Yeast_TF_Network.ipynb

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  "metadata": {
    "colab": {
      "name": "Yeast_TF_Network.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyM3aoMG/C3btbWxGLw4Vqof",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/moqri/gene-regulatory-network/blob/master/Yeast_TF_Network.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "e17IOTQ03eGS",
        "colab_type": "code",
        "outputId": "5f1a738a-35c0-4b96-fa3a-3305065687bd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 289
        }
      },
      "source": [
        "!wget -O expression.zip -nc https://storage.googleapis.com/calico-website-pin-public-bucket/datasets/idea_tall_expression_data.zip\n",
        "!unzip -n expression.zip"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "--2020-06-04 14:26:11--  https://storage.googleapis.com/calico-website-pin-public-bucket/datasets/idea_tall_expression_data.zip\n",
            "Resolving storage.googleapis.com (storage.googleapis.com)... 108.177.111.128, 2607:f8b0:4001:c07::80\n",
            "Connecting to storage.googleapis.com (storage.googleapis.com)|108.177.111.128|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 368238973 (351M) [application/zip]\n",
            "Saving to: ‘expression.zip’\n",
            "\n",
            "expression.zip      100%[===================>] 351.18M  46.4MB/s    in 9.7s    \n",
            "\n",
            "2020-06-04 14:26:21 (36.2 MB/s) - ‘expression.zip’ saved [368238973/368238973]\n",
            "\n",
            "Archive:  expression.zip\n",
            "  inflating: idea_tall_expression_data.tsv  \n",
            "   creating: __MACOSX/\n",
            "  inflating: __MACOSX/._idea_tall_expression_data.tsv  \n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZdpfW05g3obG",
        "colab_type": "code",
        "outputId": "706a27fa-81c3-4517-8bab-fa669680d7a3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "import pandas as pd\n",
        "expression_df=pd.read_table('idea_tall_expression_data.tsv')\n",
        "expression_df.shape"
      ],
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(10454275, 15)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Y8by0Bgi4DcP",
        "colab_type": "code",
        "outputId": "f399fd58-6d70-41c1-f818-0d98faa354ec",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "df=expression_df#[expression_df.GeneName.isin(set(expression_df.TF))]\n",
        "df.shape"
      ],
      "execution_count": 119,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(10454275, 15)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 119
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jfwoLcyF3yzN",
        "colab_type": "code",
        "outputId": "fb9c0cae-c04b-4439-8e22-75082b9ba301",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "df=df[df.time==45]\n",
        "df.shape"
      ],
      "execution_count": 120,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1315275, 15)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 120
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "a5m4jNT05CJh",
        "colab_type": "code",
        "outputId": "c795beef-0df5-470c-859c-5dec523afea2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 402
        }
      },
      "source": [
        "cols=['TF','GeneName','log2_shrunken_timecourses']\n",
        "df=df[cols]\n",
        "df[df.log2_shrunken_timecourses>0]"
      ],
      "execution_count": 121,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>TF</th>\n",
              "      <th>GeneName</th>\n",
              "      <th>log2_shrunken_timecourses</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>ACA1</td>\n",
              "      <td>AAD10</td>\n",
              "      <td>0.332777</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>182</th>\n",
              "      <td>ACA1</td>\n",
              "      <td>ACA1</td>\n",
              "      <td>5.188579</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>198</th>\n",
              "      <td>ACA1</td>\n",
              "      <td>ACC1</td>\n",
              "      <td>0.410071</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>614</th>\n",
              "      <td>ACA1</td>\n",
              "      <td>AFR1</td>\n",
              "      <td>0.640908</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>702</th>\n",
              "      <td>ACA1</td>\n",
              "      <td>AGX1</td>\n",
              "      <td>0.488140</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10415049</th>\n",
              "      <td>ZNF1</td>\n",
              "      <td>FAT3</td>\n",
              "      <td>0.672468</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10441657</th>\n",
              "      <td>ZNF1</td>\n",
              "      <td>TPP1</td>\n",
              "      <td>0.060767</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10447113</th>\n",
              "      <td>ZNF1</td>\n",
              "      <td>YFL051C</td>\n",
              "      <td>3.015795</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10448905</th>\n",
              "      <td>ZNF1</td>\n",
              "      <td>YJL086C</td>\n",
              "      <td>0.160719</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10454185</th>\n",
              "      <td>ZNF1</td>\n",
              "      <td>ZNF1</td>\n",
              "      <td>3.275457</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>46986 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            TF GeneName  log2_shrunken_timecourses\n",
              "22        ACA1    AAD10                   0.332777\n",
              "182       ACA1     ACA1                   5.188579\n",
              "198       ACA1     ACC1                   0.410071\n",
              "614       ACA1     AFR1                   0.640908\n",
              "702       ACA1     AGX1                   0.488140\n",
              "...        ...      ...                        ...\n",
              "10415049  ZNF1     FAT3                   0.672468\n",
              "10441657  ZNF1     TPP1                   0.060767\n",
              "10447113  ZNF1  YFL051C                   3.015795\n",
              "10448905  ZNF1  YJL086C                   0.160719\n",
              "10454185  ZNF1     ZNF1                   3.275457\n",
              "\n",
              "[46986 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 121
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "B00gPbLi5j7E",
        "colab_type": "code",
        "outputId": "a0c52e89-8726-4c3f-e2f2-b652b6d870a8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 252
        }
      },
      "source": [
        "df=df[df.log2_shrunken_timecourses>0]\n",
        "df = df[df.TF != df.GeneName]\n",
        "df=df.groupby(['TF','GeneName']).mean().reset_index()\n",
        "df.sort_values"
      ],
      "execution_count": 122,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<bound method DataFrame.sort_values of          TF GeneName  log2_shrunken_timecourses\n",
              "0      ACA1    AAD10                   0.332777\n",
              "1      ACA1     ACC1                   0.410071\n",
              "2      ACA1     AFR1                   0.640908\n",
              "3      ACA1     AGX1                   0.488140\n",
              "4      ACA1      AI1                   0.611329\n",
              "...     ...      ...                        ...\n",
              "44096  ZAP1     ZRT3                   0.581537\n",
              "44097  ZNF1     FAT3                   0.672468\n",
              "44098  ZNF1     TPP1                   0.060767\n",
              "44099  ZNF1  YFL051C                   3.015795\n",
              "44100  ZNF1  YJL086C                   0.160719\n",
              "\n",
              "[44101 rows x 3 columns]>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 122
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GaQGxT8773qU",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "purturb_dic={}\n",
        "for TF in set(df.TF):\n",
        "  purturb_dic[TF]=set(df[df.TF==TF].GeneName)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "alrnFf3j5Ag_",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 222
        },
        "outputId": "2d403af1-489d-4665-c882-91dbecb4c460"
      },
      "source": [
        "!wget -O TF_binding.tsv -nc https://raw.githubusercontent.com/moqri/gene-regulatory-network/master/yeast_TF_binding.tsv"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "--2020-06-04 14:27:39--  https://raw.githubusercontent.com/moqri/gene-regulatory-network/master/yeast_TF_binding.tsv\n",
            "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 151.101.0.133, 151.101.64.133, 151.101.128.133, ...\n",
            "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|151.101.0.133|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 353637 (345K) [text/plain]\n",
            "Saving to: ‘TF_binding.tsv’\n",
            "\n",
            "\rTF_binding.tsv        0%[                    ]       0  --.-KB/s               \rTF_binding.tsv      100%[===================>] 345.35K  --.-KB/s    in 0.05s   \n",
            "\n",
            "2020-06-04 14:27:39 (6.19 MB/s) - ‘TF_binding.tsv’ saved [353637/353637]\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xOJZoklz48uN",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "4b5c60e7-548a-43e0-bae6-663c5825d674"
      },
      "source": [
        "TF_df=pd.read_table('TF_binding.tsv',sep=';',header=None)\n",
        "TF_df.shape"
      ],
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(32088, 2)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZwDXPAvW5Lj0",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 402
        },
        "outputId": "750517c8-f549-40e2-8e5d-9289da047ef7"
      },
      "source": [
        "TF_df.columns=['TF','Gene']\n",
        "TF_df=TF_df[TF_df.TF!=TF_df.Gene]\n",
        "TF_df"
      ],
      "execution_count": 87,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>TF</th>\n",
              "      <th>Gene</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>RLM1</td>\n",
              "      <td>PST1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>RLM1</td>\n",
              "      <td>CWP1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>RLM1</td>\n",
              "      <td>NCW2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>RLM1</td>\n",
              "      <td>SLT2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>RLM1</td>\n",
              "      <td>KDX1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32083</th>\n",
              "      <td>YAP3</td>\n",
              "      <td>ASR1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32084</th>\n",
              "      <td>YAP3</td>\n",
              "      <td>RDS3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32085</th>\n",
              "      <td>YAP3</td>\n",
              "      <td>VPS4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32086</th>\n",
              "      <td>RTG2</td>\n",
              "      <td>CIT1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32087</th>\n",
              "      <td>DIG1</td>\n",
              "      <td>FLO11</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>32055 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "         TF   Gene\n",
              "0      RLM1   PST1\n",
              "1      RLM1   CWP1\n",
              "2      RLM1   NCW2\n",
              "3      RLM1   SLT2\n",
              "4      RLM1   KDX1\n",
              "...     ...    ...\n",
              "32083  YAP3   ASR1\n",
              "32084  YAP3   RDS3\n",
              "32085  YAP3   VPS4\n",
              "32086  RTG2   CIT1\n",
              "32087  DIG1  FLO11\n",
              "\n",
              "[32055 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 87
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JYbRmO-f59rW",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "d1eebe18-fc7f-4bfd-ebbb-2b5ca338cd68"
      },
      "source": [
        "TF_dic={}\n",
        "for TF in set(TF_df.TF):\n",
        "  TF_dic[TF]=set(TF_df[TF_df.TF==TF].Gene)\n",
        "len(TF_dic)  "
      ],
      "execution_count": 88,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "104"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 88
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9dBLfK5C6ZA4",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "edges=[]\n",
        "pk=sorted(purturb_dic.keys())\n",
        "for key in sorted(TF_dic.keys()):\n",
        "  if key in pk:\n",
        "    genes=purturb_dic[key]\n",
        "    for gene in TF_dic[key]:\n",
        "      if gene in genes:\n",
        "        edges.append([key,gene])"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mgaz0wjFNgsu",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "62c899c3-68af-4f9b-8f80-0e3cee51358b"
      },
      "source": [
        "len(edges)"
      ],
      "execution_count": 91,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "177"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 91
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2cXA3qR41Yyu",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "edges_df=pd.DataFrame(edges)\n",
        "edges_df.to_csv('edges.csv',index=None,header=['source','target'])"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KEe0rax481da",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import networkx as nx\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "G = nx.DiGraph()\n",
        "G.add_edges_from(edges)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qI1bqF4mYxF6",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "outputId": "ff0ed3f0-5a94-4a0b-ccef-c030f35586c0"
      },
      "source": [
        "pos = nx.spring_layout(G)\n",
        "nx.draw_networkx_labels(G, pos)\n",
        "nx.draw_networkx_nodes(G, pos, cmap=plt.get_cmap('jet'), \n",
        "                       node_size = 500)\n",
        "nx.draw_networkx_edges(G, pos, G.edges, arrows=False)\n",
        "plt.figure(figsize=(20,10))\n",
        "plt.show()"
      ],
      "execution_count": 118,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x720 with 0 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8xQ4iXcjY1YO",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}