{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Using TensorFlow backend.\n"
]
}
],
"source": [
"from __future__ import print_function\n",
"import keras\n",
"from keras.models import Sequential, Model, load_model\n",
"from keras import backend as K\n",
"\n",
"import tensorflow as tf\n",
"\n",
"import os\n",
"import pandas as pd\n",
"\n",
"import numpy as np\n",
"\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib.cm as cm\n",
"\n",
"import aparent.visualization as vis\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Load APARENT model \n",
"Example: PSMC6 Gene variant prediction \n",
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"#Example PAS sequence from APADB (gene = PSMC6)\n",
"\n",
"#PAS Sequence\n",
"seq = 'AGATAGTGGTATAAGAAAGCATTTCTTATGACTTATTTTGTATCATTTGTTTTCCTCATCTAAAAAGTTGAATAAAATCTGTTTGATTCAGTTCTCCTACATATATATTCTTGTCTTTTCTGAGTATATTTACTGTGGTCCTTTAGGTTCTTTAGCAAGTAAACTATTTGATAACCCAGATGGATTGTGGATTTTTGAATATTAT'\n",
"\n",
"#Predict mutation map (single-nucleotide variants)\n",
"vis.mut_map(\n",
" aparent_model,\n",
" seq,\n",
" [(100, 'T', 'red')],\n",
" seq_start=70-45,\n",
" seq_end=70+6+45,\n",
" isoform_start=80,\n",
" isoform_end=110,\n",
" figsize=(14, 6),\n",
" height_ratios=[4, 1, 1.5],\n",
" logodds_clip=1.0\n",
")\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python [conda env:aparent]",
"language": "python",
"name": "conda-env-aparent-py"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.8"
}
},
"nbformat": 4,
"nbformat_minor": 2
}