1.data-exploration/4.cell_line_summary_figure.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "d9832fdc-4f3b-470f-bc79-6fcb43509905",
   "metadata": {},
   "source": [
    "## Create a single, two-panel figure summarizing the DepMap dataset\n",
    "\n",
    "| Panel | Description | Importance | Plot type |\n",
    "| :---: | :---------: | :--------: | :-------: |\n",
    "| A     | Distribution of ages | How many pediatric vs adult cancers | Histogram |\n",
    "| B     | Distribution of pediatric cancer types by sex | View how many pediatric cancer types of each | Bar |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c5dde536-0c91-4bac-a466-272b1efb0532",
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "“package ‘ggplot2’ was built under R version 4.2.3”\n",
      "Warning message:\n",
      "“package ‘cowplot’ was built under R version 4.2.3”\n"
     ]
    }
   ],
   "source": [
    "suppressPackageStartupMessages(library(dplyr))\n",
    "suppressPackageStartupMessages(library(ggplot2))\n",
    "suppressPackageStartupMessages(library(cowplot))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8cc03047-3549-46d9-9747-bf2db793733b",
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "# Set i/o paths and files\n",
    "data_dir <- file.path(\"../0.data-download/data\")\n",
    "fig_dir <- file.path(\"figures\")\n",
    "\n",
    "model_input_file <- file.path(data_dir, \"Model.parquet\")\n",
    "crispr_input_file <- file.path(data_dir, \"CRISPRGeneEffect.parquet\")\n",
    "\n",
    "figure_output_file <- file.path(fig_dir, \"age_and_ped_model_distributions.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6d82be0c-403a-431e-be76-6521384e2d18",
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "# Set figure sizes\n",
    "text_size = 9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "898ada53-a6b0-4776-a24c-5c14cd75b19e",
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "ename": "ERROR",
     "evalue": "Error: 'read_parquet' is not an exported object from 'namespace:readr'\n",
     "output_type": "error",
     "traceback": [
      "Error: 'read_parquet' is not an exported object from 'namespace:readr'\nTraceback:\n"
     ]
    }
   ],
   "source": [
    "# Process dataset\n",
    "model_df <- readr::read_parquet(\n",
    "    model_input_file,\n",
    "    col_types = readr::cols(\n",
    "        .default = \"c\",\n",
    "        Age = \"d\"\n",
    "    )\n",
    ")\n",
    "\n",
    "print(dim(model_df))\n",
    "\n",
    "crispr_df <- readr::read_parquet(\n",
    "    crispr_input_file,\n",
    "    col_types = readr::cols(\n",
    "        .default = \"d\",\n",
    "        ModelID = \"c\"\n",
    "    )\n",
    ")\n",
    "\n",
    "print(dim(crispr_df))\n",
    "\n",
    "# Get common depmap identifiers\n",
    "common_depmap_ids <- intersect(model_df$ModelID, crispr_df$ModelID)\n",
    "\n",
    "# Subset the model dataframe to only those we have dependency data for\n",
    "model_df <- model_df %>%\n",
    "    dplyr::filter(ModelID %in% common_depmap_ids)\n",
    "\n",
    "# The updated dimensions should be the same as crispr_df\n",
    "print(dim(model_df))\n",
    "\n",
    "# Show model_df\n",
    "head(model_df, 3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2e484fa0-3804-43d2-8854-cf959a4b30b4",
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "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>'ModelID'</li><li>'PatientID'</li><li>'CellLineName'</li><li>'StrippedCellLineName'</li><li>'DepmapModelType'</li><li>'OncotreeLineage'</li><li>'OncotreePrimaryDisease'</li><li>'OncotreeSubtype'</li><li>'OncotreeCode'</li><li>'LegacyMolecularSubtype'</li><li>'LegacySubSubtype'</li><li>'PatientMolecularSubtype'</li><li>'RRID'</li><li>'Age'</li><li>'AgeCategory'</li><li>'Sex'</li><li>'PatientRace'</li><li>'PrimaryOrMetastasis'</li><li>'SampleCollectionSite'</li><li>'SourceType'</li><li>'SourceDetail'</li><li>'CatalogNumber'</li><li>'PatientTreatmentStatus'</li><li>'PatientTreatmentType'</li><li>'PatientTreatmentDetails'</li><li>'Stage'</li><li>'StagingSystem'</li><li>'PatientTumorGrade'</li><li>'PatientTreatmentResponse'</li><li>'GrowthPattern'</li><li>'OnboardedMedia'</li><li>'FormulationID'</li><li>'PlateCoating'</li><li>'EngineeredModel'</li><li>'TissueOrigin'</li><li>'ModelDerivationMaterial'</li><li>'PublicComments'</li><li>'CCLEName'</li><li>'HCMIID'</li><li>'WTSIMasterCellID'</li><li>'SangerModelID'</li><li>'COSMICID'</li><li>'DateSharedIndbGaP'</li></ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'ModelID'\n",
       "\\item 'PatientID'\n",
       "\\item 'CellLineName'\n",
       "\\item 'StrippedCellLineName'\n",
       "\\item 'DepmapModelType'\n",
       "\\item 'OncotreeLineage'\n",
       "\\item 'OncotreePrimaryDisease'\n",
       "\\item 'OncotreeSubtype'\n",
       "\\item 'OncotreeCode'\n",
       "\\item 'LegacyMolecularSubtype'\n",
       "\\item 'LegacySubSubtype'\n",
       "\\item 'PatientMolecularSubtype'\n",
       "\\item 'RRID'\n",
       "\\item 'Age'\n",
       "\\item 'AgeCategory'\n",
       "\\item 'Sex'\n",
       "\\item 'PatientRace'\n",
       "\\item 'PrimaryOrMetastasis'\n",
       "\\item 'SampleCollectionSite'\n",
       "\\item 'SourceType'\n",
       "\\item 'SourceDetail'\n",
       "\\item 'CatalogNumber'\n",
       "\\item 'PatientTreatmentStatus'\n",
       "\\item 'PatientTreatmentType'\n",
       "\\item 'PatientTreatmentDetails'\n",
       "\\item 'Stage'\n",
       "\\item 'StagingSystem'\n",
       "\\item 'PatientTumorGrade'\n",
       "\\item 'PatientTreatmentResponse'\n",
       "\\item 'GrowthPattern'\n",
       "\\item 'OnboardedMedia'\n",
       "\\item 'FormulationID'\n",
       "\\item 'PlateCoating'\n",
       "\\item 'EngineeredModel'\n",
       "\\item 'TissueOrigin'\n",
       "\\item 'ModelDerivationMaterial'\n",
       "\\item 'PublicComments'\n",
       "\\item 'CCLEName'\n",
       "\\item 'HCMIID'\n",
       "\\item 'WTSIMasterCellID'\n",
       "\\item 'SangerModelID'\n",
       "\\item 'COSMICID'\n",
       "\\item 'DateSharedIndbGaP'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'ModelID'\n",
       "2. 'PatientID'\n",
       "3. 'CellLineName'\n",
       "4. 'StrippedCellLineName'\n",
       "5. 'DepmapModelType'\n",
       "6. 'OncotreeLineage'\n",
       "7. 'OncotreePrimaryDisease'\n",
       "8. 'OncotreeSubtype'\n",
       "9. 'OncotreeCode'\n",
       "10. 'LegacyMolecularSubtype'\n",
       "11. 'LegacySubSubtype'\n",
       "12. 'PatientMolecularSubtype'\n",
       "13. 'RRID'\n",
       "14. 'Age'\n",
       "15. 'AgeCategory'\n",
       "16. 'Sex'\n",
       "17. 'PatientRace'\n",
       "18. 'PrimaryOrMetastasis'\n",
       "19. 'SampleCollectionSite'\n",
       "20. 'SourceType'\n",
       "21. 'SourceDetail'\n",
       "22. 'CatalogNumber'\n",
       "23. 'PatientTreatmentStatus'\n",
       "24. 'PatientTreatmentType'\n",
       "25. 'PatientTreatmentDetails'\n",
       "26. 'Stage'\n",
       "27. 'StagingSystem'\n",
       "28. 'PatientTumorGrade'\n",
       "29. 'PatientTreatmentResponse'\n",
       "30. 'GrowthPattern'\n",
       "31. 'OnboardedMedia'\n",
       "32. 'FormulationID'\n",
       "33. 'PlateCoating'\n",
       "34. 'EngineeredModel'\n",
       "35. 'TissueOrigin'\n",
       "36. 'ModelDerivationMaterial'\n",
       "37. 'PublicComments'\n",
       "38. 'CCLEName'\n",
       "39. 'HCMIID'\n",
       "40. 'WTSIMasterCellID'\n",
       "41. 'SangerModelID'\n",
       "42. 'COSMICID'\n",
       "43. 'DateSharedIndbGaP'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       " [1] \"ModelID\"                  \"PatientID\"               \n",
       " [3] \"CellLineName\"             \"StrippedCellLineName\"    \n",
       " [5] \"DepmapModelType\"          \"OncotreeLineage\"         \n",
       " [7] \"OncotreePrimaryDisease\"   \"OncotreeSubtype\"         \n",
       " [9] \"OncotreeCode\"             \"LegacyMolecularSubtype\"  \n",
       "[11] \"LegacySubSubtype\"         \"PatientMolecularSubtype\" \n",
       "[13] \"RRID\"                     \"Age\"                     \n",
       "[15] \"AgeCategory\"              \"Sex\"                     \n",
       "[17] \"PatientRace\"              \"PrimaryOrMetastasis\"     \n",
       "[19] \"SampleCollectionSite\"     \"SourceType\"              \n",
       "[21] \"SourceDetail\"             \"CatalogNumber\"           \n",
       "[23] \"PatientTreatmentStatus\"   \"PatientTreatmentType\"    \n",
       "[25] \"PatientTreatmentDetails\"  \"Stage\"                   \n",
       "[27] \"StagingSystem\"            \"PatientTumorGrade\"       \n",
       "[29] \"PatientTreatmentResponse\" \"GrowthPattern\"           \n",
       "[31] \"OnboardedMedia\"           \"FormulationID\"           \n",
       "[33] \"PlateCoating\"             \"EngineeredModel\"         \n",
       "[35] \"TissueOrigin\"             \"ModelDerivationMaterial\" \n",
       "[37] \"PublicComments\"           \"CCLEName\"                \n",
       "[39] \"HCMIID\"                   \"WTSIMasterCellID\"        \n",
       "[41] \"SangerModelID\"            \"COSMICID\"                \n",
       "[43] \"DateSharedIndbGaP\"       "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "colnames(model_df)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "55b244cd-b371-4cd7-b119-f59b2779dfab",
   "metadata": {},
   "source": [
    "## Age distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "48a15988-9454-4f66-839d-83b4df51ddcb",
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[22m`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.\n",
      "Warning message:\n",
      "“\u001b[1m\u001b[22mRemoved 217 rows containing non-finite outside the scale range (`stat_bin()`).”\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "age_distrib_gg = (\n",
    "    ggplot(model_df, aes(x = Age))\n",
    "    + geom_histogram()\n",
    "    + theme_bw()\n",
    "    + theme(\n",
    "        axis.text = element_text(size = text_size),\n",
    "        axis.title = element_text(size = text_size + 1)\n",
    "    )\n",
    ")\n",
    "\n",
    "age_distrib_gg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6a0b6d08-d080-49f6-85a2-605780777597",
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "# Subset to pediatric cancers only\n",
    "ped_model_df <- model_df %>%\n",
    "    dplyr::filter(AgeCategory == \"Pediatric\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a9073ea2-d3b5-4393-bc27-69ee0692f4d0",
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "                                                                                      Neuroblastoma \n",
       "                                                                                                 35 \n",
       "                                                                                      Ewing Sarcoma \n",
       "                                                                                                 15 \n",
       "                                                                                    Embryonal Tumor \n",
       "                                                                                                 14 \n",
       "                                                                                   Rhabdomyosarcoma \n",
       "                                                                                                 13 \n",
       "                                                                                       Osteosarcoma \n",
       "                                                                                                 11 \n",
       "                                                                  B-Lymphoblastic Leukemia/Lymphoma \n",
       "                                                                                                 10 \n",
       "                                                                                    Rhabdoid Cancer \n",
       "                                                                                                  9 \n",
       "                                                                             Acute Myeloid Leukemia \n",
       "                                                                                                  7 \n",
       "                                                                          Mature T and NK Neoplasms \n",
       "                                                                                                  6 \n",
       "                                                                            Mature B-Cell Neoplasms \n",
       "                                                                                                  5 \n",
       "                                                                  T-Lymphoblastic Leukemia/Lymphoma \n",
       "                                                                                                  3 \n",
       "                                                                                   Synovial Sarcoma \n",
       "                                                                                                  3 \n",
       "                                                                                     Retinoblastoma \n",
       "                                                                                                  2 \n",
       "                                                                               Renal Cell Carcinoma \n",
       "                                                                                                  2 \n",
       "                                                                                     Hepatoblastoma \n",
       "                                                                                                  2 \n",
       "Undifferentiated Pleomorphic Sarcoma/Malignant Fibrous Histiocytoma/High-Grade Spindle Cell Sarcoma \n",
       "                                                                                                  1 \n",
       "                                                                            Ovarian Germ Cell Tumor \n",
       "                                                                                                  1 \n",
       "                                                                       Myeloproliferative Neoplasms \n",
       "                                                                                                  1 \n",
       "                                                                                           Melanoma \n",
       "                                                                                                  1 \n",
       "                                                                                Epithelioid Sarcoma \n",
       "                                                                                                  1 \n",
       "                                                                                     Diffuse Glioma \n",
       "                                                                                                  1 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rev(sort(table(ped_model_df$OncotreePrimaryDisease)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "84cf2f21-e7d5-4043-b2f6-0566dd3b3344",
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "disease_type_recode <- ped_model_df$OncotreePrimaryDisease %>%\n",
    "    dplyr::recode(\n",
    "        `Diffuse Glioma` = \"Other/Rare (13 unique)\",\n",
    "        `Epithelioid Sarcoma` = \"Other/Rare (13 unique)\",\n",
    "        `Melanoma` = \"Other/Rare (13 unique)\",\n",
    "        `Myeloproliferative Neoplasms` = \"Other/Rare (13 unique)\",\n",
    "        `Ovarian Epithelial Tumor` = \"Other/Rare (13 unique)\",\n",
    "        `Ovarian Germ Cell Tumor` = \"Other/Rare (13 unique)\",\n",
    "        `Undifferentiated Pleomorphic Sarcoma/Malignant Fibrous Histiocytoma/High-Grade Spindle Cell Sarcoma` = \"Other/Rare (13 unique)\",\n",
    "        `Hepatoblastoma` = \"Other/Rare (13 unique)\",\n",
    "        `Renal Cell Carcinoma` = \"Other/Rare (13 unique)\",\n",
    "        `Retinoblastoma` = \"Other/Rare (13 unique)\",\n",
    "        `Rhabdoid Cancer` = \"Other/Rare (13 unique)\",\n",
    "        `Synovial Sarcoma` = \"Other/Rare (13 unique)\",\n",
    "        `T-Lymphoblastic Leukemia/Lymphoma` = \"Other/Rare (13 unique)\",\n",
    "        `B-Lymphoblastic Leukemia/Lymphoma` = \"B-ALL\"\n",
    "    )\n",
    "\n",
    "ped_model_df <- ped_model_df %>%\n",
    "    dplyr::mutate(disease_type_recoded = disease_type_recode)\n",
    "\n",
    "ped_model_df$disease_type_recoded <- factor(\n",
    "    ped_model_df$disease_type_recoded,\n",
    "    levels = names(sort(rev(table(ped_model_df$disease_type_recoded))))\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c2fbafb4-eac4-4638-9497-0f4a61801efd",
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "“\u001b[1m\u001b[22mA numeric `legend.position` argument in `theme()` was deprecated in ggplot2\n",
      "3.5.0.\n",
      "\u001b[36mℹ\u001b[39m Please use the `legend.position.inside` argument of `theme()` instead.”\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cancer_type_distrib_gg = (\n",
    "    ggplot(ped_model_df, aes(x = disease_type_recoded))\n",
    "    + geom_bar(aes(fill = Sex), position = \"stack\")\n",
    "    + coord_flip()\n",
    "    + theme_bw()\n",
    "    + geom_text(\n",
    "        stat = \"count\",\n",
    "        aes(label = after_stat(count)),\n",
    "        vjust = 0.5,\n",
    "        hjust = -0.25,\n",
    "        size = 3\n",
    "    )\n",
    "    + scale_fill_manual(\n",
    "        values = c(\n",
    "            \"Male\" = \"#90CAF9\",\n",
    "            \"Female\" = \"pink\",\n",
    "            \"Unknown\" = \"black\"\n",
    "        )\n",
    "    )\n",
    "    + ylim(c(0, 40))\n",
    "    + theme(\n",
    "        axis.text = element_text(size = text_size),\n",
    "        axis.title = element_text(size = text_size + 1),\n",
    "        legend.text = element_text(size = text_size - 2),\n",
    "        legend.title = element_text(size = text_size - 1),\n",
    "        legend.position = c(0.75, 0.3),\n",
    "        legend.key.size = unit(0.3, 'cm')\n",
    "    )\n",
    "    + labs(y = \"Pediatric Count\", x = \"\")\n",
    "    + guides(fill = guide_legend(override.aes = list(size = 0.5)))\n",
    ")\n",
    "\n",
    "cancer_type_distrib_gg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "08e39982-65f1-46be-b6ae-09093a784af4",
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[22m`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.\n",
      "Warning message:\n",
      "“\u001b[1m\u001b[22mRemoved 217 rows containing non-finite outside the scale range (`stat_bin()`).”\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "full_gg <- cowplot::plot_grid(\n",
    "    age_distrib_gg,\n",
    "    cancer_type_distrib_gg,\n",
    "    labels = c(\"A\", \"B\"),\n",
    "    ncol = 2,\n",
    "    rel_widths = c(0.45, 1)\n",
    ")\n",
    "\n",
    "ggsave(figure_output_file, full_gg, width = 4.75, height = 1.75, dpi = 500)\n",
    "\n",
    "full_gg"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "4.2.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}