{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
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      },
      "outputs": [],
      "source": [
        "%matplotlib inline"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "\n# Normalizing a cancer contact count matrix with\u00a0LOIC\n\n\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "from iced import datasets\nfrom iced import normalization\nimport matplotlib.pyplot as plt\nfrom matplotlib import colors\n\n# Loading a sample dataset\ncounts, lengths, cnv = datasets.load_sample_cancer()\n\nnormed = normalization.ICE_normalization(counts, counts_profile=cnv)\n\n# Plotting the results using matplotlib\nchromosomes = [\"I\", \"II\", \"III\", \"IV\", \"V\", \"VI\"]\n\nfig, axes = plt.subplots(ncols=2, figsize=(12, 4))\n\naxes[0].imshow(counts, cmap=\"RdBu_r\", norm=colors.SymLogNorm(1),\n               origin=\"bottom\",\n               extent=(0, len(counts), 0, len(counts)))\n\n[axes[0].axhline(i, linewidth=1, color=\"#000000\") for i in lengths.cumsum()]\n[axes[0].axvline(i, linewidth=1, color=\"#000000\") for i in lengths.cumsum()]\naxes[0].set_title(\"Raw contact counts\", fontweight=\"bold\")\n\nm = axes[1].imshow(normed, cmap=\"RdBu_r\", norm=colors.SymLogNorm(1),\n                   origin=\"bottom\",\n                   extent=(0, len(counts), 0, len(counts)))\n[axes[1].axhline(i, linewidth=1, color=\"#000000\") for i in lengths.cumsum()]\n[axes[1].axvline(i, linewidth=1, color=\"#000000\") for i in lengths.cumsum()]\ncb = fig.colorbar(m)\naxes[1].set_title(\"Normalized contact counts with LOIC\", fontweight=\"bold\")"
      ]
    }
  ],
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      "name": "python3"
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      "file_extension": ".py",
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