example_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "S8t3TTkY2SoL"
   },
   "source": [
    "# Example analysis notebook - single cell studies database\n",
    "\n",
    "This notebook produces figures in the manuscript `A curated database reveals trends in single cell transcriptomics`\n",
    "\n",
    "Notebook repository: https://github.com/vals/single-cell-studies/\n",
    "\n",
    "The database is available at: https://www.nxn.se/single-cell-studies/\n",
    "\n",
    "Running this notebook will save the following figures in the current folder:\n",
    "```\n",
    "all_studies.pdf\n",
    "biorxiv_over_time.pdf\n",
    "cells_per_month.pdf\n",
    "clustering_over_time.pdf\n",
    "clusters_per_cells.pdf\n",
    "pseudotime_over_time.pdf\n",
    "scrnaseq_studies.pdf\n",
    "studies_over_time.pdf\n",
    "techniques_over_time.pdf\n",
    "tsne_over_time.pdf\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "Tchw8PpC2SoO"
   },
   "outputs": [],
   "source": [
    "# %pylab inline\n",
    "# %config InlineBackend.figure_format = 'retina'\n",
    "\n",
    "import io\n",
    "\n",
    "import matplotlib.font_manager\n",
    "from mizani.breaks import date_breaks\n",
    "from mizani.formatters import date_format\n",
    "\n",
    "# Only pandas >= v0.25.0 supports column names with spaces in queries\n",
    "import pandas as pd\n",
    "ts = pd.Timestamp  # Alias for pd.Timestamp\n",
    "import plotnine as p\n",
    "import requests\n",
    "import numpy as np\n",
    "import statsmodels.api as sm\n",
    "import statsmodels.formula.api as smf\n",
    "\n",
    "import warnings\n",
    "import matplotlib.colors as mplcol\n",
    "import colorsys\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")  # plotnine has a lot of MatplotlibDeprecationWarning's"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "lN_eZ5Jz2SoX",
    "outputId": "61038cf2-096b-4359-8907-7a139aa663a2"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1035, 27)\n"
     ]
    }
   ],
   "source": [
    "url = \"http://nxn.se/single-cell-studies/data.tsv\"\n",
    "df = pd.read_csv(url, sep='\\t')\n",
    "\n",
    "# converts string to date format, can only be run once!\n",
    "df['Date'] = pd.to_datetime(df['Date'], format='%Y%m%d')\n",
    "\n",
    "# converts string of reported cells total to float, can only be run once!\n",
    "df['Reported cells total'] = df['Reported cells total'].str.replace(',', '').map(float)\n",
    "\n",
    "print(df.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 295
    },
    "colab_type": "code",
    "id": "vfYNyZeT2Sof",
    "outputId": "03107d87-23cb-40e6-ac88-648f79887403",
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "findfont: Font family ['Arial'] not found. Falling back to DejaVu Sans.\n",
      "findfont: Font family ['Arial'] not found. Falling back to DejaVu Sans.\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<ggplot: (8747085252798)>\n"
     ]
    }
   ],
   "source": [
    "# plot number of studies over time\n",
    "p.options.figure_size = (9, 2)\n",
    "fig = (\n",
    "    p.ggplot(p.aes(x='Date', y='DOI'), data=df.resample('1M', on='Date').count()[['DOI']].reset_index())\n",
    "    + p.geom_bar(stat='identity')\n",
    "    + p.theme_minimal(base_family='Arial')\n",
    "    + p.scale_x_datetime(breaks=date_breaks('1 years'), labels=date_format('%Y'))\n",
    "    + p.labs(y='Number of studies')\n",
    ")\n",
    "fig.save('studies_over_time.pdf')\n",
    "print(fig)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "plKbXOwB2Sok"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 102
    },
    "colab_type": "code",
    "id": "ydNxXc9f2Soo",
    "outputId": "75150e87-964f-4dcc-b7bd-f6927d17ee57"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Chromium': 'Chromium',\n",
       " 'Drop-seq': 'Drop-seq',\n",
       " 'InDrops': 'InDrops',\n",
       " 'SMARTer (C1)': 'SMARTer (C1)',\n",
       " 'Smart-seq2': 'Smart-seq2'}"
      ]
     },
     "execution_count": 4,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tdf = df.assign(Technique = df['Technique'].str.split(' & ')).explode('Technique')\n",
    "\n",
    "# Technique dictionary for top 5 techniques\n",
    "t_dict = {k: k for k in tdf['Technique'].value_counts().head(5).index}\n",
    "\n",
    "t_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "pUD3GRo02Sos"
   },
   "outputs": [],
   "source": [
    "# Maps remaining techniques to 'Other'.\n",
    "tdf['Technique'] = tdf['Technique'].map(lambda s: t_dict.get(s, 'Other'))\n",
    "\n",
    "# list of techniques in alphabetic order for the plot with 'Other' at the end.\n",
    "techs = list(\n",
    "    tdf['Technique']\n",
    "    .value_counts()\n",
    "    .sort_index()\n",
    "    .index\n",
    "    .difference(['Other'])\n",
    ")\n",
    "techs.append('Other')\n",
    "\n",
    "tdf['Technique'] = (\n",
    "    pd.Categorical(\n",
    "       tdf['Technique'],\n",
    "        categories=techs,\n",
    "\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "nXT1mpSH2Sox"
   },
   "outputs": [],
   "source": [
    "def lightness(color, lightness):\n",
    "    '''Proportionally modulate color.\n",
    "    '''\n",
    "    rgb = mplcol.colorConverter.to_rgb(color)\n",
    "    h, l, s = colorsys.rgb_to_hls(*rgb)\n",
    "    l = lightness\n",
    "    new_color = colorsys.hls_to_rgb(h, l, s)\n",
    "    hex_color = '#{:02x}{:02x}{:02x}'.format(*map(lambda c: int(c * 255), new_color))\n",
    "\n",
    "    return hex_color\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 286
    },
    "colab_type": "code",
    "id": "B6er8Owr2Soy",
    "outputId": "ae013a8c-4c06-4b5e-989a-3970aac56de2",
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (-9223363289799617820)>"
      ]
     },
     "execution_count": 8,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Lighten matplotlib default colors\n",
    "clrs = list(map(lambda c: lightness(c, 0.8), ['C0', 'C1', 'C2', 'C3', 'C4', 'grey']))\n",
    "\n",
    "# Plot number of studies per month by technique\n",
    "per_month = (\n",
    "    tdf\n",
    "    .groupby('Technique')\n",
    "    .resample('1M', on='Date')\n",
    "    .count()['DOI']\n",
    "    .reset_index()\n",
    ")\n",
    "\n",
    "p.options.figure_size = (9, 2)\n",
    "fig = (\n",
    "    p.ggplot(\n",
    "        p.aes(x='Date', y='DOI', fill='Technique'),\n",
    "        data=per_month.query('Date > @ts(\"20130101T010101\")')\n",
    "    )\n",
    "    + p.geom_bar(stat='identity', color='grey')\n",
    "    + p.theme_minimal(base_family='Arial')\n",
    "    + p.scale_x_datetime(\n",
    "        breaks=date_breaks('1 years'),\n",
    "        labels=date_format('%Y')\n",
    "    )\n",
    "    + p.labs(y='Number of studies')\n",
    "    + p.scale_fill_manual(clrs)\n",
    ")\n",
    "fig.save('techniques_over_time.pdf')\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "YhaH8iOs2So0"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 305
    },
    "colab_type": "code",
    "id": "_aW-D9BJ2So2",
    "outputId": "439ebf26-4e43-4c4b-f79c-44419f887a18"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "findfont: Font family ['Arial'] not found. Falling back to DejaVu Sans.\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (8747055176077)>"
      ]
     },
     "execution_count": 9,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# plot number of studies doing clustering over time\n",
    "\n",
    "tdf = df[['Date', 'Cell clustering', 'DOI']].dropna()\n",
    "tdf['Date'] = pd.to_datetime(tdf['Date'], format='%Y%m%d')\n",
    "per_month = (\n",
    "    tdf\n",
    "    .groupby('Cell clustering')\n",
    "    .resample('1M', on='Date')\n",
    "    .count()['DOI']\n",
    "    .reset_index()\n",
    ")\n",
    "per_month['Cell clustering'] = (\n",
    "    pd.Categorical(\n",
    "        per_month['Cell clustering'],\n",
    "        categories=['Yes', 'No'],\n",
    "    )\n",
    ")\n",
    "\n",
    "p.options.figure_size = (9, 2)\n",
    "fig = (\n",
    "    p.ggplot(\n",
    "        p.aes(x='Date', y='DOI', fill='Cell clustering'),\n",
    "        data=per_month.query('Date > @ts(\"20130101T010101\")')\n",
    "    )\n",
    "    + p.geom_bar(stat='identity', color='grey')\n",
    "    + p.theme_minimal(base_family='Arial')\n",
    "    + p.scale_x_datetime(breaks=date_breaks('1 years'), labels=date_format('%Y'))\n",
    "    + p.labs(y='Number of studies', title='Perfomed cell clustering')\n",
    "    + p.scale_fill_brewer(palette='Greys')\n",
    ")\n",
    "fig.save('clustering_over_time.pdf')\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 68
    },
    "colab_type": "code",
    "id": "bdZlzjqD2So4",
    "outputId": "8c5f7e08-49ba-4bb7-b1dd-6907877075f6"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Yes    0.897361\n",
       "No     0.102639\n",
       "Name: Cell clustering, dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tdf['Cell clustering'].value_counts(normalize=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 288
    },
    "colab_type": "code",
    "id": "ATVQD6Pm2So6",
    "outputId": "d34a0e6f-53db-4bff-992c-82dfe1c4c611",
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (-9223363289799778209)>"
      ]
     },
     "execution_count": 11,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# plot number of studies using tsne over time\n",
    "\n",
    "tdf = df[['Date', 'tSNE', 'DOI']].dropna()\n",
    "tdf['Date'] = pd.to_datetime(tdf['Date'], format='%Y%m%d')\n",
    "per_month = (\n",
    "    tdf\n",
    "    .groupby('tSNE')\n",
    "    .resample('1M', on='Date')\n",
    "    .count()['DOI']\n",
    "    .reset_index()\n",
    ")\n",
    "per_month['tSNE'] = (\n",
    "    pd.Categorical(\n",
    "        per_month['tSNE'],\n",
    "        categories=['Yes', 'No'],\n",
    "    )\n",
    ")\n",
    "\n",
    "p.options.figure_size = (9, 2)\n",
    "fig = (\n",
    "    p.ggplot(p.aes(x='Date', y='DOI', fill='tSNE'), data=per_month.query('Date > @ts(\"20130101T010101\")'))\n",
    "    + p.geom_bar(stat='identity', color='grey')\n",
    "    + p.theme_minimal(base_family='Arial')\n",
    "    + p.scale_x_datetime(breaks=date_breaks('1 years'), labels=date_format('%Y'))\n",
    "    + p.labs(y='Number of studies', title='Performed tSNE')\n",
    "    + p.scale_fill_brewer(palette='Greys')\n",
    ")\n",
    "fig.save('tsne_over_time.pdf')\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 288
    },
    "colab_type": "code",
    "id": "ROWN2kO_2So8",
    "outputId": "04dd7847-ea0d-401b-bee2-b598026e16ec"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (-9223363289799888903)>"
      ]
     },
     "execution_count": 12,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#plot number of studies performing pseudoanalysis over time\n",
    "\n",
    "tdf = df[['Date', 'Pseudotime', 'DOI']].dropna()\n",
    "tdf['Date'] = pd.to_datetime(tdf['Date'], format='%Y%m%d')\n",
    "per_month = (\n",
    "    tdf\n",
    "    .groupby('Pseudotime')\n",
    "    .resample('1M', on='Date')\n",
    "    .count()['DOI']\n",
    "    .reset_index()\n",
    ")\n",
    "per_month['Pseudotime'] = (\n",
    "    pd.Categorical(\n",
    "        per_month['Pseudotime'],\n",
    "        categories=['Yes', 'No']\n",
    "    )\n",
    ")\n",
    "\n",
    "p.options.figure_size = (9, 2)\n",
    "fig = (\n",
    "    p.ggplot(p.aes(x='Date', y='DOI', fill='Pseudotime'), data=per_month.query('Date > @ts(\"20130101T010101\")'))\n",
    "    + p.geom_bar(stat='identity', color='grey')\n",
    "    + p.theme_minimal(base_family='Arial')\n",
    "    + p.scale_x_datetime(breaks=date_breaks('1 years'), labels=date_format('%Y'))\n",
    "    + p.labs(y='Number of studies', title='Perfomed pseudotime analysis')\n",
    "    + p.scale_fill_brewer(palette='Greys')\n",
    ")\n",
    "fig.save('pseudotime_over_time.pdf')\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "KPyGMCrN26Aj"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "YLLdzhrt2SpF"
   },
   "outputs": [],
   "source": [
    "tdf = df.assign(Authors = df['Authors'].str.split(', ')).explode('Authors')\n",
    "cts_ = tdf.resample('1M', on='Date').count().index[1]\n",
    "\n",
    "unique_authors = {}\n",
    "for cts_ in tdf.resample('1M', on='Date').count().index:\n",
    "    unique_authors[cts_] = tdf.query('Date < @cts_')[['Authors']].nunique()\n",
    "    \n",
    "unique_authors = pd.DataFrame(unique_authors).T.reset_index().rename(columns={'index': 'Date'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 492
    },
    "colab_type": "code",
    "id": "r286QaW_2SpH",
    "outputId": "1c3a56ed-62c1-490d-da3e-1cdb8ca77d67",
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x500 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (-9223363289799740556)>"
      ]
     },
     "execution_count": 17,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p.options.figure_size = (9, 5)\n",
    "fig = (\n",
    "    p.ggplot(p.aes(x='Date', y='Authors'), unique_authors)\n",
    "    + p.geom_line()\n",
    "    + p.scale_y_log10()\n",
    "    + p.scale_x_datetime(\n",
    "        breaks=date_breaks('3 years'),\n",
    "        labels=date_format('%Y')\n",
    "    )\n",
    "    + p.labs(y='Unique authors')\n",
    "    + p.theme_minimal(base_family='Arial')\n",
    ")\n",
    "\n",
    "fig.save('unique_authors.pdf')\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "zK6bPQMl2SpJ"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 638
    },
    "colab_type": "code",
    "id": "elniIyHz2SpM",
    "outputId": "a0333b86-a3bf-4713-fc2d-fa2020974521"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>doubling_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2002</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2003</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2004</td>\n",
       "      <td>1.119715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2005</td>\n",
       "      <td>2.583825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2006</td>\n",
       "      <td>5.271610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2007</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2008</td>\n",
       "      <td>3.985924</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2009</td>\n",
       "      <td>1.805004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2010</td>\n",
       "      <td>9.624041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2011</td>\n",
       "      <td>12.119113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2012</td>\n",
       "      <td>4.170681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2013</td>\n",
       "      <td>7.963570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2014</td>\n",
       "      <td>12.268957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2015</td>\n",
       "      <td>9.730522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2016</td>\n",
       "      <td>14.082149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2017</td>\n",
       "      <td>17.531507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2018</td>\n",
       "      <td>14.539674</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2019</td>\n",
       "      <td>14.759696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2020</td>\n",
       "      <td>15.051003</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    year  doubling_time\n",
       "0   2002            NaN\n",
       "1   2003            NaN\n",
       "2   2004       1.119715\n",
       "3   2005       2.583825\n",
       "4   2006       5.271610\n",
       "5   2007            NaN\n",
       "6   2008       3.985924\n",
       "7   2009       1.805004\n",
       "8   2010       9.624041\n",
       "9   2011      12.119113\n",
       "10  2012       4.170681\n",
       "11  2013       7.963570\n",
       "12  2014      12.268957\n",
       "13  2015       9.730522\n",
       "14  2016      14.082149\n",
       "15  2017      17.531507\n",
       "16  2018      14.539674\n",
       "17  2019      14.759696\n",
       "18  2020      15.051003"
      ]
     },
     "execution_count": 18,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unique_authors['authors_pct_change'] = (\n",
    "    unique_authors['Authors']\n",
    "    .pct_change()\n",
    "    .replace(0., np.nan)\n",
    ")\n",
    "\n",
    "doubling_time = (\n",
    "    unique_authors\n",
    "    .assign(year = unique_authors['Date'].dt.year)\n",
    "    .groupby('year')\n",
    "    .apply(lambda d: np.log(2) / np.log(1 + d['authors_pct_change'].mean()))\n",
    "    .to_frame()\n",
    "    .rename(columns={0: 'doubling_time'})\n",
    "    .reset_index()\n",
    ")\n",
    "\n",
    "doubling_time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 492
    },
    "colab_type": "code",
    "id": "iTZoilB12SpO",
    "outputId": "8c60bc29-2da6-4732-e515-6349d49aa909"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x500 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (8747054448823)>"
      ]
     },
     "execution_count": 19,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p.options.figure_size = (9, 5)\n",
    "(\n",
    "    p.ggplot(p.aes(x='year', y='doubling_time'), doubling_time)\n",
    "    + p.geom_point()\n",
    "    + p.scale_y_log10()\n",
    "    + p.theme_minimal(base_family='Arial')\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "2viftpTE2SpQ"
   },
   "outputs": [],
   "source": [
    "unique_authors['doubing_time'] = (\n",
    "    (np.log(2) / np.log(1 + unique_authors['authors_pct_change']))\n",
    "    .replace([np.inf, -np.inf], np.nan)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 492
    },
    "colab_type": "code",
    "id": "hrgmpM_J2SpR",
    "outputId": "be531eef-a293-4e20-9397-a36c4b18e272"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x500 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (-9223363289800382776)>"
      ]
     },
     "execution_count": 21,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p.options.figure_size = (9, 5)\n",
    "(\n",
    "    p.ggplot(p.aes(x='Date', y='doubing_time'), unique_authors)\n",
    "    + p.geom_point()\n",
    "    + p.scale_y_log10()\n",
    "    + p.theme_minimal(base_family='Arial')\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "GryolxOD2SpT"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 266
    },
    "colab_type": "code",
    "id": "kNKGqxVG2SpV",
    "outputId": "cab42997-7d4c-45e4-9049-0ca9c126170a"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Journal</th>\n",
       "      <th>Studies</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>bioRxiv</td>\n",
       "      <td>136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Nature</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Cell</td>\n",
       "      <td>73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Nat Commun</td>\n",
       "      <td>71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Cell Reports</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Science</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Cell Stem Cell</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Journal  Studies\n",
       "0         bioRxiv      136\n",
       "1          Nature       82\n",
       "2            Cell       73\n",
       "3      Nat Commun       71\n",
       "4    Cell Reports       66\n",
       "5         Science       48\n",
       "6  Cell Stem Cell       28"
      ]
     },
     "execution_count": 22,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check top 7 journals.\n",
    "top_journals = (\n",
    "    df['Journal']\n",
    "    .value_counts()\n",
    "    .head(7)\n",
    "    .to_frame()\n",
    "    .reset_index()\n",
    "    .rename(columns={'index': 'Journal', 'Journal': 'Studies'})\n",
    ")\n",
    "top_journals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 266
    },
    "colab_type": "code",
    "id": "hxDnaWdB2SpX",
    "outputId": "ad70c274-108e-4511-a089-7bc29ce0df0e"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Tissue</th>\n",
       "      <th>Studies</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Brain</td>\n",
       "      <td>171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Culture</td>\n",
       "      <td>107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Blood</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Pancreas</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Lung</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Heart</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Bone marrow</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Tissue  Studies\n",
       "0        Brain      171\n",
       "1      Culture      107\n",
       "2        Blood       35\n",
       "3     Pancreas       33\n",
       "4         Lung       32\n",
       "5        Heart       25\n",
       "6  Bone marrow       22"
      ]
     },
     "execution_count": 23,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check top 7 most common tissues.\n",
    "tdf = df.assign(Tissue = df['Tissue'].str.split(' & ')).explode('Tissue')\n",
    "top_tissues = (\n",
    "    tdf['Tissue']\n",
    "    .value_counts()\n",
    "    .to_frame()\n",
    "    .reset_index()\n",
    "    .rename(columns={'index': 'Tissue', 'Tissue': 'Studies'})\n",
    "    .head(7)\n",
    ")\n",
    "top_tissues"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 102
    },
    "colab_type": "code",
    "id": "WzEIu97N2Spa",
    "outputId": "3a28dcf7-313f-476e-8912-041370bbdd01"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No         415\n",
      "Unknown    366\n",
      "Yes        254\n",
      "Name: did_bioRxiv, dtype: int64\n",
      "Fraction of studies in biorxiv: 0.24541062801932367\n"
     ]
    }
   ],
   "source": [
    "# Number of studies with preprints in the biorxiv.\n",
    "\n",
    "df['did_bioRxiv'] = df['bioRxiv DOI'].fillna('?').map(lambda s: {'-': 'No', '?': 'Unknown'}.get(s, 'Yes'))\n",
    "print(df['did_bioRxiv'].value_counts())\n",
    "bx_fracs = df['did_bioRxiv'].value_counts()\n",
    "\n",
    "print('Fraction of studies in biorxiv:', bx_fracs['Yes'] / bx_fracs.sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 288
    },
    "colab_type": "code",
    "id": "iQvMBwqO2Spb",
    "outputId": "37382fe7-03df-4449-d54f-f40366951683"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (8747054437054)>"
      ]
     },
     "execution_count": 25,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# plot studies in the bioRxiv over time\n",
    "\n",
    "tdf = df[['Date', 'did_bioRxiv', 'DOI']].dropna()\n",
    "tdf['Date'] = pd.to_datetime(tdf['Date'], format='%Y%m%d')\n",
    "per_month = (\n",
    "    tdf\n",
    "    .groupby('did_bioRxiv')\n",
    "    .resample('1M', on='Date')\n",
    "    .count()['DOI']\n",
    "    .reset_index()\n",
    ")\n",
    "per_month['did_bioRxiv'] = (\n",
    "    pd.Categorical(\n",
    "        per_month['did_bioRxiv'],\n",
    "        categories=['Yes', 'No', 'Unknown'],\n",
    "    )\n",
    ")\n",
    "\n",
    "p.options.figure_size = (9, 2)\n",
    "fig = (\n",
    "    p.ggplot(\n",
    "        p.aes(x='Date', y='DOI', fill='did_bioRxiv'),\n",
    "        data=per_month.query('Date > @ts(\"20130101T010101\")')\n",
    "    )\n",
    "    + p.geom_bar(stat='identity', color='grey')\n",
    "    + p.theme_minimal(base_family='Arial')\n",
    "    + p.scale_x_datetime(\n",
    "        breaks=date_breaks('1 years'),\n",
    "        labels=date_format('%Y')\n",
    "    )\n",
    "    + p.labs(\n",
    "        y='Number of studies',\n",
    "        title='Published studies with pre-print deposited to the bioRxiv',\n",
    "        fill='bioRxiv'\n",
    "    )\n",
    "    + p.scale_fill_brewer(palette='Greys')\n",
    ")\n",
    "fig.save('biorxiv_over_time.pdf')\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 102
    },
    "colab_type": "code",
    "id": "NRWlQk0o2Spd",
    "outputId": "0a132455-bb0b-49a5-ca19-17fe40a66c11"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No         415\n",
      "Unknown    365\n",
      "Yes        254\n",
      "Name: did_bioRxiv, dtype: int64\n",
      "Fraction of studies in biorxiv: 0.24564796905222436\n"
     ]
    }
   ],
   "source": [
    "tdf = df.query('Date > @ts(20190101)')\n",
    "tdf['did_bioRxiv'] = tdf['bioRxiv DOI'].fillna('?').map(lambda s: {'-': 'No', '?': 'Unknown'}.get(s, 'Yes'))\n",
    "print(tdf['did_bioRxiv'].value_counts())\n",
    "bx_fracs = tdf['did_bioRxiv'].value_counts()\n",
    "\n",
    "print('Fraction of studies in biorxiv:', bx_fracs['Yes'] / bx_fracs.sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 390
    },
    "colab_type": "code",
    "id": "TuD-uxKO2Spf",
    "outputId": "ba260da1-e863-40ce-a49d-4a7a2ac60318"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>did_bioRxiv</th>\n",
       "      <th>Yes</th>\n",
       "      <th>No</th>\n",
       "      <th>Unknown</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-06-30</th>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-05-31</th>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-30</th>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>30.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-31</th>\n",
       "      <td>14.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>55.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-29</th>\n",
       "      <td>10.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>46.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-31</th>\n",
       "      <td>17.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>39.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-31</th>\n",
       "      <td>19.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-11-30</th>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-10-31</th>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-09-30</th>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "did_bioRxiv   Yes   No  Unknown\n",
       "Date                           \n",
       "2020-06-30    3.0  0.0      3.0\n",
       "2020-05-31    5.0  0.0      9.0\n",
       "2020-04-30    8.0  0.0     30.0\n",
       "2020-03-31   14.0  0.0     55.0\n",
       "2020-02-29   10.0  2.0     46.0\n",
       "2020-01-31   17.0  1.0     39.0\n",
       "2019-12-31   19.0  1.0     15.0\n",
       "2019-11-30    5.0  0.0      7.0\n",
       "2019-10-31    6.0  0.0     18.0\n",
       "2019-09-30   13.0  0.0     10.0"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# display breakdown of deposited studies in biorXiv over the last 10 months \n",
    "display(\n",
    "    per_month\n",
    "    .pivot(index='Date', columns='did_bioRxiv', values='DOI')\n",
    "    .fillna(0)\n",
    "    .sort_index(ascending=False)\n",
    "    .head(10)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "4iO9bKMs2Sph"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "IAGSmH_n2Spj"
   },
   "outputs": [],
   "source": [
    "tdf = (\n",
    "    df.assign(Measurement = df['Measurement'].str.split(' & '))\n",
    "    .explode('Measurement')\n",
    "    .dropna(subset=['Measurement'])\n",
    ")\n",
    "\n",
    "cats = tdf['Measurement'].value_counts().index\n",
    "\n",
    "tdf['Measurement'] = (\n",
    "    tdf['Measurement']\n",
    "    .pipe(pd.Categorical, categories=cats)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 261
    },
    "colab_type": "code",
    "id": "ctyT6ICM2Spk",
    "outputId": "2b116d76-1ce3-424e-d66a-312eea9ac065"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (8747054344354)>"
      ]
     },
     "execution_count": 29,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Plot kind of measurement over time vs number of cells reported.\n",
    "m_idx = tdf['Measurement'].value_counts().index\n",
    "\n",
    "clrs = list(map(lambda c: lightness(c, 0.6), ['C0', 'C1', 'C2', 'C3', 'C4']))\n",
    "\n",
    "p.options.figure_size = (9, 2)\n",
    "fig = (\n",
    "    p.ggplot(\n",
    "        p.aes(x='Date', y='Reported cells total', color='Measurement'), \n",
    "        data=tdf.sort_values('Measurement')\n",
    "    )\n",
    "    + p.geom_point()\n",
    "    + p.scale_y_log10()\n",
    "    + p.theme_minimal(base_family='Arial')\n",
    "    + p.scale_x_datetime(breaks=date_breaks('1 years'), labels=date_format('%Y'))\n",
    "    + p.scale_color_manual(['k'] + clrs)\n",
    ")\n",
    "fig.save('all_studies.pdf')\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "Szx1QahE2Spm"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "5F27cD0N2Spn"
   },
   "outputs": [],
   "source": [
    "# Make list of techniques\n",
    "df['Tech'] = df['Technique'].map(lambda s: t_dict.get(s, 'Other'))\n",
    "\n",
    "techs = list(\n",
    "    df['Tech']\n",
    "    .value_counts()\n",
    "    .sort_index()\n",
    "    .index\n",
    "    .difference(['Other'])\n",
    ")\n",
    "techs.append('Other')\n",
    "\n",
    "df['Tech'] = (\n",
    "    pd.Categorical(\n",
    "       df['Tech'],\n",
    "        categories=techs\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 286
    },
    "colab_type": "code",
    "id": "NzolzXMf2Spp",
    "outputId": "a6998be8-eca9-49fe-e147-b7ff0461a561"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (-9223363289799731403)>"
      ]
     },
     "execution_count": 31,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# plot reported number of cells vs technology used over time\n",
    "p.options.figure_size = (9, 2)\n",
    "fig = (\n",
    "    p.ggplot(\n",
    "        p.aes(x='Date', y='Reported cells total', fill='Tech'),\n",
    "        data=df.query('Measurement == \"RNA-seq\"')\n",
    "    )\n",
    "    + p.geom_point(alpha=1, color='none', size=1)\n",
    "    + p.scale_y_log10()\n",
    "    + p.theme_minimal(base_family='Arial')\n",
    "    + p.scale_x_datetime(\n",
    "        breaks=date_breaks('1 years'),\n",
    "        labels=date_format('%Y')\n",
    "    )\n",
    "    + p.scale_fill_manual(['C0', 'C1', 'C2', 'C3', 'C4', 'black'])\n",
    "    + p.labs(fill='Technology')\n",
    ")\n",
    "fig.save('scrnaseq_studies.pdf')\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 266
    },
    "colab_type": "code",
    "id": "1cn23Rwl2Spq",
    "outputId": "c2149636-5f46-4b2c-e0db-030c0df61ec3"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Median cells</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-11-30</td>\n",
       "      <td>39895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-12-31</td>\n",
       "      <td>15601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>35173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-02-29</td>\n",
       "      <td>36044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-03-31</td>\n",
       "      <td>31514</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2020-04-30</td>\n",
       "      <td>30396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2020-05-31</td>\n",
       "      <td>22000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date  Median cells\n",
       "0 2019-11-30         39895\n",
       "1 2019-12-31         15601\n",
       "2 2020-01-31         35173\n",
       "3 2020-02-29         36044\n",
       "4 2020-03-31         31514\n",
       "5 2020-04-30         30396\n",
       "6 2020-05-31         22000"
      ]
     },
     "execution_count": 32,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Display median cells per month for last 7 months.\n",
    "\n",
    "cells_per_study = (\n",
    "    df\n",
    "    .query('Measurement == \"RNA-seq\"')\n",
    "    .resample('1M', on='Date')[['Reported cells total']]\n",
    "    .median()\n",
    "    .tail(8).iloc[:-1]\n",
    "    .astype(int)\n",
    "    .reset_index()\n",
    "    .rename(columns={'Reported cells total': 'Median cells'})\n",
    ")\n",
    "cells_per_study"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 266
    },
    "colab_type": "code",
    "id": "D7pAV_pr2Sps",
    "outputId": "815dba82-5dab-4303-d7ae-0f752a20fe0d"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Studies</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-11-30</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-12-31</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-02-29</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-03-31</td>\n",
       "      <td>68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2020-04-30</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2020-05-31</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date  Studies\n",
       "0 2019-11-30       12\n",
       "1 2019-12-31       29\n",
       "2 2020-01-31       57\n",
       "3 2020-02-29       50\n",
       "4 2020-03-31       68\n",
       "5 2020-04-30       38\n",
       "6 2020-05-31       13"
      ]
     },
     "execution_count": 33,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Display data for number of studies using RNA-seq for the last 10 months.\n",
    "\n",
    "studies_per_month = (\n",
    "    df\n",
    "    .query('Measurement == \"RNA-seq\"')\n",
    "    .resample('1M', on='Date')\n",
    "    .count()\n",
    "    .tail(8)[['DOI']].iloc[:-1]\n",
    "    .reset_index()\n",
    "    .rename(columns={'DOI': 'Studies'})\n",
    ")\n",
    "studies_per_month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 266
    },
    "colab_type": "code",
    "id": "Mpee4JtM2Spt",
    "outputId": "16e45da9-70e7-4d42-d161-b2fd1d58dc53"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Month</th>\n",
       "      <th>Studies</th>\n",
       "      <th>Median cells</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>November 2019</td>\n",
       "      <td>12</td>\n",
       "      <td>39895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>December 2019</td>\n",
       "      <td>29</td>\n",
       "      <td>15601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>January 2020</td>\n",
       "      <td>57</td>\n",
       "      <td>35173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>February 2020</td>\n",
       "      <td>50</td>\n",
       "      <td>36044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>March 2020</td>\n",
       "      <td>68</td>\n",
       "      <td>31514</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>April 2020</td>\n",
       "      <td>38</td>\n",
       "      <td>30396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>May 2020</td>\n",
       "      <td>13</td>\n",
       "      <td>22000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Month  Studies  Median cells\n",
       "0  November 2019       12         39895\n",
       "1  December 2019       29         15601\n",
       "2   January 2020       57         35173\n",
       "3  February 2020       50         36044\n",
       "4     March 2020       68         31514\n",
       "5     April 2020       38         30396\n",
       "6       May 2020       13         22000"
      ]
     },
     "execution_count": 34,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "monthly_stats = (\n",
    "    studies_per_month\n",
    "    .merge(cells_per_study)\n",
    "    .assign(\n",
    "        Month=studies_per_month['Date'].dt.strftime('%B %Y')\n",
    "    )[['Month', 'Studies', 'Median cells']]\n",
    ")\n",
    "\n",
    "monthly_stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "bWCd_g0R2Spv"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 297
    },
    "colab_type": "code",
    "id": "9wMzfV482Spx",
    "outputId": "a9baabe2-c191-4a5d-f3ba-7d96024f4ec7"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"3\" halign=\"left\">Monthly statistics</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Top tissues</th>\n",
       "      <th colspan=\"2\" halign=\"left\">Top journals</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>Month</th>\n",
       "      <th>Studies</th>\n",
       "      <th>Median cells</th>\n",
       "      <th>Tissue</th>\n",
       "      <th>Studies</th>\n",
       "      <th>Journal</th>\n",
       "      <th>Studies</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>November 2019</td>\n",
       "      <td>12</td>\n",
       "      <td>39895</td>\n",
       "      <td>Brain</td>\n",
       "      <td>171</td>\n",
       "      <td>bioRxiv</td>\n",
       "      <td>136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>December 2019</td>\n",
       "      <td>29</td>\n",
       "      <td>15601</td>\n",
       "      <td>Culture</td>\n",
       "      <td>107</td>\n",
       "      <td>Nature</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>January 2020</td>\n",
       "      <td>57</td>\n",
       "      <td>35173</td>\n",
       "      <td>Blood</td>\n",
       "      <td>35</td>\n",
       "      <td>Cell</td>\n",
       "      <td>73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>February 2020</td>\n",
       "      <td>50</td>\n",
       "      <td>36044</td>\n",
       "      <td>Pancreas</td>\n",
       "      <td>33</td>\n",
       "      <td>Nat Commun</td>\n",
       "      <td>71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>March 2020</td>\n",
       "      <td>68</td>\n",
       "      <td>31514</td>\n",
       "      <td>Lung</td>\n",
       "      <td>32</td>\n",
       "      <td>Cell Reports</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>April 2020</td>\n",
       "      <td>38</td>\n",
       "      <td>30396</td>\n",
       "      <td>Heart</td>\n",
       "      <td>25</td>\n",
       "      <td>Science</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>May 2020</td>\n",
       "      <td>13</td>\n",
       "      <td>22000</td>\n",
       "      <td>Bone marrow</td>\n",
       "      <td>22</td>\n",
       "      <td>Cell Stem Cell</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Monthly statistics                       ... Top tissues    Top journals        \n",
       "               Month Studies Median cells  ...     Studies         Journal Studies\n",
       "0      November 2019      12        39895  ...         171         bioRxiv     136\n",
       "1      December 2019      29        15601  ...         107          Nature      82\n",
       "2       January 2020      57        35173  ...          35            Cell      73\n",
       "3      February 2020      50        36044  ...          33      Nat Commun      71\n",
       "4         March 2020      68        31514  ...          32    Cell Reports      66\n",
       "5         April 2020      38        30396  ...          25         Science      48\n",
       "6           May 2020      13        22000  ...          22  Cell Stem Cell      28\n",
       "\n",
       "[7 rows x 7 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summary_table = pd.concat({\n",
    "    'Monthly statistics': monthly_stats.T,\n",
    "    'Top tissues': top_tissues.T,\n",
    "    'Top journals': top_journals.T\n",
    "}).T\n",
    "\n",
    "summary_table.to_excel('Table 1.xlsx')\n",
    "summary_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "PlsdaF_i2Sp0",
    "outputId": "7f3877a2-6b87-4070-f586-8e3264ed7268"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1035, 29)"
      ]
     },
     "execution_count": 36,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 68
    },
    "colab_type": "code",
    "id": "l1Xg6mqu2Sp1",
    "outputId": "ac37984d-d64a-4131-98d6-56439854effc"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Reported cells total                         17800.0\n",
       "Number of reported cell types or clusters       13.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 37,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Query median number of cells reported in 2019\n",
    "df.query('Measurement == \"RNA-seq\" and Date > @ts(\"20190101T010101\")').median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 297
    },
    "colab_type": "code",
    "id": "X6uHT8Cd2Sp2",
    "outputId": "44ec815d-96f1-4de0-ccc4-1ab667471ebf"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Reported cells total</th>\n",
       "      <th>Number of reported cell types or clusters</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-11-30</th>\n",
       "      <td>39895.5</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-31</th>\n",
       "      <td>15601.0</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-31</th>\n",
       "      <td>35173.0</td>\n",
       "      <td>8.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-29</th>\n",
       "      <td>36044.0</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-31</th>\n",
       "      <td>31514.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-30</th>\n",
       "      <td>30396.0</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-05-31</th>\n",
       "      <td>22000.0</td>\n",
       "      <td>20.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Reported cells total  Number of reported cell types or clusters\n",
       "Date                                                                       \n",
       "2019-11-30               39895.5                                       15.0\n",
       "2019-12-31               15601.0                                       16.0\n",
       "2020-01-31               35173.0                                        8.5\n",
       "2020-02-29               36044.0                                       17.0\n",
       "2020-03-31               31514.0                                       15.0\n",
       "2020-04-30               30396.0                                       17.0\n",
       "2020-05-31               22000.0                                       20.5"
      ]
     },
     "execution_count": 38,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Display median for last 7 months\n",
    "df.query('Measurement == \"RNA-seq\"').resample('1M', on='Date').median().tail(8).iloc[:-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "eCcSm1-y2Sp5"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "id": "iN6jXapN2Sp7",
    "outputId": "cf4c09bc-de8d-435b-e31f-751ecf247d83"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Reported cells total    1355585.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 39,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(\n",
    "    df\n",
    "    .query('Measurement == \"RNA-seq\" and Date > @ts(\"20200101T010101\")')\n",
    "    .resample('1M', on='Date')\n",
    "    .sum()\n",
    "    .tail(8)[['Reported cells total']].iloc[:-1]\n",
    "    .median()\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 261
    },
    "colab_type": "code",
    "id": "3VYEsE5Z2Sp9",
    "outputId": "0d96186a-30d8-471c-bc82-61c6934c52c1"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (8747051959609)>"
      ]
     },
     "execution_count": 40,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Plot total number of cells in studies published each month over time\n",
    "rna_df = df.query('Measurement == \"RNA-seq\"').resample('M', on='Date').sum().reset_index()\n",
    "p.options.figure_size = (9, 2)\n",
    "fig = (\n",
    "    p.ggplot(p.aes(x='Date', y='Reported cells total'), data=rna_df.query('`Reported cells total` > 0'))\n",
    "    + p.geom_bar(stat='identity')\n",
    "    + p.scale_y_log10()\n",
    "    + p.theme_minimal(base_family='Arial')\n",
    "    + p.scale_x_datetime(breaks=date_breaks('1 years'), labels=date_format('%Y'))\n",
    "    + p.labs(y='Cells per month')\n",
    ")\n",
    "fig.save('cells_per_month.pdf')\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "ZlotJ3KO2Sp_",
    "outputId": "f96c5aa2-d809-4ca6-8ae5-fab467cf88b7"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7739200.0"
      ]
     },
     "execution_count": 41,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.query('Date > @ts(\"20200101T010101\")')['Reported cells total'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 261
    },
    "colab_type": "code",
    "id": "occIqFW62SqB",
    "outputId": "c69dabef-4ca1-4aa4-93b3-bf66b6cf29c1"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (8747055002716)>"
      ]
     },
     "execution_count": 42,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Plot median number of cells in studies each month\n",
    "median_rna_df = df.query('Measurement == \"RNA-seq\"').resample('1M', on='Date').median().reset_index()\n",
    "p.options.figure_size = (9, 2)\n",
    "fig = (\n",
    "    p.ggplot(p.aes(x='Date', y='Reported cells total'), data=median_rna_df.query('`Reported cells total` > 0'))\n",
    "    + p.geom_bar(stat='identity')\n",
    "    + p.scale_y_log10()\n",
    "    + p.theme_minimal(base_family='Arial')\n",
    "    + p.scale_x_datetime(breaks=date_breaks('1 years'), labels=date_format('%Y'))\n",
    "    + p.labs(y='Median cells \\nper study \\nper month')\n",
    ")\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "colab_type": "code",
    "id": "x0t8KNZi2SqC",
    "outputId": "11690047-baf0-44f0-c11a-d5b65d209004"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>1030</th>\n",
       "      <th>1031</th>\n",
       "      <th>1032</th>\n",
       "      <th>1033</th>\n",
       "      <th>1034</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Shorthand</th>\n",
       "      <td>Zhang et al bioRxiv</td>\n",
       "      <td>Niederriter Shami et al DCell</td>\n",
       "      <td>He et al bioRxiv</td>\n",
       "      <td>Le et al Immunity</td>\n",
       "      <td>Fischer et al</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DOI</th>\n",
       "      <td>10.1101/2020.06.04.105700</td>\n",
       "      <td>10.1016/j.devcel.2020.05.010</td>\n",
       "      <td>10.1101/2020.06.14.150599</td>\n",
       "      <td>10.1016/j.immuni.2020.05.010</td>\n",
       "      <td>10.1038/s41467-020-16893-3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Authors</th>\n",
       "      <td>Meng Zhang, Stephen W. Eichhorn, Brian Zingg, ...</td>\n",
       "      <td>Adrienne Niederriter Shami, Xianing Zheng, Sar...</td>\n",
       "      <td>Peng He, Brian A Williams, Diane Trout, Georgi...</td>\n",
       "      <td>Justin Le, Jeong Eun Park, Vi Luan Ha, Annie L...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Journal</th>\n",
       "      <td>bioRxiv</td>\n",
       "      <td>Developmental Cell</td>\n",
       "      <td>bioRxiv</td>\n",
       "      <td>Immunity</td>\n",
       "      <td>Nat Commun</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Title</th>\n",
       "      <td>Molecular, spatial and projection diversity of...</td>\n",
       "      <td>Single-Cell RNA Sequencing of Human, Macaque, ...</td>\n",
       "      <td>The changing mouse embryo transcriptome at who...</td>\n",
       "      <td>Single-Cell RNA-Seq Mapping of Human Thymopoie...</td>\n",
       "      <td>Post-surgical adhesions are triggered by calci...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <td>2020-06-05 00:00:00</td>\n",
       "      <td>2020-06-05 00:00:00</td>\n",
       "      <td>2020-06-15 00:00:00</td>\n",
       "      <td>2020-06-16 00:00:00</td>\n",
       "      <td>NaT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bioRxiv DOI</th>\n",
       "      <td>10.1101/2020.06.04.105700</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.1101/2020.06.14.150599</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Reported cells total</th>\n",
       "      <td>300000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Organism</th>\n",
       "      <td>Mouse</td>\n",
       "      <td>Human, Macaque, Mouse</td>\n",
       "      <td>Mouse</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tissue</th>\n",
       "      <td>Brain</td>\n",
       "      <td>Testes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Technique</th>\n",
       "      <td>MERFISH</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Chromium &amp; Smart-seq2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Data location</th>\n",
       "      <td>ftp://download.brainimagelibrary.org:8811/02/2...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Panel size</th>\n",
       "      <td>118</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Measurement</th>\n",
       "      <td>In Situ</td>\n",
       "      <td>RNA-seq</td>\n",
       "      <td>RNA-seq</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cell source</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Disease</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Contrasts</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Developmental stage</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Number of reported cell types or clusters</th>\n",
       "      <td>95</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cell clustering</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pseudotime</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Yes</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RNA Velocity</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PCA</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tSNE</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>H5AD location</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Isolation</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BC --&gt; Cell ID _OR_ BC --&gt; Cluster ID</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>did_bioRxiv</th>\n",
       "      <td>Yes</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Unknown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tech</th>\n",
       "      <td>Other</td>\n",
       "      <td>Other</td>\n",
       "      <td>Other</td>\n",
       "      <td>Other</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                                        1030  ...                                               1034\n",
       "Shorthand                                                                Zhang et al bioRxiv  ...                                      Fischer et al\n",
       "DOI                                                                10.1101/2020.06.04.105700  ...                         10.1038/s41467-020-16893-3\n",
       "Authors                                    Meng Zhang, Stephen W. Eichhorn, Brian Zingg, ...  ...                                                NaN\n",
       "Journal                                                                              bioRxiv  ...                                         Nat Commun\n",
       "Title                                      Molecular, spatial and projection diversity of...  ...  Post-surgical adhesions are triggered by calci...\n",
       "Date                                                                     2020-06-05 00:00:00  ...                                                NaT\n",
       "bioRxiv DOI                                                        10.1101/2020.06.04.105700  ...                                                NaN\n",
       "Reported cells total                                                                  300000  ...                                                NaN\n",
       "Organism                                                                               Mouse  ...                                                NaN\n",
       "Tissue                                                                                 Brain  ...                                                NaN\n",
       "Technique                                                                            MERFISH  ...                                                NaN\n",
       "Data location                              ftp://download.brainimagelibrary.org:8811/02/2...  ...                                                NaN\n",
       "Panel size                                                                               118  ...                                                NaN\n",
       "Measurement                                                                          In Situ  ...                                                NaN\n",
       "Cell source                                                                              NaN  ...                                                NaN\n",
       "Disease                                                                                  NaN  ...                                                NaN\n",
       "Contrasts                                                                                NaN  ...                                                NaN\n",
       "Developmental stage                                                                      NaN  ...                                                NaN\n",
       "Number of reported cell types or clusters                                                 95  ...                                                NaN\n",
       "Cell clustering                                                                          NaN  ...                                                NaN\n",
       "Pseudotime                                                                               NaN  ...                                                NaN\n",
       "RNA Velocity                                                                             NaN  ...                                                NaN\n",
       "PCA                                                                                      NaN  ...                                                NaN\n",
       "tSNE                                                                                     NaN  ...                                                NaN\n",
       "H5AD location                                                                            NaN  ...                                                NaN\n",
       "Isolation                                                                                NaN  ...                                                NaN\n",
       "BC --> Cell ID _OR_ BC --> Cluster ID                                                    NaN  ...                                                NaN\n",
       "did_bioRxiv                                                                              Yes  ...                                            Unknown\n",
       "Tech                                                                                   Other  ...                                              Other\n",
       "\n",
       "[29 rows x 5 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Take a look at the last 5 entries in the dataset (newest studies)\n",
    "df.tail().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "4yyE6t3y2SqE"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "NsKzHXaN2SqF"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 136
    },
    "colab_type": "code",
    "id": "Gm9P6pIW2SqH",
    "outputId": "2a663b97-57c9-470c-b9d0-a64c5a072106"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "data_scale\n",
       "(0.3, 2.606]        153.298134\n",
       "(2.606, 3.441]      210.756797\n",
       "(3.441, 4.063]     8100.666657\n",
       "(4.063, 4.568]    13892.320871\n",
       "(4.568, 6.402]     3333.339182\n",
       "dtype: float64"
      ]
     },
     "execution_count": 44,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ = df.query('Measurement == \"RNA-seq\"')\n",
    "\n",
    "formula = 'Q(\"Number of reported cell types or clusters\") ~ Q(\"Reported cells total\")'\n",
    "\n",
    "df_['data_scale'] = df_['Reported cells total'].pipe(np.log10).pipe(pd.qcut, 5)\n",
    "\n",
    "def get_regression_coeff(d):\n",
    "    c = (\n",
    "        smf.ols(formula=formula, data=d)\n",
    "        .fit()\n",
    "        .params['Q(\"Reported cells total\")']\n",
    "    )\n",
    "    \n",
    "    return c\n",
    "\n",
    "def predict_number_celltypes(d):\n",
    "    fit = (\n",
    "        smf.ols(formula=formula, data=d)\n",
    "        .fit()\n",
    "    )\n",
    "    \n",
    "    return d.assign(p_ = fit.predict(d))\n",
    "    \n",
    "df_ = df_.groupby('data_scale').apply(predict_number_celltypes)\n",
    "df_.groupby('data_scale').apply(get_regression_coeff).pipe(np.reciprocal)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "4MJBC4vD2SqK"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 422
    },
    "colab_type": "code",
    "id": "OvzXsZQC2SqL",
    "outputId": "605fc096-2672-472b-c7b0-2c864f9fd36a",
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (8747054773105)>"
      ]
     },
     "execution_count": 45,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# plot number of reported cell types/clusters vs total number of cells\n",
    "\n",
    "p.options.figure_size = (6, 4)\n",
    "fig = (\n",
    "    p.ggplot(\n",
    "        p.aes(\n",
    "            x='Reported cells total',\n",
    "            y='Number of reported cell types or clusters',\n",
    "            group='data_scale'\n",
    "        ),\n",
    "        data=df_\n",
    "    )\n",
    "    + p.geom_point(alpha=1, size=2)\n",
    "    + p.scale_x_log10()\n",
    "    + p.scale_y_log10()\n",
    "    + p.geom_line(p.aes(y='p_'), color='r', size=1)\n",
    "    + p.labs(color='Technology')\n",
    "    + p.theme_minimal(base_family='Arial')\n",
    ")\n",
    "fig.save('clusters_per_cells.pdf')\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "nzcr8ft32SqN"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "bdGyWYVK2SqP"
   },
   "outputs": [],
   "source": [
    "tdf = df.assign(Tissue = df['Tissue'].str.split(', ')).explode('Tissue')\n",
    "\n",
    "t_dict = {k: k for k in tdf.query('Tissue not in [\"Culture\", \"Tumor\", \"Embryo\"]')['Tissue'].value_counts().head(11).index}\n",
    "\n",
    "tdf['Tissue_'] = tdf['Tissue'].map(lambda s: t_dict.get(s, 'Other'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 379
    },
    "colab_type": "code",
    "id": "1WtLKaz82SqR",
    "outputId": "81f29073-dd25-4c57-ac37-e8bd8ee92b08",
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 900x200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (-9223363289800396572)>"
      ]
     },
     "execution_count": 47,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "per_month = (\n",
    "    tdf\n",
    "    .groupby('Tissue_')\n",
    "    .resample('1M', on='Date')\n",
    "    .count()['DOI']\n",
    "    .reset_index()\n",
    "    .query('Tissue_ != \"Other\"')\n",
    ")\n",
    "\n",
    "p.options.figure_size = (9, 2)\n",
    "fig = (\n",
    "    p.ggplot(\n",
    "        p.aes(x='Date', y='DOI', fill='Tissue_'),\n",
    "        data=per_month.query('Date > @ts(\"20130101T010101\")')\n",
    "    )\n",
    "    + p.geom_bar(stat='identity', color='grey')\n",
    "    + p.theme_minimal(base_family='Arial')\n",
    "    + p.scale_x_datetime(\n",
    "        breaks=date_breaks('1 years'),\n",
    "        labels=date_format('%Y')\n",
    "    )\n",
    "    + p.labs(y='Number of studies')\n",
    ")\n",
    "\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "fuVBHVX_2SqS"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 238
    },
    "colab_type": "code",
    "id": "e2Ba2Gii2SqX",
    "outputId": "59094540-64e8-45e2-9828-f35c36d44f9c"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Other          638\n",
       "Brain          171\n",
       "Blood           35\n",
       "Pancreas        33\n",
       "Lung            32\n",
       "Heart           25\n",
       "Bone marrow     22\n",
       "Skin            19\n",
       "Kidney          19\n",
       "Spleen          18\n",
       "Testis          12\n",
       "Eye             11\n",
       "Name: Tissue_, dtype: int64"
      ]
     },
     "execution_count": 48,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tdf = df.copy()\n",
    "\n",
    "exclude_tissues = [\"Culture\", \"Tumor\", \"Embryo\", \"Whole organism\", \"Organoid\"]\n",
    "t_dict = {k: k for k in tdf.query('Tissue not in @exclude_tissues')['Tissue'].value_counts().head(11).index}\n",
    "\n",
    "tdf['Tissue_'] = tdf['Tissue'].map(lambda s: t_dict.get(s, 'Other'))\n",
    "\n",
    "tdf['Tissue_'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "hvnAUxUr2Sqa"
   },
   "outputs": [],
   "source": [
    "t_ = pd.Categorical(tdf['Tissue_'])\n",
    "idx = tdf['Tissue_'].value_counts().index.drop('Other').append(pd.Index(['Other']))\n",
    "tdf['Tissue_'] = pd.Categorical(tdf['Tissue_'], categories=idx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 666
    },
    "colab_type": "code",
    "id": "G9aySJTp2Sqe",
    "outputId": "d1cd2bf1-7246-4071-d381-83c47df77cfd",
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1100x700 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (8747055166244)>"
      ]
     },
     "execution_count": 50,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p.options.figure_size = (11, 7)\n",
    "\n",
    "fig = (\n",
    "    p.ggplot(p.aes(x='Reported cells total', y='Number of reported cell types or clusters'), tdf)\n",
    "    + p.geom_point()\n",
    "    + p.scale_x_log10()\n",
    "    + p.scale_y_log10()\n",
    "    + p.theme_minimal(base_family='Arial')\n",
    "    + p.stat_smooth(method='lm', se=False, color='red', size=0.66)\n",
    "    + p.facet_wrap('~Tissue_', ncol=4)\n",
    ")\n",
    "fig.save('clusters_per_cells_by_tissue.pdf')\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 255
    },
    "colab_type": "code",
    "id": "7PwfWGDs2Sqh",
    "outputId": "943af2a2-93ed-44f6-8506-e824197397f7"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Tissue_\n",
       "Brain           True\n",
       "Blood          False\n",
       "Pancreas        True\n",
       "Lung            True\n",
       "Heart           True\n",
       "Bone marrow    False\n",
       "Skin           False\n",
       "Kidney         False\n",
       "Spleen          True\n",
       "Testis          True\n",
       "Eye             True\n",
       "Other           True\n",
       "dtype: bool"
      ]
     },
     "execution_count": 51,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "formula = formula = 'np.log(Q(\"Number of reported cell types or clusters\")) ~ np.log(Q(\"Reported cells total\"))'\n",
    "\n",
    "def get_coeff_pval(d):\n",
    "    c = (\n",
    "        smf.ols(formula=formula, data=d)\n",
    "        .fit()\n",
    "        .pvalues['np.log(Q(\"Reported cells total\"))']\n",
    "    )\n",
    "    \n",
    "    return c\n",
    "\n",
    "tdf.groupby('Tissue_').apply(get_coeff_pval) < 0.05"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "JHUqAk7Y2Sqk"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "ZXH9HKiM2Sq4"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "tK1xceMT2Sq4"
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [],
   "include_colab_link": true,
   "name": "Example analysis.ipynb",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}