{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# For its use in colab notebook\n",
"!pip install jbrowse-jupyter"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# For its use in colab notebook\n",
"!pip install pandas\n",
"!pip install --force-reinstall MarkupSafe==2.0.1"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"from jbrowse_jupyter import launch, create"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"hg38 = create('LGV', genome='hg38')"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" refName start end name\n",
"0 10 100 175 feature1\n",
"1 10 150 225 feature2\n",
"2 10 200 275 feature3\n",
"3 10 250 325 feature4\n"
]
}
],
"source": [
"data = {'refName':['10', '10', '10', '10'],\n",
" 'start':[100, 150, 200, 250],\n",
" 'end':[175, 225, 275, 325],\n",
" 'name':['feature1', 'feature2', 'feature3', 'feature4']}\n",
"\n",
"df = pd.DataFrame(data)\n",
"print(df)\n",
"hg38.add_df_track(df, 'track_name', track_id=\"df_track_id\", overwrite=True)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
" "
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"hg38.set_location(\"10:100..350\")\n",
"hg38.set_default_session(['df_track_id'], False)\n",
"new_conf = hg38.get_config()\n",
"launch(new_conf, port=3013)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"tracks = [\n",
" (\"https://s3.amazonaws.com/jbrowse.org/genomes/GRCh38/ncbi_refseq/GCA_000001405.15_GRCh38_full_analysis_set.refseq_annotation.sorted.gff.gz\", \"gff-demo\"),\n",
" (\"https://s3.amazonaws.com/jbrowse.org/genomes/GRCh38/skbr3/SKBR3_Feb17_GRCh38.sorted.bam\", \"bam-demo\"),\n",
" (\"https://hgdownload.cse.ucsc.edu/goldenpath/hg38/phyloP100way/hg38.phyloP100way.bw\", \"bigwig-demo\"),\n",
" (\"https://ftp.ncbi.nlm.nih.gov/pub/clinvar/vcf_GRCh38/clinvar.vcf.gz\", \"vcf-demo\"),\n",
" (\"https://jbrowse.org/genomes/GRCh38/repeats.bb\", \"bigbed\")\n",
"]\n",
"for track in tracks:\n",
" data = track[0]\n",
" track_id = track[1]\n",
" hg38.add_track(data, track_id=track_id)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
" "
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# set theme\n",
"hg38.set_theme(\"#311b92\", \"#0097a7\", \"#f57c00\", \"#d50000\")\n",
"hg38.set_default_session(['gff-demo', 'bigbed'],False)\n",
"hg38.set_location(\"1:110654228..110936130\")\n",
"new_conf2 = hg38.get_config()\n",
"launch(new_conf2, id=\"test-2\",height=800, dash_comp=\"LGV\", port=8000)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"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": "3.8.13"
},
"vscode": {
"interpreter": {
"hash": "aaf81c8f28912d07c45359b3a81eb2244c23c90e1b370733684a5666e4e4597e"
}
}
},
"nbformat": 4,
"nbformat_minor": 4
}