MIS11602_analysis.ipynb

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      "metadata": {
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      "source": [
        "<a href=\"https://colab.research.google.com/github/yyw-informatics/RNA-seq-InfluenzaNP-CD8-T-cells/blob/main/MIS11602_analysis.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Kj3fWXKkyp5R"
      },
      "source": [
        "# Preprocessing"
      ]
    },
    {
      "cell_type": "code",
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        "outputId": "9287a6c6-5bda-4bbd-c078-3c1bd7d9d741"
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      "source": [
        "## Install packages\n",
        "system('apt-get -q install libgsl-dev', intern = TRUE)\n",
        "system('apt-get install libcairo2-dev', intern = TRUE) # for Cairo package that is required by ComplexHeatmap package\n",
        "install.packages('BiocManager')"
      ],
      "execution_count": null,
      "outputs": [
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              "<ol class=list-inline><li>'Reading package lists...'</li><li>'Building dependency tree...'</li><li>'Reading state information...'</li><li>'The following package was automatically installed and is no longer required:'</li><li><span style=white-space:pre-wrap>'  libnvidia-common-460'</span></li><li>'Use \\'apt autoremove\\' to remove it.'</li><li>'The following additional packages will be installed:'</li><li><span style=white-space:pre-wrap>'  libgsl23 libgslcblas0'</span></li><li>'Suggested packages:'</li><li><span style=white-space:pre-wrap>'  gsl-ref-psdoc | gsl-doc-pdf | gsl-doc-info | gsl-ref-html'</span></li><li>'The following NEW packages will be installed:'</li><li><span style=white-space:pre-wrap>'  libgsl-dev libgsl23 libgslcblas0'</span></li><li>'0 upgraded, 3 newly installed, 0 to remove and 4 not upgraded.'</li><li>'Need to get 1,926 kB of archives.'</li><li>'After this operation, 9,474 kB of additional disk space will be used.'</li><li>'Get:1 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libgslcblas0 amd64 2.4+dfsg-6 [79.7 kB]'</li><li>'Get:2 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libgsl23 amd64 2.4+dfsg-6 [823 kB]'</li><li>'Get:3 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libgsl-dev amd64 2.4+dfsg-6 [1,023 kB]'</li><li>'Fetched 1,926 kB in 1s (1,302 kB/s)'</li><li>'Selecting previously unselected package libgslcblas0:amd64.\\r'</li><li>'(Reading database ... \\r(Reading database ... 5%\\r(Reading database ... 10%\\r(Reading database ... 15%\\r(Reading database ... 20%\\r(Reading database ... 25%\\r(Reading database ... 30%\\r(Reading database ... 35%\\r(Reading database ... 40%\\r(Reading database ... 45%\\r(Reading database ... 50%\\r(Reading database ... 55%\\r(Reading database ... 60%\\r(Reading database ... 65%\\r(Reading database ... 70%\\r(Reading database ... 75%\\r(Reading database ... 80%\\r(Reading database ... 85%\\r(Reading database ... 90%\\r(Reading database ... 95%\\r(Reading database ... 100%\\r(Reading database ... 123942 files and directories currently installed.)\\r'</li><li>'Preparing to unpack .../libgslcblas0_2.4+dfsg-6_amd64.deb ...\\r'</li><li>'Unpacking libgslcblas0:amd64 (2.4+dfsg-6) ...\\r'</li><li>'Selecting previously unselected package libgsl23:amd64.\\r'</li><li>'Preparing to unpack .../libgsl23_2.4+dfsg-6_amd64.deb ...\\r'</li><li>'Unpacking libgsl23:amd64 (2.4+dfsg-6) ...\\r'</li><li>'Selecting previously unselected package libgsl-dev.\\r'</li><li>'Preparing to unpack .../libgsl-dev_2.4+dfsg-6_amd64.deb ...\\r'</li><li>'Unpacking libgsl-dev (2.4+dfsg-6) ...\\r'</li><li>'Setting up libgslcblas0:amd64 (2.4+dfsg-6) ...\\r'</li><li>'Setting up libgsl23:amd64 (2.4+dfsg-6) ...\\r'</li><li>'Setting up libgsl-dev (2.4+dfsg-6) ...\\r'</li><li>'Processing triggers for man-db (2.8.3-2ubuntu0.1) ...\\r'</li><li>'Processing triggers for libc-bin (2.27-3ubuntu1.6) ...\\r'</li></ol>\n"
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            "text/markdown": "1. 'Reading package lists...'\n2. 'Building dependency tree...'\n3. 'Reading state information...'\n4. 'The following package was automatically installed and is no longer required:'\n5. <span style=white-space:pre-wrap>'  libnvidia-common-460'</span>\n6. 'Use \\'apt autoremove\\' to remove it.'\n7. 'The following additional packages will be installed:'\n8. <span style=white-space:pre-wrap>'  libgsl23 libgslcblas0'</span>\n9. 'Suggested packages:'\n10. <span style=white-space:pre-wrap>'  gsl-ref-psdoc | gsl-doc-pdf | gsl-doc-info | gsl-ref-html'</span>\n11. 'The following NEW packages will be installed:'\n12. <span style=white-space:pre-wrap>'  libgsl-dev libgsl23 libgslcblas0'</span>\n13. '0 upgraded, 3 newly installed, 0 to remove and 4 not upgraded.'\n14. 'Need to get 1,926 kB of archives.'\n15. 'After this operation, 9,474 kB of additional disk space will be used.'\n16. 'Get:1 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libgslcblas0 amd64 2.4+dfsg-6 [79.7 kB]'\n17. 'Get:2 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libgsl23 amd64 2.4+dfsg-6 [823 kB]'\n18. 'Get:3 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libgsl-dev amd64 2.4+dfsg-6 [1,023 kB]'\n19. 'Fetched 1,926 kB in 1s (1,302 kB/s)'\n20. 'Selecting previously unselected package libgslcblas0:amd64.\\r'\n21. '(Reading database ... \\r(Reading database ... 5%\\r(Reading database ... 10%\\r(Reading database ... 15%\\r(Reading database ... 20%\\r(Reading database ... 25%\\r(Reading database ... 30%\\r(Reading database ... 35%\\r(Reading database ... 40%\\r(Reading database ... 45%\\r(Reading database ... 50%\\r(Reading database ... 55%\\r(Reading database ... 60%\\r(Reading database ... 65%\\r(Reading database ... 70%\\r(Reading database ... 75%\\r(Reading database ... 80%\\r(Reading database ... 85%\\r(Reading database ... 90%\\r(Reading database ... 95%\\r(Reading database ... 100%\\r(Reading database ... 123942 files and directories currently installed.)\\r'\n22. 'Preparing to unpack .../libgslcblas0_2.4+dfsg-6_amd64.deb ...\\r'\n23. 'Unpacking libgslcblas0:amd64 (2.4+dfsg-6) ...\\r'\n24. 'Selecting previously unselected package libgsl23:amd64.\\r'\n25. 'Preparing to unpack .../libgsl23_2.4+dfsg-6_amd64.deb ...\\r'\n26. 'Unpacking libgsl23:amd64 (2.4+dfsg-6) ...\\r'\n27. 'Selecting previously unselected package libgsl-dev.\\r'\n28. 'Preparing to unpack .../libgsl-dev_2.4+dfsg-6_amd64.deb ...\\r'\n29. 'Unpacking libgsl-dev (2.4+dfsg-6) ...\\r'\n30. 'Setting up libgslcblas0:amd64 (2.4+dfsg-6) ...\\r'\n31. 'Setting up libgsl23:amd64 (2.4+dfsg-6) ...\\r'\n32. 'Setting up libgsl-dev (2.4+dfsg-6) ...\\r'\n33. 'Processing triggers for man-db (2.8.3-2ubuntu0.1) ...\\r'\n34. 'Processing triggers for libc-bin (2.27-3ubuntu1.6) ...\\r'\n\n\n",
            "text/latex": "\\begin{enumerate*}\n\\item 'Reading package lists...'\n\\item 'Building dependency tree...'\n\\item 'Reading state information...'\n\\item 'The following package was automatically installed and is no longer required:'\n\\item '  libnvidia-common-460'\n\\item 'Use \\textbackslash{}'apt autoremove\\textbackslash{}' to remove it.'\n\\item 'The following additional packages will be installed:'\n\\item '  libgsl23 libgslcblas0'\n\\item 'Suggested packages:'\n\\item '  gsl-ref-psdoc \\textbar{} gsl-doc-pdf \\textbar{} gsl-doc-info \\textbar{} gsl-ref-html'\n\\item 'The following NEW packages will be installed:'\n\\item '  libgsl-dev libgsl23 libgslcblas0'\n\\item '0 upgraded, 3 newly installed, 0 to remove and 4 not upgraded.'\n\\item 'Need to get 1,926 kB of archives.'\n\\item 'After this operation, 9,474 kB of additional disk space will be used.'\n\\item 'Get:1 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libgslcblas0 amd64 2.4+dfsg-6 {[}79.7 kB{]}'\n\\item 'Get:2 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libgsl23 amd64 2.4+dfsg-6 {[}823 kB{]}'\n\\item 'Get:3 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libgsl-dev amd64 2.4+dfsg-6 {[}1,023 kB{]}'\n\\item 'Fetched 1,926 kB in 1s (1,302 kB/s)'\n\\item 'Selecting previously unselected package libgslcblas0:amd64.\\textbackslash{}r'\n\\item '(Reading database ... \\textbackslash{}r(Reading database ... 5\\%\\textbackslash{}r(Reading database ... 10\\%\\textbackslash{}r(Reading database ... 15\\%\\textbackslash{}r(Reading database ... 20\\%\\textbackslash{}r(Reading database ... 25\\%\\textbackslash{}r(Reading database ... 30\\%\\textbackslash{}r(Reading database ... 35\\%\\textbackslash{}r(Reading database ... 40\\%\\textbackslash{}r(Reading database ... 45\\%\\textbackslash{}r(Reading database ... 50\\%\\textbackslash{}r(Reading database ... 55\\%\\textbackslash{}r(Reading database ... 60\\%\\textbackslash{}r(Reading database ... 65\\%\\textbackslash{}r(Reading database ... 70\\%\\textbackslash{}r(Reading database ... 75\\%\\textbackslash{}r(Reading database ... 80\\%\\textbackslash{}r(Reading database ... 85\\%\\textbackslash{}r(Reading database ... 90\\%\\textbackslash{}r(Reading database ... 95\\%\\textbackslash{}r(Reading database ... 100\\%\\textbackslash{}r(Reading database ... 123942 files and directories currently installed.)\\textbackslash{}r'\n\\item 'Preparing to unpack .../libgslcblas0\\_2.4+dfsg-6\\_amd64.deb ...\\textbackslash{}r'\n\\item 'Unpacking libgslcblas0:amd64 (2.4+dfsg-6) ...\\textbackslash{}r'\n\\item 'Selecting previously unselected package libgsl23:amd64.\\textbackslash{}r'\n\\item 'Preparing to unpack .../libgsl23\\_2.4+dfsg-6\\_amd64.deb ...\\textbackslash{}r'\n\\item 'Unpacking libgsl23:amd64 (2.4+dfsg-6) ...\\textbackslash{}r'\n\\item 'Selecting previously unselected package libgsl-dev.\\textbackslash{}r'\n\\item 'Preparing to unpack .../libgsl-dev\\_2.4+dfsg-6\\_amd64.deb ...\\textbackslash{}r'\n\\item 'Unpacking libgsl-dev (2.4+dfsg-6) ...\\textbackslash{}r'\n\\item 'Setting up libgslcblas0:amd64 (2.4+dfsg-6) ...\\textbackslash{}r'\n\\item 'Setting up libgsl23:amd64 (2.4+dfsg-6) ...\\textbackslash{}r'\n\\item 'Setting up libgsl-dev (2.4+dfsg-6) ...\\textbackslash{}r'\n\\item 'Processing triggers for man-db (2.8.3-2ubuntu0.1) ...\\textbackslash{}r'\n\\item 'Processing triggers for libc-bin (2.27-3ubuntu1.6) ...\\textbackslash{}r'\n\\end{enumerate*}\n",
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              " [1] \"Reading package lists...\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      \n",
              " [2] \"Building dependency tree...\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   \n",
              " [3] \"Reading state information...\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  \n",
              " [4] \"The following package was automatically installed and is no longer required:\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  \n",
              " [5] \"  libnvidia-common-460\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        \n",
              " [6] \"Use 'apt autoremove' to remove it.\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            \n",
              " [7] \"The following additional packages will be installed:\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          \n",
              " [8] \"  libgsl23 libgslcblas0\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       \n",
              " [9] \"Suggested packages:\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           \n",
              "[10] \"  gsl-ref-psdoc | gsl-doc-pdf | gsl-doc-info | gsl-ref-html\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   \n",
              "[11] \"The following NEW packages will be installed:\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 \n",
              "[12] \"  libgsl-dev libgsl23 libgslcblas0\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            \n",
              "[13] \"0 upgraded, 3 newly installed, 0 to remove and 4 not upgraded.\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                \n",
              "[14] \"Need to get 1,926 kB of archives.\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             \n",
              "[15] \"After this operation, 9,474 kB of additional disk space will be used.\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                         \n",
              "[16] \"Get:1 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libgslcblas0 amd64 2.4+dfsg-6 [79.7 kB]\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          \n",
              "[17] \"Get:2 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libgsl23 amd64 2.4+dfsg-6 [823 kB]\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               \n",
              "[18] \"Get:3 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libgsl-dev amd64 2.4+dfsg-6 [1,023 kB]\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           \n",
              "[19] \"Fetched 1,926 kB in 1s (1,302 kB/s)\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           \n",
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              "[21] \"(Reading database ... \\r(Reading database ... 5%\\r(Reading database ... 10%\\r(Reading database ... 15%\\r(Reading database ... 20%\\r(Reading database ... 25%\\r(Reading database ... 30%\\r(Reading database ... 35%\\r(Reading database ... 40%\\r(Reading database ... 45%\\r(Reading database ... 50%\\r(Reading database ... 55%\\r(Reading database ... 60%\\r(Reading database ... 65%\\r(Reading database ... 70%\\r(Reading database ... 75%\\r(Reading database ... 80%\\r(Reading database ... 85%\\r(Reading database ... 90%\\r(Reading database ... 95%\\r(Reading database ... 100%\\r(Reading database ... 123942 files and directories currently installed.)\\r\"\n",
              "[22] \"Preparing to unpack .../libgslcblas0_2.4+dfsg-6_amd64.deb ...\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               \n",
              "[23] \"Unpacking libgslcblas0:amd64 (2.4+dfsg-6) ...\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               \n",
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              "[25] \"Preparing to unpack .../libgsl23_2.4+dfsg-6_amd64.deb ...\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   \n",
              "[26] \"Unpacking libgsl23:amd64 (2.4+dfsg-6) ...\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   \n",
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              "[28] \"Preparing to unpack .../libgsl-dev_2.4+dfsg-6_amd64.deb ...\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 \n",
              "[29] \"Unpacking libgsl-dev (2.4+dfsg-6) ...\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       \n",
              "[30] \"Setting up libgslcblas0:amd64 (2.4+dfsg-6) ...\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              \n",
              "[31] \"Setting up libgsl23:amd64 (2.4+dfsg-6) ...\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  \n",
              "[32] \"Setting up libgsl-dev (2.4+dfsg-6) ...\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      \n",
              "[33] \"Processing triggers for man-db (2.8.3-2ubuntu0.1) ...\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       \n",
              "[34] \"Processing triggers for libc-bin (2.27-3ubuntu1.6) ...\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      "
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              "<ol class=list-inline><li>'Reading package lists...'</li><li>'Building dependency tree...'</li><li>'Reading state information...'</li><li>'The following package was automatically installed and is no longer required:'</li><li><span style=white-space:pre-wrap>'  libnvidia-common-460'</span></li><li>'Use \\'apt autoremove\\' to remove it.'</li><li>'The following additional packages will be installed:'</li><li><span style=white-space:pre-wrap>'  libcairo-script-interpreter2 libpixman-1-dev libxcb-shm0-dev'</span></li><li>'Suggested packages:'</li><li><span style=white-space:pre-wrap>'  libcairo2-doc'</span></li><li>'The following NEW packages will be installed:'</li><li><span style=white-space:pre-wrap>'  libcairo-script-interpreter2 libcairo2-dev libpixman-1-dev libxcb-shm0-dev'</span></li><li>'0 upgraded, 4 newly installed, 0 to remove and 4 not upgraded.'</li><li>'Need to get 930 kB of archives.'</li><li>'After this operation, 3,986 kB of additional disk space will be used.'</li><li>'Get:1 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libcairo-script-interpreter2 amd64 1.15.10-2ubuntu0.1 [53.5 kB]'</li><li>'Get:2 http://archive.ubuntu.com/ubuntu bionic/main amd64 libpixman-1-dev amd64 0.34.0-2 [244 kB]'</li><li>'Get:3 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libxcb-shm0-dev amd64 1.13-2~ubuntu18.04 [6,684 B]'</li><li>'Get:4 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libcairo2-dev amd64 1.15.10-2ubuntu0.1 [626 kB]'</li><li>'Fetched 930 kB in 1s (721 kB/s)'</li><li>'Selecting previously unselected package libcairo-script-interpreter2:amd64.\\r'</li><li>'(Reading database ... \\r(Reading database ... 5%\\r(Reading database ... 10%\\r(Reading database ... 15%\\r(Reading database ... 20%\\r(Reading database ... 25%\\r(Reading database ... 30%\\r(Reading database ... 35%\\r(Reading database ... 40%\\r(Reading database ... 45%\\r(Reading database ... 50%\\r(Reading database ... 55%\\r(Reading database ... 60%\\r(Reading database ... 65%\\r(Reading database ... 70%\\r(Reading database ... 75%\\r(Reading database ... 80%\\r(Reading database ... 85%\\r(Reading database ... 90%\\r(Reading database ... 95%\\r(Reading database ... 100%\\r(Reading database ... 124214 files and directories currently installed.)\\r'</li><li>'Preparing to unpack .../libcairo-script-interpreter2_1.15.10-2ubuntu0.1_amd64.deb ...\\r'</li><li>'Unpacking libcairo-script-interpreter2:amd64 (1.15.10-2ubuntu0.1) ...\\r'</li><li>'Selecting previously unselected package libpixman-1-dev:amd64.\\r'</li><li>'Preparing to unpack .../libpixman-1-dev_0.34.0-2_amd64.deb ...\\r'</li><li>'Unpacking libpixman-1-dev:amd64 (0.34.0-2) ...\\r'</li><li>'Selecting previously unselected package libxcb-shm0-dev:amd64.\\r'</li><li>'Preparing to unpack .../libxcb-shm0-dev_1.13-2~ubuntu18.04_amd64.deb ...\\r'</li><li>'Unpacking libxcb-shm0-dev:amd64 (1.13-2~ubuntu18.04) ...\\r'</li><li>'Selecting previously unselected package libcairo2-dev:amd64.\\r'</li><li>'Preparing to unpack .../libcairo2-dev_1.15.10-2ubuntu0.1_amd64.deb ...\\r'</li><li>'Unpacking libcairo2-dev:amd64 (1.15.10-2ubuntu0.1) ...\\r'</li><li>'Setting up libcairo-script-interpreter2:amd64 (1.15.10-2ubuntu0.1) ...\\r'</li><li>'Setting up libxcb-shm0-dev:amd64 (1.13-2~ubuntu18.04) ...\\r'</li><li>'Setting up libpixman-1-dev:amd64 (0.34.0-2) ...\\r'</li><li>'Setting up libcairo2-dev:amd64 (1.15.10-2ubuntu0.1) ...\\r'</li><li>'Processing triggers for libc-bin (2.27-3ubuntu1.6) ...\\r'</li></ol>\n"
            ],
            "text/markdown": "1. 'Reading package lists...'\n2. 'Building dependency tree...'\n3. 'Reading state information...'\n4. 'The following package was automatically installed and is no longer required:'\n5. <span style=white-space:pre-wrap>'  libnvidia-common-460'</span>\n6. 'Use \\'apt autoremove\\' to remove it.'\n7. 'The following additional packages will be installed:'\n8. <span style=white-space:pre-wrap>'  libcairo-script-interpreter2 libpixman-1-dev libxcb-shm0-dev'</span>\n9. 'Suggested packages:'\n10. <span style=white-space:pre-wrap>'  libcairo2-doc'</span>\n11. 'The following NEW packages will be installed:'\n12. <span style=white-space:pre-wrap>'  libcairo-script-interpreter2 libcairo2-dev libpixman-1-dev libxcb-shm0-dev'</span>\n13. '0 upgraded, 4 newly installed, 0 to remove and 4 not upgraded.'\n14. 'Need to get 930 kB of archives.'\n15. 'After this operation, 3,986 kB of additional disk space will be used.'\n16. 'Get:1 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libcairo-script-interpreter2 amd64 1.15.10-2ubuntu0.1 [53.5 kB]'\n17. 'Get:2 http://archive.ubuntu.com/ubuntu bionic/main amd64 libpixman-1-dev amd64 0.34.0-2 [244 kB]'\n18. 'Get:3 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libxcb-shm0-dev amd64 1.13-2~ubuntu18.04 [6,684 B]'\n19. 'Get:4 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libcairo2-dev amd64 1.15.10-2ubuntu0.1 [626 kB]'\n20. 'Fetched 930 kB in 1s (721 kB/s)'\n21. 'Selecting previously unselected package libcairo-script-interpreter2:amd64.\\r'\n22. '(Reading database ... \\r(Reading database ... 5%\\r(Reading database ... 10%\\r(Reading database ... 15%\\r(Reading database ... 20%\\r(Reading database ... 25%\\r(Reading database ... 30%\\r(Reading database ... 35%\\r(Reading database ... 40%\\r(Reading database ... 45%\\r(Reading database ... 50%\\r(Reading database ... 55%\\r(Reading database ... 60%\\r(Reading database ... 65%\\r(Reading database ... 70%\\r(Reading database ... 75%\\r(Reading database ... 80%\\r(Reading database ... 85%\\r(Reading database ... 90%\\r(Reading database ... 95%\\r(Reading database ... 100%\\r(Reading database ... 124214 files and directories currently installed.)\\r'\n23. 'Preparing to unpack .../libcairo-script-interpreter2_1.15.10-2ubuntu0.1_amd64.deb ...\\r'\n24. 'Unpacking libcairo-script-interpreter2:amd64 (1.15.10-2ubuntu0.1) ...\\r'\n25. 'Selecting previously unselected package libpixman-1-dev:amd64.\\r'\n26. 'Preparing to unpack .../libpixman-1-dev_0.34.0-2_amd64.deb ...\\r'\n27. 'Unpacking libpixman-1-dev:amd64 (0.34.0-2) ...\\r'\n28. 'Selecting previously unselected package libxcb-shm0-dev:amd64.\\r'\n29. 'Preparing to unpack .../libxcb-shm0-dev_1.13-2~ubuntu18.04_amd64.deb ...\\r'\n30. 'Unpacking libxcb-shm0-dev:amd64 (1.13-2~ubuntu18.04) ...\\r'\n31. 'Selecting previously unselected package libcairo2-dev:amd64.\\r'\n32. 'Preparing to unpack .../libcairo2-dev_1.15.10-2ubuntu0.1_amd64.deb ...\\r'\n33. 'Unpacking libcairo2-dev:amd64 (1.15.10-2ubuntu0.1) ...\\r'\n34. 'Setting up libcairo-script-interpreter2:amd64 (1.15.10-2ubuntu0.1) ...\\r'\n35. 'Setting up libxcb-shm0-dev:amd64 (1.13-2~ubuntu18.04) ...\\r'\n36. 'Setting up libpixman-1-dev:amd64 (0.34.0-2) ...\\r'\n37. 'Setting up libcairo2-dev:amd64 (1.15.10-2ubuntu0.1) ...\\r'\n38. 'Processing triggers for libc-bin (2.27-3ubuntu1.6) ...\\r'\n\n\n",
            "text/latex": "\\begin{enumerate*}\n\\item 'Reading package lists...'\n\\item 'Building dependency tree...'\n\\item 'Reading state information...'\n\\item 'The following package was automatically installed and is no longer required:'\n\\item '  libnvidia-common-460'\n\\item 'Use \\textbackslash{}'apt autoremove\\textbackslash{}' to remove it.'\n\\item 'The following additional packages will be installed:'\n\\item '  libcairo-script-interpreter2 libpixman-1-dev libxcb-shm0-dev'\n\\item 'Suggested packages:'\n\\item '  libcairo2-doc'\n\\item 'The following NEW packages will be installed:'\n\\item '  libcairo-script-interpreter2 libcairo2-dev libpixman-1-dev libxcb-shm0-dev'\n\\item '0 upgraded, 4 newly installed, 0 to remove and 4 not upgraded.'\n\\item 'Need to get 930 kB of archives.'\n\\item 'After this operation, 3,986 kB of additional disk space will be used.'\n\\item 'Get:1 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libcairo-script-interpreter2 amd64 1.15.10-2ubuntu0.1 {[}53.5 kB{]}'\n\\item 'Get:2 http://archive.ubuntu.com/ubuntu bionic/main amd64 libpixman-1-dev amd64 0.34.0-2 {[}244 kB{]}'\n\\item 'Get:3 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libxcb-shm0-dev amd64 1.13-2\\textasciitilde{}ubuntu18.04 {[}6,684 B{]}'\n\\item 'Get:4 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libcairo2-dev amd64 1.15.10-2ubuntu0.1 {[}626 kB{]}'\n\\item 'Fetched 930 kB in 1s (721 kB/s)'\n\\item 'Selecting previously unselected package libcairo-script-interpreter2:amd64.\\textbackslash{}r'\n\\item '(Reading database ... \\textbackslash{}r(Reading database ... 5\\%\\textbackslash{}r(Reading database ... 10\\%\\textbackslash{}r(Reading database ... 15\\%\\textbackslash{}r(Reading database ... 20\\%\\textbackslash{}r(Reading database ... 25\\%\\textbackslash{}r(Reading database ... 30\\%\\textbackslash{}r(Reading database ... 35\\%\\textbackslash{}r(Reading database ... 40\\%\\textbackslash{}r(Reading database ... 45\\%\\textbackslash{}r(Reading database ... 50\\%\\textbackslash{}r(Reading database ... 55\\%\\textbackslash{}r(Reading database ... 60\\%\\textbackslash{}r(Reading database ... 65\\%\\textbackslash{}r(Reading database ... 70\\%\\textbackslash{}r(Reading database ... 75\\%\\textbackslash{}r(Reading database ... 80\\%\\textbackslash{}r(Reading database ... 85\\%\\textbackslash{}r(Reading database ... 90\\%\\textbackslash{}r(Reading database ... 95\\%\\textbackslash{}r(Reading database ... 100\\%\\textbackslash{}r(Reading database ... 124214 files and directories currently installed.)\\textbackslash{}r'\n\\item 'Preparing to unpack .../libcairo-script-interpreter2\\_1.15.10-2ubuntu0.1\\_amd64.deb ...\\textbackslash{}r'\n\\item 'Unpacking libcairo-script-interpreter2:amd64 (1.15.10-2ubuntu0.1) ...\\textbackslash{}r'\n\\item 'Selecting previously unselected package libpixman-1-dev:amd64.\\textbackslash{}r'\n\\item 'Preparing to unpack .../libpixman-1-dev\\_0.34.0-2\\_amd64.deb ...\\textbackslash{}r'\n\\item 'Unpacking libpixman-1-dev:amd64 (0.34.0-2) ...\\textbackslash{}r'\n\\item 'Selecting previously unselected package libxcb-shm0-dev:amd64.\\textbackslash{}r'\n\\item 'Preparing to unpack .../libxcb-shm0-dev\\_1.13-2\\textasciitilde{}ubuntu18.04\\_amd64.deb ...\\textbackslash{}r'\n\\item 'Unpacking libxcb-shm0-dev:amd64 (1.13-2\\textasciitilde{}ubuntu18.04) ...\\textbackslash{}r'\n\\item 'Selecting previously unselected package libcairo2-dev:amd64.\\textbackslash{}r'\n\\item 'Preparing to unpack .../libcairo2-dev\\_1.15.10-2ubuntu0.1\\_amd64.deb ...\\textbackslash{}r'\n\\item 'Unpacking libcairo2-dev:amd64 (1.15.10-2ubuntu0.1) ...\\textbackslash{}r'\n\\item 'Setting up libcairo-script-interpreter2:amd64 (1.15.10-2ubuntu0.1) ...\\textbackslash{}r'\n\\item 'Setting up libxcb-shm0-dev:amd64 (1.13-2\\textasciitilde{}ubuntu18.04) ...\\textbackslash{}r'\n\\item 'Setting up libpixman-1-dev:amd64 (0.34.0-2) ...\\textbackslash{}r'\n\\item 'Setting up libcairo2-dev:amd64 (1.15.10-2ubuntu0.1) ...\\textbackslash{}r'\n\\item 'Processing triggers for libc-bin (2.27-3ubuntu1.6) ...\\textbackslash{}r'\n\\end{enumerate*}\n",
            "text/plain": [
              " [1] \"Reading package lists...\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      \n",
              " [2] \"Building dependency tree...\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   \n",
              " [3] \"Reading state information...\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  \n",
              " [4] \"The following package was automatically installed and is no longer required:\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  \n",
              " [5] \"  libnvidia-common-460\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        \n",
              " [6] \"Use 'apt autoremove' to remove it.\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            \n",
              " [7] \"The following additional packages will be installed:\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          \n",
              " [8] \"  libcairo-script-interpreter2 libpixman-1-dev libxcb-shm0-dev\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                \n",
              " [9] \"Suggested packages:\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           \n",
              "[10] \"  libcairo2-doc\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               \n",
              "[11] \"The following NEW packages will be installed:\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 \n",
              "[12] \"  libcairo-script-interpreter2 libcairo2-dev libpixman-1-dev libxcb-shm0-dev\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  \n",
              "[13] \"0 upgraded, 4 newly installed, 0 to remove and 4 not upgraded.\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                \n",
              "[14] \"Need to get 930 kB of archives.\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               \n",
              "[15] \"After this operation, 3,986 kB of additional disk space will be used.\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                         \n",
              "[16] \"Get:1 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libcairo-script-interpreter2 amd64 1.15.10-2ubuntu0.1 [53.5 kB]\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              \n",
              "[17] \"Get:2 http://archive.ubuntu.com/ubuntu bionic/main amd64 libpixman-1-dev amd64 0.34.0-2 [244 kB]\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              \n",
              "[18] \"Get:3 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libxcb-shm0-dev amd64 1.13-2~ubuntu18.04 [6,684 B]\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           \n",
              "[19] \"Get:4 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libcairo2-dev amd64 1.15.10-2ubuntu0.1 [626 kB]\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              \n",
              "[20] \"Fetched 930 kB in 1s (721 kB/s)\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               \n",
              "[21] \"Selecting previously unselected package libcairo-script-interpreter2:amd64.\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 \n",
              "[22] \"(Reading database ... \\r(Reading database ... 5%\\r(Reading database ... 10%\\r(Reading database ... 15%\\r(Reading database ... 20%\\r(Reading database ... 25%\\r(Reading database ... 30%\\r(Reading database ... 35%\\r(Reading database ... 40%\\r(Reading database ... 45%\\r(Reading database ... 50%\\r(Reading database ... 55%\\r(Reading database ... 60%\\r(Reading database ... 65%\\r(Reading database ... 70%\\r(Reading database ... 75%\\r(Reading database ... 80%\\r(Reading database ... 85%\\r(Reading database ... 90%\\r(Reading database ... 95%\\r(Reading database ... 100%\\r(Reading database ... 124214 files and directories currently installed.)\\r\"\n",
              "[23] \"Preparing to unpack .../libcairo-script-interpreter2_1.15.10-2ubuntu0.1_amd64.deb ...\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       \n",
              "[24] \"Unpacking libcairo-script-interpreter2:amd64 (1.15.10-2ubuntu0.1) ...\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       \n",
              "[25] \"Selecting previously unselected package libpixman-1-dev:amd64.\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              \n",
              "[26] \"Preparing to unpack .../libpixman-1-dev_0.34.0-2_amd64.deb ...\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              \n",
              "[27] \"Unpacking libpixman-1-dev:amd64 (0.34.0-2) ...\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              \n",
              "[28] \"Selecting previously unselected package libxcb-shm0-dev:amd64.\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              \n",
              "[29] \"Preparing to unpack .../libxcb-shm0-dev_1.13-2~ubuntu18.04_amd64.deb ...\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    \n",
              "[30] \"Unpacking libxcb-shm0-dev:amd64 (1.13-2~ubuntu18.04) ...\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    \n",
              "[31] \"Selecting previously unselected package libcairo2-dev:amd64.\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                \n",
              "[32] \"Preparing to unpack .../libcairo2-dev_1.15.10-2ubuntu0.1_amd64.deb ...\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      \n",
              "[33] \"Unpacking libcairo2-dev:amd64 (1.15.10-2ubuntu0.1) ...\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      \n",
              "[34] \"Setting up libcairo-script-interpreter2:amd64 (1.15.10-2ubuntu0.1) ...\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      \n",
              "[35] \"Setting up libxcb-shm0-dev:amd64 (1.13-2~ubuntu18.04) ...\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   \n",
              "[36] \"Setting up libpixman-1-dev:amd64 (0.34.0-2) ...\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             \n",
              "[37] \"Setting up libcairo2-dev:amd64 (1.15.10-2ubuntu0.1) ...\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     \n",
              "[38] \"Processing triggers for libc-bin (2.27-3ubuntu1.6) ...\\r\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Installing package into ‘/usr/local/lib/R/site-library’\n",
            "(as ‘lib’ is unspecified)\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZpgGDkzpkhBF"
      },
      "source": [
        "\n",
        "## Install packages"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DLhgbjF_tXw0",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c0780acd-14b8-41a2-9955-17cff21064d8"
      },
      "source": [
        "required_packages <- c(\n",
        "  'DESeq2', 'dplyr', 'tximportData','tximport',\n",
        "  'org.Mm.eg.db', 'org.Hs.eg.db',\n",
        "  'ComplexHeatmap', 'ggnewscale', # plotting\n",
        "  'goseq',\n",
        "  'biomaRt',\n",
        "  'DOSE', 'enrichplot', # pathway analysis\n",
        "  'VennDiagram',\n",
        "  'limma',\n",
        "  'ggwordcloud',\n",
        "  'eulerr',\n",
        "  'ggplot2',\n",
        "  'ggrepel',\n",
        "  'tibble',\n",
        "  'circlize',\n",
        "  'patchwork',\n",
        "  'stringi',\n",
        "  'stringr',\n",
        "  'clusterProfiler',\n",
        "  'formattable',\n",
        "  'reshape2',\n",
        "  \"tidyr\"\n",
        ")\n",
        "missing_packages <- required_packages[!required_packages %in% rownames(installed.packages())]\n",
        "if (length(missing_packages) > 0){\n",
        "    BiocManager::install(missing_packages)\n",
        "}\n",
        "missing_packages <- required_packages[!required_packages %in% rownames(installed.packages())]\n",
        "if (length(missing_packages) > 0){\n",
        "    install.packages(missing_packages)\n",
        "}\n",
        "# Load packages\n",
        "invisible(lapply(required_packages, library, character.only = TRUE))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "'getOption(\"repos\")' replaces Bioconductor standard repositories, see\n",
            "'?repositories' for details\n",
            "\n",
            "replacement repositories:\n",
            "    CRAN: https://cran.rstudio.com\n",
            "\n",
            "\n",
            "Bioconductor version 3.16 (BiocManager 1.30.19), R 4.2.1 (2022-06-23)\n",
            "\n",
            "Installing package(s) 'BiocVersion', 'DESeq2', 'tximportData', 'tximport',\n",
            "  'org.Mm.eg.db', 'org.Hs.eg.db', 'ComplexHeatmap', 'ggnewscale', 'goseq',\n",
            "  'biomaRt', 'DOSE', 'enrichplot', 'VennDiagram', 'limma', 'ggwordcloud',\n",
            "  'eulerr', 'ggrepel', 'circlize', 'patchwork', 'clusterProfiler',\n",
            "  'formattable', 'reshape2'\n",
            "\n",
            "also installing the dependencies ‘bitops’, ‘Rhtslib’, ‘RCurl’, ‘GenomeInfoDbData’, ‘zlibbioc’, ‘xtable’, ‘plogr’, ‘Biostrings’, ‘Rsamtools’, ‘GenomicAlignments’, ‘BiocIO’, ‘restfulr’, ‘gridGraphics’, ‘tweenr’, ‘RcppEigen’, ‘gridExtra’, ‘lazyeval’, ‘formatR’, ‘GenomeInfoDb’, ‘XVector’, ‘MatrixGenerics’, ‘DelayedArray’, ‘snow’, ‘BH’, ‘annotate’, ‘RSQLite’, ‘KEGGREST’, ‘rjson’, ‘iterators’, ‘rtracklayer’, ‘GenomicFeatures’, ‘filelock’, ‘cowplot’, ‘fastmatch’, ‘ggfun’, ‘ggplotify’, ‘ggforce’, ‘viridis’, ‘tidygraph’, ‘graphlayouts’, ‘ape’, ‘tidytree’, ‘treeio’, ‘lambda.r’, ‘futile.options’, ‘S4Vectors’, ‘IRanges’, ‘GenomicRanges’, ‘SummarizedExperiment’, ‘BiocGenerics’, ‘Biobase’, ‘BiocParallel’, ‘genefilter’, ‘locfit’, ‘geneplotter’, ‘Rcpp’, ‘RcppArmadillo’, ‘AnnotationDbi’, ‘GetoptLong’, ‘clue’, ‘GlobalOptions’, ‘png’, ‘matrixStats’, ‘foreach’, ‘doParallel’, ‘BiasedUrn’, ‘geneLenDataBase’, ‘GO.db’, ‘XML’, ‘BiocFileCache’, ‘HDO.db’, ‘fgsea’, ‘GOSemSim’, ‘qvalue’, ‘aplot’, ‘ggraph’, ‘igraph’, ‘plyr’, ‘scatterpie’, ‘shadowtext’, ‘ggtree’, ‘yulab.utils’, ‘futile.logger’, ‘GenSA’, ‘polyclip’, ‘polylabelr’, ‘shape’, ‘downloader’, ‘gson’, ‘htmlwidgets’\n",
            "\n",
            "\n",
            "Old packages: 'callr', 'data.table', 'devtools', 'digest', 'jsonlite',\n",
            "  'openssl', 'pkgload', 'processx', 'ps', 'roxygen2', 'sys', 'tibble',\n",
            "  'tidyverse', 'vctrs', 'xfun', 'yaml', 'zip', 'foreign', 'mgcv', 'rpart'\n",
            "\n",
            "Loading required package: S4Vectors\n",
            "\n",
            "Loading required package: stats4\n",
            "\n",
            "Loading required package: BiocGenerics\n",
            "\n",
            "\n",
            "Attaching package: ‘BiocGenerics’\n",
            "\n",
            "\n",
            "The following objects are masked from ‘package:stats’:\n",
            "\n",
            "    IQR, mad, sd, var, xtabs\n",
            "\n",
            "\n",
            "The following objects are masked from ‘package:base’:\n",
            "\n",
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            "\n",
            "\n",
            "Loading required package: Biobase\n",
            "\n",
            "Welcome to Bioconductor\n",
            "\n",
            "    Vignettes contain introductory material; view with\n",
            "    'browseVignettes()'. To cite Bioconductor, see\n",
            "    'citation(\"Biobase\")', and for packages 'citation(\"pkgname\")'.\n",
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            "    select\n",
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            "Loading required package: grid\n",
            "\n",
            "========================================\n",
            "ComplexHeatmap version 2.14.0\n",
            "Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/\n",
            "Github page: https://github.com/jokergoo/ComplexHeatmap\n",
            "Documentation: http://jokergoo.github.io/ComplexHeatmap-reference\n",
            "\n",
            "If you use it in published research, please cite either one:\n",
            "- Gu, Z. Complex Heatmap Visualization. iMeta 2022.\n",
            "- Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional \n",
            "    genomic data. Bioinformatics 2016.\n",
            "\n",
            "\n",
            "The new InteractiveComplexHeatmap package can directly export static \n",
            "complex heatmaps into an interactive Shiny app with zero effort. Have a try!\n",
            "\n",
            "This message can be suppressed by:\n",
            "  suppressPackageStartupMessages(library(ComplexHeatmap))\n",
            "========================================\n",
            "\n",
            "\n",
            "Loading required package: BiasedUrn\n",
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            "\n",
            "    unfactor\n",
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            "\n",
            "DOSE v3.24.0  For help: https://yulab-smu.top/biomedical-knowledge-mining-book/\n",
            "\n",
            "If you use DOSE in published research, please cite:\n",
            "Guangchuang Yu, Li-Gen Wang, Guang-Rong Yan, Qing-Yu He. DOSE: an R/Bioconductor package for Disease Ontology Semantic and Enrichment analysis. Bioinformatics 2015, 31(4):608-609\n",
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            "\n",
            "========================================\n",
            "circlize version 0.4.15\n",
            "CRAN page: https://cran.r-project.org/package=circlize\n",
            "Github page: https://github.com/jokergoo/circlize\n",
            "Documentation: https://jokergoo.github.io/circlize_book/book/\n",
            "\n",
            "If you use it in published research, please cite:\n",
            "Gu, Z. circlize implements and enhances circular visualization\n",
            "  in R. Bioinformatics 2014.\n",
            "\n",
            "This message can be suppressed by:\n",
            "  suppressPackageStartupMessages(library(circlize))\n",
            "========================================\n",
            "\n",
            "\n",
            "clusterProfiler v4.6.0  For help: https://yulab-smu.top/biomedical-knowledge-mining-book/\n",
            "\n",
            "If you use clusterProfiler in published research, please cite:\n",
            "T Wu, E Hu, S Xu, M Chen, P Guo, Z Dai, T Feng, L Zhou, W Tang, L Zhan, X Fu, S Liu, X Bo, and G Yu. clusterProfiler 4.0: A universal enrichment tool for interpreting omics data. The Innovation. 2021, 2(3):100141\n",
            "\n",
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        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GhH6FIU3q0ui"
      },
      "source": [
        "## Upload files"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "## Download data from urls\n",
        "urls <- c(\n",
        "  'https://raw.githubusercontent.com/yyw-informatics/RNA-seq-InfluenzaNP-CD8-T-cells/main/Data/MIS11602A1_mouse_NP__CD8___1_trimmed.tsv',\n",
        "  'https://raw.githubusercontent.com/yyw-informatics/RNA-seq-InfluenzaNP-CD8-T-cells/main/Data/MIS11602A2_mouse_NP__CD8___2_trimmed.tsv',\n",
        "  'https://raw.githubusercontent.com/yyw-informatics/RNA-seq-InfluenzaNP-CD8-T-cells/main/Data/MIS11602A3_mouse_NP__CD8___3_trimmed.tsv',\n",
        "  'https://raw.githubusercontent.com/yyw-informatics/RNA-seq-InfluenzaNP-CD8-T-cells/main/Data/MIS11602A4_mouse_NP__CD8___4_trimmed.tsv'\n",
        ")\n",
        "invisible(lapply(urls, function(url) download.file(url, basename(url))))"
      ],
      "metadata": {
        "id": "yizLgF2rMxq0"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#abundance_files <- c(basename(urls))\n",
        "abundance_files <- c(\n",
        "  'MIS11602A1_mouse_NP__CD8___1_trimmed.tsv',\n",
        "  'MIS11602A2_mouse_NP__CD8___2_trimmed.tsv',\n",
        "  'MIS11602A3_mouse_NP__CD8___3_trimmed.tsv',\n",
        "  'MIS11602A4_mouse_NP__CD8___4_trimmed.tsv')\n",
        "# Check if all files are downloaded \n",
        "file.exists(abundance_files)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "id": "YZ65ZtBrTsxh",
        "outputId": "a428f60f-7a3f-4e25-fea4-462fcc18588b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<style>\n",
              ".list-inline {list-style: none; margin:0; padding: 0}\n",
              ".list-inline>li {display: inline-block}\n",
              ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
              "</style>\n",
              "<ol class=list-inline><li>TRUE</li><li>TRUE</li><li>TRUE</li><li>TRUE</li></ol>\n"
            ],
            "text/markdown": "1. TRUE\n2. TRUE\n3. TRUE\n4. TRUE\n\n\n",
            "text/latex": "\\begin{enumerate*}\n\\item TRUE\n\\item TRUE\n\\item TRUE\n\\item TRUE\n\\end{enumerate*}\n",
            "text/plain": [
              "[1] TRUE TRUE TRUE TRUE"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8Zrgwlp5wHOW"
      },
      "source": [
        "## Parameters\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lAVAwl_cuZ_i"
      },
      "source": [
        "MIN_READS = 5\n",
        "MIN_SAMPLES = 2\n",
        "species = \"mmusculus_gene_ensembl\"\n",
        "PVAL <- 0.05\n",
        "PVAL_TOP_10 <- 0.01\n",
        "FC_DOWN <- -1         # Notes: log2(1/2) = -1; log2(1/4) = -2 \n",
        "FC_UP <- 1            # Notes: log2(2) = 1; log2(4) = 2 \n",
        "TOP_N <- 10"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2LSAPPh_DLVZ"
      },
      "source": [
        "## Functions"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eUJBi4OeDI0H"
      },
      "source": [
        "########### FUNCTION: format raw data and annotate\n",
        "format_and_annotate <- function(abundance_files, MIN_READS, MIN_SAMPLES, species){\n",
        "  # step 1\n",
        "  sprintf(\"1. Read the RNA-seq counts as SummarizedExperiment format\") %>% message()\n",
        "  x <- lapply(abundance_files, function(f) read.table(f, sep = '\\t', header = TRUE))\n",
        "  counts <- do.call('cbind', lapply(x, function(xx) xx$est_counts)) %>%\n",
        "      as.matrix() %>%\n",
        "      round()\n",
        "  rownames(counts) <- x[[1]]$target_id\n",
        "  se <- SummarizedExperiment(\n",
        "    assays = list(counts = counts), \n",
        "    rowData = data.frame(target_id = rownames(counts)),\n",
        "    colData= data.frame(\n",
        "      abundance_file = abundance_files, \n",
        "      dose = c('low', 'low', 'high', 'high')))\n",
        "  rowData(se)$ensembl_transcript_id  <- gsub('\\\\.\\\\d+', '', rowData(se)$target_id)\n",
        "  colData(se)$sample_id <- sprintf('%s_%d', colData(se)$dose, rep(1:2, 2))\n",
        "  \n",
        "  # step 2\n",
        "  sprintf(\"2. Filter number of transcripts that have at least X reads in at least Y samples:\") %>% message()\n",
        "  keep <- rowSums(assays(se)$counts > MIN_READS) >= MIN_SAMPLES\n",
        "  sprintf('   Number of transcripts that have at least %d reads in at least %d samples: %d/%d', MIN_READS, MIN_SAMPLES, sum(keep), nrow(se)) %>% message()\n",
        "  se <- se[keep]\n",
        "  \n",
        "  # step 3\n",
        "  sprintf(\"3. Retrieve the gene symbols\") %>% message()\n",
        "  mouse <-  useEnsembl(biomart=\"ensembl\", dataset = species) # takes a couple of minutes\n",
        "\n",
        "  # step 4\n",
        "  sprintf(\"4. Map EnsEMBL transcript IDs to ensembl gene id, gene symbol, entrezgene id\") %>% message()\n",
        "  bm <- getBM(\n",
        "    attributes = c('ensembl_transcript_id','ensembl_gene_id','external_gene_name', 'entrezgene_accession', 'entrezgene_trans_name','entrezgene_id'),\n",
        "    filters = \"ensembl_transcript_id\", \n",
        "    values = rowData(se)$ensembl_transcript_id,\n",
        "    mart = mouse)\n",
        "\n",
        "  df <- data.frame(\n",
        "    id = 1:nrow(se), \n",
        "    ensembl_transcript_id = rowData(se)$ensembl_transcript_id) %>%\n",
        "    left_join(bm, by = 'ensembl_transcript_id')  \n",
        "  rowData(se)$ensembl_gene_id <- rep(NA, nrow(se))\n",
        "  rowData(se)$ensembl_gene_id[df$id] <- df$ensembl_gene_id\n",
        "  rowData(se)$symbol <- rep(NA, nrow(se))\n",
        "  rowData(se)$symbol[df$id] <- df$external_gene_name\n",
        "  rowData(se)$entrezgene_id <- rep(NA, nrow(se))\n",
        "  rowData(se)$entrezgene_id[df$id] <- df$entrezgene_id\n",
        "  return(se)\n",
        "}\n",
        "\n",
        "########### FUNCTION: run DeSeq2\n",
        "run_deseq2 <- function(se){\n",
        "  se <- DESeqDataSet(se, design = ~ dose)\n",
        "  se <- estimateSizeFactors(se)\n",
        "  se <- DESeq(se)\n",
        "  # assays(se)$normalized_counts <- log2(counts(se, normalized = TRUE) + 1) \n",
        "  res <- results(se, contrast = c('dose', 'high', 'low'))\n",
        "  summary(res) %>% message()\n",
        "  return(res)\n",
        "}\n",
        "\n",
        "########### FUNCTION: clean up results\n",
        "clean_up_res <- function(se, res, PVAL, FC_UP, FC_DOWN){\n",
        "  # label the DEGs\n",
        "  res2 <- res %>%\n",
        "  as.data.frame() %>% \n",
        "  mutate(\n",
        "    ensembl_gene_id = rowData(se)$ensembl_gene_id,\n",
        "    ensembl_transcript_id = rowData(se)$ensembl_transcript_id,\n",
        "    symbol = rowData(se)$symbol,\n",
        "    entrezgene_id = rowData(se)$entrezgene_id\n",
        "  ) %>%\n",
        "  mutate(is_down = !is.na(padj) & padj < PVAL & log2FoldChange < FC_DOWN) %>%\n",
        "  mutate(is_up = !is.na(padj) & padj < PVAL & log2FoldChange > FC_UP) %>%\n",
        "  mutate(labels = if_else(is_down == TRUE, \"Down\",if_else(is_up == TRUE, \"Up\",\"No\"))) %>%\n",
        "  mutate(is_sig = !is.na(padj) & padj < PVAL & abs(log2FoldChange) > FC_UP) # if all three met,then is_sig = TRUE\n",
        "  cat(\" labels added to DESeq2 results\") %>% message()\n",
        "\n",
        "  if ((length(unique(rownames(res2)))!= nrow(res2)) && (nrow(assays(se)$counts) != length(unique(rownames(res2))))){\n",
        "    cat(\"res2 and se can't be merged, please check\") %>% message()\n",
        "  } else {\n",
        "  \n",
        "  # add count data\n",
        "  res3 <- merge(res2,assays(se)$counts,by='row.names',all=TRUE) \n",
        "  res3 <-column_to_rownames(as.data.frame(res3), var = \"Row.names\") %>%\n",
        "    rename(Low_dose_rep_1 = V1,Low_dose_rep_2 = V2, High_dose_rep_1 = V3, High_dose_rep_2 = V4) %>% \n",
        "    filter(!is.na(padj)) %>%\n",
        "    mutate(labels_2 = if_else(\n",
        "    (is_sig == TRUE & Low_dose_rep_1 == 0 & Low_dose_rep_2 == 0),\"Induced\",\n",
        "      if_else(\n",
        "        (is_sig == TRUE & High_dose_rep_1 == 0 & High_dose_rep_2 == 0), \"Inhibited\",\"No\")), .after = labels) %>%\n",
        "    mutate(padj_rounded = round(padj, 3), .after = 'padj') %>%\n",
        "    dplyr::select(\n",
        "       baseMean, log2FoldChange, lfcSE, stat, padj, padj_rounded, ensembl_gene_id, ensembl_transcript_id, symbol, entrezgene_id, labels, labels_2,\n",
        "       Low_dose_rep_1, Low_dose_rep_2, High_dose_rep_1, High_dose_rep_1, High_dose_rep_2) %>%\n",
        "    arrange(desc(log2FoldChange)) \n",
        "    cat(\" counts added to DESeq2 results\") %>% message()\n",
        "  return(res3)\n",
        "  }\n",
        "}\n",
        "\n",
        "########### FUNCTION: summarize\n",
        "summary_table <- function(res_genes){\n",
        "  total_genes_mapped <- res_genes %>% distinct_at(vars(symbol)) %>% nrow()\n",
        "  total_deg <- res_genes %>% filter(labels != \"No\") %>% filter(padj <= 0.05) %>% distinct_at(vars(symbol)) %>% nrow()\n",
        "  up_deg <- res_genes %>% filter(labels == \"Up\") %>% filter(padj <= 0.05) %>% distinct_at(vars(symbol)) %>% nrow()\n",
        "  down_deg <- res_genes %>% filter(labels == \"Down\") %>% filter(padj <= 0.05) %>% distinct_at(vars(symbol)) %>% nrow()\n",
        "  induced_deg <- res_genes %>% filter(labels_2 == \"Induced\") %>% filter(padj <= 0.05) %>% distinct_at(vars(symbol)) %>% nrow()\n",
        "  suppressed_deg <- res_genes %>% filter(labels_2 == \"Inhibited\") %>% filter(padj <= 0.05) %>% distinct_at(vars(symbol)) %>% nrow()\n",
        "  overall <- matrix(c(\n",
        "    total_genes_mapped, total_deg, up_deg, down_deg,induced_deg, suppressed_deg,\n",
        "    100, \n",
        "    round(total_deg/total_genes_mapped*100,2), \n",
        "    round(up_deg/total_genes_mapped*100,2), \n",
        "    round(down_deg/total_genes_mapped*100,2), \n",
        "    round(induced_deg/total_genes_mapped*100,2), \n",
        "    round(suppressed_deg/total_genes_mapped*100,2)),\n",
        "    nrow = 2, ncol = 6, byrow = TRUE)\n",
        "  rownames(overall) <- c('Count','Percentage(%)')\n",
        "  colnames(overall) <- c('Total_genes','Signficant_genes','Up','Down','Induced','Suppressed')\n",
        "  return(overall)\n",
        "}\n",
        "\n",
        "########### FUNCTION: get top N genes/trans & up/down\n",
        "get_tops <- function(res_table, PVAL_TOP_10, TOP_N, up_regulated = TRUE, transcript = TRUE, sort_by_fc = TRUE){\n",
        "  if (sort_by_fc == TRUE) {\n",
        "    if (up_regulated == TRUE) {        \n",
        "      topN_up <- res_table %>% \n",
        "      filter(labels == \"Up\" & padj <= PVAL_TOP_10) %>%\n",
        "      arrange(desc(log2FoldChange)) %>%\n",
        "      mutate(rank_up = 1:length(log2FoldChange), .after = labels_2) %>%\n",
        "      distinct()\n",
        "      up <- topN_up[1:TOP_N,c('id', 'labels','labels_2','symbol')]  # keep only top N\n",
        "      if (transcript == TRUE){         # sort by fc + up + transcripts \n",
        "        write.csv(topN_up[1:10,],paste0(\"Top\",TOP_N,\"_up_trans_\",Sys.Date(),\".csv\"), row.names = FALSE)\n",
        "      } else {                         # sort by fc + up + genes\n",
        "        write.csv(topN_up[1:10,],paste0(\"Top\",TOP_N,\"_up_genes_\",Sys.Date(),\".csv\"), row.names = FALSE)}\n",
        "      return(up)\n",
        "    } else {\n",
        "      topN_down <- res_table %>%       \n",
        "      filter(labels == \"Down\" & padj <= PVAL_TOP_10) %>%\n",
        "      arrange((log2FoldChange)) %>%\n",
        "      mutate(rank_down = 1:length(log2FoldChange)) %>%\n",
        "      distinct()\n",
        "      down <- topN_down[1:TOP_N,c('id', 'labels','labels_2','symbol')]  # keep only top N\n",
        "      if (transcript == TRUE){         # sort by fc + down + transcripts \n",
        "        write.csv(topN_down[1:10,],paste0(\"Top\",TOP_N,\"_down_trans_\",Sys.Date(),\".csv\"), row.names = FALSE)\n",
        "      } else {                         # sort by fc + down + genes \n",
        "        write.csv(topN_down[1:10,],paste0(\"Top\",TOP_N,\"_down_genes_\",Sys.Date(),\".csv\"), row.names = FALSE)}\n",
        "      return(down)\n",
        "   }\n",
        "  } else {\n",
        "    if (up_regulated == TRUE) {        \n",
        "      topN_up <- res_table %>% \n",
        "      filter(labels == \"Up\" & padj <= PVAL_TOP_10) %>%\n",
        "      arrange(padj) %>%\n",
        "      mutate(rank_up = 1:length(padj), .after = labels_2) %>%\n",
        "      distinct()\n",
        "      up <- topN_up[1:TOP_N,c('id', 'labels','labels_2','symbol')]  # keep only top N\n",
        "      if (transcript == TRUE){\n",
        "        write.csv(topN_up[1:10,],paste0(\"Top\",TOP_N,\"_up_trans_\",Sys.Date(),\".csv\"), row.names = FALSE)\n",
        "      } else {\n",
        "        write.csv(topN_up[1:10,],paste0(\"Top\",TOP_N,\"_up_genes_\",Sys.Date(),\".csv\"), row.names = FALSE)}\n",
        "      return(up)\n",
        "    } else {\n",
        "      topN_down <- res_table %>% \n",
        "      filter(labels == \"Down\" & padj <= PVAL_TOP_10) %>%\n",
        "      arrange(padj) %>%\n",
        "      mutate(rank_down = 1:length(padj)) %>%\n",
        "      distinct()\n",
        "      down <- topN_down[1:TOP_N,c('id', 'labels','labels_2','symbol')]  # keep only top N\n",
        "      if (transcript == TRUE){\n",
        "        write.csv(topN_down[1:10,],paste0(\"Top\",TOP_N,\"_down_trans_\",Sys.Date(),\".csv\"), row.names = FALSE)\n",
        "      } else {\n",
        "        write.csv(topN_down[1:10,],paste0(\"Top\",TOP_N,\"_down_genes_\",Sys.Date(),\".csv\"), row.names = FALSE)}\n",
        "      return(down)\n",
        "    }\n",
        "  }\n",
        "}\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Q0UC5Zd5s0Vf"
      },
      "source": [
        "# Format as SummerizeExperiment, filtering and add annotation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_nez8LA-owPs",
        "outputId": "3f2ea33d-d2e0-497c-ae4e-fdff5b696c61"
      },
      "source": [
        "se <- format_and_annotate(abundance_files, MIN_READS, MIN_SAMPLES, species)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "1. Read the RNA-seq counts as SummarizedExperiment format\n",
            "\n",
            "2. Filter number of transcripts that have at least X reads in at least Y samples:\n",
            "\n",
            "   Number of transcripts that have at least 5 reads in at least 2 samples: 79054/118489\n",
            "\n",
            "3. Retrieve the gene symbols\n",
            "\n",
            "4. Map EnsEMBL transcript IDs to ensembl gene id, gene symbol, entrezgene id\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gIE29Fcujah9"
      },
      "source": [
        "# Run DESeq2 analysis"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Re9cWCsZ1Ret",
        "outputId": "155fff6e-0547-4f80-e778-c828b3f5e0b9"
      },
      "source": [
        "se <- tximport(abundance_files, type = \"kallisto\", tx2gene = tx2gene, ignoreAfterBar = TRUE)\n",
        "res <- run_deseq2(se)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "converting counts to integer mode\n",
            "\n",
            "Warning message in DESeqDataSet(se, design = ~dose):\n",
            "“some variables in design formula are characters, converting to factors”\n",
            "using pre-existing size factors\n",
            "\n",
            "estimating dispersions\n",
            "\n",
            "gene-wise dispersion estimates\n",
            "\n",
            "mean-dispersion relationship\n",
            "\n",
            "final dispersion estimates\n",
            "\n",
            "fitting model and testing\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "out of 79054 with nonzero total read count\n",
            "adjusted p-value < 0.1\n",
            "LFC > 0 (up)       : 2503, 3.2%\n",
            "LFC < 0 (down)     : 1344, 1.7%\n",
            "outliers [1]       : 0, 0%\n",
            "low counts [2]     : 7664, 9.7%\n",
            "(mean count < 9)\n",
            "[1] see 'cooksCutoff' argument of ?results\n",
            "[2] see 'independentFiltering' argument of ?results\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "D5tlgYvf3vgn"
      },
      "source": [
        "# Map Annotations "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1TtpE5i326XY"
      },
      "source": [
        "## Use getBM() to get annotations\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZeHWumUc2x_b"
      },
      "source": [
        "mouse <-  useEnsembl(biomart=\"ensembl\", dataset = species, mirror = \"www\") # takes a couple of minutes\n",
        "bm <- getBM(\n",
        "    attributes = c('ensembl_transcript_id_version','ensembl_transcript_id','ensembl_gene_id','external_gene_name', 'entrezgene_accession', 'entrezgene_trans_name','entrezgene_id'),\n",
        "    filters = \"ensembl_transcript_id\", \n",
        "    values = rowData(se)$ensembl_transcript_id,\n",
        "    mart = mouse)\n",
        "bm <- bm %>% rename(symbol = external_gene_name) %>% select(symbol, entrezgene_id, ensembl_gene_id)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-NMhG4zfqzf6"
      },
      "source": [
        "## Manually add unmapped gene symbols\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wVwVuqilwrz8",
        "outputId": "db59a40a-6020-4c77-da11-56c3ad8187a0"
      },
      "source": [
        "res_trans <- clean_up_res(se, res, PVAL, FC_UP, FC_DOWN)\n",
        "check <- which((!is.na(res_trans$ensembl_transcript_id) & is.na(res_trans$symbol) & res_trans$labels != \"No\")) # subset the unmapped to csv file\n",
        "# write.csv(res_trans[check,], file = \"manually_check_2.csv\") if first time\n",
        "# res_trans\n",
        "res_trans <- clean_up_res(se, res, PVAL, FC_UP, FC_DOWN)\n",
        "check <- which((!is.na(res_trans$ensembl_transcript_id) & is.na(res_trans$symbol) & res_trans$labels != \"No\")) # subset the unmapped to csv file\n",
        "res_trans <- res_trans[-check,]                              # check rows removed\n",
        "checked <- read.csv(\"manually_checked_2.csv\", header = TRUE) # read the new annotations\n",
        "colnames(checked)[1] <- c('id')\n",
        "checked2 <- merge(checked, bm, by = 'symbol') %>%\n",
        "  select(-entrezgene_id.x) %>%\n",
        "  select(-ensembl_gene_id.x) %>%\n",
        "  rename(entrezgene_id = entrezgene_id.y) %>%\n",
        "  rename(ensembl_gene_id = ensembl_gene_id.y) %>%\n",
        "  distinct()      \n",
        "                                           \n",
        "res_trans <- res_trans %>% \n",
        "  rownames_to_column(var = \"id\") %>% \n",
        "  rbind(checked2) %>%\n",
        "  filter(!is.na(symbol))                                   \n",
        "\n",
        "res_genes <- res_trans %>%\n",
        "  group_by(symbol) %>%  \n",
        "  summarize(padj=min(padj)) %>% \n",
        "  arrange(padj) %>%\n",
        "  left_join(res_trans, by = c('symbol','padj')) %>% \n",
        "  distinct()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " labels added to DESeq2 results"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " counts added to DESeq2 results"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " labels added to DESeq2 results"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " counts added to DESeq2 results"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CteE1MZq8Jth"
      },
      "source": [
        "# Results: "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KMGkFQHlbEbK"
      },
      "source": [
        "### Count summary of DEGs"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 129
        },
        "id": "_yFRNa44XIgf",
        "outputId": "9d3a4210-8b10-402e-fd49-d3f244dab109"
      },
      "source": [
        "summary_table(res_genes)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<table class=\"dataframe\">\n",
              "<caption>A matrix: 2 × 6 of type dbl</caption>\n",
              "<thead>\n",
              "\t<tr><th></th><th scope=col>Total_genes</th><th scope=col>Signficant_genes</th><th scope=col>Up</th><th scope=col>Down</th><th scope=col>Induced</th><th scope=col>Suppressed</th></tr>\n",
              "</thead>\n",
              "<tbody>\n",
              "\t<tr><th scope=row>Count</th><td>23626</td><td>1567.00</td><td>888.00</td><td>679.00</td><td>144.00</td><td>178.00</td></tr>\n",
              "\t<tr><th scope=row>Percentage(%)</th><td>  100</td><td>   6.63</td><td>  3.76</td><td>  2.87</td><td>  0.61</td><td>  0.75</td></tr>\n",
              "</tbody>\n",
              "</table>\n"
            ],
            "text/markdown": "\nA matrix: 2 × 6 of type dbl\n\n| <!--/--> | Total_genes | Signficant_genes | Up | Down | Induced | Suppressed |\n|---|---|---|---|---|---|---|\n| Count | 23626 | 1567.00 | 888.00 | 679.00 | 144.00 | 178.00 |\n| Percentage(%) |   100 |    6.63 |   3.76 |   2.87 |   0.61 |   0.75 |\n\n",
            "text/latex": "A matrix: 2 × 6 of type dbl\n\\begin{tabular}{r|llllll}\n  & Total\\_genes & Signficant\\_genes & Up & Down & Induced & Suppressed\\\\\n\\hline\n\tCount & 23626 & 1567.00 & 888.00 & 679.00 & 144.00 & 178.00\\\\\n\tPercentage(\\%) &   100 &    6.63 &   3.76 &   2.87 &   0.61 &   0.75\\\\\n\\end{tabular}\n",
            "text/plain": [
              "              Total_genes Signficant_genes Up     Down   Induced Suppressed\n",
              "Count         23626       1567.00          888.00 679.00 144.00  178.00    \n",
              "Percentage(%)   100          6.63            3.76   2.87   0.61    0.75    "
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IlBHR6okTspU"
      },
      "source": [
        "### Volcano: \n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fO_FVF_N0j1q"
      },
      "source": [
        "wp <- read.csv('Weiping_hl_genes.csv', header = TRUE)\n",
        "# Top genes\n",
        "# Rank by FC\n",
        "up_genes_sort_by_fc   <- get_tops(res_genes, PVAL_TOP_10, TOP_N, up_regulated = TRUE, transcript = FALSE, sort_by_fc = TRUE)\n",
        "down_genes_sort_by_fc <- get_tops(res_genes, PVAL_TOP_10, TOP_N, up_regulated = FALSE, transcript = FALSE, sort_by_fc = TRUE)\n",
        "# Rank by adjusted p-value\n",
        "up_genes_sort_by_p  <- get_tops(res_genes, PVAL_TOP_10, TOP_N, up_regulated = TRUE, transcript = FALSE, sort_by_fc = FALSE)\n",
        "down_genes_sort_by_p <- get_tops(res_genes, PVAL_TOP_10, TOP_N, up_regulated = FALSE, transcript = FALSE, sort_by_fc = FALSE)\n",
        "\n",
        "alltop_ups <- rbind(up_genes_sort_by_fc, up_genes_sort_by_p) %>% distinct()\n",
        "alltop_ds <- rbind(down_genes_sort_by_fc, down_genes_sort_by_p) %>% distinct()\n",
        "tops <- rbind(alltop_ups, alltop_ds) %>% rename(label_tops = symbol) \n",
        "\n",
        "# All genes\n",
        "res_genes_outlier_removed <- res_genes %>% filter(symbol != \"Gm15056\") %>% filter(symbol != \"Cadm1\") # not related to CD8+\n",
        "res = res_genes_outlier_removed # note that res is the final results data \n",
        "res <- res %>% mutate(label_tops = symbol)\n",
        "res2 <- res %>% select(id, labels, labels_2, label_tops) \n",
        "hilight <- wp %>% left_join(res2, by = \"label_tops\") # just to fill info for the highlighted genes\n",
        "keep <- intersect(hilight$label_tops,tops$label_tops) # these are the top genes related to CD8+ functions\n",
        "hilight <- hilight %>% filter(label_tops %in% keep) # find the genes overlapping the highlight list and the top list\n",
        "res <- res %>% mutate(gene_label = if_else(label_tops %in% hilight$label_tops, symbol, \"\"))\n",
        "res <- res %>% mutate(wp_label = if_else(label_tops %in% wp$label_tops, symbol, \"\"))\n",
        "res <- res %>% mutate(on_wp_list = if_else(label_tops %in% wp$label_tops, 1, 0))\n",
        "res <- res %>% select(\n",
        "  symbol, on_wp_list, wp_label, gene_label, padj, log2FoldChange, labels, labels_2, Low_dose_rep_1,Low_dose_rep_2, High_dose_rep_1, High_dose_rep_2)\n",
        "res <- res %>% rename(color_label = labels) \n",
        "res <- res %>% rename(top_label = labels_2)\n",
        "res$color_label <- as.factor(res$color_label)\n",
        "levels(res$color_label) <- c(\"Down\",\"No\",\"Up\")\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 292
        },
        "id": "Fdc2YOqZGPc6",
        "outputId": "c4cee9ef-ec09-4232-ef80-5ed3d9e7d8aa"
      },
      "source": [
        "options(repr.plot.width = 5, repr.plot.height = 4)\n",
        "main_title = paste0(\"Top CD8+ genes ranked by both FC and p-value\")\n",
        "g = ggplot(data=res, \n",
        "            aes(x=log2FoldChange, y=-log10(padj), \n",
        "                # Colour based on the threshold defined before\n",
        "                colour=color_label)) +\n",
        "    # Define the look of the points\n",
        "    geom_point(alpha=0.9, size=1) +\n",
        "    # Hide the legend\n",
        "    theme(legend.position=c(10, 60), legend.justification = c(10, 60)) +\n",
        "    # Apply another theme\n",
        "    theme_bw() + \n",
        "    xlab(\"log2 fold change\") + \n",
        "    ylab(\"-log10 FDR\") + \n",
        "    labs(color='Differentially\\n Expressed\\n Genes') +\n",
        "    xlim(-15,15) + \n",
        "    ylim(0, 50) + # change the y lim here \n",
        "    guides(size = FALSE) +\n",
        "    ggtitle(main_title) +\n",
        "    geom_text_repel(aes(label=gene_label, size = 13), box.padding = 2, max.overlaps = Inf, show.legend = FALSE) + # labels are here!\n",
        "    scale_color_manual(values=c(\"blue\", \"black\", \"red\"))\n",
        "g"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Warning message:\n",
            "“`guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> = \"none\")` instead.”\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "plot without title"
            ],
            "image/png": 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atWcbMIv/jC5quvlIMHJx46BEAil1sBKSkp2T4xLQ2AdXq6JZCcnJxZwLpSqfgx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"
          },
          "metadata": {
            "image/png": {
              "width": 300,
              "height": 240
            }
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Hg4GKDHsjdSd"
      },
      "source": [
        "### Barplot of GO terms:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pDzaqccpyNcT"
      },
      "source": [
        "##### By ensembl_gene_id ##### \n",
        "# all genes\n",
        "glist <- res_genes %>% arrange(desc(log2FoldChange)) %>% pull(log2FoldChange)\n",
        "names(glist) <- res_genes$ensembl_gene_id\n",
        "# all sig genes\n",
        "siglist <- res_genes %>% filter(labels != \"No\") %>% arrange(desc(log2FoldChange)) %>% pull(log2FoldChange)\n",
        "names(siglist) <- res_genes %>% filter(labels != \"No\") %>% pull(ensembl_gene_id)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GMa17K-X4V4-"
      },
      "source": [
        "test_list <- names(siglist)\n",
        "bkgd_list <- names(glist)\n",
        "ego <- enrichGO(gene          = test_list,\n",
        "                universe      = bkgd_list,\n",
        "                OrgDb         = org.Mm.eg.db,\n",
        "                ont           = \"BP\",\n",
        "                keyType       = 'ENSEMBL',\n",
        "                pAdjustMethod = \"fdr\",\n",
        "                pvalueCutoff  = 0.05,\n",
        "                readable      = TRUE)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RX8zzaLR5Cxd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 380
        },
        "outputId": "67ae2380-6ea8-4e1c-d2c8-f3257e3774fb"
      },
      "source": [
        "finalgo <- read.csv(\"GO_terms_final_10_27.csv\", header = TRUE)\n",
        "gobar <- ego %>% filter(ID %in% finalgo$ID)\n",
        "gobar <- gobar@result %>% as.data.frame() %>% select(ID, Description, p.adjust, Count) %>% arrange(p.adjust)\n",
        "gobar"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<table class=\"dataframe\">\n",
              "<caption>A data.frame: 9 × 4</caption>\n",
              "<thead>\n",
              "\t<tr><th></th><th scope=col>ID</th><th scope=col>Description</th><th scope=col>p.adjust</th><th scope=col>Count</th></tr>\n",
              "\t<tr><th></th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;int&gt;</th></tr>\n",
              "</thead>\n",
              "<tbody>\n",
              "\t<tr><th scope=row>GO:0009615</th><td>GO:0009615</td><td>response to virus                    </td><td>1.342417e-09</td><td>68</td></tr>\n",
              "\t<tr><th scope=row>GO:0019221</th><td>GO:0019221</td><td>cytokine-mediated signaling pathway  </td><td>1.670171e-07</td><td>70</td></tr>\n",
              "\t<tr><th scope=row>GO:0001558</th><td>GO:0001558</td><td>regulation of cell growth            </td><td>5.575062e-04</td><td>63</td></tr>\n",
              "\t<tr><th scope=row>GO:0022407</th><td>GO:0022407</td><td>regulation of cell-cell adhesion     </td><td>7.400250e-04</td><td>68</td></tr>\n",
              "\t<tr><th scope=row>GO:0007159</th><td>GO:0007159</td><td>leukocyte cell-cell adhesion         </td><td>2.094466e-03</td><td>57</td></tr>\n",
              "\t<tr><th scope=row>GO:0042098</th><td>GO:0042098</td><td>T cell proliferation                 </td><td>9.375935e-03</td><td>36</td></tr>\n",
              "\t<tr><th scope=row>GO:0072676</th><td>GO:0072676</td><td>lymphocyte migration                 </td><td>1.044989e-02</td><td>20</td></tr>\n",
              "\t<tr><th scope=row>GO:0007015</th><td>GO:0007015</td><td>actin filament organization          </td><td>1.689196e-02</td><td>57</td></tr>\n",
              "\t<tr><th scope=row>GO:0002697</th><td>GO:0002697</td><td>regulation of immune effector process</td><td>3.418617e-02</td><td>53</td></tr>\n",
              "</tbody>\n",
              "</table>\n"
            ],
            "text/markdown": "\nA data.frame: 9 × 4\n\n| <!--/--> | ID &lt;chr&gt; | Description &lt;chr&gt; | p.adjust &lt;dbl&gt; | Count &lt;int&gt; |\n|---|---|---|---|---|\n| GO:0009615 | GO:0009615 | response to virus                     | 1.342417e-09 | 68 |\n| GO:0019221 | GO:0019221 | cytokine-mediated signaling pathway   | 1.670171e-07 | 70 |\n| GO:0001558 | GO:0001558 | regulation of cell growth             | 5.575062e-04 | 63 |\n| GO:0022407 | GO:0022407 | regulation of cell-cell adhesion      | 7.400250e-04 | 68 |\n| GO:0007159 | GO:0007159 | leukocyte cell-cell adhesion          | 2.094466e-03 | 57 |\n| GO:0042098 | GO:0042098 | T cell proliferation                  | 9.375935e-03 | 36 |\n| GO:0072676 | GO:0072676 | lymphocyte migration                  | 1.044989e-02 | 20 |\n| GO:0007015 | GO:0007015 | actin filament organization           | 1.689196e-02 | 57 |\n| GO:0002697 | GO:0002697 | regulation of immune effector process | 3.418617e-02 | 53 |\n\n",
            "text/latex": "A data.frame: 9 × 4\n\\begin{tabular}{r|llll}\n  & ID & Description & p.adjust & Count\\\\\n  & <chr> & <chr> & <dbl> & <int>\\\\\n\\hline\n\tGO:0009615 & GO:0009615 & response to virus                     & 1.342417e-09 & 68\\\\\n\tGO:0019221 & GO:0019221 & cytokine-mediated signaling pathway   & 1.670171e-07 & 70\\\\\n\tGO:0001558 & GO:0001558 & regulation of cell growth             & 5.575062e-04 & 63\\\\\n\tGO:0022407 & GO:0022407 & regulation of cell-cell adhesion      & 7.400250e-04 & 68\\\\\n\tGO:0007159 & GO:0007159 & leukocyte cell-cell adhesion          & 2.094466e-03 & 57\\\\\n\tGO:0042098 & GO:0042098 & T cell proliferation                  & 9.375935e-03 & 36\\\\\n\tGO:0072676 & GO:0072676 & lymphocyte migration                  & 1.044989e-02 & 20\\\\\n\tGO:0007015 & GO:0007015 & actin filament organization           & 1.689196e-02 & 57\\\\\n\tGO:0002697 & GO:0002697 & regulation of immune effector process & 3.418617e-02 & 53\\\\\n\\end{tabular}\n",
            "text/plain": [
              "           ID         Description                           p.adjust     Count\n",
              "GO:0009615 GO:0009615 response to virus                     1.342417e-09 68   \n",
              "GO:0019221 GO:0019221 cytokine-mediated signaling pathway   1.670171e-07 70   \n",
              "GO:0001558 GO:0001558 regulation of cell growth             5.575062e-04 63   \n",
              "GO:0022407 GO:0022407 regulation of cell-cell adhesion      7.400250e-04 68   \n",
              "GO:0007159 GO:0007159 leukocyte cell-cell adhesion          2.094466e-03 57   \n",
              "GO:0042098 GO:0042098 T cell proliferation                  9.375935e-03 36   \n",
              "GO:0072676 GO:0072676 lymphocyte migration                  1.044989e-02 20   \n",
              "GO:0007015 GO:0007015 actin filament organization           1.689196e-02 57   \n",
              "GO:0002697 GO:0002697 regulation of immune effector process 3.418617e-02 53   "
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 287
        },
        "id": "AJKZZ-Hp8z4S",
        "outputId": "91b1adaa-4424-4e83-e91a-e649fc6a179e"
      },
      "source": [
        "options(repr.plot.width = 6, repr.plot.height = 4.5)\n",
        "finalgo <- read.csv(\"GO_terms_final_10_27.csv\", header = TRUE)\n",
        "gobar <- ego %>% filter(ID %in% finalgo$ID)\n",
        "barplot(gobar, showCategory = nrow(finalgo))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "plot without title"
            ],
            "image/png": 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1YoFFOmTNHR0Tl06BD5+/n78PBwiqKq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\n/QN4jqRxoay3cgAAAABJRU5ErkJggg=="
          },
          "metadata": {
            "image/png": {
              "width": 360,
              "height": 270
            }
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "a2py286k8VSB"
      },
      "source": [
        "## Heatmap of key genes:\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "N2cqHqtxkhRx"
      },
      "source": [
        "### Prepare data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "R8ZhOK8lY7x7",
        "outputId": "043c4e56-d919-421e-e390-eee6adb81a7b"
      },
      "source": [
        "gomat <- res %>% filter(on_wp_list == 1)\n",
        "bm_to_show <- getBM(\n",
        "    attributes = c('external_gene_name','description'),\n",
        "    filters = \"external_gene_name\", \n",
        "    values = gomat$symbol,\n",
        "    mart = mouse) %>% \n",
        "    rename(symbol = external_gene_name) %>% \n",
        "    mutate(gene_name = gsub(\"\\\\[[^\\\\]]*\\\\]\", \"\", description, perl=TRUE)) %>%\n",
        "    select(-c('description'))\n",
        "label_order <- c(\"Induced\", \"Up\", \"Suppressed\",\"Down\")\n",
        "gomat <- gomat %>% left_join(bm_to_show) %>%\n",
        "  mutate(gene_description = paste(symbol, gene_name, sep = \" - \")) %>%       \n",
        "  select(-c(\"gene_name\")) %>%\n",
        "  mutate(label = ifelse(color_label == \"Down\", \n",
        "    ifelse(top_label == \"Inhibited\",\"Suppressed\",\"Down\"),\n",
        "      ifelse(color_label == \"Up\",\n",
        "        ifelse(top_label == \"Induced\",\"Induced\",\"Up\"), \"No\")), .after = padj) %>%  # this is to combine labels\n",
        "  arrange(sapply(label, function(y) which(y == label_order))) %>%\n",
        "  select(-c(\"on_wp_list\",\"wp_label\",\"gene_label\",\"color_label\",\"top_label\")) %>%\n",
        "  relocate(gene_description, .after = symbol)\n",
        "  gomat <- gomat %>% filter(symbol != \"Cadm1\") %>% filter(symbol != \"Clec9a\") # these genes are mostly involved in innate function, hence not show in the heatmap\n",
        "  gomat <- gomat %>% arrange(symbol)\n",
        "  gomat$gene_description[which(gomat$symbol == 'Cd74')] <- 'Cd74 - CD74 antigen'\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\u001b[1m\u001b[22mJoining, by = \"symbol\"\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wzYHI1Qdl3Cf"
      },
      "source": [
        "### Prepare 2 heatmaps"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TspNtKJt42Qn"
      },
      "source": [
        "# Top label: dose\n",
        "dose_annotation = HeatmapAnnotation(\n",
        "  Dose = c('Low dose','Low dose','High dose','High dose'),\n",
        "  col = list(Dose = c(\"Low dose\" = \"#C0C0C0\", \"High dose\" = \"#2F4F4F\")))\n",
        "\n",
        "# Cell color: expression values\n",
        "cell_cols <- colorRamp2(c(-2, 0, 2), c(\"blue\", \"black\", \"red\"))\n",
        "\n",
        "# Heatmap 1: cells and gene names \n",
        "y <- gomat %>% select(contains('dose_rep')) %>% as.data.frame()\n",
        "#rownames(y) <- gomat$symbol # For gene symbol only\n",
        "rownames(y) <- gomat$gene_description # For gene symbol and annotation\n",
        "\n",
        "h_main <- Heatmap(\n",
        "  y %>% t() %>% scale() %>% t(),\n",
        "  row_split = factor(gomat$label, levels = c(\"Induced\",\"Up\",\"Suppressed\",\"Down\")),\n",
        "  cluster_rows      = FALSE, \n",
        "  cluster_columns   = FALSE,\n",
        "  show_column_dend  = FALSE,\n",
        "  show_row_dend     = FALSE,\n",
        "  show_column_names = FALSE,\n",
        "  col = cell_cols,\n",
        "  width = unit(20, \"mm\"),\n",
        "  top_annotation = dose_annotation,\n",
        "  heatmap_legend_param = list(direction = \"horizontal\", title = \"Scaled Expression Value\"),\n",
        "  rect_gp = gpar(col = \"white\", lwd = 0.5)) # white border \n",
        "\n",
        "# Heatmap 2: color block on the left \n",
        "cols_category = c(\"Induced\" = \"tomato4\",\"Up\" = \"tomato\",\"Suppressed\" = \"steelblue4\",\"Down\" = \"steelblue3\",\"No\" = \"grey\")                      # GO color\n",
        "h_category <- Heatmap(\n",
        "  gomat$label, \n",
        "  row_split = factor(gomat$label, levels = c(\"Induced\",\"Up\",\"Suppressed\",\"Down\")),\n",
        "  name = \" \", \n",
        "  width = unit(5, \"mm\"), \n",
        "  heatmap_legend_param = list(title = \"Expression Level\"),\n",
        "  col = cols_category)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Plot the heatmap"
      ],
      "metadata": {
        "id": "bQADbYEsfUOj"
      }
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 497
        },
        "id": "99CPIY_5lvUi",
        "outputId": "fc23d739-3486-46db-be1e-a815c28289b9"
      },
      "source": [
        "# Set plot size\n",
        "options(repr.plot.width = 18, repr.plot.height = 8)\n",
        "#par(mar=c(0,0,4,0)) # bottom, left, top , right\n",
        "\n",
        "# Plot two heatmaps  \n",
        "h = h_category + h_main\n",
        "draw(h, \n",
        "  heatmap_legend_side = \"left\", \n",
        "  annotation_legend_side = \"left\", \n",
        "  merge_legend = TRUE,\n",
        "  #legend_grouping = \"original\",\n",
        "  padding = unit(c(2, 3, 5, 2), \"mm\"))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "plot without title"
            ],
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IAvhd3I3tLPYWiwZWxHKUoZRK+XYp83ljVaWlLGUVVW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\n/8zlcpO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yEVUOR8oWAEDY6dOnY2NjIyIi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XE2VkZOTn5+fl5Y1KtDFLGwAAAABgvMAbKgAAAAAAnFJTU6WkpAoKCsTFxbEWJycnJpN5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mU5YtW0aNpgBA//79mUzm69evqa9ycnLR0dGjRo0K\nDg7++PFjQUFBWlqajIwMdZR6DTw+Pn7lypVaWlqPHj0KDw+fNWvWhw8fFi5cCAA9e/ZMT0+f\nPHmypaUldUqnTp2Sk5MHDRr0hdu4fv369evX18/p5+cnsreKmZnZsmXLNm7cKCcnt2PHjgbL\nb6w08agZM/S+3LSampqYmBgZGZlp06YBgLy8/JQpU+Li4k6ePGlvb0/lYbPZL1++LC4uVlNT\no1K2bt0qUo7w83FFRUVLS8vk5OTCwsKOHTs2GM+bN28UFRXl5OSa25DWk6STG9Tcnpek36hR\nt2fPnokfUHF2dqanTejq6g4ePPjKlSv5+fna2tqnTp1SV1e3sbGhM/fs2dPc3DwtLa2srKxD\nhw7if0eNaeyCamhoNFkjnS4rKztjxozdu3dfv36d2pK9pKTk6tWr06ZNU1RUlKSuY8eOGRkZ\naWtr0yt0sdlsCwuL33//vaKigr5/mnv7UQQCQUpKSteuXYV3PFqwYAG9ohpJkhIGIOyb/dOE\nEEIIfV04oIIQQgghhBBCzVNXVwcALNb///eU8DQOgiDk5OSqqqrolBEjRri4uISEhAgEgmXL\nllH7LlB8fHwWLVo0fvz4du3aUSkODg7G/8fevcfFmP//439dOikdbKppVUrlTKJYIjkUWunI\nflqn3RirFiGh7AohqSUksW+HcliVlWMsb4fashF2W7vOpxI76UAYndTM74/rt9d33tM0czXX\nFPG4/zW95jXP6/l6Xa9r3FyvuV6v/v2XLl0aEBCgqal569atcePG1dXVrV+/vmvXriUlJRs2\nbHB3d//5559lbrZRUVERFhbG/GlraxsaGqqSNg4ePNjJyalhzYaF1dXVJ06caNOmjVAoTElJ\n+eabbxp+ysHBoeFm13V1dTt37pSTFb3ukJGRkVQ5vR39lClTmA1LAgIC9u7du2PHDmZCJTIy\nct68eV26dPHy8hoxYsTo0aPpSSNJXbt2lfyTrlBcXKytrS2zV9XU1CR3E6ENHTr04sWLkiUv\nXryQsxeFTArPo5xOlv/ZpvY8m36j51oargolxc7OTvJPa2vrCxcuFBYWqqurv3z50sHBQWoP\nmG7duuXk5Ny9e5e+ZORcR41p7IQSQtgckcHn87dt25aUlERPqBw6dKi+vp5+HErhsdq0aVNW\nVlZWViZzXuTx48fMEl6NRZA/oSIQCKqqqqwlf1fy73pctJKSEpYJSFL5VxMAAMCHARMqAAAA\nAAAATUPvxtyxY0emRIvZx6kRM2bMoH8wTm/vwWi4elXPnj0///zzw4cP//nnnwMGDJg+ffqz\nZ8/u3r3L3MX29/fv2rXr119//ejRI+axGIZQKNy+fTvz55AhQ5SbUGnYxtGjR0s9idKYkJCQ\nGzduHDx4MDIyMiQkZNSoUTY2NlJ1PDw8GkYTCoXyJ1RevXpFCJF8LIBGr/c1fPjw+/fv0yXm\n5uY8Hu/cuXMPHz6k7zUHBwf37t07Pj4+PT197969FEW5u7tv3brV0tKSiaOjoyMZlr6VXFFR\n0VivduzY8f79+8+fP5fckd7b27t3797067Nnz9I92VQKz6OcTpb/2ab2PJt+o6eL6EWi5GCm\nu2h0b1dXV79584b829uS6AdQ6HdpjV1HjWnshOrp6bE8Is3BwaFfv35paWmbN2/W1tZOS0uz\nsLAYNWoU+2PZ29uvXbu2YYaSl1hjEeS3sbKykhDStm1bycK2bdsyc0WvX79mmYAklX81AQAA\nfBiwKT0AAAB8gHbt2tWvXz9dXV0rK6ugoCCFv5llKTExUVtbe8KECVyCJCcn9+rVS0tLy8zM\nbNGiRfRvwN+HxBjN1HsAHwyRSJSRkUEIGTZsGPuPzJkzh8fjdejQ4dtvvxWLxfLr07/3FwqF\nQqHw8uXLn332meQzATo6OqNGjXr69Ondu3cbftbc3FwsoeEO2ywTbmobGceOHUtMTJw+ffqE\nCROSk5Nra2unTp1aX1+vRBoN0XfkpW7c37lzh95bm8/nd/lX165dnz17JhaLJecJRo4cefjw\n4fLy8v/+97/Tpk07deqUq6trbW0tU0HqTjp9oA4dOjTWq/SO6FL7sYeGhm77V8NnQeSQzET+\neZTfySoZA5IU9ht907/hRJcUyce2yL8zATo6OvSSUw2nMegSekKCNP06ahiTOaEsjyhpxowZ\nr169ysjIKC4uzsrKmjZtmuSu73KOxUQbK4vko0uNRZDfRnoSqLq6WrJQKBQy/cM+AYW4fDUB\nAAB8GDChAgAAAB+auLi4GTNmuLq6Hj16NCwsLC0tjVnvRWnPnz/39vZetWqV1K9rmyo1NTUg\nIGD8+PEnT55cvnz5zp07g4OD34fEGM3RewAfmO3btz969MjT05PH47H8yIYNG3Jzczdt2vTD\nDz9kZ2czO14IhcLExMQDBw5I1b9x4wYhxNLSsqqqSiwWS90qJf/ePG1YripKtJH2zz//TJ8+\n3crKauPGjYSQfv36LV26NDc3V+ZP45VAL/ZVXl4uWUg/nsLn8w/+r71796qpqe3evbuurk6y\nvpaWlqura1JSUmBg4P379/Pz85m3bt26JVmT3rJFzoJL9JbjkZGR9NxAk9A/4ZecVn/06BGb\nDzZ3JzdGTr+VlpYSWUuxSZHqXvrZHWtra1NTU0NDw1u3bknNkdy8eZOiqG7dutF/NnYdsT8i\nc0JZHlHS5MmTtbW1U1NTU1NTRSLR119/zfJYPB7PyMjo9u3bUs+a0J3GJoL8NpqammpqakoN\nnuvXrzOv2SfAeG+/mgAAAN45TKgAAADAB0UkEq1du3bq1KmxsbGjRo0KDAxcuXLl+fPni4qK\nuIRNT08XCoV//PGHwvsa8kVGRn7xxRfR0dGjRo365ptv1q1b9+OPPz59+vSdJ0Zrpt4D+GCI\nRKLExMT58+fr6+vHxsay/NTdu3cjIiI+//zz//u///v6669HjBixdOlS+lapjo7OmjVrvvnm\nm9u3bzP1jx49mpOT069fP2tra2Nj486dO1+9elXyF98VFRVnz57V19dn1pVSIeXayHx22rRp\nL168SE5OZn4U/9133/Xr1y8yMvLatWvc02M2P2dK6O3otbS0oqKiJvyvKVOmeHt7CwSCjIyM\nS5cumZmZ7dmzRzIa/YSB5NpEu3btYl7fvXv3ypUr3bp1MzY2biyfIUOGTJ069d69e2PHji0s\nLJR8q6amZvPmzcePH9fT09PU1Gz4Wfp7W/IeulR6MrVAJ0ti2W/0eLa1tZUfTbJ7nzx58ttv\nv/Xs2dPU1JQQ4uvrKxAIjh49ylTIz8/Py8sbOXIk/QiFnOuI5RGlTqjCI0pp3769r6/vyZMn\nk5KShg4d2rCxco41ceLE6upqyQuqtLTUzs5u/PjxLCOoqamRBo/40NTV1Z2cnO7fv3/lyhWm\nMCEhQbIOywQY7+FXEwAAwHsCe6gAAADAB4WiqNzcXMnFOug15cvKyiwsLJQO6+7uPn36dKnF\nPZqqqKjo5s2b33//PVPi7e39zTffnD59evr06e8wMUYz9R5A63X27Fn6p9ZisbikpITeQNvE\nxOTQoUNS20c3hv4le5s2beiNHwgh27Zts7OzCwgI+PXXX+lyb29vR0dHf3//jh07/v3330eO\nHNHX19+xYwddf/369RMmTHBycgoMDLSxsREIBDt27Hj+/HlCQoLCjVtU28Zffvmlse0cxo0b\n5+bmFhMTc+7cuYULF0ouFKahoZGcnOzo6DhlypTff/+dXp5IafSuFefPn/f09KRLDh06VF5e\nHhAQIHPaY+7cuYcOHfrPf/5z5MgRQ0PDmTNn5uTk2NvbUxR19epV+s64vb09U7+mpmb8+PEe\nHh4ikSgmJkYsFkdERMhP6T//+Y9YLN63b1/Xrl2HDRvWtWtXkUj0+PHj7Ozs169f9+/fPzk5\nWWpvDNq0adMSExNDQkJiY2N1dHSOHj0q9Q0sUwt0siRHR0eF/SYWi8+fP29ra2tlZSU/Wk1N\njY+Pj7u7e2Vl5Y8//lhbW7ts2TL6rZUrV544cWLq1KnBwcHdunUrKChISEjQ1dXdsGEDYXEd\nyTliYydU/hFl4vP5+/fvz8/PZy5PlsdasWJFRkZGVFSUQCBwcXH5559/tm3bVl5eLvWUqpwI\n9D5A0dHRjx49cnZ2HjBggOQHFy9enJWV5eHhMX369A4dOmRlZVVWVkquwMYyAcb78NUEAADw\nfsKECgAAAHxQKIqS2vo4IyOjQ4cOPXr04BJWcolwpd25c4f87w94jY2N9fX1JX/++U4SYzRT\n7wG0XhcvXrx48SL9Wl9fv1u3bjNmzJgzZ84nn3zCMkJcXFxubu6GDRuYHby7du363XffRURE\nbNy4MSQkxNPT8+LFi6tWrTp06JBQKDQxMZk6deqyZcuY7wofH5+cnJyYmJgff/zxxYsXenp6\nDg4OW7Zs+fzzz1u4jZcvX758+bLMIEZGRu3bt4+IiOjVq9eaNWuk3u3Tp8/y5cu/++67JUuW\nsFmmSQ4HBwcej3fmzBmmhN59fd68eTLru7i49OnT55dffqH3vVi1atXx48f379+voaFhZWW1\nevXquXPnMnt3E0ISExMTEhIiIyPLyspsbW2TkpImTZokPyUtLa29e/fOmDFj586dOTk5OTk5\n6urqn376qbe394QJE8aPHy8ZX9KgQYOSkpJiYmLGjRunr6/v5eV1/Pjxnj171tTUNHasK1eu\ntEAnS1JXV1fYb3/88UdJSYn89SHpSbuUlJTIyMgVK1aUl5fb2Njs3r3b39+frtCxY8e8vLzl\ny5fv3r27tLTU0NBw5MiRERER9D9ACq+jxo4r54TKP6JMw4cP79SpU1lZ2RdffNGkY5mYmFy+\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q6vHjx01MTBQUFDgRcnNzL168SH1+//59\nVVUV50zysLCwQYMGJSYmenh4sFgsHx8fXV3d+/fvnz17VlVV9fDhwzLvzr///e8pU6bs3Lkz\nLS1t9uzZ2traTU1Njx49+umnn969e7dnzx7O+yL//ve/2Wz28ePHhw8fPnny5OHDh3d2dj57\n9iwvL+/Nmzfjxo377rvvODtr9UQf/f39k5KSQkND4+LilJSUzp07V1BQwNkSiqOtrc3T03Pm\nzJnNzc2HDh1qb2/fuHEjf7Tw8PCcnJy5c+cGBQVpaWn9/PPPbW1t3KeqiNkchVoEio2NffLk\niYODgzRnwHQLnU4/ceLEuHHj5s+fX1xcrK6uvmnTpqysrG3btlVXVzs6Oj5//vzAgQMNDQ0r\nVqyQYbvR0dGZmZl+fn4rVqwYMWLE06dPExISlJWV9+zZQ1VYu3Ztbm6ui4vLl19+OWjQoNzc\n3ObmZsmOOemdHgEAAAB0FxZUAAAAAAAARJCXl8/Nzd28efOFCxdOnDhBp9OHDBmyZcuW5cuX\nU2due3l5HTlyZOfOnV9//fXgwYN9fX2joqLS0tI459IXFBRwv7NSU1PD+RoYGDho0CA3N7df\nfvll8+bNP/zwQ1NTk5aWlp+f38aNG01NTWXeHQMDg6KiosTExPPnz58+ffrVq1cMBsPAwMDX\n1zc4OJjFYnFqKigopKamLly48MiRI/n5+fn5+fLy8oMHD/bw8PDy8nJ1deU+crwn+mhjY5OS\nkrJz587Zs2erqqq6u7tfuHDBzMysra2NqkAd2nHy5MmYmJhNmzY1NDQMHTr06NGjPj4+/NE+\n/fTTU6dObdmyJT4+XkVFxdXV9Ztvvhk0aJD4zXFzc3ObO3dudnb248ePDx061GsLKoSQ4cOH\n7927NzAwcNGiRenp6VpaWrdu3YqJicnMzExNTVVWVp48eXJ6evqECRNk2Kiurm5hYWFUVNTR\no0fr6uqYTKaTk1NkZOSoUaOoCjNnzkxLS9u6deuePXvU1NRcXV13795tYWEhwTk0vdMjAAAA\ngO6iyfYYQwAAAAAAkIxHwj3pg5xdOk7I1YNGamypj0nXj0uKXr5IyiBfxyemn/nvzbxS0VWF\n+vnONifWWimD6Btq5BbtkjIIv9evX6upqbm5uXFvkQQfIHl5eRaLdfPmzb5OBAAAAAA+dDhD\nBQAAAAAAQFpHjx6dMmXK3bt3OSUpKSmEEHt7+z7LCQAAAAAAZApbfgEAAAAAfCymbv9G+jfU\n/ztYd+2u/VIGGWtjx1B56eJpJWWcgcwBW+O/lDKIQn+6lBEIIWZmZjdv3nRxcQkODtbV1f31\n118PHTpkaGi4aJG0b/MAAAAAAMAHAgsqAAAAAAAfixsRK6Xf8mvgzsRNq5ZIGSR6b9KPZ6oL\n8h5IGcd2svnXq1KlDKJvOMjzM1spg0ycOPHq1atbt25NSEh4+fKllpaWv7//5s2b1dXVpYwM\nAAAAAAAfCGz5BQAAAAAAIAN2dnbZ2dkvXrxob2+vrKw8cuSIrq5uXydFCCE+Pj40Gq2mpqaX\n2/3+++/19fXl5eXDwsJ6ueluef/+vcgDVHp6DKn4lZWVPRRfIHl5eRsbm95sUTJ9dQMDAAAA\n8MOCCgAAAAAAAK/S0lIajebs7CzDmC9fvlyzZo2RkZGCgoKxsbGHhwfPc/zGxsaVK1cOGTKE\nwWDo6uoGBgZWV1dL366lpeWMGTMUFBTErB8bG1tWViZlo69evQoMDGxqatq8efOMGTOkjNb7\neAahu2PY02QyR32lu8l/aIMPAAAAHzMsqAAAAAAAAPS4//73v+PGjdu9e/eYMWPWrVtnZ2eX\nlZU1derU33//narQ3t7+ySef7N27l8Vibdq0aebMmceOHbOzs3v58qWUTYeHh1+6dGngwIHi\nVK6uro6IiJD+Yf3jx49bWlrmz58fERExbdo0KaP1Mv5B6NYY9jRZzVGfkCD5D2rwAQAA4COH\nM1QAAAAAAAB6XGRk5NOnT/ft27ds2TKqZM6cOXPnzg0PD8/KyiKEJCQk3Lt3b8eOHWvXrqUq\nzJgx47PPPtu6deuuXbt6Lc/bt2/LJE5rayshREVFRSbRepmsBqGHfODpCfe3Th4AAAAAb6gA\nAAAAAACI1tbWFhcXN3bsWDU1NRUVFQsLi7i4uM7OTk6FrKysCRMmKCkp6ejohISEtLS0GBgY\njBs3jrpKp9M/+eSTxYsXc+p7enoqKio+ePCA+nrs2DEVFZWQkBBOhX/961+mpqapqalsNlua\nzLmPoJg3bx6NRmtqalq3bt2QIUMUFBQMDAzi4+OpJlxcXNzd3QkhM2fOpNFo+fn5VIQXL14s\nXbrUyMiIwWBoamp6eHhwPxan4tfW1k6fPl1RUfH8+fPOzs4ODg6EkB07dtBotKCgIMniUOXl\n5eUBAQF6enoMBkNDQ8PNza2wsJDzK+E96oqQ2RQ4CPxj2NjYuHjxYm1tbSUlJRsbm8LCwubm\n5pUrV+rp6SkrK0+aNOnevXuc5lxcXKifcErev39Po9G6enensLDQ09NTQ0ODwWAMGTLEz8/v\n6dOnnFASzBEhJDs729raWlFRUUtLKzAwkDsZgTw9PWk0WnV1dWBgoLa2toKCwsiRI5OSkqSZ\nL2luMHFuYAAAAICehjdUAAAAAAAARAsODj569Oi8efOCg4NpNNrly5fXrl1bXl6+f/9+Qsj1\n69fd3d01NTXDw8M1NDTS09N9fHzevHmjp6dH/Tw+Pp4nYHt7+/v37/X19Qkhra2tv//++5Qp\nU3gOirC3t09JSXny5ImJiYlMesFgMAghXl5exsbGJ0+e7OzsjI6ODg0NVVdXDwgI2LBhA5PJ\nTE1NjYyMtLKyMjMzI4TU1dVNnDixsbExKCho9OjRFRUViYmJDg4Oly9fdnR05MRctWoVnU6P\njIw0MTGJiopydHRcv379nDlz/Pz8jI2NJYtDCKmoqJgwYUJzc3NwcLC5uXlVVVViYuLkyZOv\nXLlib28vskcSzKbAQeAfQ29vbwcHh0uXLhUXFwcFBXl7e1tYWJibm58/f/7p06eBgYGzZs2q\nqKig0+ndnaO7d+86OjoymcyQkBAdHZ2//vorISHhp59+KikpGTRokGRzlJ+f7+bmpq2tHRkZ\nqampmZub6+bm1q+fsH9hSd2KHh4eU6dO/fHHHzs7O2NiYpYsWUKn0wMDAyWbL8mS5x/87k43\nAAAAgKxgQQUAAAAAAEC0U6dO2dranjhxgvq6ePHi0NDQZ8+edXR0yMnJbdmypaOj48KFCywW\ni7o6ffr0V69eCQl48ODBd+/e+fj4EEIqKio6OjoMDAx46hgZGRFC/vrrL1ktqMjLyxNCmEwm\n51WDpKSkoUOHZmRkBAQE2NjY5OTkEEJsbW2dnZ2pClFRUVVVVQUFBVTXCCG+vr7m5uZr1qyh\nXiOg1gzq6+svXrzIeUbf0dFBCBk2bJiHh4c0cTZu3FhbW5uRkeHp6UmVeHp6jhkzJiwsrKCg\nQGSPuhoHIbMpcBD4x3DYsGGRkZGEECsrq+zs7NOnT0+YMCE2NpYQYm1tnZeXt3fv3tu3b0+a\nNEmsieFSWFhoZma2e/fuKVOmUCV6enrLly9PS0tbtmyZZHO0devWjo6Os2fPjh8/nhASGBi4\ndOnSvLw8kckMHTqU6hQhJD09XVtbe+vWrdSCigTzJVny3CSbbgAAAABZwZZfAAAAAAAAotHp\n9PLy8traWk7Jnj17zpw5IycnRwjJy8sbOXIk54mwnJzcunXrhETLzc0NCwuzt7entsN68+YN\nIWTAgAE81ZSVlTlXZWjBggWczyYmJkpKSpWVlQJrstns9PR0CwsLfX39mv+h0+mTJk26c+dO\nU1MTIYRGo1ExhbzxIFkcNpt99uxZbW1tzqoMIWTUqFG2trY3b95saGiQoEcU4bMpjjlz5nA+\nDxs2jBBCbWZFGTFiBCGkurpazGjcgoOD7969S62mvHv3rrW1lXqTg7PrFw+RY9vZ2Zmbmzt0\n6FBqNYWyaNEicZKhFvwoampqDg4OT58+pfolzXyJn7zArLo73QAAAACygjdUAAAAAAAARIuJ\niQkJCRk2bJi7u/vUqVM//fRTznZejY2Nra2tpqam3PWFvJqQlpYWEBAwevToc+fOUf/inkI9\noeZGnQzBX041Gh4ezvlqamq6Zs0aMftiaGjI/ZVOp797905gzdra2vr6+vr6+sGDB/Nfffbs\nGWdHLGoJoSuSxampqXn16pW1tTXPCIwYMSI/P/+PP/6wtbUV3qOuRknIbIqJuz41idwl1Nsb\nXY2qSKmpqYcPHy4uLuY5dkVgZZFjq6am1tLSwvOS08iRI8XJZPjw4dxfqT7W1NRw2pJsvsRP\nnn/LNdKdGxgAAABAtrCgAgAAAAAAINqKFStGjx69b9++jIyM1NRUGo02c+bMxMREIyMj6p/e\nKykpcddXUVHhf92BzWZv2rQpJibG2dn59OnTKioqVLmqqioR9CbK69evqVD8+TQ1NR08eJDz\n1c7OTvwFFfEP9qBSsrS03L59O/9VXV1dzmc1NTWZx3n79i0R9OKOoqIi5yqlqx51NUpCZlNI\nL7jxtyjBcSkCrV+/fvv27SwWKz4+3tjYWEFB4cGDB9QuWwKJHNu6ujpCSP/+/bnL+/fvL3Ch\njgfPXU3NBfcyj2TzJX7yArOS1VADAAAAdBcWVAAAAAAAAMTi5OTk5OTU1taWl5d3/PjxY8eO\nTZs27cGDB9Tj3dbWVu7Kzc3N1DkiHGw2OzAwMDk5efny5fHx8dzLLYaGhvLy8uXl5Twt/vnn\nn+R/O0rx0NfXp95f6VGctRyBp4n0dBxqxzP+B/FUicB1Jh5CRqmr2aSOPe9p7e3tAstbW1u/\n+eYbAwODa9euUd0nhAg/jEfk2FIbZ/Hcn01NTeLcPzyDT2UyaNAggZUlmC9Z3WAAAAAAvQNn\nqAAAAAAAAHSDgoLCtGnTUlJSgoKCysrKioqKdHR0+vXrx7MccuvWLZ4frlq1Kjk5edu2bd9+\n+y3PyysMBsPa2rqwsLC5uZlTSB19YWBgwLPBUW/S1tbW0NAoLS3lfimBEEK99NDTcXR0dJhM\n5sOHD3ke/ZeUlNBoNOGbjImJfzalj8mPfwewJ0+eCKxZU1PT0tLCYrE4qymEkNzcXCHBRY6t\njo4Og8HgabG4uFiczB8+fMj99fHjx4QQgdtzEYnmS1Y3GAAAAEDvwIIKAAAAAACACDdv3tTT\n0zt27Bh3IXUWN51OZzAYLBaruLi4tLSUutTR0bFjxw7uyhkZGXv37g0JCYmIiBDYxMKFC5ub\nm+Pi4jglhw4dev78uZC9nnoCtdLT0tLCKfH29m5tbeVOrK6uzsLCwtXVtVuRJYszZ86c6urq\nc+fOcUqKiooKCwudnJzU1dW7lQCH8NkkggZBStQKBPfiBE/rHNra2jQajfv8+aKiIqoy5xWT\n7s6RvLz8pEmTysrKbt++zamQkJAgTubJycmcz3/88cft27dHjBihqanZVX2R89VzNxgAAABA\nL8CWXwAAAAAAACKwWCwmk7lo0aL8/HxLS0sajXbnzp2UlBR7e3tLS0tCSFhYmLe396xZs5Ys\nWaKqqnr8+HETExMFBQVOhLVr1xJCOjs7uc9Ip6xbt27gwIFffvllamrqpk2bfv3113Hjxj18\n+PDUqVNjxowR/2QUmaCOLo+NjX3y5ImDg8P48eM3bdqUlZW1bdu26upqR0fH58+fHzhwoKGh\nYcWKFd2KLFmc6OjozMxMPz+/FStWjBgx4unTpwkJCcrKynv27JG4jyJnk38QJG6L4u/vn5SU\nFBoaGhcXp6SkdO7cuYKCAoFbYCkqKs6ePTszMzMoKGjKlCklJSX79+8/ceKEm5tbVlZWWlqa\nm5ubBHO0du3a3NxcFxeXL7/8ctCgQbm5uc3NzcKPvaG0tbW5urq6uLh0dnbu3LmTzWZHRkYK\nqS9yvnruBgMAAADoBVhQAQAAAAAAEEFeXj43N3fz5s0XLlw4ceIEnU4fMmTIli1bli9fTp3s\n7eXldeTIkZ07d3799deDBw/29fWNiopKS0vjbO1FnYayb98+/uBBQUEDBw6Uk5PLzs6Ojo5O\nT0/Pzs7W0tJasmRJTEwMz6ngPc3NzW3u3LnZ2dmPHz8+dOjQ+PHjtbS0bt26FRMTk5mZmZqa\nqqysPHny5PT09AkTJnQrsmRxdHV1CwsLo6Kijh49WldXx2QynZycIiMjR40aJXEfRc4m/yBI\n3BbFxsYmJSVl586ds2fPVlVVdXd3v3DhgpmZWVtbG3/l5OTklStXZmRknDx50tra+vz58/b2\n9hs3boyLiwsNDZ06daoEczRz5sy0tLStW7fu2bNHTU3N1dV19+7dFhYWXR3lwpGUlJSQkBAT\nE1NfX29qapqSkjJv3jwh9UXOV8/dYAAAAAC9gNYLxxgCAAAAAIBIHgn3pA9yduk4IVdTjNTY\n//eYdAkM3Jn49VJpN6GK3pv045nqgrwHUsb5+W78J6yNUgbRNxyUWxQrZRB+r1+/VlNTc3Nz\n497+CODvwsfH59SpUxUVFfr6+n2dCwAAAMCHAmeoAAAAAAAASOvo0aNTpky5e/cupyQlJYUQ\nYm9v32c5AQAAAACATGHLLwAAAACAj8WohO+kf0PdeMTIk6mnpAxiyLLRH9ow78spUsbR1hm4\n/+hKKYMoKTGkjEAIMTMzu3nzpouLS3BwsK6u7q+//nro0CFDQ8NFixZJHxwAAAAAAD4EWFAB\nAAAAAPhY7A1a0Cn1ll9hew+eCQ2SMsicnfu/OfmoIK9Yyji5dw+FBKRLGUTPUP1akbSrMhMn\nTrx69erWrVsTEhJevnyppaXl7++/efNmdXV1KSMDAAAAAMAHAlt+AQAAAAAAyICdnV12dvaL\nFy/a29srKyuPHDmiq6sr/s99fHxoNFplZaU0OVBBampqpAnyN229K/Ly8jY2NtTnwMBAGo1W\nVlbWQ219mCMgXFc33smTJ9lstmwPUJHyJuf+OfdQy+RvBwAAAEAceEMFAAAAAACgS/Ly8h3/\ne63n66+/3rJlS9/mI5ylpWVjY6OCgkLvNBcbG+vl5WVqatonrX+AMAK9BkMNAAAAfQJvqAAA\nAAAAAHQpJCQkJCRk5syZfZ2IWMLDwy9dujRw4MBeaKu6ujoiIoL7bY/ebP3DhBHoNRhqAAAA\n6BN4QwUAAAAAAKBLu3fvJoScPHny4sWLfZ3Lh+X27dt9nQIAAAAAQK/CGyoAAAAAAADdVlhY\n6OnpqaGhwWAwhgwZ4ufn9/TpU87VefPm0Wi0xsbGxYsXa2trKykp2djYFBYWNjc3r1y5Uk9P\nT1lZedKkSffu3ZNtVtwHS7i4uFA5cK6+f/+eRqNNmzaNO8mmpqZ169YNGTJEQUHBwMAgPj6e\nzWZzflJTUxMYGKinpzdgwICxY8fu3bv3/fv3VHB3d3dCyMyZM2k0Wn5+PuE7QaS8vDwgIEBP\nT4/BYGhoaLi5uRUWFvIMkfDW+QkfdkJIdna2tbW1oqKilpZWYGAgd/c5+vXrt2PHDhMTEwUF\nBUNDw82bN3M3+uLFi6VLlxoZGTEYDE1NTQ8PD+6lo7a2tri4uLFjx6qpqamoqFhYWMTFxXV2\ndvKPf0+MgGT3lfA0eAjvPun6liBi3HLdbUsIIcfVdHZ2zp07t1+/fsePH5e+IQAAAABueEMF\nAAAAAACge+7evevo6MhkMkNCQnR0dP7666+EhISffvqppKRk0KBBhBAGg0EI8fb2dnBwuHTp\nUnFxcVBQkLe3t4WFhbm5+fnz558+fRoYGDhr1qyKigo6nd4nvaCS9PLyMjY2PnnyZGdnZ3R0\ndGhoqLq6ekBAACGkrq6OxWI1NTX5+/sbGRnl5OSsXLny999/P3z48IYNG5hMZmpqamRkpJWV\nlZmZGU/wioqKCRMmNDc3BwcHm5ubV1VVJSYmTp48+cqVK/b29uK0zk/ksOfn57u5uWlra0dG\nRmpqaubm5rq5ufXrx/vvCLds2VJUVPTVV1/Jycnt27cvMjLS1NT0888/p7o8ceLExsbGoP+P\nvbuPhzL7/wd+JoaISBgbUiRFK6GWSsrqxiZ3Zdcqqm36RoUi3WijdKd0v27a3ZLuVqkkSdmP\n3czSkrY+aje2m8+WaEl8ViU3xczvj+ux85vPzLjmMoNqez3/mrmuc51z3udcc/XoOs45QUEj\nRoyorKxMSkpycnLKzc11dnYmhAQHBx86dMjf3z84OJjFYuXm5q5cubKioiIhIaEHWkCO+0pm\nNUTJDJ/mlqC71aSRWZbcVqxYkZGRsWPHjjlz5nRrQQAAAPAewoAKAAAAAABA55SUlFhaWu7c\nuXPixInUEUNDw5CQkLS0tKVLlxJClJWVCSHm5ubR0dGEkFGjRuXk5KSnp48ZMyYuLo4QYmdn\nV1BQsHfv3mvXro0dO/aNREFVUkdHJzk5mTqSnJxsZmaWkZFBvdCPiYl5/Phxbm7ulClTCCER\nERHu7u4HDx5cvny5g4NDfn4+IcTR0XHatGmSma9bt662tjYjI8Pb25s64u3t/eGHH0ZGRhYV\nFTEpXZLMZt+8eXN7e3tmZubo0aMJIVwud8mSJQUFBWL53Lt37+rVq9R4w8cff2xnZ3fixAlq\nQIUKuaioyN7enko8Z84cKyurFStWUHMaTp486ejoePz4cersokWLwsPDHz161N7erqSk1N0t\nIMd9JbMaomSGT3NLWFlZSa1zR2SWJZ/ExMTdu3dHRkZGRER0a0EAAADwfsKSXwAAAAAAAJ0T\nHBx8/fp16rX+69evW1paqCkaYstP+fj4CD+bm5sTQqhlsigWFhaEkOrq6p6occfmzp0r/Gxq\naqqurl5VVUUIEQgE6enpxsbGkydPFibYt2/fjz/+yOFw6PMUCASZmZkcDsfLy0t4cPjw4Y6O\njsXFxfX19TJLl4q+2fl8Po/HMzMzo0ZTKAsXLpTMJyIiQjgraNSoUUpKSn/++SdV7VOnTllb\nWxsZGdX8jc1mjx079pdffmlsbCSEsNnsioqK2tpaYW67du06ffq02GhKN7UAhfl9xbwaTMJX\n5JYQw6Sp5XD+/PmwsLDAwMBt27Z1a0EAAADw3sIMFQAAAAAAgE47evTogQMHbt26JbZjhGga\nQ0ND4WdqboHoEeqd/uvXr2WW1dDQsHr1auHXIUOGrFixQoG6/4+BAweKfmWz2VSVqqur6+vr\nbW1tWSyW8KypqampqanMPGtqap49e2ZnZyd6LSHEwsKisLDw7t27jo6O9KV3hKbZq6urm5ub\nxao3bNgwyUyoQQgKi8XS0NBobm4mhNTW1tbV1dXV1X3wwQeSVz169MjS0jI2NjYsLMzc3NzT\n03PSpElTpkwR7dMeaAHSmfuKeTWYhK+trS33LSGGSVN3Ns/r16/Pnj3bwcHh4MGDwhp2R0EA\nAADwPsOACgAAAAAAQOdERUVt3brV3t5+9+7dgwcPVlVVvX37NpfLFUsmuTmKfNulNDY2fv31\n18Kv48aN68IBlY6qRI0xqKqqypHny5cvCSF9+vQRO66mpiY8S1+6VPTN3tTURAjp3bu36CW9\ne/cWG0sgHQf14sULQoiNjc3WrVslzw4YMIAQEhoaOmLEiK+++iojI+Po0aMsFsvNzS0pKcnE\nxEQ0cTe1QEeXdJQJ82oQBuFTM1rkuyXEMGnqzgoICHj58uVvv/1WVVU1aNCg7isIAAAA3mcY\nUAEAAAAAAJBBIBAQQqjtzVtaWvbs2WNsbHz58mUNDQ0qwbNnz7qvdCMjI6oCCnr16hXzxAYG\nBoQQ0YkgzFHNIva+XnhEU1NTjjxlNjs1SNDS0iJ6FbVQFcMihBWTuiuMkIuLi4uLS2tra0FB\nwbFjx44cOeLq6nr79m1qx3hKd7SAHDpVDZnhU8M2nbolOrrlGDZ1pzg4OCxZssTHx2f27Nk/\n/fQTtQhbdxQEAAAA7zPsoQIAAAAAAPA/vvrqKysrq8uXLwuPUDtS6OjoEEJqamqam5vt7e2F\nr/UJITwer+frSU9ySbEHDx4wv7xPnz56enrl5eWiOdy5cychIeH27dv01xoYGOjo6JSXl4sN\nZpSVlbFYLGqTj86S2ewGBgYqKipiMd66dYt5ERwOR1dX9/fffxcbM3j69KlkYlVVVVdX19TU\n1KCgoPv375eWloqe7Y4WkEOnqiEzfJm3BPNbrlNNzVBKSoqnp+fKlSt//vnnDRs2dF9BAAAA\n8D7DgAoAAAAAAMD/6NevX1lZWXx8PJ/PJ4S8evXq2LFjhJAJEyYQQjgcDovFEt1/vrS09MiR\nI0RiesSbRW0aUV5eLjxCVZI5T0/P+vr6w4cPC4+sX78+JCSktbWVEELNAKBWBpPk4+NTXV19\n7tw54ZHS0tKSkhIXFxdtbe1OVYMis9mVlZXHjh17//79a9euCdMkJiZ2qhRfX9+Wlpb4+Hjh\nkadPn1pbW8+YMYMQUlxcbGhoKNaM1LwlyUW3urwF5NOpatCHT2TdEp265WSWJZ/Y2Fh7e/st\nW7YUFBR0a0EAAADwfsKSXwAAAAAAAP/js88+271798WLF21tbR0dHX/66aeysjJfX19bW1tC\niJqa2vTp07Ozs4OCgiZOnFhWVpaQkHD8+HEPD48LFy6kpaV5eHi86QgIISQwMDA5OTk8PDw+\nPl5dXf3cuXNFRUWdWmwqJiYmOzs7ODj45s2bJiYmPB4vOzs7MDCQagdqK/K4uLgHDx44OTmN\nHj1a9NoNGzZkZ2cHBASEhoZaWFg8fPgwMTFRQ0Nj165d8oXDpNlXrlzJ4/Hc3d2/+OKL/v37\n83i8pqYmLS0t5qWsX7/+woULW7Zsqa6udnZ2/vPPP/fv319fXx8aGkoIsbe319HRWbhwYWFh\noY2NDYvF+uWXX1JTU8ePH29jYyPWmMX4AAAgAElEQVSWVZe3gHw6VQ368ImsW6JTt5zMsuTD\nZrOPHz9ua2s7e/bsW7duaWtrd1NBAAAA8H7CDBUAAAAAAID/wWazf/jhhxUrVrx48SIlJeXl\ny5dbt25NS0sTJkhJSfH398/IyAgKCrpy5UpWVpabm9u6desaGhrCw8OpfbDfOAcHh9TU1Obm\n5unTp1MTC86fP6+pqUlNJmDCyMiouLjYz88vPT09KiqqrKxs586dKSkp1FkPD4+ZM2f++uuv\nmzZtqqioELt2wIABJSUlvr6+hw4dWrBgQWJioouLy9WrV62treWOSGazu7m5paWlcTicXbt2\nbd++XV9f/8yZM3379mW+eYy+vv7Vq1eDg4Pz8vK4XO727dttbGwKCwsnT55MCFFWVubxeIsX\nL/7xxx8jIyPXrFlz/fr1TZs2Xbx4kcVi9UALyKFT1aAPn8i6JTp1y8ksS25Dhw7du3dvZWXl\nwoULu7UgAAAAeA+xumRvQwAAAAAAUJBX4g3FM8lcYktz1t9Ii9/ermARkXu/Ph0epGAmPtsT\ndp64U1TQif0tpOJd/2aK/TcKZmI4UPty6TIFM3lL+Pn5nTx5srq6mtpSHgAAAAAAuhCW/AIA\nAAAAeF/oGZsoPqCioq7ez9hEwUx6a2rq6Wsbm3AUzIfNZhub9FMwE86Avgrm8Pb466+/CCHq\n6upvuiIAAAAAAP9AGFABAAAAAHhfBAXMFxBFZ6gLjAdr+gYqmEmfYSNcX/W3HGGqYD7a/TQ+\nnTdcwUw0+6opmMPb4Pr167m5uTwez8TEpG/ff84QEQAAAADA2wMDKgAAAAAA74ub29YLFJ6h\nohzXf+u6KAUz0e7X/9zZ+4ov+eXmMTZ+Q6aCmRgN7O8/30nBTN64vLy8L7/80szMLCEh4U3X\nBQAAAADgnwmb0gMAAAAAAMjJz8+PxWJVVVXJnaCrrFq1is/n37t3b+rUqTLLpc7W1NSIpeyx\n2jLHvHrdWnnRFlMkB9FAJNsfeh6T9v/uu++MjIyUlZUjIyO7tRq4JSShNQAA4G2DARUAAAAA\nAABxx44dY7FY69evFzt+8uRJJSWlMWPGPH/+vKvKev369Zo1a5SUlOzt7bsqT3o2NjZTp05V\nVVXtmeLeRXFxcffv3xd+7doWez/bX6xJ3xXPnj3jcrmNjY0bN26kRiu7Q1fdEj354PpH6vmn\nMQAAvHMwoAIAAAAAAMBIdnZ2QEDAhx9+mJub21X7lJSXlzs4OCQmJnZJbgytXr360qVL/fr1\n68lC3yHV1dVr1qwRffvftS32Hra/ZJO+K+7du9fc3Dx79uw1a9a4urp2Uyndekt0x4PrH+mN\nPI0BAOCdgwEVAAAAAAAA2X788UdfX19zc/N//etfXfXe8/nz53Z2dr169bpx4wabze6SPEFx\n165de9NV+Kd5d5u0paWFEKKpqfmmKyKn7nhw/SPhaQwAAAxhQAUAAAAAAECG4uJiT09PY2Pj\nvLw8PT09qWmotf5ra2snT56spqaWlZUlmYbP58+cObNXr17Hjh0jhLS1tS1evPjnn38eMmRI\nt9ZfrFyGO4I8efJkyZIlJiYmKioqenp6Xl5eoq/FmcRLqamp4XK5hoaGffr0GTly5N69e9va\n2hiWIjeZ2XZUK3d3d09PT0KIm5sbi8UqLCwk/9ti/v7+LBarsbFx1apVgwYNUlVVNTY23r17\nt0AgYFg3mvYX6ykmgUjNXLJf5G4QJpd7e3uzWKzq6moul8vhcFRVVYcNG5acnEydldqkhJCK\nior58+cbGhqqqKjo6up6eHiUlJTIDERMa2trfHz8yJEjtbS0NDU1ra2t4+Pj+Xy+sGgWi9XQ\n0CBM39bWxmKxxOaavHr1KiIiwtDQkKp5UlISdXzatGlOTk6EkG3btrFYrKCgIOp4SUmJt7e3\nrq6uiorKoEGDAgICHj58KMyNukMaGhoWLVrE4XDU1dUdHBxKSkqampqWLVtmaGiooaExduzY\nGzduiAUrdks4OTkpKSlVVlaKHqyvr2ez2Y6OjlJbQwyTB1dH5IiCyLpP5MuTdNxBTApleCP1\n2NMYAADedcpvugIAAAAAAABvtZs3b7q5ufXv3/+HH3744IMPOkqmoqJCCFm+fDmbzY6OjjY1\nNZVMs2LFioyMjB07dsyZM4cQoqOjs2PHju6reUflMvH06dOPPvqooaEhKChoxIgRlZWVSUlJ\nTk5Oubm5zs7OhFm8VD729vaNjY2BgYEmJib5+fnLli379ddfDxw4wKQU+cjMlqZWX375pY6O\nztGjR6Ojo0eNGmVpaSmWORX4rFmzBg8efOLECT6fv2HDhvDwcG1t7fnz58tdZ4pYT8nRPlL7\nRZEGYXI5tfmHl5fXpEmTzp49y+fzY2NjFy9ezGazuVyu1CatrKwcM2ZMU1NTcHCwlZXV48eP\nk5KSJkyYkJeXN378+I4CkRQcHHzo0CF/f//g4GAWi5Wbm7ty5cqKioqEhATmzR4aGvr8+fOl\nS5e2tLQcO3ZsyZIlKioqXC43JibG2dk5KirKx8cnICBg8ODBhJDr1687Ozvr6OiEhYUZGBj8\n8ccfiYmJ33//fVlZWf/+/YU19/X1dXJyunTp0q1bt4KCgnx9fa2tra2srLKysh4+fMjlcj/5\n5JPKykqayRBcLrewsPDIkSNr164VHjxz5kxbW9u8efNkBsXwwdUROaJg+NCQo2U66iDmhcq8\nkXrsaQwAAO86DKgAAAAAAAB06M6dO1OmTOnTp8+PP/5obGxMk5J6/VdXV3fx4sVevaQsBpCY\nmLh79+7IyMiIiIjuqq408pUbExPz+PHjoqIi4ebMc+bMsbKyWrFiBfXX3zLjFc0nNzd3ypQp\nhJCIiAh3d/eDBw8uX77cyspKZinykZktTa0cHBzy8/MJIY6OjtOmTZPMXFlZmRCio6MjnIGR\nnJxsZmaWkZGh4ICKZE/J0T5S+0WRBmHeTWZmZnFxcdTnU6dOcTiczZs3c7lcqU26bt262tra\njIwMb29v6oi3t/eHH34YGRlZVFTUUSCSTp486ejoePz4cerrokWLwsPDHz161N7erqSkxLDl\nnz9/np+fT5XyxRdfDB06dMuWLVwu19HRsb29nRBibm7u5eVFJS4pKbG0tNy5c+fEiROpI4aG\nhiEhIWlpaUuXLiV/3yHm5ubR0dGEkFGjRuXk5KSnp48ZM4ZqHzs7u4KCgr179167dm3s2LEd\n1crX1zcsLOzw4cOiAyrp6em9e/f28/Ojj4j5g6sjckQh8z6Ru2U66iAmhTK8kQAAABjCvyUA\nAAAAAADSVVRUuLq61tbWDhgwYMCAAfSJWSwWIWTu3LlS39mdP38+LCwsMDBw27Zt3VLXDshX\nrkAgOHXqlLW1tZGRUc3f2Gz22LFjf/nll8bGRiIrXmE+6enpxsbGkydPFh7ct2/fjz/+yOFw\nmJQiB5nZ0teKYSlz584VfjY1NVVXV6+qqpKvwhTJnpKvfST7RcEGYV4N0bf8WlpaTk5ODx8+\nrK6ulqykQCDIzMzkcDjCUQpCyPDhwx0dHYuLi+vr66UGIhWbza6oqKitrRUe2bVr1+nTp5mP\nphBCgoKChKWYmJiMGzfuwYMHYmttCQUHB1+/fp0aTXn9+nVLSws150Z01S9CiI+Pj/Czubk5\nIYRa94xiYWFBCJHaOELq6uqff/75vXv3rly5Qh15+vRpfn6+t7e3lpYWzYWdenDRYx4F8/tE\njpbpqIO66kkFAADAHGaoAAAAAAAASJeamjpixAgPD4+kpKT58+enpaXJvIR6Gyjm+vXrs2fP\ndnBwOHjwIPV2Tz4NDQ2rV68Wfh0yZMiKFSto0stdbm1tbV1dXV1dndSVgh49eiRcCEtqvELV\n1dX19fW2traipZuamlKr7jx58oRhKZ0is/La2to0tWJo4MCBol/ZbPbr169J5/uIIrWnmPeC\nJNF+UbBBmHfT0KFDRU8ZGhoSQmpqaiQvrKmpefbsmZ2dndhtaWFhUVhYePfuXeEeIfQ3GCEk\nNjY2LCzM3Nzc09Nz0qRJU6ZMocrtFGtra9Gvpqamly9frqio6Ghux9GjRw8cOHDr1i2x3VlE\n04hWg5qZIXqEmjZB3TM0uFzu/v37U1NTx40bRwg5c+ZMe3u7zIlQcjy4OsI8Cua3qxwt01EH\nqaiodMmTCgAAgDkMqAAAAAAAAEg3ZcqUs2fPqqmp1dTUnDhxYtiwYTExMfSXSP3L8YCAgJcv\nX/72229VVVWDBg2Suz6NjY1ff/218Ou4cePoX9bLXe6LFy8IITY2Nlu3bpU8K/o37/R/Kd/c\n3Ez+3mBDkVI6RWa21ASIjmrFUEdbX3S2jyhSe0qR9hHtFwUbhHk11NXVRU/16dOHECI65CD0\n8uVLYQJRampqwrOSgUgVGho6YsSIr776KiMj4+jRoywWy83NLSkpycTEhP5CUX379hX9SgXS\n0tIiNXFUVNTWrVvt7e137949ePBgVVXV27dvU8tPiZK8Q2i2S+mInZ3dqFGj0tPT9+3bp6am\nRk0k+vjjj+mvkuPB1RHmUTC/T+RomY46qKueVAAAAMxhQAUAAAAAAEA6R0dH6s3d4cOH7969\nu2HDhuHDh3/66aedzcfBwWHJkiU+Pj6zZ8/+6aefOrUYkSgjIyOBQNAD5WpqalIfpG4iwpyB\ngQHp4JV6F5bS2Wypt7cd1UpBne0jitSe6qr2UbBBmFdDdCCEEPLs2TNCCLVPuxgNDQ3J9MIj\nwhIZcnFxcXFxaW1tLSgoOHbs2JEjR1xdXW/fvk3tRi7m1atXkgepkT+hpqYmIjE+RGlpadmz\nZ4+xsfHly5epKMjfkXaTBQsWLF269MKFC+PHj+fxeGvWrJG5dFVXPbg6pZt+zpSOOqhbCwUA\nAJAKK0gCAAAAAADIoKGhkZWVpaOjM2/ePDk2S09JSfH09Fy5cuXPP/+8YcOG7qhh15bL4XB0\ndXV///13sZfsT58+7VQF+vTpo6enV15eLrqAz507dxISEm7fvt1VpXS28vS1UqRouUntqa5q\nHwUbhHk1ysvLRb/eu3ePECJ1LSYDAwMdHZ3y8nKxwaeysjIWiyXf6kyqqqqurq6pqalBQUH3\n798vLS0l0taPevDggeS1YjX/z3/+QwiRugRcTU1Nc3Ozvb29cDSFEMLj8eSoMEOzZ89WU1M7\nefLkyZMn+Xz+vHnzmF+r4IOrU7rp50zpqIO6tVAAAACpMKACAAAAAAAg2+DBg9PT01+/fu3p\n6Snf9uOxsbH29vZbtmwpKCjo8up1ebm+vr4tLS3x8fHCI0+fPrW2tp4xY0anSvf09Kyvrz98\n+LDwyPr160NCQlpbW7uwlM5Wnr5W1AQRsT+K7wGSPdVV7aNggzCsRkpKivDz3bt3r127ZmFh\noaenR6Q1qY+PT3V19blz54RHSktLS0pKXFxctLW1GcZVXFxsaGh45MgR0YPUBA5qKIUazhF9\nHS+WWLLmVVVVP//8s6WlJTW/SgyHw2GxWKL7z5eWllJ5drREmIK0tbV9fHxycnJSU1PHjx8/\nZMiQTl0u9cH16tWr0tLS+/fvd21Vu+nnTGg7qPsKBQAAkApLfgEAAAAAADDi4uKya9eu0NBQ\nDw+PgoICyR0g6LHZ7OPHj9va2s6ePfvWrVva2to8Hu/ixYvU2ba2tsePHwv3M4+MjJS6VpIc\nJMtlctX69esvXLiwZcuW6upqZ2fnP//8c//+/fX19aGhoZ0qPSYmJjs7Ozg4+ObNmyYmJjwe\nLzs7OzAw0NbWtgtL6Wzl6WtFTU2Ii4t78OCBk5PT6NGjFakMc5I91VXto2CDMKxGa2vrjBkz\n3N3d+Xz+9u3bBQJBdHQ0dUqySTds2JCdnR0QEBAaGmphYfHw4cPExEQNDY1du3Yxj8ve3l5H\nR2fhwoWFhYU2NjYsFuuXX36hBh5sbGwIIYGBgcnJyeHh4fHx8erq6ufOnSsqKpJcUqy1tdXb\n29vNza2pqembb7559erVunXrpJaopqY2ffr07OzsoKCgiRMnlpWVJSQkHD9+3MPD48KFC2lp\naR4eHszrzxCXyz1+/HhpaemBAwfkuFzywfXo0aNRo0aNGzeusLCwC+vZTT9nQttBXVVozzyN\nAQDgHwADKgAAAAAAAEyFhITcvHnz4MGDAQEBZ86c6ezlQ4cO3bt3L5fLXbhw4alTp4qKirZt\n2yY8W1NTI/zK5XK78BWeWLlMLtHX17969WpsbGx2dvbRo0c1NDQmTJhw6tSpMWPGdKpoIyOj\n4uLiL7/8Mj09/a+//jI2Nt65c2dYWFjXltLZytPXysPDY+bMmTk5Offu3fvmm296bECFSPRU\nV7WPgg3CsBrJycmJiYmxsbF1dXVDhgxJTU319/enTkk26YABA0pKSmJiYg4dOvT06VMdHR0X\nF5fo6Ojhw4czj0tZWZnH423cuPH8+fPHjx9ns9mDBg3atGlTSEgIi8UihDg4OKSmpm7fvn36\n9Ol9+/b19PQ8f/68paUlNfOG/D2t5MSJE7GxsevXr6+vrzczMzt06JCfn19HhaakpCxbtiwj\nI+PEiRN2dnZZWVnjx49ft25dfHx8eHj4pEmTmNefoYkTJw4cOLCurk7ufVCkPrhk7sXSWd3x\nc5bZQV1VaI89jQEA4F3HkmO7PAAAAAAA6HJeiTcUzyRziS3N2RMmWoL2dgWLUI5LjFi0QMFM\ntiV8fe7s/aKCWwrmw7v+rav9JgUzMRrYP790o4KZALzP/Pz8Tp48WVlZaWRk9Kbr8g9UWVlp\nZma2YMGC5OTkrsozJSUlKysrMzOzqzIEAAB4T2CGCgAAAADA+8LE6zMi4Cuay8BB3n7+CuZh\naj7UaaKmwQeK/s2vRl91z08VmspACNHpryE7EQDAGxIREUEIWb58eRfmmZOTM27cuC7MEAAA\n4D2BARUAAAAAgPeF5gcfCPiKDqi0qavrGBgqWhNtbZ3+TR8M0FMwn96qKpwPFB0O0dJWVzAH\nAIAud//+/e+///7cuXPff/99TEzM0KFDuyrn5uZma2vrhQsXdlWGAAAA7w8MqAAAAAAAvC/u\nJO1WfMmvV0Zme+O3yU5Hy9TULOfcA8WX/PosYMrXe3MUzMRooO6isE8UzAQAoGvdunVr6dKl\nurq6W7ZsEW6Q3iXU1NSio6O7MEMAAID3RxdvQQYAAAAAAPBe8fPzY7FYVVVVb7oib6/vvvvO\nyMhIWVk5MjKym4qgeqGmpoagRzqgrKzs4ODQTZmfOHFCIBDQb6Ai2kf/DJ2KSI7wfXx8+Hx+\nbW3tmjVrWCyWvNUEAACAroQBFQAAAAAAAHHHjh1jsVi9e/e+e/eu5NkhQ4bY2Nh0SUGpqaks\naTZt2qRgzsxDoFKuX7+ePisxqqqqpqamCxcufPDgAU01nj17xuVyGxsbN27cOHXqVMVi6pCN\njc3UqVNVVVW7I3OBQHD69GkvL68BAwaoqqrq6+vb29tv3rz5yZMnUtOvWLGCxWJpa2s3NzeL\nnWLekmIpVVRUDAwMpkyZsnfv3mfPnnVHmN2tW/uoS8TFxd2/f595+k5F1N3hd9+TBAAAAERh\nyS8AAAAAAADpWltbFy9enJeX131FNDQ0EEI+//zzgQMHih7vqv2iuzCEcePGjR8/Xvj1r7/+\nunbt2oEDB06dOlVYWDhixAipV927d6+5uXn+/Plr1qxRvA4dWb16ddeuiSTU0NDg6+ubl5en\nrq7+8ccfm5iY1NfXl5SUfPnll3v37j1z5oyTk5No+levXh0+fLhXr17Pnj07depUYGCgZJ7M\nW1KY8tWrV48fPy4oKPjXv/61devWY8eOubq6dke83af7+qhLVFdXr1mzxsbGZsiQIQwv6VRE\n3R1+dz9JAAAAgIIBFQAAAAAAAOmcnJx++OGHY8eOzZkzp5uKoF6DhoeH29vbd0f+XRiCq6ur\n5CyWHTt2REZGRkVFZWVlSb2qpaWFEKKpqalg6W/K7Nmz8/LyPD09v/32Wz09Peogn8//5ptv\nli5d6unp+fvvv+vr6wvTnzlzpq6ubvHixcnJyd9++63UARXmLSmWsr29PTU1NTQ01MPDg8fj\njR49uusCfd9du3btTVdBId39JAEAAAAKlvwCAAAAAACQLiIiwsTEJCIi4q+//mKSntomoba2\ndvLkyWpqasI34zU1NVwu19DQsE+fPiNHjty7d29bWxt1inoNqq2t/ZaE0FmhoaEqKipXrlyR\nenbatGnUBI5t27axWKygoCDqeElJibe3t66uroqKyqBBgwICAh4+fCi8yt/fn8ViNTQ0LFq0\niMPhqKurOzg4lJSUNDU1LVu2zNDQUENDY+zYsTdu3BBeInWDCicnJyUlpcrKStGD9fX1bDbb\n0dGRSXSXLl3KycmxtbU9ffq0cDSFENKrV6+goKDY2FhbW9v//Oc/opd88803hJBly5aNHz++\nsLCwvLycSUFEVktSlJSUFixYcPjw4ebm5tDQUJqUOTk5dnZ2ampq+vr6XC6Xus1EVVRUzJ8/\n39DQUEVFRVdX18PDo6SkRHhWji4gsrpVtI+o/BsbG1etWjVo0CBVVVVjY+Pdu3cLBAKaoGh+\nRwwj6qhEd3d3T09PQoibmxuLxSosLOzyiDob/oULF8aMGaOurm5gYBAWFtb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FTkSuQmCC"
          },
          "metadata": {
            "image/png": {
              "width": 1080,
              "height": 480
            }
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "identical(invisible(row_order(h_main)),invisible(row_order(h_category)))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 173
        },
        "id": "e2HRKXFQezN3",
        "outputId": "5620de4a-1f17-47e9-806b-12a1c273176e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Warning message:\n",
            "“The heatmap has not been initialized. You might have different results\n",
            "if you repeatedly execute this function, e.g. when row_km/column_km was\n",
            "set. It is more suggested to do as `ht = draw(ht); row_order(ht)`.”\n",
            "Warning message:\n",
            "“The heatmap has not been initialized. You might have different results\n",
            "if you repeatedly execute this function, e.g. when row_km/column_km was\n",
            "set. It is more suggested to do as `ht = draw(ht); row_order(ht)`.”\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "TRUE"
            ],
            "text/markdown": "TRUE",
            "text/latex": "TRUE",
            "text/plain": [
              "[1] TRUE"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Heatmap of metabolic genes"
      ],
      "metadata": {
        "id": "MRS9IcDShkDI"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Prepare data"
      ],
      "metadata": {
        "id": "DoNLzX07h2TM"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# read gene names\n",
        "mg <- read.csv('/content/Metabolic_genes.csv')\n",
        "mg$Function <- str_trim(mg$Function) # trim white space\n",
        "mg$Function <- gsub(\"(^|[[:space:]])([[:alpha:]])\", \"\\\\1\\\\U\\\\2\", mg$Function,perl = TRUE) # Capitalize first letter \n",
        "mg <- mg %>% distinct(.keep_all = TRUE)  \n",
        "# get gene annotations\n",
        "gene_annotations <- getBM(\n",
        "    attributes = c('external_gene_name','description'),\n",
        "    filters = \"external_gene_name\", \n",
        "    values = mg$Gene,\n",
        "    mart = mouse) %>% \n",
        "    rename(Gene = external_gene_name) %>% \n",
        "    mutate(Gene_annot = gsub(\"\\\\[[^\\\\]]*\\\\]\", \"\", description, perl=TRUE)) %>%\n",
        "    select(-c('description'))\n",
        "# get gene expression columns\n",
        "res2 <- res %>% \n",
        "  select(symbol, padj, log2FoldChange, color_label, Low_dose_rep_1, Low_dose_rep_2,\tHigh_dose_rep_1,\tHigh_dose_rep_2) %>% \n",
        "  rename(Gene = symbol)\n",
        "# join 3 parts \n",
        "mg <- mg %>% \n",
        "  left_join(gene_annotations, by = 'Gene') %>%\n",
        "  left_join(res2, by = 'Gene') %>%\n",
        "  arrange(Gene)\n",
        "mg <- mg %>%\n",
        "  mutate(Gene_name = paste(Gene, Gene_annot, sep = ' - ')) \n",
        "rownames(mg) <- mg$Gene_name"
      ],
      "metadata": {
        "id": "ggu-ojfHwO9-"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Prepare Heatmaps"
      ],
      "metadata": {
        "id": "WHTmlUktiSTf"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Main heatmap\n",
        "y1 <- mg %>% select(contains('dose')) \n",
        "\n",
        "h_up_main <- Heatmap(\n",
        "  y1 %>% t() %>% scale() %>% t(),\n",
        "  row_split = factor(mg$Function, levels = c(\"Fatty Acid Oxidation/Synthesis\",\"Glycolysis\",\"TCA Cycle\")),\n",
        "  cluster_rows      = FALSE, \n",
        "  cluster_columns   = FALSE,\n",
        "  show_column_dend  = FALSE,\n",
        "  show_row_dend     = FALSE,\n",
        "  show_column_names = FALSE,\n",
        "  col = cell_cols, # defined in previous heatmaps\n",
        "  width = unit(22, \"mm\"),\n",
        "  top_annotation = dose_annotation, # defined in previous heatmaps\n",
        "  heatmap_legend_param = list(direction = \"horizontal\", title = \"Scaled Expression Value\"),\n",
        "  rect_gp = gpar(col = \"white\", lwd = 0.5)) # white border \n",
        "\n",
        "# Color block for function groups on the left \n",
        "\n",
        "# Function annotation colors\n",
        "func_cols = c(\n",
        "  'TCA Cycle' = \"#4297A0\", #teal green\n",
        "  'Fatty Acid Oxidation/Synthesis' = \"#EFE7D3\", #ivory\n",
        "  'Glycolysis' = \"#E57F84\") #coral                      \n",
        "\n",
        "h_up_functions <- Heatmap(\n",
        "  mg$Function, \n",
        "  row_split = factor(mg$Function, levels = c(\"Fatty Acid Oxidation/Synthesis\",\"Glycolysis\",\"TCA Cycle\")),\n",
        "  name = \" \", \n",
        "  width = unit(5, \"mm\"), \n",
        "  heatmap_legend_param = list(title = \"Metabolic Pathways\"),\n",
        "  col = func_cols)"
      ],
      "metadata": {
        "id": "s2xEhxX0mhfX"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Set plot size\n",
        "options(repr.plot.width = 15, repr.plot.height = 8)\n",
        "#par(mar=c(0,0,4,0)) # bottom, left, top , right\n",
        "\n",
        "h_up = h_up_functions + h_up_main \n",
        "draw(h_up, \n",
        "  heatmap_legend_side = \"left\", \n",
        "  annotation_legend_side = \"left\", \n",
        "  merge_legend = TRUE,\n",
        "  #legend_grouping = \"original\",\n",
        "  padding = unit(c(2, 3, 5, 2), \"mm\"))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 497
        },
        "id": "RS18-nxxpHfC",
        "outputId": "bb963980-d75e-4b97-ba8b-5d401b7f6a28"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "plot without title"
            ],
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9Clps5+FvNBRqMn9Nuz/aJESrMe1nPu6Loru7dLpLQ+tiPNrIdc3f+TRErT6dlr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\n4dHR0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KysrKioiBOrqqpwiUwmE4+W4uFRLvBTlgih2tpaPDba0NDQ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\nLy+PyLN8+XJ3d3c9PT1JScnr168T6Tdu3EAIjRs3jp9iy8rK0tPT8bs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G7//v2fPHly7do1+LkCfnhvwzaIpR7tsNUt7dq/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\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YgjRRwW4iLEQYj79/84CHGRlLyRI5Vy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\nwsKPPvpoz549a9eu3b1bpSdqmQoMp6beAwB0p5MnT2L/xGazBQJ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gSiK+85bnt7hf1CP0NvZoTlLEd3xfvXoVGBg4a9asRYsW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09u/fz3xXRUWFq8D4lC58u0mu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\nzddff92lDtEVbNiwobu0Dtjb23/yyScMBkOBeb548YLFY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