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cthoyt/ground_odisea.ipynb

Last active May 5, 2022 13:45
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Ground ODiseA
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ground_odisea.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "ee895d12",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Disease_ID</th>\n",
" <th>Disease_name</th>\n",
" <th>Gene_symbol</th>\n",
" <th>Tissue</th>\n",
" <th>Inflicted</th>\n",
" <th>Pathogenic</th>\n",
" <th>Phenotypic_series_ID</th>\n",
" <th>Phenotypic_series_name</th>\n",
" <th>Gene_expression_TPM</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>617140</td>\n",
" <td>ZTTK syndrome</td>\n",
" <td>SON</td>\n",
" <td>Kidney</td>\n",
" <td>Yes</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>35.4364\\r</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>216340</td>\n",
" <td>Yunis-Varon syndrome</td>\n",
" <td>FIG4</td>\n",
" <td>Blood and bone marrow</td>\n",
" <td>Yes</td>\n",
" <td>Yes</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>10.2865\\r</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>615829</td>\n",
" <td>Xia-Gibbs syndrome</td>\n",
" <td>AHDC1</td>\n",
" <td>Brain</td>\n",
" <td>Yes</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>\\r</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>278300</td>\n",
" <td>Xanthinuria, type I</td>\n",
" <td>XDH</td>\n",
" <td>Kidney</td>\n",
" <td>Yes</td>\n",
" <td>NaN</td>\n",
" <td>PS278300</td>\n",
" <td>Xanthinuria</td>\n",
" <td>0.200846\\r</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>278000</td>\n",
" <td>Wolman disease</td>\n",
" <td>LIPA</td>\n",
" <td>Blood and bone marrow</td>\n",
" <td>Yes</td>\n",
" <td>Yes</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>15.211\\r</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Disease_ID Disease_name Gene_symbol Tissue \\\n",
"0 617140 ZTTK syndrome SON Kidney \n",
"1 216340 Yunis-Varon syndrome FIG4 Blood and bone marrow \n",
"2 615829 Xia-Gibbs syndrome AHDC1 Brain \n",
"3 278300 Xanthinuria, type I XDH Kidney \n",
"4 278000 Wolman disease LIPA Blood and bone marrow \n",
"\n",
" Inflicted Pathogenic Phenotypic_series_ID Phenotypic_series_name \\\n",
"0 Yes NaN NaN NaN \n",
"1 Yes Yes NaN NaN \n",
"2 Yes NaN NaN NaN \n",
"3 Yes NaN PS278300 Xanthinuria \n",
"4 Yes Yes NaN NaN \n",
"\n",
" Gene_expression_TPM \n",
"0 35.4364\\r \n",
"1 10.2865\\r \n",
"2 \\r \n",
"3 0.200846\\r \n",
"4 15.211\\r "
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import pandas as pd\n",
"import gilda\n",
"\n",
"# can't get directly?\n",
"# url = \"https://netbio.bgu.ac.il/8dfcaffc-94d2-4aa4-a687-11d9962c6d51\"\n",
"df = pd.read_csv(\"ODiseA_data.csv\")\n",
"df.head()"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "a7baa9c1",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"45"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.Tissue.nunique()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "2f91d167",
"metadata": {},
"outputs": [],
"source": [
"rows = []\n",
"for text in df.Tissue.unique():\n",
" parts = text.split(\"-\")\n",
" row = [text]\n",
" for part in parts:\n",
" results = gilda.ground(part, namespaces=[\"MESH\", \"UBERON\", \"BTO\"])\n",
" if results:\n",
" row.extend((\n",
" part,\n",
" results[0].term.db,\n",
" results[0].term.id,\n",
" results[0].term.entry_name,\n",
" ))\n",
" else:\n",
" row.extend((part, None, None, None))\n",
" rows.append(row)\n",
"\n",
"results_df = pd.DataFrame(rows)\n",
"results_df.to_csv(\"results.tsv\", sep=\"\\t\", index=False)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.2"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
Raw
results.tsv
0 1 2 3 4 5 6 7 8 9 10 11 12
Kidney Kidney MESH D007668 Kidney
Blood and bone marrow Blood and bone marrow
Brain Brain MESH D001921 Brain
Respiratory system-Lung Respiratory system MESH D012137 Respiratory System Lung MESH D008168 Lung
Respiratory system Respiratory system MESH D012137 Respiratory System
Testis Testis MESH D013737 Testis
Brain-Cortex Brain MESH D001921 Brain Cortex
Ovary Ovary MESH D010053 Ovary
Skin Skin MESH D012867 Skin
Liver Liver MESH D008099 Liver
Respiratory system-Trachea Respiratory system MESH D012137 Respiratory System Trachea MESH D014132 Trachea
Heart Heart MESH D006321 Heart
Heart-Ventricle Heart MESH D006321 Heart Ventricle
Heart-Atrium Heart MESH D006321 Heart Atrium
Thyroid Thyroid MESH D013961 Thyroid Gland
Peripheral nerve Peripheral nerve MESH D010525 Peripheral Nerves
Skeletal muscle Skeletal muscle MESH D018482 Muscle, Skeletal
Artery-Aorta Artery MESH D001158 Arteries Aorta MESH D001011 Aorta
Artery Artery MESH D001158 Arteries
Brain-Basal ganglia Brain MESH D001921 Brain Basal ganglia MESH D001479 Basal Ganglia
Brain-Basal ganglia-Caudate nucleus Brain MESH D001921 Brain Basal ganglia MESH D001479 Basal Ganglia Caudate nucleus MESH D002421 Caudate Nucleus
Artery-Coronary Artery MESH D001158 Arteries Coronary
Brain-Basal ganglia-Substantia nigra Brain MESH D001921 Brain Basal ganglia MESH D001479 Basal Ganglia Substantia nigra MESH D013378 Substantia Nigra
Brain-Basal ganglia-Putamen Brain MESH D001921 Brain Basal ganglia MESH D001479 Basal Ganglia Putamen MESH D011699 Putamen
Brain-Basal ganglia-Nucleus accumbens Brain MESH D001921 Brain Basal ganglia MESH D001479 Basal Ganglia Nucleus accumbens MESH D009714 Nucleus Accumbens
Brain-Cerebellum Brain MESH D001921 Brain Cerebellum MESH D002531 Cerebellum
Spinal cord Spinal cord MESH D013116 Spinal Cord
Adipose-Subcutaneous Adipose Subcutaneous
Adipose Adipose
Adipose-Visceral Adipose Visceral
Pituitary Pituitary
Digestive system-Esophagus Digestive system MESH D004064 Digestive System Esophagus MESH D004947 Esophagus
Digestive system Digestive system MESH D004064 Digestive System
Digestive system-Esophagus-Mucosa Digestive system MESH D004064 Digestive System Esophagus MESH D004947 Esophagus Mucosa MESH D009092 Mucous Membrane
Eye Eye MESH D005123 Eye
Brain-Hypothalamus Brain MESH D001921 Brain Hypothalamus MESH D007031 Hypothalamus
Bone Bone
Digestive system-Esophagus-Gastroesophageal junction Digestive system MESH D004064 Digestive System Esophagus MESH D004947 Esophagus Gastroesophageal junction MESH D004943 Esophagogastric Junction
Cervix Cervix MESH D002584 Cervix Uteri
Eye-Retina Eye MESH D005123 Eye Retina MESH D012160 Retina
Digestive system-Colon Digestive system MESH D004064 Digestive System Colon MESH D003106 Colon
Uterus Uterus MESH D014599 Uterus
Mammary gland Mammary gland MESH D042361 Mammary Glands, Human
Brain-Cortex-Frontal Brain MESH D001921 Brain Cortex Frontal
Pancreas Pancreas MESH D010179 Pancreas
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