Datasets
Models
Downloads: 1
1070 lines (1069 with data), 60.0 kB
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Downloads for DeepSEA and DanQ binding prediction"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This notebook downloads data required for the DeepSEA and DanQ use case."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"import pandas as pd\n",
"import urllib.request"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"output = '../02_deepsea_danq_prediction/data'\n",
"os.makedirs(output, exist_ok=True)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"df = pd.read_csv('../extra/urls.txt', header=None)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
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"wgEncodeAwgTfbsHaibHepg2Mbd4sc271530V0422111UniPk.narrowPeak.gz\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
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{
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"wgEncodeAwgTfbsUtaMcf7Pol2UniPk.narrowPeak.gz\n"
]
},
{
"name": "stdout",
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"E129-H3K4me2.narrowPeak.gz\n",
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"E129-H3K79me2.narrowPeak.gz\n",
"E129-H3K9me3.narrowPeak.gz\n"
]
}
],
"source": [
"for idx, row in df.iterrows():\n",
" print(os.path.basename(row[0]))\n",
" urllib.request.urlretrieve (row[0], os.path.join(output, os.path.basename(row[0])))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"--2019-06-26 01:06:07-- http://hgdownload.cse.ucsc.edu/goldenPath/hg19/bigZips/hg19.fa.gz\n",
"Resolving hgdownload.cse.ucsc.edu (hgdownload.cse.ucsc.edu)... 128.114.119.163\n",
"Connecting to hgdownload.cse.ucsc.edu (hgdownload.cse.ucsc.edu)|128.114.119.163|:80... connected.\n",
"HTTP request sent, awaiting response... 200 OK\n",
"Length: 948731419 (905M) [application/x-gzip]\n",
"Saving to: ‘../02_deepsea_danq_prediction/data/hg19.fa.gz’\n",
"\n",
"../02_deepsea_danq_ 100%[===================>] 904,78M 759KB/s in 20m 54s \n",
"\n",
"2019-06-26 01:27:02 (739 KB/s) - ‘../02_deepsea_danq_prediction/data/hg19.fa.gz’ saved [948731419/948731419]\n",
"\n",
"gzip: ../02_deepsea_danq_prediction/data/hg19.fa already exists; do you wish to overwrite (y or n)? "
]
}
],
"source": [
"!wget http://hgdownload.cse.ucsc.edu/goldenPath/hg19/bigZips/hg19.fa.gz -O {output}/hg19.fa.gz\n",
"!gunzip {output}/hg19.fa.gz"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.6.7"
}
},
"nbformat": 4,
"nbformat_minor": 2
}