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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# APA Analysis"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"After detecting chromatin loops using Polaris, we can use Aggregated Peak Analysis (APA) to visualize the results and assess their quality. This approach allows us to aggregate the detected loops across different genomic regions and observe their behavior in a visually intuitive way."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"You can run the following command to get a quick check of loops detected by Polaris."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"%%bash \n",
"\n",
"polaris util pileup --savefig \"./GM12878_250M_chr151617_loops.pileup.png\" --p2ll True \"../loop_annotation/GM12878_250M_chr151617_loops.bedpe\" \"../loop_annotation/GM12878_250M.bcool\""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The result will be saved at `\"./GM12878_250M_chr151617_loops.pileup.png\"`."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "polaris",
"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": "3.9.20"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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