{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "Custom interactions\n", "===================\n", "\n", "RNAvigate can create Interactions data from several common filetypes through the use of\n", "[standard data keywords](../get_started/loading_data).\n", "However, you may wish to visualize Interactions that come from other sources of data.\n", "\n", "Below, I show an example of Interactions data created from a manually created DataFrame and sequence.\n", "This also applies to data that was created in Python or that is stored in an otherwise unsupported file type.\n", "As long as it can be coerce into a DataFrame with the following structure, it can be visualized with RNAvigate.\n", "\n", "1. One row per interaction\n", "2. Two columns with the positions of the interacting nucleotides (1-indexed)\n", " - for interacting windows, the position of the 5' most nucleotide of each window\n", "3. Additional columns to hold quantitative information about each interaction\n", "\n", "If you ever have trouble getting data to work with RNAvigate,\n", "feel free to submit an [issue](https://github.com/Weeks-UNC/RNAvigate/issues/).\n", "I usually respond with a day or two.\n", "Please include example data.\n", "\n", "For common standardized file formats, I can add automatic parsing to RNAvigate.\n", "This is usually very easy and worth my time.\n", "To request this, submit a GitHub issue, included an example file, a detailed file format specification, and an example visualization (for the default color palette).\n", "\n", "Manually created Interactions data\n", "----------------------------------" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAcQAAADZCAYAAAC+YEDuAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAABWIAAAViAHE10CgAAAnJUlEQVR4nO3de1xVZb7H8c8GxXvmaFqSdtGzSUQELyGOchQF0xxvBWKKpqaWpTFOqScdjx4zLTMzw7zNeA9FzUteE0zHqaTxkqaT10LwkuYNxEBAnvOHsWO7QRgV9i6/79eLV4tnPetZv/X46Je19t5kMcYYRERE7nFuzi5ARETEFSgQRUREUCCKiIgACkQRERFAgSgiIgIoEEVERAAFooiICKBAFBERARSIIiIigAJRREQEUCCKiIgACkQRERFAgSgiIgIoEEUcjBw5Ei8vL1JTU51dioiUIAWiiIgICkQRERFAgSgiIgIoEMUFRUZG0qNHDxISEujevTu+vr4EBQUxe/ZsAJYuXUq7du3w8/PjmWeeYdeuXXbHX7x4kUmTJtGuXTsaNGiAn58f3bp1Y82aNQ7n2rZtG+Hh4fj5+dG6dWv+9re/5VtTWloab7/9NsHBwfj4+NCqVSsmTpxIWlpaka+pSZMmDu0TJkzAy8uLkydPApCQkICXlxebNm3i//7v/3jyySdp0qQJgwYN4siRI4WeJzU1ldGjR9vqDAoKYtSoUZw9e9auX0ZGBlOnTiUkJARfX1/atm3L1KlTSU9Pt+u3bt06wsLC8PX1pXHjxvTr189hvkeOHElQUBCrV6+mefPm+Pv7s2DBgrsybyIlqZSzCxDJz4kTJxg8eDDdu3enc+fOxMbGMmXKFHbt2sWRI0fo1asXANHR0bzyyits2bKFSpUqkZmZSWRkJD/++CM9e/akVq1anDt3jqVLlzJ8+HA8PT1twbRx40b+/Oc/U7duXaKiokhNTWXmzJlkZ2fb1ZKenk7Pnj1JTEwkPDycOnXqcPjwYRYvXkxCQgIxMTGUK1furl7/O++8A8CAAQNIT09n/vz5PPfcc6xcuZJHHnmkwOOioqLYs2cPkZGR1K5dm8TERBYuXMj+/ftZs2YNbm5uZGdn06dPH/bt20enTp3w9/fn8OHDzJ49m8OHDzNz5kwApk2bxowZM2jQoAHDhg0jPT2d5cuX07t3b6ZOnUq7du1s57106RITJkxg4MCBZGZmEhAQ4JR5E7kjRsTF9OrVy1itVvPJJ5/Y2g4dOmSsVqupX7++SUpKsrXPmjXLWK1W88UXXxhjjNmwYYOxWq1m7dq1dmPu3bvXWK1WM378eGOMMTk5OSYoKMiEhoaatLQ0W78jR44YHx8fY7VaTUpKijHGmOnTpxsvLy/z9ddf240ZHx9vrFarmTFjRpGuqXHjxg7tb775prFarSY5OdkYY8zOnTuN1Wo1Tz75pDl//ryt3549e4zVajXDhg0r8BwXLlwwVqvVjBs3zq599uzZpnPnzrZzLFu2zFitVjN79my7fu+8846xWq3m4MGD5vvvvzdPPPGE6dmzp8nMzLT1uXz5smnRooUJCAgwP//8szHGmBEjRhir1Wr+/ve/2413N+ZNpCTpkam4rNDQUNt2nTp1APD29qZWrVq29ty7pXPnzgHQvn17vvrqK9q3b2/rk5OTw/Xr1wG4evUqAAcPHuTHH3+kS5cuVKhQwdb3v/7rvwgKCrKrY/PmzdSqVYs6depw8eJF25efnx/VqlUjPj7+bl42ABEREVStWtX2vb+/P40aNWLbtm3k5OTke0zFihWpWLEiGzZsYMWKFVy8eBG4cZe5evVqHn74YQC2bt1K6dKl6d27t93xAwcOZM2aNdStW5f4+HhycnIYMGAApUuXtvWpXLkykZGRXLp0yeHRqSvMm8id0CNTcUnly5e3C6pSpW4s1bwhAeDu7g5gFxKlSpVi4cKF7N69m6SkJJKTk22vjRljAEhOTgbI9/Fj3bp1iYuLs32flJRERkYGgYGB+daaO+aVK1fIyMiw21epUiXKli1bhCt2rOFmjz76KHv27OHy5cv84Q9/cNjv4eHB+PHjGTVqFKNGjcLNzQ1vb2+Cg4MJDw/ngQceAODkyZPUqFGDMmXK2B1fuXJlKleubOsDv/4gktfjjz9u1yfXzTUVdd5EXIUCUVxSbtDdzGKx3PK406dPExERQUpKCoGBgQQHB/PEE09gtVrp0KGDwzjXrl1zGCP3bjJXTk4O9erVY/jw4fmeMzesJ0yYwKpVq+z2TZw4kW7duhVY783nypX3rixvHVDw3AB06NCBli1bsnXrVnbs2MFXX33FBx98wPz581m6dCl16tQhOzvbIQwLOld+8527z8PDw6795rqKOm8irkIrUn5Xpk+fztmzZ1m5ciU+Pj629mPHjtn1q127NgA//PCDwxhJSUl233t6epKSkkLz5s0d+m7cuBFPT08AXnjhBTp16mS3P/dOz83NjczMTIfjz58/n+913FwDQGJiIlWqVLHdxd0sPT2dQ4cOUbNmTTp37kznzp0xxhAbG8uYMWNYvnw5I0eOxNPTk927d5OVlWUXvKdOnWLy5Ml0797d9lj62LFjtuvLdfz4cQAeeuihfOvIVdR5E3EVeg1RflcuX76Mu7s7jz76qK3NGMP8+fMBbO8g9fb2pnbt2sTGxnLp0iVb3+TkZLZu3Wo3ZkhICKdPn2blypV27Zs3byYqKooVK1YAN8KvefPmdl/Vq1cHoFq1aly7ds0WJgAXLlxg586d+V5HbGys3ePXXbt28c0339i9s/Nmp06dIiIigrlz59raLBYLvr6+wK93cMHBwaSnpztcz4oVK9i4cSPly5cnODgYi8XCnDlzyMrKsvVJSUlhyZIlVK5cOd+PkeRV1HkTcRW6Q5TflVatWrF161bb3VpWVhabN2/mm2++oXTp0naffxs7diyDBg3i2WefpUePHmRlZbF48WIqVapke0MK3HizSVxcHKNHj2b37t34+vqSmJjIxx9/zIMPPsjLL79caF1dunRh3bp1DB48mF69epGRkUFMTAxVq1YlJSXFof+5c+cIDw+nW7duXLp0iYULF1KjRg2GDh1a4Dnq1q1LcHAwixcvJi0tDX9/f1JSUoiJiaF8+fKEhYUBEBYWxqpVqxg3bhwHDhzAx8eHgwcPsnLlSrp06ULDhg1t1z1r1ix69OhBx44dycjIIDY2losXLzJlyhSHR6Y3uxvzJlKSFIjyuxIeHk5aWhqxsbFMmjSJ+++/Hy8vLxYvXkx0dDS7du0iMzMTDw8P/vjHPzJ//nymTZtGdHQ0FSpUoHv37mRnZzNr1izbmJUqVWLp0qVER0cTFxfH2rVrqVatGk8//TRDhgyhRo0ahdbVsmVL3nzzTebNm8fbb7/NQw89RO/evalUqRJvvPGGQ/9XXnmFkydPMn36dEqVKkVISAh/+ctfHN5UdLN3332XOXPmsHHjRtavX0/ZsmVp0qQJQ4cOtd01e3h4MH/+fKKjo9m0aRNr1qzB09OTqKgonn/+edtYw4YN47HHHmPRokW89957lC1bFj8/P959910aNWpU6DXfjXkTKUkWo7d6ibiMhIQEevfuzf/8z//YhZOIFD+9higiIoICUUREBFAgioiIAHoNUUREBNAdooiICKBAFBERARSIIiIigAJRREQEUCCKiIgACkQRERHABX6XaYhbmH2Dxe2X/1jy3cbNAr/8P9osbm62bey2LVjy6Y/FcqNf7rZde57tgo7NM37utrFYfv2x4qYxja0/hbYbiwUsv45j7PblPR67441de57jbdvYru3GODiMWaR2t6IeW9i2Jd92+/oL3s53TIo2TpHGukVNuYpaNxZT+Ji2bfNre57zmTzjcNM4edtNnnFy+1gKOpa8fQra/vVYi8XkWb72/X9dcsaun9sv3998fN52Nwpov2nbjV/Hccvbnk8fh/Y85/q1PafAdne79hzbOO44HutuMbiRt0+e7dxjybNtybEbx37bcRx3S47tum5s/1qfOzm2+tzJW3eO7Xzu2B9vO59dn1+v3528Nf16zTf68Os2v2xbwP2XFeAGuFtyty152i152t1w+6Xd3XLju/y4PXgk3/aS4JRAdAhBERERIOdHq227pMOxxAJRISgiIv+J3HAsqWAs9kBUEIqIyJ0oqbvGYglEhaCIiBSH4gzHuxaICkERESlJd/uR6h0HooJQRESc6W4Foz6HKCIiwl24Q9ySs9y2rbtFEREpaS7zyDQvhaOIiJSE4ni3abF97CI3HBWMIiJyNxT35xGL/XOIumsUEZHbVZK/raZEf3WbwlFERIrCGb/T1Gm/3FvhKCIieTnzF3sDWIwxxqkV/MLHxweAAwcOOLmS26P6neu3XP9vuXZQ/c70W64dXK9+fQ5RREQEBaKIiAigQBQREQEUiCIiIoACUUREBFAgioiIAApEERERQIEoIiICuNAH80VERJxJd4giIiIoEEVERAAFooiICKBAFBERARSIIiIigAJRREQEUCCKiIgAdykQd+7cSUREBH5+fjRv3pzx48dz9erVIh8/dOhQhg4dmu++jz/+mKeeeooGDRoQGhrKggULHPokJyczZMgQAgICaNSoES+99BJJSUlOrT0tLY3JkycTGhpKw4YNad++PR9++CGZmZl2/aKiovDy8nL4mjFjhlPrP378eL51eXt72/W7k7kvrvqnT5+eb+25X6tWrbL1dcb8JyQkEBkZSUBAAM2aNaN///75/g9SXXHtF6V2V177Ranfldd+YfW7+trfvXs3kZGRNG7cmICAAEaMGMHZs2cd+hX32i+QuUP79u0zPj4+ZvDgwWbbtm1m/vz5pmHDhmbQoEGFHpuVlWX+93//11itVjNkyBCH/fPnzzdeXl5m8uTJ5h//+Id58803jdVqNX//+99tfVJTU03r1q1Nhw4dzKZNm8y6detMSEiICQoKMqmpqU6p/fr166Zv377mySefNIsWLTJffvmlmTFjhmnQoIEZPHiwXd/Q0FATFRVl9u7da/f1448/FlpDcc792rVrjdVqNf/85z/t6vrmm29sfe5k7ouz/jNnzjjM5+7du03btm1Nq1atzIULF2x9S3r+ExISTL169czLL79sPv/8c7NlyxYTERFh6tevb/bt22fr54prvyi1u/LaL+rcu+raL0r9rrz2Dxw4YBo0aGD69etntm/fbtatW2fatm1rQkNDzbVr12z9invt38odB2K/fv1M+/btzfXr121t69atM1ar1ezdu7fA4/bv32/Cw8ONr6+v8fX1dfhHLT093TRt2tT89a9/tWv/61//aho3bmybwFmzZhlvb29z6tQpW59Tp06Z+vXrm1mzZjml9n/961/GarWaDRs22LXPmjXLWK1Wc+zYMWOMMVeuXDFeXl4mNjb2lnWWdP3GGDNp0iTTsmXLW57/Tua+uOu/2fTp0423t7f59ttvbW3OmP/evXubjh072h2TlpZmnnzySfPqq68aY1x37Reldlde+0Wp3xjXXftFrf9mrrL2hw0bZv74xz+ajIwMW9uXX35prFar2bx5szGmZNb+rdzRI9PMzEwSEhJo27Ytbm6/DtW2bVtKly7Ntm3bCjz21VdfpVSpUixfvpyqVas67N+3bx8pKSmEhobatbdv354rV66we/duAHbs2EGDBg2oWbOmrU/NmjVp2LDhLc9fnLW7u7sTHh5Os2bN7Noff/xxANsjgkOHDmGMcXgUUxTFWT/Av//970Lrut25L4n680pKSmLmzJn07t0bHx8fW7sz5t/f35/evXvbHVOhQgUeeugh27pw1bVflNpdee0XpX5w3bVf1PrzcqW1//rrrzN37lzKlClja8vdvnbtGlD8a78wdxSIycnJZGVl8dhjj9m1lylThho1avD9998XeGx0dDRLlizBarXmu//48eMADmM/8sgjALaxjx8/7tAHoHbt2rc8f3HW7u/vz/jx46lSpYpd+6ZNm3Bzc6NOnTrAjb94AMuXL6dly5bUr1+fbt26sX379gLPXRL1w42/MD///DM9evTA19eXgIAAxowZQ1pamq3P7c59SdSf17vvvkvlypUZMmSIXbsz5j8qKoqwsDC7tuPHj3P06FHb9bjq2i9K7a689otSP7ju2i9q/Xm50tp/8MEHeeKJJwBIT09n9+7djBs3jocffpjg4GDb9UDxrf3C3FEgpqamAlCpUiWHfRUqVLBbQDerV6/eLce+cuVKvmNXqFDBbn9qaioVK1b8j89fnLXnZ926daxbt46wsDBq1KgBwHfffQfAzz//zOTJk/nggw+oVKkSgwYNYuvWrbccrzjrP3XqFJcvX+b7778nPDycv/3tb/Tv359PP/2Ufv36cf36dVsNtzP3xV1/XomJiWzZsoW+fftSvnx5u33Omv+8rl69yvDhw/Hw8KB///6Aa6/9wmrPjyut/cLqd/W1X1j9ebny2m/VqhXPPfccP/zwA6NHj3ZY28W19gtT6raPBEwh/6OMvLfTtzu2xWIpdOyi9Clo/ILcSe03W7VqFaNHj6Zp06aMGjXK1v7CCy/wpz/9iebNm9vagoKC6NSpE1OnTrX91JSf4qy/SpUqzJs3j0cffdT2SKJp06ZUr16dESNGEB8fb3ukcTtzDyU3/4sXL6ZcuXL06NHDYZ+z5//SpUu8+OKLHD58mPfff5/atWvbje3Ka7+g2m/mqmu/oPp/K2u/KPPvymt/8uTJWCwWYmNjGTx4MJMmTaJz587FvvYLc0f/6tx3330A+Sby1atX8/0Joqhyj7157Ny39ebur1Sp0m2dvzhrz2WMYerUqYwcOZLmzZsza9Ysu+fnderUsVuQAKVLl6ZFixYcOXKE7Oxsp9Rfvnx5mjdvbvd8HrD9Jcl93HK7cw8lN/+bNm2ibdu2tp8w83Lm/B87dozw8HAOHz7M9OnTadu2rW2fq6/9W9Wey5XX/q3q/y2s/aLOv6uufbgRvi1btmTatGl4e3sTHR0NFP/aL8wdBWLt2rUpVaoUJ06csGu/du0aZ8+etb1ecDtyX4RPTEy0a889V926dW39bj5/br9bnb84a4cbLzwPHTqUmTNn8uyzz/LRRx85PLZYu3YtX3zxhcOx165do3LlypQqVfANfHHWf+zYMWJiYhwWXEZGBoDt9aHbnfvirj/Xt99+y08//USHDh3y3e+s+f/qq6+IiIjg6tWrLFiwgNatW9vtd+W1X1jt4Nprv7D6XX3tF2X+wTXXflxcHAkJCXZtbm5u1K9fnzNnzgDFv/YLc0eB6OHhQbNmzdiyZYvdTxRbtmwhKyuLoKCg2x67UaNGVKxYkY0bN9q1b9y4kfvvvx9fX1/gxk8a+/bt4/Tp07Y+p0+fZv/+/bc8f3HWDvDaa6/x2WefERUVxYQJE/JdYAsWLGDMmDF2H1hOS0vj888/d3iXXknWf/LkScaOHcuGDRvs2tevX4/FYiEgIAC4/bkv7vpz7d27F4vFQqNGjfLd74z5379/Py+++CJVq1YlNjaWhg0bOvRx1bVflNrBddd+Uep35bVf1PkH11z7c+bMYcyYMWRlZdnaMjMz+frrr23vCyjutV+o2/7Axi/27Nlj6tWrZ/r3728+//xzs2DBAuPn52f32bC9e/eao0ePFjhG69at8/0s2Zw5c4zVajUTJkww//jHP8yECROM1Wo1ixYtsvVJSUkxLVq0MCEhIWb9+vVm/fr1JiQkxLRu3dpcuXLFKbV/+umnxmq1mhdeeMHhQ6979+41KSkpxhhjPv/8c+Pl5WX69u1rtm3bZjZs2GC6du1qGjdubBITE29Ze3HWn5mZabp37278/PzMvHnzzBdffGHee+89U79+fTN27FhbvzuZ++KsP9fIkSNNixYtCjy2pOf/+vXrpn379sbb29usX7/eYV0cPnzYdpyrrf2i1u6qa7+o9bvq2v9P1o4xrrf2jTHmn//8p6lXr54ZMGCA2bZtm/nss89Mz549jY+Pj9m1a5etX3Gv/Vu540A0xpgdO3aYbt26GR8fH9OiRQvz1ltvmfT0dNt+q9VqevXqVeDxt/pHbd68eaZNmzamfv36pl27diYmJsahT2Jiohk0aJDx8/MzTZs2Na+88opJTk52Wu0vv/yysVqtBX5t3brV7vzPPfecady4sWnUqJEZNGiQOXLkSJFqL676jbmx4N566y0THBxs6tevb0JDQ83s2bPtPohrzJ3NfXHWb4wxAwYMME8//XSh5y+p+f/uu+9uuS66du1qN7Yrrf2i1u6qa/8/mXtXXPv/6dpxtbWfa+fOnaZXr16mcePGxt/f37zwwgt2vzAgV3Gv/YJYjCnkLUMiIiL3AP3fLkRERFAgioiIAApEERERQIEoIiICKBBFREQABaKIiAigQBQREQEUiCIiIoACUUREBFAgioiIAApEERERQIEoIiICKBBFREQABaKIiAigQBQREQEUiCIiIoACUUREBFAgioiIAApEERERQIEoIiICKBBFREQABaKIiAigQBQREQEUiCIiIoACUUREBFAgioiIAApEERERQIEoIiICKBBFREQABaKIiAigQBQREQEUiCIiIoACUUREBFAgioiIAApEERERQIEoIiICKBBFREQABaKIiAigQBQREQEUiCIiIoACUUREBFAgioiIAApEERERQIEoIiICKBBFREQABaKIiAigQBQREQEUiCIiIoACUUREBFAgioiIAApEERERQIEoIiICKBBFREQABaKIiAigQJR7SGpqKqNHjyY4OBgfHx+CgoIYNWoUZ8+etfVJS0vj7bfftvVp1aoVEydOJC0tzW6snJwc5s6dS2hoKL6+vnTr1o2EhAR69OhBZGSkrd/IkSPx8vIiNTXV7vj58+fj5eVFQkKCrc0Yw5IlS+jUqRMNGjQgICCAqKgoEhMT7Y6NjIykR48e7Nq1ix49etCwYUOaNWvGqFGjuHz5sl3fjIwMpk6dSkhICL6+vrRt25apU6eSnp5u12/Dhg2EhYXRsGFDGjduzIABA/j2229vZ5pFfrNKObsAkZISFRXFnj17iIyMpHbt2iQmJrJw4UL279/PmjVruHbtGj179iQxMZHw8HDq1KnD4cOHWbx4MQkJCcTExFCuXDkAxo4dy7JlywgKCqJPnz58++23DBw4kPvuu49HH330tuobM2YMsbGxPPXUU0RERHD+/HliYmJ49tlnWbp0KXXr1rX1TU5OZsCAAXTq1ImuXbvy5ZdfsmLFCtLS0pg2bRoA2dnZ9OnTh3379tGpUyf8/f05fPgws2fP5vDhw8ycOROAjz76iPfff58WLVrw+uuvc+XKFVasWMFzzz3HnDlzaNas2Z1NvMhvhRG5B1y4cMFYrVYzbtw4u/bZs2ebzp07m+TkZDN9+nTj5eVlvv76a7s+8fHxxmq1mhkzZhhjjDl69Kjx8vIyL774osnJybH1++CDD4zVajW9evWytY0YMcJYrVaTkpJiN+a8efOM1Wo1O3fuNMYY8/XXXxur1Wqio6Pt+p05c8Y0btzYPP/887a2Xr16GavVapYvX27XNywszHh7e5uff/7ZGGPMsmXLjNVqNbNnz7br98477xir1WoOHjxokpKSTL169cwbb7xh1+fKlSumdevWJjQ01O4aRX7P9MhU7gkVK1akYsWKbNiwgRUrVnDx4kUABgwYwOrVq3n44YfZvHkztWrVok6dOly8eNH25efnR7Vq1YiPjwdg69atGGPo06cPFovFdo5+/fpRpkyZ26pv8+bNAISEhNid28PDg8DAQHbu3Gn32NZisdChQwe7Mby9vcnOzrY9Nt26dSulS5emd+/edv0GDhzImjVrqFu3LnFxcVy/fp3Q0FC782ZmZtKmTRsSExM5fvz4bV2TyG+NHpnKPcHDw4Px48czatQoRo0ahZubG97e3gQHBxMeHs4DDzxAUlISGRkZBAYG5juGMQaA06dPA1C7dm27/RUqVKBmzZq3Vd+JEycA6NixY4F9zp49S8WKFQEoX7485cuXt9tfunRpAK5fvw7AyZMnqVGjhkNIV65cmcqVK9udd+DAgQWe99SpU3aPa0V+rxSIcs/o0KEDLVu2ZOvWrezYsYOvvvqKDz74gPnz57N06VJycnKoV68ew4cPz/f4UqUK/+tStmzZItWSG1q5cnJycHd3Z86cOXZ3nXk9+OCDtm03t8If7mRnZxd6x5qTkwPAlClT+MMf/pBvnyeeeKLQc4n8HigQ5Z6Qnp7OoUOHqFmzJp07d6Zz584YY4iNjWXMmDEsX74cT09PUlJSaN68ucPxGzduxNPTE8D2ppnvv//e7o7w+vXrnDx5knr16tnacoMrMzPTbrzz58/bfe/p6cn169epXbs2tWrVstu3c+dOcnJy8PDw+I+u2dPTk927d5OVlWW7e4Qbd3yTJ0+me/fuPPzwwwBUrVrV4c54//79XL58ucghL/Jbp9cQ5Z5w6tQpIiIimDt3rq3NYrHg6+sLgLu7OyEhIZw+fZqVK1faHbt582aioqJYsWIFcON1Pnd3d+bNm2e7wwL45JNPuHLlit2xDzzwAAD//ve/bW0ZGRm21yNzhYSEAPDhhx861P3SSy8xfvz4It2h5hUcHEx6errD9axYsYKNGzdSvnx52rRpg8ViYebMmWRnZ9v6pKSk8Oqrr/Laa68VeMcq8nujO0S5J9StW5fg4GAWL15MWloa/v7+pKSkEBMTQ/ny5QkLC6Nq1arExcUxevRodu/eja+vL4mJiXz88cc8+OCDvPzyy8CNO6+oqCimTJlCnz59aNeuHYmJicTGxuLu7m533k6dOjF79mzeeOMN+vbtS+nSpVm+fLlDv5YtW9KxY0dWr17NuXPnaNOmDVevXmXJkiVkZWUxevTo/ziYwsLCWLVqFePGjePAgQP4+Phw8OBBVq5cSZcuXWjYsCFw4/XDWbNmERERQceOHTHGsGzZMk6fPs3EiRNtHzUR+b2zmNx3Coj8zl29epU5c+awceNGzpw5Q9myZWnSpAlDhw61vU6WkpJCdHQ0cXFxnDt3jmrVqhEYGMiQIUMc3jCzatUq5s6dy4kTJ3jsscd47bXX+Mtf/kK9evVYtGiRrV98fDzR0dEcPXqUKlWq0K1bN5o0aUL//v1ZuHAhAQEBwI3X8xYuXMjKlStJTEykQoUK+Pj4MHjwYBo1amQbLzIyku+++45du3bZ1TNhwgQWLlxIfHy87VFoWloa0dHRbNq0ifPnz+Pp6Um3bt14/vnn7R7Brl69miVLlnDkyBE8PDywWq0MGDCAVq1a3dU/AxFXpkAUuYuaNGniEIgi8tug1xBFRERQIIqIiAAKRBEREUCvIYqIiAC6QxQREQEUiCIiIoACUUREBFAgioiIAApEERERQIEoIiIC3IVf7h3wasrdqEOK0YCnKzu7BClE2PQ/ObsEKUTlnn7OLkEKEzH+jg7XHaKIiAgKRBEREUCBKCIiAigQRUREAAWiiIgIoEAUEREBFIgiIiKAAlFERARQIIqIiAAKRBEREUCBKCIiAigQRUREAAWiiIgIABZjjHF2Ea7Ex8cHgAMHDji5EimI/oxcn/6MXJ/+jBzpDlFERAQFooiICKBAFBERARSIIiIigAJRREQEUCCKiIgACkQRERFAgSgiIgLog/kiIiKA7hBFREQABaKIiAigQBQREQEUiCIiIoACUUREBFAgioiIAApEERERQIHoYMqUKXh5eTFy5EhnlyK/GDlyJAEBAQXuf/vtt/Hy8irBiqQgycnJvPPOOzz99NM0atQIPz8//vSnP/H++++TkpLi7PIEOHz4MKNHj6ZNmzb4+vrSqlUrhgwZwv79+51dmtMpEPPIzs5m1apVeHl5sWHDBi5duuTskkR+M+Li4ujcuTPbt28nIiKC6OhoPvroIzp06MCyZct45pln+Omnn5xd5j1t+fLlPPPMM5w4cYIhQ4YwZ84chg0bxrlz54iIiGDdunXOLtGpFIh5bNu2jZ9++olx48aRk5PDihUrnF2SyG/CiRMneP3112nUqBGrVq0iMjKSwMBAAgMDeemll4iNjeXSpUu89957zi71nrV3717Gjh1LWFgYixYtokuXLgQEBNCpUycWLVqEv78/o0eP5sKFC84u1WkUiHksX76cxx9/HH9/f4KCgoiJiSEnJ8fZZYm4vLlz55KTk8Nbb72Fh4eHw/5atWrx4osvUq1aNSdUJ3Djz6hSpUoMHz7cYZ+HhwcjRoygR48eXLlyxQnVuYZSzi7AVZw9e5YdO3bw5z//GYBnn32Wl156ie3bt9O6dWsnVyfi2j777DMCAwOpXr16gX0GDBhQghVJXsYYduzYQZs2bShXrly+fXx9ffH19S3hylyL7hB/sXLlSiwWC127dgXgv//7v6levTpLlixxcmUiri01NZXLly/z2GOPOezLzs52+JKSd+nSJa5du4anp6ezS3FpukPkxk9PK1euJDAwEA8PD1JTUwFo3749Cxcu5MSJEzzyyCNOrvLeZbFYnF2C3ML169cL3Fe/fn2Htk8//RSr1VqcJclN3Nxu3Pvc6s9KFIgAfPnll5w8eZKTJ0/StGlTh/0xMTH6GIYTlStXjszMzAL3Z2ZmUr58+RKsSPKqUqUKFStW5OTJkw778r4xbdu2bXz44YclWZr84v7776dixYqcOnWqwD7GGH788UceeuihEqzMtSgQufFmmsqVKzN9+nSHfVOnTuWTTz7h1VdfLfDZuxSvBx54gPT0dNLS0qhYsaLD/jNnztzytSspfm3btuWzzz4jNTWV++67z9beoEED2/bRo0edUZr8IigoiC+++IL09PR8/y3btWsXvXr1YuTIkfTt29cJFTrfPf8a4sWLF4mLi+Opp54iICDA4SsiIoKUlJR7/vM5ztSsWTOMMWzcuNFh36VLl9i5cyfNmjVzQmWSa9CgQQAMHz6cjIyMfPsoEJ2rf//+pKWl8e677zrsy8zMZMqUKXh4eNChQwcnVOcaLMYY4+winGnevHlMmjSJJUuW0KRJE4f96enptGjRgtq1a7Nq1SonVCgAUVFRxMXF0adPHwIDAylTpgw//PAD8+fP58qVK6xYsYIaNWo4u8x72vbt2xk+fDj33XcfYWFheHt74+7uzqFDh1i9ejWHDh2iefPmTJs2ze4uUkrOggULmDhxIoGBgXTt2pUaNWqQlJTEwoULOX78OO+//z6hoaHOLtNp7vlAfPrpp0lPTyc+Pr7AN2+MGTOGZcuWERMTQ6NGjUq4QoEbbwZYvHgxa9euJSkpiWvXrlG9enVatWrFwIED9cjURfz0008sXbqU+Ph4Tp48SWZmJtWrV6dJkyZ07dr1lr+CT0rGv/71LxYtWsT+/fu5cOEC1apVo2HDhgwaNIh69eo5uzynuucDUUREBPQaooiICKBAFBERARSIIiIigAJRREQEUCCKiIgACkQRERFAgSgiIgIoEEVERAAFooiICKBAFBERARSIIiIigAJRREQEUCCKiIgACkQRERFAgSgiIgLA/wPmg5/9kpOSPgAAAABJRU5ErkJggg==", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import rnavigate as rnav\n", "import pandas as pd\n", "\n", "sample = rnav.Sample(\n", " sample=\"test custom interactions\",\n", " interactions=rnav.data.Interactions(\n", " input_data=pd.DataFrame(\n", " {\n", " \"i\": [1, 10, 20],\n", " \"j\": [30, 40, 50],\n", " \"score\": [0.1, 0.2, 0.3],\n", " }\n", " ),\n", " sequence=\"AUCGCAUCGCAUCGCAUCGCAUCGCAUCGCAUCGCAUCGCAUCGCAUCGC\",\n", " metric=\"score\",\n", " metric_defaults={\n", " \"score\": {\n", " \"metric_column\": \"score\",\n", " \"cmap\": \"viridis\",\n", " \"normalization\": \"min_max\",\n", " \"values\": [0.1, 0.3],\n", " \"extend\": \"both\",\n", " \"title\": \"made-up score\",\n", " \"alpha\": 0.7,\n", " }\n", " },\n", " ),\n", ")\n", "\n", "rnav.plot_arcs(\n", " samples=[sample],\n", " sequence=\"interactions\",\n", " interactions=\"interactions\",\n", ")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "RNAvigate", "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": "3.9.2" } }, "nbformat": 4, "nbformat_minor": 2 }