{ "cells": [ { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import matplotlib as mpl\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "?np.loadtxt\n", "# check the arguments: delimiter, dtype, comments, skiprows" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": [ "# please, paste your own data path\n", "mtx_filename = '/home/agalicina/SINGLE_CELL/HIC/WD/pairsamtools_ag/examples_single_cell/DATA/TXT/mtx.A6.100.chr2L.txt'\n", "mtx = np.loadtxt(mtx_filename)" ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [], "source": [ "tads_filename = '' # ... \n", "tads = np.loadtxt(tads_filename, delimiter='\\t') # or delimiter='\\s'" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": [ "# I do not have TADs called, so I create some dumb values\n", "tads = np.array([[1,10],\n", " [11,30],\n", " [30,50],\n", " [50,100]\n", " ])" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": [ "?sns.heatmap\n", "# check the arguments: cmap, vmax, vmin, center, cbar" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#basic usage\n", "bgn = 0\n", "end = 100\n", "sns.heatmap(mtx[bgn:end, bgn:end])" ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# let's make it nice!\n", "\n", "# global settings of the plot\n", "bgn = 10\n", "end = 100\n", "tads_color = 'blue'\n", "\n", "# plot tuning\n", "plt.figure(figsize=(24,20))\n", "sns.heatmap(mtx[bgn:end, bgn:end], cmap='Reds')\n", "plt.xticks([])\n", "plt.yticks([])\n", "\n", "# tads drawing, please, check +-1 errors on real data!\n", "for i in tads:\n", " tad_bgn = i[0] - bgn # guess why we need this? \n", " tad_end = i[1] - bgn\n", " plt.plot([tad_bgn, tad_end], [tad_bgn, tad_bgn], color=tads_color)\n", " plt.plot([tad_end, tad_end], [tad_bgn, tad_end], color=tads_color)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "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": "3.6.3" } }, "nbformat": 4, "nbformat_minor": 2 }