DiMO_PWM_Viz.ipynb

dimo_pwm_viz.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "DiMO_PWM_Viz.ipynb",
      "version": "0.3.2",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "[View in Colaboratory](https://colab.research.google.com/gist/AvantiShri/74715c97c7c6632f5c8cdbe150947862/dimo_pwm_viz.ipynb)"
      ]
    },
    {
      "metadata": {
        "id": "2IsUMZUqKKkT",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "6b349d90-162c-4f52-a0a9-e6e2005fd0f9"
      },
      "cell_type": "code",
      "source": [
        "!pip install deeplift\n",
        "!wget https://unibind.uio.no/temp/UniBind_trained_model_DiMO_ENCSR000BGQ_GM12878_SPI120181004.tar.gz -O UniBind_trained_model_DiMO_ENCSR000BGQ_GM12878_SPI120181004.tar.gz"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "--2018-10-04 17:56:46--  https://unibind.uio.no/temp/UniBind_trained_model_DiMO_ENCSR000BGQ_GM12878_SPI120181004.tar.gz\n",
            "Resolving unibind.uio.no (unibind.uio.no)... 129.240.235.122\n",
            "Connecting to unibind.uio.no (unibind.uio.no)|129.240.235.122|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 1921153 (1.8M) [application/x-tar]\n",
            "Saving to: ‘UniBind_trained_model_DiMO_ENCSR000BGQ_GM12878_SPI120181004.tar.gz’\n",
            "\n",
            "UniBind_trained_mod 100%[===================>]   1.83M  1.33MB/s    in 1.4s    \n",
            "\n",
            "2018-10-04 17:56:48 (1.33 MB/s) - ‘UniBind_trained_model_DiMO_ENCSR000BGQ_GM12878_SPI120181004.tar.gz’ saved [1921153/1921153]\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "7LDF0ltkOG_-",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        ""
      ]
    },
    {
      "metadata": {
        "id": "ZrwdRfGaKOPh",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 119
        },
        "outputId": "e90cbfdf-755a-47ab-d183-85d4a86e2d16"
      },
      "cell_type": "code",
      "source": [
        "!tar -xzvf UniBind_trained_model_DiMO_ENCSR000BGQ_GM12878_SPI120181004.tar.gz"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "./\n",
            "./MACS_SPI1_MA0080.4_dimo.tfbs.bed\n",
            "./MACS_SPI1_MA0080.4_dimo.thr\n",
            "./MACS_SPI1_MA0080.4_dimo.png\n",
            "./MACS_SPI1_MA0080.4_dimo.pfm\n",
            "./MACS_SPI1_MA0080.4_dimo.tfbs.fa\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "BMrhRyxsKQ7I",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 122
        },
        "outputId": "5eddc522-f50f-411e-dc5d-638388290614"
      },
      "cell_type": "code",
      "source": [
        "!cat MACS_SPI1_MA0080.4_dimo.pfm"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "> motif 1 \n",
            "A | 0.999915582150143 0.999999996047336 1 1 1 1.36580980642214e-33 1 3.11545923476612e-74 6.71893082915983e-157 1 1 2.0835229596603e-73 4.42783945294251e-81 1.77410701022433e-73\n",
            "C | 3.51274095294723e-06 7.83219540396717e-21 3.72038200247359e-55 7.58008087842899e-66 1.33875961872131e-66 5.1740586442117e-42 2.17262173415875e-29 1.42734260830406e-147 5.49990710083103e-166 8.35177987619389e-158 2.03076019554857e-141 1.08966768340447e-24 1.8404094491604e-55 5.48462932591285e-55\n",
            "G | 8.09050955072679e-05 3.95266398862005e-09 1.06194364133965e-32 1.23249551962165e-34 4.95310622191081e-40 1 3.27123468842742e-17 1 1 1.21491052516256e-162 1.65592574931133e-171 1 1.30546066754647e-93 1\n",
            "T | 1.33967114369032e-11 2.47816907265125e-25 5.66980356672689e-34 8.69274674057672e-39 3.47231221712671e-24 3.78981720543144e-78 3.37462388211995e-100 1.48397208078606e-160 1.14881107224093e-173 2.9954919416754e-137 1.96225065499569e-106 4.17886734518175e-126 1 1.33529711035941e-90\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "IKOAZtf_KwYb",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "\n",
        "mat = np.array([\n",
        "    [float(x) for x in \"0.999915582150143 0.999999996047336 1 1 1 1.36580980642214e-33 1 3.11545923476612e-74 6.71893082915983e-157 1 1 2.0835229596603e-73 4.42783945294251e-81 1.77410701022433e-73\".split()],\n",
        "    [float(x) for x in \"3.51274095294723e-06 7.83219540396717e-21 3.72038200247359e-55 7.58008087842899e-66 1.33875961872131e-66 5.1740586442117e-42 2.17262173415875e-29 1.42734260830406e-147 5.49990710083103e-166 8.35177987619389e-158 2.03076019554857e-141 1.08966768340447e-24 1.8404094491604e-55 5.48462932591285e-55\".split()],\n",
        "    [float(x) for x in \"8.09050955072679e-05 3.95266398862005e-09 1.06194364133965e-32 1.23249551962165e-34 4.95310622191081e-40 1 3.27123468842742e-17 1 1 1.21491052516256e-162 1.65592574931133e-171 1 1.30546066754647e-93 1\".split()],\n",
        "    [float(x) for x in \"1.33967114369032e-11 2.47816907265125e-25 5.66980356672689e-34 8.69274674057672e-39 3.47231221712671e-24 3.78981720543144e-78 3.37462388211995e-100 1.48397208078606e-160 1.14881107224093e-173 2.9954919416754e-137 1.96225065499569e-106 4.17886734518175e-126 1 1.33529711035941e-90\".split()]])"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "YKse-ULsKxJz",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 157
        },
        "outputId": "9a071c55-f1f0-4891-b86a-523a6f815490"
      },
      "cell_type": "code",
      "source": [
        "from deeplift.visualization import viz_sequence\n",
        "viz_sequence.plot_weights(mat)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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CL2HfzVCyDY8t8XIzKpoq2Jm90+KYQwWHOF503OIYb8Nb4xbhWwSSEXGL4BpE8qcbs69g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\nUqhqAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f893adffeb8>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "STsPbhxFK3lj",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}