HP:0012608] 1.000000 \n", - "Hypomagnesemia [HP:0002917] 1.000000 \n", - "Hypocalcemic seizures [HP:0002199] 1.000000 \n", - "Polydipsia [HP:0001959] 1.000000 \n", - "Hypercalciuria [HP:0002150] 1.000000 \n", - "Elevated circulating parathyroid hormone level ... 1.000000 " - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from gpsea.model import VariantEffect\n", - "from gpsea.analysis.predicate.genotype import VariantPredicates\n", - "\n", - "is_missense = VariantPredicates.variant_effect(VariantEffect.MISSENSE_VARIANT, tx_id=CLDN16_transcript)\n", - "missense = analysis.compare_hpo_vs_genotype(is_missense)\n", - "missense.summarize(hpo, PatientCategories.YES)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "enviro", - "language": "python", - "name": "enviro" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.10" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/case_studies/KMT2D/KMT2D_correlations.ipynb b/case_studies/KMT2D/KMT2D_correlations.ipynb deleted file mode 100644 index caadd52d..00000000 --- a/case_studies/KMT2D/KMT2D_correlations.ipynb +++ /dev/null @@ -1,1555 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# KMT2D" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Loaded HPO v2023-10-09\n", - "Using gpsea version 0.1.1dev\n" - ] - } - ], - "source": [ - "import gpsea\n", - "import hpotk\n", - "\n", - "store = hpotk.configure_ontology_store()\n", - "hpo = store.load_minimal_hpo(release='v2023-10-09')\n", - "print(f'Loaded HPO v{hpo.version}')\n", - "print(f\"Using gpsea version {gpsea.__version__}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "KTM2D_transcript_id = 'NM_003482.4'\n", - "KTM2D_protein_id = \"NP_003473.3\"" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Patients Created: 100%|██████████| 65/65 [02:01<00:00, 1.87s/it]\n", - "Validated under none policy\n", - "No errors or warnings were found\n" - ] - } - ], - "source": [ - "from ppktstore.registry import configure_phenopacket_registry\n", - "from gpsea.preprocessing import configure_caching_cohort_creator, load_phenopackets\n", - "\n", - "cohort_creator = configure_caching_cohort_creator(hpo)\n", - "\n", - "cohort_name = 'KMT2D'\n", - "phenopacket_store_release = '0.1.19'\n", - "\n", - "registry = configure_phenopacket_registry()\n", - "with registry.open_phenopacket_store(phenopacket_store_release) as ps:\n", - " phenopackets = tuple(ps.iter_cohort_phenopackets(cohort_name))\n", - "\n", - "cohort, validation = load_phenopackets(\n", - " phenopackets=phenopackets, \n", - " cohort_creator=cohort_creator,\n", - ")\n", - "del phenopackets\n", - "validation.summarize()" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - " \n", - " Cohort\n", - " \n", - "\n", - "\n", - "\n", - "

GPSEA cohort analysis

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Successfully loaded 65 individuals.

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No errors encountered.

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\n", - "

Top 10 HPO Terms

\n", - " A total of 239 HPO terms were used to annotated the cohort.\n", - "
HPO TermIDSeen in n individuals
Depressed nasal tipHP:000043736
Prominent fingertip padsHP:000121230
Global developmental delayHP:000126330
Long palpebral fissureHP:000063725
MacrotiaHP:000040024
Highly arched eyebrowHP:000255322
Intellectual disabilityHP:000124921
Eversion of lateral third of lower eyelidsHP:000765518
Cleft palateHP:000017517
Hearing impairmentHP:000036516
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Top 10 Variants

\n", - " Variants are shown according to NM_003482.4. A total of 65 unique variants were identified in the cohort.\n", - "
CountVariant keyVariant NameProtein VariantVariant Class
412_49034182_49034182_A_Gc.10625T>Cp.Leu3542ProMISSENSE_VARIANT
412_49022655_49022655_C_Tc.16273G>Ap.Glu5425LysMISSENSE_VARIANT
312_49034082_49034082_C_Gc.10725G>Cp.Gln3575HisMISSENSE_VARIANT
312_49034225_49034225_G_Cc.10582C>Gp.Leu3528ValMISSENSE_VARIANT
312_49033960_49033960_C_Tc.10745G>Ap.Arg3582GlnMISSENSE_VARIANT
212_49022634_49022634_G_Ac.16294C>Tp.Arg5432TrpMISSENSE_VARIANT
112_49032140_49032140_C_Ac.12565G>Tp.Gly4189TerSTOP_GAINED
112_49033067_49033067_G_Tc.11638C>Ap.Leu3880MetMISSENSE_VARIANT
112_49032398_49032398_G_Ac.12307C>Tp.Gln4103TerSTOP_GAINED
112_49031446_49031446_C_Tc.13259G>Ap.Arg4420GlnMISSENSE_VARIANT
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Diseases

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Disease NameDisease IDAnnotation Count
Kabuki Syndrome 1OMIM:14792065
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Variant categories for NM_003482.4

\n", - "
Variant effectAnnotation Count
MISSENSE_VARIANT36
STOP_GAINED15
FRAMESHIFT_VARIANT14
\n", - " \n", - "\n", - "\n", - "\n", - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from gpsea.view import CohortViewable\n", - "from IPython.display import HTML, display\n", - "\n", - "viewer = CohortViewable(hpo)\n", - "display(HTML(viewer.process(cohort=cohort, transcript_id=KTM2D_transcript_id)))" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "from gpsea.preprocessing import configure_protein_metadata_service\n", - "from gpsea.preprocessing import VVMultiCoordinateService\n", - "from gpsea.model.genome import GRCh38\n", - "\n", - "pms = configure_protein_metadata_service()\n", - "protein_meta = pms.annotate(KTM2D_protein_id)\n", - "txc_service = VVMultiCoordinateService(genome_build=GRCh38)\n", - "tx_coordinates = txc_service.fetch(KTM2D_transcript_id)\n" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "from gpsea.view import ProteinVisualizable, ProteinVisualizer, ProteinViewable\n", - "\n", - "pvis = ProteinVisualizable(tx_coordinates=tx_coordinates, protein_meta=protein_meta, cohort=cohort)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - " \n", - " Cohort\n", - " \n", - "\n", - "\n", - "\n", - "

GPSEA protein analysis

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The UniProt API successfully returned protein information for ID: NP_003473.3

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Protein Name: Histone-lysine N-methyltransferase 2D

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\n", - "

Protein Features

\n", - "
Feature NameFeature TypeFeature CoordinatesVariants in Feature
Disorderedregion1 - 602
Disorderedregion368 - 3870
Disorderedregion393 - 4160
Disorderedregion436 - 13313
15 X 5 AA repeats of S/P-P-P-E/P-E/Aregion439 - 6680
1repeat442 - 4460
2repeat460 - 4640
3repeat469 - 4730
4repeat496 - 5000
5repeat504 - 5080
6repeat521 - 5250
7repeat555 - 5590
8repeat564 - 5680
9repeat573 - 5770
10repeat582 - 5860
11repeat609 - 6130
12repeat618 - 6220
13repeat627 - 6310
14repeat645 - 6490
15repeat663 - 6670
Disorderedregion1340 - 13590
Disorderedregion1610 - 17673
Disorderedregion1793 - 18890
Disorderedregion1904 - 20023
Disorderedregion2165 - 26833
LXXLL motif 1motif2686 - 26900
Disorderedregion2697 - 28142
Disorderedregion2835 - 29962
LXXLL motif 2motif3038 - 30420
Disorderedregion3078 - 31100
Disorderedregion3147 - 32090
Disorderedregion3263 - 33390
Disorderedregion3462 - 34990
Disorderedregion3596 - 36730
Disorderedregion3758 - 38020
Disorderedregion3984 - 41912
LXXLL motif 3motif4222 - 42260
Disorderedregion4233 - 43980
LXXLL motif 4motif4253 - 42570
Disorderedregion4410 - 44521
LXXLL motif 5motif4463 - 44670
Disorderedregion4503 - 45440
Disorderedregion4613 - 47270
Disorderedregion4822 - 48570
Disorderedregion4905 - 49800
LXXLL motif 6motif4990 - 49940
FYR N-terminaldomain5175 - 52350
FYR C-terminaldomain5236 - 53210
WDR5 interaction motif (WIN)motif5337 - 53420
SETdomain5397 - 55139
Post-SETdomain5521 - 55370
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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "drawer = ProteinVisualizer()\n", - "drawer.draw_fig(pvis=pvis)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "from gpsea.analysis import configure_cohort_analysis, CohortAnalysisConfiguration\n", - "from gpsea.analysis.predicate import PatientCategories\n", - "from gpsea.model.genome import Region\n", - "\n", - "analysis_config = CohortAnalysisConfiguration()\n", - "analysis_config.missing_implies_excluded = False\n", - "analysis_config.hpo_mtc_strategy()\n", - "\n", - "analysis = configure_cohort_analysis(cohort, hpo, config=analysis_config)" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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MISSENSE_VARIANT on NM_003482.4YesNo
CountPercentCountPercentp valueCorrected p value
Sensorineural hearing impairment [HP:0000407]6/1155%0/130%0.0034320.15103
Hearing impairment [HP:0000365]14/1974%8/2138%0.0308711.00000
Ventricular septal defect [HP:0001629]0/150%5/2124%0.0619431.00000
High forehead [HP:0000348]5/683%1/520%0.0800871.00000
Motor delay [HP:0001270]2/825%2/2100%0.1333331.00000
Hypotonia [HP:0001252]2/729%10/1471%0.1588241.00000
Decreased proportion of CD4-positive, alpha-beta memory T cells [HP:0410386]6/875%2/540%0.2929291.00000
Blue sclerae [HP:0000592]4/757%3/1030%0.3499591.00000
Highly arched eyebrow [HP:0002553]8/989%14/2167%0.3741901.00000
Atrial septal defect [HP:0001631]5/771%6/1346%0.3742261.00000
Eversion of lateral third of lower eyelids [HP:0007655]2/367%16/1889%0.3864661.00000
Sacral dimple [HP:0000960]0/20%6/1060%0.4545451.00000
Recurrent otitis media [HP:0000403]8/1553%6/1735%0.4764511.00000
Decreased proportion of memory B cells [HP:0030374]6/875%5/5100%0.4871791.00000
Renal duplication [HP:0000075]0/50%2/825%0.4871791.00000
Intellectual disability, mild [HP:0001256]3/1225%1/250%0.5054951.00000
Long palpebral fissure [HP:0000637]8/8100%17/2181%0.5520191.00000
Sparse lateral eyebrow [HP:0005338]6/786%5/862%0.5692311.00000
Seizure [HP:0001250]2/825%2/1712%0.5699601.00000
Congenital hip dislocation [HP:0001374]1/714%5/1631%0.6213851.00000
Clinodactyly of the 5th finger [HP:0004209]2/922%4/1136%0.6424151.00000
Proportionate short stature [HP:0003508]7/1164%4/944%0.6534171.00000
Severe short stature [HP:0003510]7/1258%4/1040%0.6699211.00000
Scoliosis [HP:0002650]6/1932%4/1724%0.7169251.00000
Depressed nasal tip [HP:0000437]16/2080%20/2774%0.7365041.00000
Thin upper lip vermilion [HP:0000219]3/475%4/667%1.0000001.00000
Delayed speech and language development [HP:0000750]8/1080%2/2100%1.0000001.00000
Feeding difficulties [HP:0011968]5/1436%3/1127%1.0000001.00000
High, narrow palate [HP:0002705]8/989%6/6100%1.0000001.00000
Joint hypermobility [HP:0001382]2/729%3/1225%1.0000001.00000
Long eyelashes [HP:0000527]0/10%3/650%1.0000001.00000
Cleft palate [HP:0000175]9/1090%8/8100%1.0000001.00000
Low posterior hairline [HP:0002162]0/10%2/633%1.0000001.00000
Prominent fingertip pads [HP:0001212]12/1580%18/2378%1.0000001.00000
Ectopic kidney [HP:0000086]0/20%2/922%1.0000001.00000
Decreased circulating IgA level [HP:0002720]2/825%2/540%1.0000001.00000
Wide nasal bridge [HP:0000431]3/3100%11/1479%1.0000001.00000
Postnatal growth retardation [HP:0008897]5/862%4/580%1.0000001.00000
Micrognathia [HP:0000347]3/650%4/944%1.0000001.00000
Microcephaly [HP:0000252]3/743%4/1136%1.0000001.00000
High palate [HP:0000218]10/1191%8/8100%1.0000001.00000
Sparse eyebrow [HP:0045075]6/786%8/1173%1.0000001.00000
Recurrent infections [HP:0002719]15/2171%15/2075%1.0000001.00000
Short stature [HP:0004322]9/1369%13/1872%1.0000001.00000
\n", - "
" - ], - "text/plain": [ - "MISSENSE_VARIANT on NM_003482.4 Yes No \\\n", - " Count Percent Count \n", - "Sensorineural hearing impairment [HP:0000407] 6/11 55% 0/13 \n", - "Hearing impairment [HP:0000365] 14/19 74% 8/21 \n", - "Ventricular septal defect [HP:0001629] 0/15 0% 5/21 \n", - "High forehead [HP:0000348] 5/6 83% 1/5 \n", - "Motor delay [HP:0001270] 2/8 25% 2/2 \n", - "Hypotonia [HP:0001252] 2/7 29% 10/14 \n", - "Decreased proportion of CD4-positive, alpha-bet... 6/8 75% 2/5 \n", - "Blue sclerae [HP:0000592] 4/7 57% 3/10 \n", - "Highly arched eyebrow [HP:0002553] 8/9 89% 14/21 \n", - "Atrial septal defect [HP:0001631] 5/7 71% 6/13 \n", - "Eversion of lateral third of lower eyelids [HP:... 2/3 67% 16/18 \n", - "Sacral dimple [HP:0000960] 0/2 0% 6/10 \n", - "Recurrent otitis media [HP:0000403] 8/15 53% 6/17 \n", - "Decreased proportion of memory B cells [HP:0030... 6/8 75% 5/5 \n", - "Renal duplication [HP:0000075] 0/5 0% 2/8 \n", - "Intellectual disability, mild [HP:0001256] 3/12 25% 1/2 \n", - "Long palpebral fissure [HP:0000637] 8/8 100% 17/21 \n", - "Sparse lateral eyebrow [HP:0005338] 6/7 86% 5/8 \n", - "Seizure [HP:0001250] 2/8 25% 2/17 \n", - "Congenital hip dislocation [HP:0001374] 1/7 14% 5/16 \n", - "Clinodactyly of the 5th finger [HP:0004209] 2/9 22% 4/11 \n", - "Proportionate short stature [HP:0003508] 7/11 64% 4/9 \n", - "Severe short stature [HP:0003510] 7/12 58% 4/10 \n", - "Scoliosis [HP:0002650] 6/19 32% 4/17 \n", - "Depressed nasal tip [HP:0000437] 16/20 80% 20/27 \n", - "Thin upper lip vermilion [HP:0000219] 3/4 75% 4/6 \n", - "Delayed speech and language development [HP:000... 8/10 80% 2/2 \n", - "Feeding difficulties [HP:0011968] 5/14 36% 3/11 \n", - "High, narrow palate [HP:0002705] 8/9 89% 6/6 \n", - "Joint hypermobility [HP:0001382] 2/7 29% 3/12 \n", - "Long eyelashes [HP:0000527] 0/1 0% 3/6 \n", - "Cleft palate [HP:0000175] 9/10 90% 8/8 \n", - "Low posterior hairline [HP:0002162] 0/1 0% 2/6 \n", - "Prominent fingertip pads [HP:0001212] 12/15 80% 18/23 \n", - "Ectopic kidney [HP:0000086] 0/2 0% 2/9 \n", - "Decreased circulating IgA level [HP:0002720] 2/8 25% 2/5 \n", - "Wide nasal bridge [HP:0000431] 3/3 100% 11/14 \n", - "Postnatal growth retardation [HP:0008897] 5/8 62% 4/5 \n", - "Micrognathia [HP:0000347] 3/6 50% 4/9 \n", - "Microcephaly [HP:0000252] 3/7 43% 4/11 \n", - "High palate [HP:0000218] 10/11 91% 8/8 \n", - "Sparse eyebrow [HP:0045075] 6/7 86% 8/11 \n", - "Recurrent infections [HP:0002719] 15/21 71% 15/20 \n", - "Short stature [HP:0004322] 9/13 69% 13/18 \n", - "\n", - "MISSENSE_VARIANT on NM_003482.4 \\\n", - " Percent p value \n", - "Sensorineural hearing impairment [HP:0000407] 0% 0.003432 \n", - "Hearing impairment [HP:0000365] 38% 0.030871 \n", - "Ventricular septal defect [HP:0001629] 24% 0.061943 \n", - "High forehead [HP:0000348] 20% 0.080087 \n", - "Motor delay [HP:0001270] 100% 0.133333 \n", - "Hypotonia [HP:0001252] 71% 0.158824 \n", - "Decreased proportion of CD4-positive, alpha-bet... 40% 0.292929 \n", - "Blue sclerae [HP:0000592] 30% 0.349959 \n", - "Highly arched eyebrow [HP:0002553] 67% 0.374190 \n", - "Atrial septal defect [HP:0001631] 46% 0.374226 \n", - "Eversion of lateral third of lower eyelids [HP:... 89% 0.386466 \n", - "Sacral dimple [HP:0000960] 60% 0.454545 \n", - "Recurrent otitis media [HP:0000403] 35% 0.476451 \n", - "Decreased proportion of memory B cells [HP:0030... 100% 0.487179 \n", - "Renal duplication [HP:0000075] 25% 0.487179 \n", - "Intellectual disability, mild [HP:0001256] 50% 0.505495 \n", - "Long palpebral fissure [HP:0000637] 81% 0.552019 \n", - "Sparse lateral eyebrow [HP:0005338] 62% 0.569231 \n", - "Seizure [HP:0001250] 12% 0.569960 \n", - "Congenital hip dislocation [HP:0001374] 31% 0.621385 \n", - "Clinodactyly of the 5th finger [HP:0004209] 36% 0.642415 \n", - "Proportionate short stature [HP:0003508] 44% 0.653417 \n", - "Severe short stature [HP:0003510] 40% 0.669921 \n", - "Scoliosis [HP:0002650] 24% 0.716925 \n", - "Depressed nasal tip [HP:0000437] 74% 0.736504 \n", - "Thin upper lip vermilion [HP:0000219] 67% 1.000000 \n", - "Delayed speech and language development [HP:000... 100% 1.000000 \n", - "Feeding difficulties [HP:0011968] 27% 1.000000 \n", - "High, narrow palate [HP:0002705] 100% 1.000000 \n", - "Joint hypermobility [HP:0001382] 25% 1.000000 \n", - "Long eyelashes [HP:0000527] 50% 1.000000 \n", - "Cleft palate [HP:0000175] 100% 1.000000 \n", - "Low posterior hairline [HP:0002162] 33% 1.000000 \n", - "Prominent fingertip pads [HP:0001212] 78% 1.000000 \n", - "Ectopic kidney [HP:0000086] 22% 1.000000 \n", - "Decreased circulating IgA level [HP:0002720] 40% 1.000000 \n", - "Wide nasal bridge [HP:0000431] 79% 1.000000 \n", - "Postnatal growth retardation [HP:0008897] 80% 1.000000 \n", - "Micrognathia [HP:0000347] 44% 1.000000 \n", - "Microcephaly [HP:0000252] 36% 1.000000 \n", - "High palate [HP:0000218] 100% 1.000000 \n", - "Sparse eyebrow [HP:0045075] 73% 1.000000 \n", - "Recurrent infections [HP:0002719] 75% 1.000000 \n", - "Short stature [HP:0004322] 72% 1.000000 \n", - "\n", - "MISSENSE_VARIANT on NM_003482.4 \n", - " Corrected p value \n", - "Sensorineural hearing impairment [HP:0000407] 0.15103 \n", - "Hearing impairment [HP:0000365] 1.00000 \n", - "Ventricular septal defect [HP:0001629] 1.00000 \n", - "High forehead [HP:0000348] 1.00000 \n", - "Motor delay [HP:0001270] 1.00000 \n", - "Hypotonia [HP:0001252] 1.00000 \n", - "Decreased proportion of CD4-positive, alpha-bet... 1.00000 \n", - "Blue sclerae [HP:0000592] 1.00000 \n", - "Highly arched eyebrow [HP:0002553] 1.00000 \n", - "Atrial septal defect [HP:0001631] 1.00000 \n", - "Eversion of lateral third of lower eyelids [HP:... 1.00000 \n", - "Sacral dimple [HP:0000960] 1.00000 \n", - "Recurrent otitis media [HP:0000403] 1.00000 \n", - "Decreased proportion of memory B cells [HP:0030... 1.00000 \n", - "Renal duplication [HP:0000075] 1.00000 \n", - "Intellectual disability, mild [HP:0001256] 1.00000 \n", - "Long palpebral fissure [HP:0000637] 1.00000 \n", - "Sparse lateral eyebrow [HP:0005338] 1.00000 \n", - "Seizure [HP:0001250] 1.00000 \n", - "Congenital hip dislocation [HP:0001374] 1.00000 \n", - "Clinodactyly of the 5th finger [HP:0004209] 1.00000 \n", - "Proportionate short stature [HP:0003508] 1.00000 \n", - "Severe short stature [HP:0003510] 1.00000 \n", - "Scoliosis [HP:0002650] 1.00000 \n", - "Depressed nasal tip [HP:0000437] 1.00000 \n", - "Thin upper lip vermilion [HP:0000219] 1.00000 \n", - "Delayed speech and language development [HP:000... 1.00000 \n", - "Feeding difficulties [HP:0011968] 1.00000 \n", - "High, narrow palate [HP:0002705] 1.00000 \n", - "Joint hypermobility [HP:0001382] 1.00000 \n", - "Long eyelashes [HP:0000527] 1.00000 \n", - "Cleft palate [HP:0000175] 1.00000 \n", - "Low posterior hairline [HP:0002162] 1.00000 \n", - "Prominent fingertip pads [HP:0001212] 1.00000 \n", - "Ectopic kidney [HP:0000086] 1.00000 \n", - "Decreased circulating IgA level [HP:0002720] 1.00000 \n", - "Wide nasal bridge [HP:0000431] 1.00000 \n", - "Postnatal growth retardation [HP:0008897] 1.00000 \n", - "Micrognathia [HP:0000347] 1.00000 \n", - "Microcephaly [HP:0000252] 1.00000 \n", - "High palate [HP:0000218] 1.00000 \n", - "Sparse eyebrow [HP:0045075] 1.00000 \n", - "Recurrent infections [HP:0002719] 1.00000 \n", - "Short stature [HP:0004322] 1.00000 " - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from gpsea.model import VariantEffect\n", - "from gpsea.analysis.predicate.genotype import VariantPredicates\n", - "\n", - "is_missense = VariantPredicates.variant_effect(VariantEffect.MISSENSE_VARIANT, tx_id=KTM2D_transcript_id)\n", - "missense = analysis.compare_hpo_vs_genotype(is_missense)\n", - "missense.summarize(hpo, PatientCategories.YES)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "enviro", - "language": "python", - "name": "enviro" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.10" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/case_studies/LMNA/LMNA.ipynb b/case_studies/LMNA/LMNA.ipynb deleted file mode 100644 index 6c9416eb..00000000 --- a/case_studies/LMNA/LMNA.ipynb +++ /dev/null @@ -1,1628 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "e74be9ff0537de82", - "metadata": {}, - "source": [ - "# LMNA" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "5a3af44bc3c0aef5", - "metadata": { - "ExecuteTime": { - "end_time": "2024-02-20T14:57:02.243666600Z", - "start_time": "2024-02-20T14:57:02.236667Z" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Loaded HPO v2023-10-09\n", - "Using gpsea version 0.2.1.dev0\n" - ] - } - ], - "source": [ - "import gpsea\n", - "import hpotk\n", - "\n", - "store = hpotk.configure_ontology_store()\n", - "hpo = store.load_minimal_hpo(release='v2023-10-09')\n", - "print(f'Loaded HPO v{hpo.version}')\n", - "print(f\"Using gpsea version {gpsea.__version__}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "5c9e5d8b5b134e1a", - "metadata": { - "ExecuteTime": { - "end_time": "2024-02-20T14:57:06.568095Z", - "start_time": "2024-02-20T14:57:02.248177800Z" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Patients Created: 100%|██████████| 127/127 [00:00<00:00, 341.23it/s]\n", - "Validated under none policy\n", - "No errors or warnings were found\n" - ] - } - ], - "source": [ - "from ppktstore.registry import configure_phenopacket_registry\n", - "from gpsea.preprocessing import configure_caching_cohort_creator, load_phenopackets\n", - "\n", - "cohort_creator = configure_caching_cohort_creator(hpo)\n", - "\n", - "cohort_name = 'LMNA'\n", - "phenopacket_store_release = '0.1.19'\n", - "\n", - "registry = configure_phenopacket_registry()\n", - "with registry.open_phenopacket_store(phenopacket_store_release) as ps:\n", - " phenopackets = tuple(ps.iter_cohort_phenopackets(cohort_name))\n", - "\n", - "cohort, validation = load_phenopackets(\n", - " phenopackets=phenopackets, \n", - " cohort_creator=cohort_creator,\n", - ")\n", - "del phenopackets\n", - "validation.summarize()" - ] - }, - { - "cell_type": "markdown", - "id": "4774dd9216a253fc", - "metadata": {}, - "source": [ - "## Transcript\n", - "Get it by looking for gene symbol in https://www.ncbi.nlm.nih.gov/clinvar/ look for pathogenic\n", - "zcopy it and go to https://variantvalidator.org/service/validate/, then scroll down to copy GRCH38 string, copy this and put into same website\n", - "\n", - "looking for MANE select plus clinical (most important transcript for clinic) if doesnt exist, use clinvar result" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "624466e48a2046e", - "metadata": { - "ExecuteTime": { - "end_time": "2024-02-20T16:06:01.974507100Z", - "start_time": "2024-02-20T16:06:01.968506100Z" - } - }, - "outputs": [], - "source": [ - "LMNA_MANE_transcript = 'NM_170707.4'\n", - "LMNA_protein_id = 'NP_005563.1'" - ] - }, - { - "cell_type": "markdown", - "id": "986dd1fb634d9a62", - "metadata": {}, - "source": [ - "## Explore Cohort" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "5c27ec7e5affa54f", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - " \n", - " Cohort\n", - " \n", - "\n", - "\n", - "\n", - "

GPSEA cohort analysis

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Successfully loaded 127 individuals.

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No errors encountered.

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Top 10 HPO Terms

\n", - " A total of 214 HPO terms were used to annotated the cohort.\n", - "
HPO TermIDSeen in n individuals
Ankle contractureHP:003467739
Elbow contractureHP:003439137
Spinal rigidityHP:000330637
Stiff neckHP:002525836
Proximal muscle weakness in upper limbsHP:000899735
Dilated cardiomyopathyHP:000164427
Atrial fibrillationHP:000511025
ArrhythmiaHP:001167523
LipodystrophyHP:000912521
Proximal muscle weakness in lower limbsHP:000899421
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Top 10 Variants

\n", - " Variants are shown according to NM_170707.4. A total of 127 unique variants were identified in the cohort.\n", - "
CountVariant keyVariant NameProtein VariantVariant Class
151_156138613_156138613_C_Tc.1824C>Tp.Gly608=SYNONYMOUS_VARIANT
111_156134474_156134474_C_Ac.585C>Ap.Asn195LysMISSENSE_VARIANT
81_156134497_156134497_A_Gc.608A>Gp.Glu203GlyMISSENSE_VARIANT
81_156137756_156137756_C_Ac.1698+13C>ANoneINTRON_VARIANT
81_156137204_156137204_G_Cc.1580G>Cp.Arg527ProMISSENSE_VARIANT
71_156115096_156115096_C_Gc.178C>Gp.Arg60GlyMISSENSE_VARIANT
71_156136984_156136984_C_Tc.1444C>Tp.Arg482TrpMISSENSE_VARIANT
61_156136413_156136413_C_Tc.1357C>Tp.Arg453TrpMISSENSE_VARIANT
61_156136036_156136036_G_Ac.1072G>Ap.Glu358LysMISSENSE_VARIANT
51_156135922_156135923_CT_Cc.960delp.Arg321GlufsTer159FRAMESHIFT_VARIANT
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Diseases

\n", - "
Disease NameDisease IDAnnotation Count
Cardiomyopathy, dilated, 1AOMIM:11520044
Emery-Dreifuss muscular dystrophy 2, autosomal dominantOMIM:18135041
Hutchinson-Gilford progeriaOMIM:17667015
LMNA-related congenital muscular dystrophyOMIM:61320515
Lipodystrophy, familial partial, type 2OMIM:15166012
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Variant categories for NM_170707.4

\n", - "
Variant effectAnnotation Count
SYNONYMOUS_VARIANT15
MISSENSE_VARIANT90
INTRON_VARIANT8
STOP_GAINED5
INFRAME_DELETION3
FRAMESHIFT_VARIANT5
SPLICE_ACCEPTOR_VARIANT1
SPLICE_REGION_VARIANT4
\n", - " \n", - "\n", - "\n", - "\n", - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from gpsea.view import CohortViewable\n", - "from IPython.display import HTML, display\n", - "\n", - "viewer = CohortViewable(hpo)\n", - "display(HTML(viewer.process(cohort=cohort, transcript_id=LMNA_MANE_transcript)))" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "5f2324c7", - "metadata": {}, - "outputs": [], - "source": [ - "from gpsea.preprocessing import configure_protein_metadata_service\n", - "from gpsea.preprocessing import VVMultiCoordinateService\n", - "from gpsea.model.genome import GRCh38\n", - "\n", - "pms = configure_protein_metadata_service()\n", - "protein_meta = pms.annotate(LMNA_protein_id)\n", - "txc_service = VVMultiCoordinateService(genome_build=GRCh38)\n", - "tx_coordinates = txc_service.fetch(LMNA_MANE_transcript)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "3b692a52", - "metadata": {}, - "outputs": [], - "source": [ - "from gpsea.view import ProteinVisualizable, ProteinVisualizer, ProteinViewable\n", - "\n", - "pvis = ProteinVisualizable(tx_coordinates=tx_coordinates, protein_meta=protein_meta, cohort=cohort)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "a8a1145a", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - " \n", - " Cohort\n", - " \n", - "\n", - "\n", - "\n", - "

GPSEA protein analysis

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The UniProt API successfully returned protein information for ID: NP_005563.1

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Protein Name: Prelamin-A/C

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Protein Features

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Feature NameFeature TypeFeature CoordinatesVariants in Feature
Interaction with MLIPregion1 - 13026
Headregion1 - 337
Disorderedregion1 - 256
IF roddomain31 - 38767
Coil 1Aregion34 - 7013
Linker 1region71 - 800
Coil 1Bregion81 - 21825
Linker 2region219 - 2425
Coil 2region243 - 38319
Necessary and sufficient for the interaction with IFFO1region259 - 3318
Tailregion384 - 66449
Disorderedregion384 - 4425
Nuclear localization signalmotif417 - 4220
LTDdomain428 - 54528
Disorderedregion552 - 5761
Disorderedregion598 - 61915
\n", - "\n", - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "viewer = ProteinViewable()\n", - "html_prot = viewer.process(cohort, pvis)\n", - "display(HTML(html_prot))" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "804d21d7", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "drawer = ProteinVisualizer()\n", - "drawer.draw_fig(pvis=pvis)" - ] - }, - { - "cell_type": "markdown", - "id": "3cde1a84a1b62676", - "metadata": {}, - "source": [ - "## Configure the analysis" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "d0ee56e0c371dcd1", - "metadata": {}, - "outputs": [], - "source": [ - "from gpsea.analysis import configure_cohort_analysis, CohortAnalysisConfiguration\n", - "from gpsea.analysis.predicate import PatientCategories\n", - "from gpsea.model.genome import Region\n", - "\n", - "analysis_config = CohortAnalysisConfiguration()\n", - "analysis_config.missing_implies_excluded = False\n", - "analysis_config.hpo_mtc_strategy()\n", - "\n", - "analysis = configure_cohort_analysis(cohort, hpo, config=analysis_config)\n" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "0be03eb2", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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MISSENSE_VARIANT on NM_170707.4YesNo
CountPercentCountPercentp valueCorrected p value
Lipodystrophy [HP:0009125]10/7513%15/3543%0.0011670.040862
Alopecia [HP:0001596]0/30%15/15100%0.0012250.042892
Prominent superficial blood vessels [HP:0007394]0/30%15/15100%0.0012250.042892
Reduced subcutaneous adipose tissue [HP:0003758]0/30%15/15100%0.0012250.042892
Proptosis [HP:0000520]0/30%15/15100%0.0012250.042892
Failure to thrive [HP:0001508]0/30%15/15100%0.0012250.042892
Micrognathia [HP:0000347]0/30%15/15100%0.0012250.042892
Short stature [HP:0004322]1/425%15/15100%0.0041280.144479
Reduced bone mineral density [HP:0004349]2/540%15/15100%0.0087720.307018
Increased circulating creatine kinase MM isoform [HP:0032234]0/40%3/3100%0.0285711.000000
Left ventricular systolic dysfunction [HP:0025169]2/258%3/743%0.0565911.000000
Abnormal left ventricular ejection fraction [HP:0034314]2/258%3/743%0.0565911.000000
Reduced left ventricular ejection fraction [HP:0012664]2/297%3/838%0.0569451.000000
Respiratory insufficiency due to muscle weakness [HP:0002747]11/1385%0/20%0.0571431.000000
Abnormal left ventricular function [HP:0005162]8/3126%6/1060%0.0644781.000000
Abnormal atrioventricular conduction [HP:0005150]26/26100%9/1182%0.0825831.000000
Cardiac conduction abnormality [HP:0031546]26/26100%10/1283%0.0938831.000000
Mildly reduced left ventricular ejection fraction [HP:0012663]1/284%2/729%0.0951871.000000
Ventricular tachycardia [HP:0004756]1/138%2/450%0.1205881.000000
Sudden cardiac death [HP:0001645]11/2152%1/714%0.1842441.000000
Dilated cardiomyopathy [HP:0001644]23/3566%4/944%0.2746871.000000
Atrial fibrillation [HP:0005110]21/3266%4/944%0.2762631.000000
Tube feeding [HP:0033454]2/1315%1/250%0.3714291.000000
Highly elevated creatine kinase [HP:0030234]15/3642%1/617%0.3804551.000000
Heart block [HP:0012722]8/8100%9/1182%0.4853801.000000
Talipes [HP:0001883]6/1638%0/20%0.5294121.000000
Abnormal circulating creatine kinase concentration [HP:0040081]25/2986%9/9100%0.5544811.000000
Loss of ambulation [HP:0002505]9/1656%1/333%0.5820431.000000
Second degree atrioventricular block [HP:0011706]3/650%3/560%1.0000001.000000
Decreased fetal movement [HP:0001558]3/1323%0/20%1.0000001.000000
Neck muscle weakness [HP:0000467]10/1377%2/2100%1.0000001.000000
Third degree atrioventricular block [HP:0001709]2/540%3/560%1.0000001.000000
Atrioventricular block [HP:0001678]8/1173%8/1080%1.0000001.000000
Talipes equinovarus [HP:0001762]3/1323%0/20%1.0000001.000000
Cardiomyopathy [HP:0001638]24/2789%4/4100%1.0000001.000000
\n", - "
" - ], - "text/plain": [ - "MISSENSE_VARIANT on NM_170707.4 Yes No \\\n", - " Count Percent Count \n", - "Lipodystrophy [HP:0009125] 10/75 13% 15/35 \n", - "Alopecia [HP:0001596] 0/3 0% 15/15 \n", - "Prominent superficial blood vessels [HP:0007394] 0/3 0% 15/15 \n", - "Reduced subcutaneous adipose tissue [HP:0003758] 0/3 0% 15/15 \n", - "Proptosis [HP:0000520] 0/3 0% 15/15 \n", - "Failure to thrive [HP:0001508] 0/3 0% 15/15 \n", - "Micrognathia [HP:0000347] 0/3 0% 15/15 \n", - "Short stature [HP:0004322] 1/4 25% 15/15 \n", - "Reduced bone mineral density [HP:0004349] 2/5 40% 15/15 \n", - "Increased circulating creatine kinase MM isofor... 0/4 0% 3/3 \n", - "Left ventricular systolic dysfunction [HP:0025169] 2/25 8% 3/7 \n", - "Abnormal left ventricular ejection fraction [HP... 2/25 8% 3/7 \n", - "Reduced left ventricular ejection fraction [HP:... 2/29 7% 3/8 \n", - "Respiratory insufficiency due to muscle weaknes... 11/13 85% 0/2 \n", - "Abnormal left ventricular function [HP:0005162] 8/31 26% 6/10 \n", - "Abnormal atrioventricular conduction [HP:0005150] 26/26 100% 9/11 \n", - "Cardiac conduction abnormality [HP:0031546] 26/26 100% 10/12 \n", - "Mildly reduced left ventricular ejection fracti... 1/28 4% 2/7 \n", - "Ventricular tachycardia [HP:0004756] 1/13 8% 2/4 \n", - "Sudden cardiac death [HP:0001645] 11/21 52% 1/7 \n", - "Dilated cardiomyopathy [HP:0001644] 23/35 66% 4/9 \n", - "Atrial fibrillation [HP:0005110] 21/32 66% 4/9 \n", - "Tube feeding [HP:0033454] 2/13 15% 1/2 \n", - "Highly elevated creatine kinase [HP:0030234] 15/36 42% 1/6 \n", - "Heart block [HP:0012722] 8/8 100% 9/11 \n", - "Talipes [HP:0001883] 6/16 38% 0/2 \n", - "Abnormal circulating creatine kinase concentrat... 25/29 86% 9/9 \n", - "Loss of ambulation [HP:0002505] 9/16 56% 1/3 \n", - "Second degree atrioventricular block [HP:0011706] 3/6 50% 3/5 \n", - "Decreased fetal movement [HP:0001558] 3/13 23% 0/2 \n", - "Neck muscle weakness [HP:0000467] 10/13 77% 2/2 \n", - "Third degree atrioventricular block [HP:0001709] 2/5 40% 3/5 \n", - "Atrioventricular block [HP:0001678] 8/11 73% 8/10 \n", - "Talipes equinovarus [HP:0001762] 3/13 23% 0/2 \n", - "Cardiomyopathy [HP:0001638] 24/27 89% 4/4 \n", - "\n", - "MISSENSE_VARIANT on NM_170707.4 \\\n", - " Percent p value \n", - "Lipodystrophy [HP:0009125] 43% 0.001167 \n", - "Alopecia [HP:0001596] 100% 0.001225 \n", - "Prominent superficial blood vessels [HP:0007394] 100% 0.001225 \n", - "Reduced subcutaneous adipose tissue [HP:0003758] 100% 0.001225 \n", - "Proptosis [HP:0000520] 100% 0.001225 \n", - "Failure to thrive [HP:0001508] 100% 0.001225 \n", - "Micrognathia [HP:0000347] 100% 0.001225 \n", - "Short stature [HP:0004322] 100% 0.004128 \n", - "Reduced bone mineral density [HP:0004349] 100% 0.008772 \n", - "Increased circulating creatine kinase MM isofor... 100% 0.028571 \n", - "Left ventricular systolic dysfunction [HP:0025169] 43% 0.056591 \n", - "Abnormal left ventricular ejection fraction [HP... 43% 0.056591 \n", - "Reduced left ventricular ejection fraction [HP:... 38% 0.056945 \n", - "Respiratory insufficiency due to muscle weaknes... 0% 0.057143 \n", - "Abnormal left ventricular function [HP:0005162] 60% 0.064478 \n", - "Abnormal atrioventricular conduction [HP:0005150] 82% 0.082583 \n", - "Cardiac conduction abnormality [HP:0031546] 83% 0.093883 \n", - "Mildly reduced left ventricular ejection fracti... 29% 0.095187 \n", - "Ventricular tachycardia [HP:0004756] 50% 0.120588 \n", - "Sudden cardiac death [HP:0001645] 14% 0.184244 \n", - "Dilated cardiomyopathy [HP:0001644] 44% 0.274687 \n", - "Atrial fibrillation [HP:0005110] 44% 0.276263 \n", - "Tube feeding [HP:0033454] 50% 0.371429 \n", - "Highly elevated creatine kinase [HP:0030234] 17% 0.380455 \n", - "Heart block [HP:0012722] 82% 0.485380 \n", - "Talipes [HP:0001883] 0% 0.529412 \n", - "Abnormal circulating creatine kinase concentrat... 100% 0.554481 \n", - "Loss of ambulation [HP:0002505] 33% 0.582043 \n", - "Second degree atrioventricular block [HP:0011706] 60% 1.000000 \n", - "Decreased fetal movement [HP:0001558] 0% 1.000000 \n", - "Neck muscle weakness [HP:0000467] 100% 1.000000 \n", - "Third degree atrioventricular block [HP:0001709] 60% 1.000000 \n", - "Atrioventricular block [HP:0001678] 80% 1.000000 \n", - "Talipes equinovarus [HP:0001762] 0% 1.000000 \n", - "Cardiomyopathy [HP:0001638] 100% 1.000000 \n", - "\n", - "MISSENSE_VARIANT on NM_170707.4 \n", - " Corrected p value \n", - "Lipodystrophy [HP:0009125] 0.040862 \n", - "Alopecia [HP:0001596] 0.042892 \n", - "Prominent superficial blood vessels [HP:0007394] 0.042892 \n", - "Reduced subcutaneous adipose tissue [HP:0003758] 0.042892 \n", - "Proptosis [HP:0000520] 0.042892 \n", - "Failure to thrive [HP:0001508] 0.042892 \n", - "Micrognathia [HP:0000347] 0.042892 \n", - "Short stature [HP:0004322] 0.144479 \n", - "Reduced bone mineral density [HP:0004349] 0.307018 \n", - "Increased circulating creatine kinase MM isofor... 1.000000 \n", - "Left ventricular systolic dysfunction [HP:0025169] 1.000000 \n", - "Abnormal left ventricular ejection fraction [HP... 1.000000 \n", - "Reduced left ventricular ejection fraction [HP:... 1.000000 \n", - "Respiratory insufficiency due to muscle weaknes... 1.000000 \n", - "Abnormal left ventricular function [HP:0005162] 1.000000 \n", - "Abnormal atrioventricular conduction [HP:0005150] 1.000000 \n", - "Cardiac conduction abnormality [HP:0031546] 1.000000 \n", - "Mildly reduced left ventricular ejection fracti... 1.000000 \n", - "Ventricular tachycardia [HP:0004756] 1.000000 \n", - "Sudden cardiac death [HP:0001645] 1.000000 \n", - "Dilated cardiomyopathy [HP:0001644] 1.000000 \n", - "Atrial fibrillation [HP:0005110] 1.000000 \n", - "Tube feeding [HP:0033454] 1.000000 \n", - "Highly elevated creatine kinase [HP:0030234] 1.000000 \n", - "Heart block [HP:0012722] 1.000000 \n", - "Talipes [HP:0001883] 1.000000 \n", - "Abnormal circulating creatine kinase concentrat... 1.000000 \n", - "Loss of ambulation [HP:0002505] 1.000000 \n", - "Second degree atrioventricular block [HP:0011706] 1.000000 \n", - "Decreased fetal movement [HP:0001558] 1.000000 \n", - "Neck muscle weakness [HP:0000467] 1.000000 \n", - "Third degree atrioventricular block [HP:0001709] 1.000000 \n", - "Atrioventricular block [HP:0001678] 1.000000 \n", - "Talipes equinovarus [HP:0001762] 1.000000 \n", - "Cardiomyopathy [HP:0001638] 1.000000 " - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from gpsea.model import VariantEffect\n", - "from gpsea.analysis.predicate import PatientCategories\n", - "from gpsea.analysis.predicate.genotype import VariantPredicates\n", - "\n", - "is_missense = VariantPredicates.variant_effect(VariantEffect.MISSENSE_VARIANT, LMNA_MANE_transcript)\n", - "by_missense = analysis.compare_hpo_vs_genotype(is_missense)\n", - "by_missense.summarize(hpo, PatientCategories.YES)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "9c7b451c", - "metadata": {}, - "outputs": [], - "source": [ - "analysis_config = CohortAnalysisConfiguration()\n", - "analysis_config.missing_implies_excluded = False\n", - "\n", - "analysis_nomtc = configure_cohort_analysis(cohort, hpo, config=analysis_config)" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "1b18c688", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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MISSENSE_VARIANT on NM_170707.4YesNo
CountPercentCountPercentp valueCorrected p value
OMIM:1766700/900%15/3741%8.025624e-104.012812e-09
OMIM:15166012/9013%0/370%1.807470e-029.037348e-02
OMIM:18135034/9038%7/3719%5.904112e-022.952056e-01
OMIM:61320513/9014%2/375%2.276691e-011.000000e+00
OMIM:11520031/9034%13/3735%1.000000e+001.000000e+00
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" - ], - "text/plain": [ - "MISSENSE_VARIANT on NM_170707.4 Yes No \\\n", - " Count Percent Count Percent p value \n", - "OMIM:176670 0/90 0% 15/37 41% 8.025624e-10 \n", - "OMIM:151660 12/90 13% 0/37 0% 1.807470e-02 \n", - "OMIM:181350 34/90 38% 7/37 19% 5.904112e-02 \n", - "OMIM:613205 13/90 14% 2/37 5% 2.276691e-01 \n", - "OMIM:115200 31/90 34% 13/37 35% 1.000000e+00 \n", - "\n", - "MISSENSE_VARIANT on NM_170707.4 \n", - " Corrected p value \n", - "OMIM:176670 4.012812e-09 \n", - "OMIM:151660 9.037348e-02 \n", - "OMIM:181350 2.952056e-01 \n", - "OMIM:613205 1.000000e+00 \n", - "OMIM:115200 1.000000e+00 " - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "by_dis = analysis_nomtc.compare_disease_vs_genotype(is_missense)\n", - "by_dis.summarize(hpo, PatientCategories.YES)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9285e5dc", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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variant has ID of 1_156138613_156138613_C_TYesNo
CountPercentCountPercentp valueCorrected p value
Lipodystrophy [HP:0009125]15/15100%10/9511%2.780126e-122.502113e-11
Prominent superficial blood vessels [HP:0007394]15/15100%0/30%1.225490e-031.102941e-02
Reduced subcutaneous adipose tissue [HP:0003758]15/15100%0/30%1.225490e-031.102941e-02
Proptosis [HP:0000520]15/15100%0/30%1.225490e-031.102941e-02
Micrognathia [HP:0000347]15/15100%0/30%1.225490e-031.102941e-02
Failure to thrive [HP:0001508]15/15100%0/30%1.225490e-031.102941e-02
Alopecia [HP:0001596]15/15100%0/30%1.225490e-031.102941e-02
Short stature [HP:0004322]15/15100%1/425%4.127967e-033.715170e-02
Reduced bone mineral density [HP:0004349]15/15100%2/540%8.771930e-037.894737e-02
\n", - "
" - ], - "text/plain": [ - "variant has ID of 1_156138613_156138613_C_T Yes No \\\n", - " Count Percent Count \n", - "Lipodystrophy [HP:0009125] 15/15 100% 10/95 \n", - "Prominent superficial blood vessels [HP:0007394] 15/15 100% 0/3 \n", - "Reduced subcutaneous adipose tissue [HP:0003758] 15/15 100% 0/3 \n", - "Proptosis [HP:0000520] 15/15 100% 0/3 \n", - "Micrognathia [HP:0000347] 15/15 100% 0/3 \n", - "Failure to thrive [HP:0001508] 15/15 100% 0/3 \n", - "Alopecia [HP:0001596] 15/15 100% 0/3 \n", - "Short stature [HP:0004322] 15/15 100% 1/4 \n", - "Reduced bone mineral density [HP:0004349] 15/15 100% 2/5 \n", - "\n", - "variant has ID of 1_156138613_156138613_C_T \\\n", - " Percent p value \n", - "Lipodystrophy [HP:0009125] 11% 2.780126e-12 \n", - "Prominent superficial blood vessels [HP:0007394] 0% 1.225490e-03 \n", - "Reduced subcutaneous adipose tissue [HP:0003758] 0% 1.225490e-03 \n", - "Proptosis [HP:0000520] 0% 1.225490e-03 \n", - "Micrognathia [HP:0000347] 0% 1.225490e-03 \n", - "Failure to thrive [HP:0001508] 0% 1.225490e-03 \n", - "Alopecia [HP:0001596] 0% 1.225490e-03 \n", - "Short stature [HP:0004322] 25% 4.127967e-03 \n", - "Reduced bone mineral density [HP:0004349] 40% 8.771930e-03 \n", - "\n", - "variant has ID of 1_156138613_156138613_C_T \n", - " Corrected p value \n", - "Lipodystrophy [HP:0009125] 2.502113e-11 \n", - "Prominent superficial blood vessels [HP:0007394] 1.102941e-02 \n", - "Reduced subcutaneous adipose tissue [HP:0003758] 1.102941e-02 \n", - "Proptosis [HP:0000520] 1.102941e-02 \n", - "Micrognathia [HP:0000347] 1.102941e-02 \n", - "Failure to thrive [HP:0001508] 1.102941e-02 \n", - "Alopecia [HP:0001596] 1.102941e-02 \n", - "Short stature [HP:0004322] 3.715170e-02 \n", - "Reduced bone mineral density [HP:0004349] 7.894737e-02 " - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "is_var_key = VariantPredicates.variant_key('1_156138613_156138613_C_T')\n", - "by_var = analysis.compare_hpo_vs_genotype(is_var_key)\n", - "by_var.summarize(hpo, PatientCategories.YES)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ab73d5d6", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9511b7a5", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "enviro", - "language": "python", - "name": "enviro" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.10" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -}