Dirichlet regression in PyMC

dirichlet-regression-pymc.ipynb

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    "# Dirichlet Regression in PyMC\n",
    "\n",
    "**author: Joshua Cook**  \n",
    "**date: November 09, 2022**\n",
    "\n",
    "## Introduction\n",
    "\n",
    "An example of a Dirichlet regression in PyMC.\n",
    "I have measured a protein’s expression in two groups, a control and experimental, across $10$ tissues. I have measured the expression in $6$ replicates for each condition across all $10$ tissues. Therefore, I have $10 \\times 6 \\times 2$ measurements. The values are all greater than or equal to $0$ (i.e. 0 or positive) and the sum of the values for each replicate sum to $1$.\n",
    "\n",
    "I want to know if the expression of the protein is different between control and experiment in each tissue.\n",
    "\n",
    "Because of the constraint on the values being $\\ge 0$ and summing to $1$ across replicates, the likelkihood should be a Dirichlet distribution.\n",
    "The exponential is the appropriate link function between the likelihood and linear combination of variables."
   ]
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   "cell_type": "markdown",
   "id": "51ef6b6e-61a1-47da-92a1-7b4e32e1f4ae",
   "metadata": {},
   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f698c9c6-de4f-4011-b367-5d2563f10e3e",
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   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8dc76aae-2ffa-405b-99bc-f10b2ee8a67c",
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   "outputs": [],
   "source": [
    "import arviz as az\n",
    "import janitor  # noqa: F401\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import pymc as pm\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "7d19825a-9fba-4ce8-83d0-81fbdfb05892",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "%config InlineBackend.figure_format = 'retina'\n",
    "sns.set_style(\"whitegrid\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cfd4919b-b75a-48a1-ac83-a9ed97828fc3",
   "metadata": {},
   "source": [
    "## Data generation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6c383df9-0924-4ba7-9495-7432195821b7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Real proportions for each tissue:\n",
      "[[0.072 0.148 0.137 0.135 0.074 0.118 0.083 0.015 0.12  0.098]\n",
      " [0.066 0.104 0.138 0.149 0.062 0.057 0.098 0.109 0.131 0.086]]\n"
     ]
    }
   ],
   "source": [
    "N_TISSUES = 10\n",
    "N_REPS = 6\n",
    "CONDITIONS = [\"C\", \"E\"]\n",
    "\n",
    "TISSUES = [f\"tissue-{i}\" for i in range(N_TISSUES)]\n",
    "REPS = [f\"{CONDITIONS[0]}-{i}\" for i in range(N_REPS)]\n",
    "REPS += [f\"{CONDITIONS[1]}-{i}\" for i in range(N_REPS)]\n",
    "\n",
    "np.random.seed(909)\n",
    "ctrl_tissue_props = np.random.beta(2, 2, N_TISSUES)\n",
    "ctrl_tissue_props = ctrl_tissue_props / np.sum(ctrl_tissue_props)\n",
    "expt_tissue_props = np.random.beta(2, 2, N_TISSUES)\n",
    "expt_tissue_props = expt_tissue_props / np.sum(expt_tissue_props)\n",
    "\n",
    "print(\"Real proportions for each tissue:\")\n",
    "print(np.vstack([ctrl_tissue_props, expt_tissue_props]).round(3))"
   ]
  },
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   "execution_count": 5,
   "id": "18adf273-c201-401d-845b-e52897d1dfa1",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tissue-0</th>\n",
       "      <th>tissue-1</th>\n",
       "      <th>tissue-2</th>\n",
       "      <th>tissue-3</th>\n",
       "      <th>tissue-4</th>\n",
       "      <th>tissue-5</th>\n",
       "      <th>tissue-6</th>\n",
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       "      <th>tissue-8</th>\n",
       "      <th>tissue-9</th>\n",
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       "      <th>replicate</th>\n",
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       "      <th>C-0</th>\n",
       "      <td>0.085</td>\n",
       "      <td>0.116</td>\n",
       "      <td>0.184</td>\n",
       "      <td>0.175</td>\n",
       "      <td>0.038</td>\n",
       "      <td>0.101</td>\n",
       "      <td>0.069</td>\n",
       "      <td>0.014</td>\n",
       "      <td>0.102</td>\n",
       "      <td>0.115</td>\n",
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       "    <tr>\n",
       "      <th>C-1</th>\n",
       "      <td>0.134</td>\n",
       "      <td>0.188</td>\n",
       "      <td>0.101</td>\n",
       "      <td>0.119</td>\n",
       "      <td>0.075</td>\n",
       "      <td>0.104</td>\n",
       "      <td>0.052</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.121</td>\n",
       "      <td>0.107</td>\n",
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       "    <tr>\n",
       "      <th>C-2</th>\n",
       "      <td>0.098</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.127</td>\n",
       "      <td>0.138</td>\n",
       "      <td>0.094</td>\n",
       "      <td>0.091</td>\n",
       "      <td>0.134</td>\n",
       "      <td>0.017</td>\n",
       "      <td>0.080</td>\n",
       "      <td>0.096</td>\n",
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       "      <th>C-3</th>\n",
       "      <td>0.069</td>\n",
       "      <td>0.154</td>\n",
       "      <td>0.140</td>\n",
       "      <td>0.082</td>\n",
       "      <td>0.065</td>\n",
       "      <td>0.182</td>\n",
       "      <td>0.054</td>\n",
       "      <td>0.011</td>\n",
       "      <td>0.110</td>\n",
       "      <td>0.132</td>\n",
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       "    <tr>\n",
       "      <th>C-4</th>\n",
       "      <td>0.033</td>\n",
       "      <td>0.208</td>\n",
       "      <td>0.151</td>\n",
       "      <td>0.090</td>\n",
       "      <td>0.067</td>\n",
       "      <td>0.109</td>\n",
       "      <td>0.064</td>\n",
       "      <td>0.003</td>\n",
       "      <td>0.160</td>\n",
       "      <td>0.115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C-5</th>\n",
       "      <td>0.074</td>\n",
       "      <td>0.130</td>\n",
       "      <td>0.130</td>\n",
       "      <td>0.113</td>\n",
       "      <td>0.081</td>\n",
       "      <td>0.129</td>\n",
       "      <td>0.059</td>\n",
       "      <td>0.020</td>\n",
       "      <td>0.111</td>\n",
       "      <td>0.152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E-0</th>\n",
       "      <td>0.100</td>\n",
       "      <td>0.105</td>\n",
       "      <td>0.114</td>\n",
       "      <td>0.081</td>\n",
       "      <td>0.088</td>\n",
       "      <td>0.056</td>\n",
       "      <td>0.120</td>\n",
       "      <td>0.087</td>\n",
       "      <td>0.167</td>\n",
       "      <td>0.081</td>\n",
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       "    <tr>\n",
       "      <th>E-1</th>\n",
       "      <td>0.043</td>\n",
       "      <td>0.124</td>\n",
       "      <td>0.184</td>\n",
       "      <td>0.098</td>\n",
       "      <td>0.071</td>\n",
       "      <td>0.040</td>\n",
       "      <td>0.122</td>\n",
       "      <td>0.071</td>\n",
       "      <td>0.157</td>\n",
       "      <td>0.089</td>\n",
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       "    <tr>\n",
       "      <th>E-2</th>\n",
       "      <td>0.099</td>\n",
       "      <td>0.108</td>\n",
       "      <td>0.102</td>\n",
       "      <td>0.139</td>\n",
       "      <td>0.089</td>\n",
       "      <td>0.039</td>\n",
       "      <td>0.115</td>\n",
       "      <td>0.092</td>\n",
       "      <td>0.158</td>\n",
       "      <td>0.059</td>\n",
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       "    <tr>\n",
       "      <th>E-3</th>\n",
       "      <td>0.076</td>\n",
       "      <td>0.074</td>\n",
       "      <td>0.122</td>\n",
       "      <td>0.142</td>\n",
       "      <td>0.058</td>\n",
       "      <td>0.062</td>\n",
       "      <td>0.103</td>\n",
       "      <td>0.081</td>\n",
       "      <td>0.106</td>\n",
       "      <td>0.176</td>\n",
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       "    <tr>\n",
       "      <th>E-4</th>\n",
       "      <td>0.098</td>\n",
       "      <td>0.103</td>\n",
       "      <td>0.117</td>\n",
       "      <td>0.113</td>\n",
       "      <td>0.048</td>\n",
       "      <td>0.110</td>\n",
       "      <td>0.113</td>\n",
       "      <td>0.104</td>\n",
       "      <td>0.166</td>\n",
       "      <td>0.027</td>\n",
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       "    <tr>\n",
       "      <th>E-5</th>\n",
       "      <td>0.059</td>\n",
       "      <td>0.110</td>\n",
       "      <td>0.119</td>\n",
       "      <td>0.190</td>\n",
       "      <td>0.059</td>\n",
       "      <td>0.054</td>\n",
       "      <td>0.071</td>\n",
       "      <td>0.065</td>\n",
       "      <td>0.155</td>\n",
       "      <td>0.117</td>\n",
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      "text/plain": [
       "           tissue-0  tissue-1  tissue-2  tissue-3  tissue-4  tissue-5  \\\n",
       "replicate                                                               \n",
       "C-0           0.085     0.116     0.184     0.175     0.038     0.101   \n",
       "C-1           0.134     0.188     0.101     0.119     0.075     0.104   \n",
       "C-2           0.098     0.125     0.127     0.138     0.094     0.091   \n",
       "C-3           0.069     0.154     0.140     0.082     0.065     0.182   \n",
       "C-4           0.033     0.208     0.151     0.090     0.067     0.109   \n",
       "C-5           0.074     0.130     0.130     0.113     0.081     0.129   \n",
       "E-0           0.100     0.105     0.114     0.081     0.088     0.056   \n",
       "E-1           0.043     0.124     0.184     0.098     0.071     0.040   \n",
       "E-2           0.099     0.108     0.102     0.139     0.089     0.039   \n",
       "E-3           0.076     0.074     0.122     0.142     0.058     0.062   \n",
       "E-4           0.098     0.103     0.117     0.113     0.048     0.110   \n",
       "E-5           0.059     0.110     0.119     0.190     0.059     0.054   \n",
       "\n",
       "           tissue-6  tissue-7  tissue-8  tissue-9  \n",
       "replicate                                          \n",
       "C-0           0.069     0.014     0.102     0.115  \n",
       "C-1           0.052     0.001     0.121     0.107  \n",
       "C-2           0.134     0.017     0.080     0.096  \n",
       "C-3           0.054     0.011     0.110     0.132  \n",
       "C-4           0.064     0.003     0.160     0.115  \n",
       "C-5           0.059     0.020     0.111     0.152  \n",
       "E-0           0.120     0.087     0.167     0.081  \n",
       "E-1           0.122     0.071     0.157     0.089  \n",
       "E-2           0.115     0.092     0.158     0.059  \n",
       "E-3           0.103     0.081     0.106     0.176  \n",
       "E-4           0.113     0.104     0.166     0.027  \n",
       "E-5           0.071     0.065     0.155     0.117  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_ctrl_data = np.random.dirichlet(ctrl_tissue_props * 100, N_REPS)\n",
    "_expt_data = np.random.dirichlet(expt_tissue_props * 100, N_REPS)\n",
    "\n",
    "expr_data = (\n",
    "    pd.DataFrame(np.vstack([_ctrl_data, _expt_data]), columns=TISSUES)\n",
    "    .assign(replicate=REPS)\n",
    "    .set_index(\"replicate\")\n",
    ")\n",
    "expr_data.round(3)"
   ]
  },
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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 273,
       "width": 371
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(expr_data, vmin=0, cmap=\"seismic\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b029503-748c-454d-b8ad-f63e1b77e60f",
   "metadata": {},
   "source": [
    "The sum of the values for each replicate should be 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6748c345-6e4e-4247-8458-0a7a0df76367",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "expr_data.values.sum(axis=1)\n",
    "# > array([1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5faccc73-fd90-4e5d-9326-e4b3dd436f23",
   "metadata": {},
   "source": [
    "## Model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "39b07ea5-936c-4bab-a4b6-821f40862b84",
   "metadata": {},
   "source": [
    "### Model specification"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1a081430-e39c-4f23-b6a2-0edb028e5ac6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$$\n",
       "            \\begin{array}{rcl}\n",
       "            \\text{a} &\\sim & \\operatorname{N}(0,~5)\\\\\\text{b} &\\sim & \\operatorname{N}(0,~2.5)\\\\\\text{eta} &\\sim & \\operatorname{Deterministic}(f(\\text{b},~\\text{a}))\\\\\\text{mu} &\\sim & \\operatorname{Deterministic}(f(\\text{b},~\\text{a}))\\\\\\text{y} &\\sim & \\operatorname{Dir}(\\text{mu})\n",
       "            \\end{array}\n",
       "            $$"
      ],
      "text/plain": [
       "  a ~ N(0, 5)\n",
       "  b ~ N(0, 2.5)\n",
       "eta ~ Deterministic(f(b, a))\n",
       " mu ~ Deterministic(f(b, a))\n",
       "  y ~ Dir(mu)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coords = {\"tissue\": TISSUES, \"replicate\": REPS}\n",
    "\n",
    "intercept = np.ones_like(expr_data)\n",
    "x_expt_cond = np.vstack([np.zeros((N_REPS, N_TISSUES)), np.ones((N_REPS, N_TISSUES))])\n",
    "\n",
    "with pm.Model(coords=coords) as dirichlet_reg:\n",
    "    a = pm.Normal(\"a\", 0, 5, dims=(\"tissue\",))\n",
    "    b = pm.Normal(\"b\", 0, 2.5, dims=(\"tissue\",))\n",
    "    eta = pm.Deterministic(\n",
    "        \"eta\",\n",
    "        a[None, :] * intercept + b[None, :] * x_expt_cond,\n",
    "        dims=(\"replicate\", \"tissue\"),\n",
    "    )\n",
    "    mu = pm.Deterministic(\"mu\", pm.math.exp(eta), dims=(\"replicate\", \"tissue\"))\n",
    "    y = pm.Dirichlet(\"y\", mu, observed=expr_data.values, dims=(\"replicate\", \"tissue\"))\n",
    "\n",
    "# pm.model_to_graphviz(dirichlet_reg)\n",
    "dirichlet_reg"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b61ff27f-95cc-498c-8d52-d5078fa13926",
   "metadata": {},
   "source": [
    "### Sampling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "0aebbf66-78a6-4e39-9526-59bbf71fc3f6",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Auto-assigning NUTS sampler...\n",
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Multiprocess sampling (2 chains in 2 jobs)\n",
      "NUTS: [a, b]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "<style>\n",
       "    /* Turns off some styling */\n",
       "    progress {\n",
       "        /* gets rid of default border in Firefox and Opera. */\n",
       "        border: none;\n",
       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
       "        background-size: auto;\n",
       "    }\n",
       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
       "        background: #F44336;\n",
       "    }\n",
       "</style>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "    <div>\n",
       "      <progress value='4000' class='' max='4000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
       "      100.00% [4000/4000 00:16<00:00 Sampling 2 chains, 0 divergences]\n",
       "    </div>\n",
       "    "
      ],
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       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Sampling 2 chains for 1_000 tune and 1_000 draw iterations (2_000 + 2_000 draws total) took 29 seconds.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "<style>\n",
       "    /* Turns off some styling */\n",
       "    progress {\n",
       "        /* gets rid of default border in Firefox and Opera. */\n",
       "        border: none;\n",
       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
       "        background-size: auto;\n",
       "    }\n",
       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
       "        background: #F44336;\n",
       "    }\n",
       "</style>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "    <div>\n",
       "      <progress value='2000' class='' max='2000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
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       "    "
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       "<IPython.core.display.HTML object>"
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     },
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    }
   ],
   "source": [
    "with dirichlet_reg:\n",
    "    trace = pm.sample(\n",
    "        draws=1000, tune=1000, chains=2, cores=2, random_seed=20, target_accept=0.9\n",
    "    )\n",
    "    _ = pm.sample_posterior_predictive(trace, random_seed=43, extend_inferencedata=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "abadfe4f-1c3a-42d7-bc05-c28c19e8cdcc",
   "metadata": {},
   "source": [
    "## Posterior analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d6f8353-9d29-4b5c-a164-150a08fa7c33",
   "metadata": {},
   "source": [
    "### Recovering known parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "97b915ba-9b25-4ff5-8567-8af95de35c94",
   "metadata": {},
   "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>index</th>\n",
       "      <th>mean</th>\n",
       "      <th>sd</th>\n",
       "      <th>hdi_5.5%</th>\n",
       "      <th>hdi_94.5%</th>\n",
       "      <th>mcse_mean</th>\n",
       "      <th>mcse_sd</th>\n",
       "      <th>ess_bulk</th>\n",
       "      <th>ess_tail</th>\n",
       "      <th>r_hat</th>\n",
       "      <th>real</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>a[tissue-0]</td>\n",
       "      <td>2.122</td>\n",
       "      <td>0.240</td>\n",
       "      <td>1.735</td>\n",
       "      <td>2.490</td>\n",
       "      <td>0.012</td>\n",
       "      <td>0.009</td>\n",
       "      <td>393.0</td>\n",
       "      <td>923.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.973280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>a[tissue-1]</td>\n",
       "      <td>2.782</td>\n",
       "      <td>0.223</td>\n",
       "      <td>2.432</td>\n",
       "      <td>3.142</td>\n",
       "      <td>0.013</td>\n",
       "      <td>0.009</td>\n",
       "      <td>309.0</td>\n",
       "      <td>657.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.691607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>a[tissue-2]</td>\n",
       "      <td>2.691</td>\n",
       "      <td>0.231</td>\n",
       "      <td>2.349</td>\n",
       "      <td>3.082</td>\n",
       "      <td>0.013</td>\n",
       "      <td>0.009</td>\n",
       "      <td>334.0</td>\n",
       "      <td>566.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.618213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>a[tissue-3]</td>\n",
       "      <td>2.529</td>\n",
       "      <td>0.234</td>\n",
       "      <td>2.163</td>\n",
       "      <td>2.903</td>\n",
       "      <td>0.013</td>\n",
       "      <td>0.009</td>\n",
       "      <td>324.0</td>\n",
       "      <td>481.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.603835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>a[tissue-4]</td>\n",
       "      <td>2.009</td>\n",
       "      <td>0.247</td>\n",
       "      <td>1.648</td>\n",
       "      <td>2.435</td>\n",
       "      <td>0.013</td>\n",
       "      <td>0.009</td>\n",
       "      <td>399.0</td>\n",
       "      <td>586.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.006772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>a[tissue-5]</td>\n",
       "      <td>2.538</td>\n",
       "      <td>0.231</td>\n",
       "      <td>2.180</td>\n",
       "      <td>2.906</td>\n",
       "      <td>0.013</td>\n",
       "      <td>0.009</td>\n",
       "      <td>322.0</td>\n",
       "      <td>641.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.465910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>a[tissue-6]</td>\n",
       "      <td>2.015</td>\n",
       "      <td>0.250</td>\n",
       "      <td>1.653</td>\n",
       "      <td>2.435</td>\n",
       "      <td>0.013</td>\n",
       "      <td>0.009</td>\n",
       "      <td>363.0</td>\n",
       "      <td>804.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.118144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>a[tissue-7]</td>\n",
       "      <td>0.159</td>\n",
       "      <td>0.324</td>\n",
       "      <td>-0.334</td>\n",
       "      <td>0.690</td>\n",
       "      <td>0.012</td>\n",
       "      <td>0.008</td>\n",
       "      <td>828.0</td>\n",
       "      <td>1068.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.407652</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>a[tissue-8]</td>\n",
       "      <td>2.497</td>\n",
       "      <td>0.230</td>\n",
       "      <td>2.123</td>\n",
       "      <td>2.843</td>\n",
       "      <td>0.013</td>\n",
       "      <td>0.009</td>\n",
       "      <td>328.0</td>\n",
       "      <td>568.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.484808</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>a[tissue-9]</td>\n",
       "      <td>2.552</td>\n",
       "      <td>0.234</td>\n",
       "      <td>2.198</td>\n",
       "      <td>2.930</td>\n",
       "      <td>0.013</td>\n",
       "      <td>0.009</td>\n",
       "      <td>333.0</td>\n",
       "      <td>688.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.281616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>b[tissue-0]</td>\n",
       "      <td>0.010</td>\n",
       "      <td>0.335</td>\n",
       "      <td>-0.507</td>\n",
       "      <td>0.549</td>\n",
       "      <td>0.016</td>\n",
       "      <td>0.011</td>\n",
       "      <td>435.0</td>\n",
       "      <td>810.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.089065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>b[tissue-1]</td>\n",
       "      <td>-0.351</td>\n",
       "      <td>0.313</td>\n",
       "      <td>-0.841</td>\n",
       "      <td>0.161</td>\n",
       "      <td>0.016</td>\n",
       "      <td>0.011</td>\n",
       "      <td>401.0</td>\n",
       "      <td>852.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.353870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>b[tissue-2]</td>\n",
       "      <td>-0.086</td>\n",
       "      <td>0.313</td>\n",
       "      <td>-0.636</td>\n",
       "      <td>0.372</td>\n",
       "      <td>0.015</td>\n",
       "      <td>0.011</td>\n",
       "      <td>413.0</td>\n",
       "      <td>680.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.009744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>b[tissue-3]</td>\n",
       "      <td>0.065</td>\n",
       "      <td>0.318</td>\n",
       "      <td>-0.445</td>\n",
       "      <td>0.560</td>\n",
       "      <td>0.016</td>\n",
       "      <td>0.011</td>\n",
       "      <td>409.0</td>\n",
       "      <td>746.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.099328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>b[tissue-4]</td>\n",
       "      <td>0.009</td>\n",
       "      <td>0.334</td>\n",
       "      <td>-0.535</td>\n",
       "      <td>0.528</td>\n",
       "      <td>0.015</td>\n",
       "      <td>0.011</td>\n",
       "      <td>486.0</td>\n",
       "      <td>884.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.184059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>b[tissue-5]</td>\n",
       "      <td>-0.682</td>\n",
       "      <td>0.324</td>\n",
       "      <td>-1.191</td>\n",
       "      <td>-0.160</td>\n",
       "      <td>0.016</td>\n",
       "      <td>0.011</td>\n",
       "      <td>433.0</td>\n",
       "      <td>743.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.720852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>b[tissue-6]</td>\n",
       "      <td>0.437</td>\n",
       "      <td>0.331</td>\n",
       "      <td>-0.082</td>\n",
       "      <td>0.987</td>\n",
       "      <td>0.016</td>\n",
       "      <td>0.011</td>\n",
       "      <td>423.0</td>\n",
       "      <td>759.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.162447</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>b[tissue-7]</td>\n",
       "      <td>2.045</td>\n",
       "      <td>0.389</td>\n",
       "      <td>1.443</td>\n",
       "      <td>2.676</td>\n",
       "      <td>0.015</td>\n",
       "      <td>0.010</td>\n",
       "      <td>703.0</td>\n",
       "      <td>1041.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.981890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>b[tissue-8]</td>\n",
       "      <td>0.298</td>\n",
       "      <td>0.306</td>\n",
       "      <td>-0.189</td>\n",
       "      <td>0.795</td>\n",
       "      <td>0.016</td>\n",
       "      <td>0.011</td>\n",
       "      <td>390.0</td>\n",
       "      <td>761.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.085959</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>b[tissue-9]</td>\n",
       "      <td>-0.384</td>\n",
       "      <td>0.325</td>\n",
       "      <td>-0.876</td>\n",
       "      <td>0.143</td>\n",
       "      <td>0.016</td>\n",
       "      <td>0.011</td>\n",
       "      <td>423.0</td>\n",
       "      <td>797.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.129034</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          index   mean     sd  hdi_5.5%  hdi_94.5%  mcse_mean  mcse_sd  \\\n",
       "0   a[tissue-0]  2.122  0.240     1.735      2.490      0.012    0.009   \n",
       "1   a[tissue-1]  2.782  0.223     2.432      3.142      0.013    0.009   \n",
       "2   a[tissue-2]  2.691  0.231     2.349      3.082      0.013    0.009   \n",
       "3   a[tissue-3]  2.529  0.234     2.163      2.903      0.013    0.009   \n",
       "4   a[tissue-4]  2.009  0.247     1.648      2.435      0.013    0.009   \n",
       "5   a[tissue-5]  2.538  0.231     2.180      2.906      0.013    0.009   \n",
       "6   a[tissue-6]  2.015  0.250     1.653      2.435      0.013    0.009   \n",
       "7   a[tissue-7]  0.159  0.324    -0.334      0.690      0.012    0.008   \n",
       "8   a[tissue-8]  2.497  0.230     2.123      2.843      0.013    0.009   \n",
       "9   a[tissue-9]  2.552  0.234     2.198      2.930      0.013    0.009   \n",
       "10  b[tissue-0]  0.010  0.335    -0.507      0.549      0.016    0.011   \n",
       "11  b[tissue-1] -0.351  0.313    -0.841      0.161      0.016    0.011   \n",
       "12  b[tissue-2] -0.086  0.313    -0.636      0.372      0.015    0.011   \n",
       "13  b[tissue-3]  0.065  0.318    -0.445      0.560      0.016    0.011   \n",
       "14  b[tissue-4]  0.009  0.334    -0.535      0.528      0.015    0.011   \n",
       "15  b[tissue-5] -0.682  0.324    -1.191     -0.160      0.016    0.011   \n",
       "16  b[tissue-6]  0.437  0.331    -0.082      0.987      0.016    0.011   \n",
       "17  b[tissue-7]  2.045  0.389     1.443      2.676      0.015    0.010   \n",
       "18  b[tissue-8]  0.298  0.306    -0.189      0.795      0.016    0.011   \n",
       "19  b[tissue-9] -0.384  0.325    -0.876      0.143      0.016    0.011   \n",
       "\n",
       "    ess_bulk  ess_tail  r_hat      real  \n",
       "0      393.0     923.0    1.0  1.973280  \n",
       "1      309.0     657.0    1.0  2.691607  \n",
       "2      334.0     566.0    1.0  2.618213  \n",
       "3      324.0     481.0    1.0  2.603835  \n",
       "4      399.0     586.0    1.0  2.006772  \n",
       "5      322.0     641.0    1.0  2.465910  \n",
       "6      363.0     804.0    1.0  2.118144  \n",
       "7      828.0    1068.0    1.0  0.407652  \n",
       "8      328.0     568.0    1.0  2.484808  \n",
       "9      333.0     688.0    1.0  2.281616  \n",
       "10     435.0     810.0    1.0 -0.089065  \n",
       "11     401.0     852.0    1.0 -0.353870  \n",
       "12     413.0     680.0    1.0  0.009744  \n",
       "13     409.0     746.0    1.0  0.099328  \n",
       "14     486.0     884.0    1.0 -0.184059  \n",
       "15     433.0     743.0    1.0 -0.720852  \n",
       "16     423.0     759.0    1.0  0.162447  \n",
       "17     703.0    1041.0    1.0  1.981890  \n",
       "18     390.0     761.0    1.0  0.085959  \n",
       "19     423.0     797.0    1.0 -0.129034  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "real_a = np.log(ctrl_tissue_props * 100)\n",
    "real_b = np.log(expt_tissue_props * 100) - real_a\n",
    "\n",
    "res_summary = (\n",
    "    az.summary(trace, var_names=[\"a\", \"b\"], hdi_prob=0.89)\n",
    "    .assign(real=np.hstack([real_a, real_b]))\n",
    "    .reset_index()\n",
    ")\n",
    "res_summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "cd19d6c0-ee16-460b-8d82-4aef8035b471",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 316,
       "width": 417
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_, ax = plt.subplots(figsize=(5, 5))\n",
    "sns.scatterplot(\n",
    "    data=res_summary,\n",
    "    y=\"index\",\n",
    "    x=\"mean\",\n",
    "    color=\"tab:blue\",\n",
    "    ax=ax,\n",
    "    zorder=10,\n",
    "    label=\"est.\",\n",
    ")\n",
    "ax.hlines(\n",
    "    res_summary[\"index\"],\n",
    "    xmin=res_summary[\"hdi_5.5%\"],\n",
    "    xmax=res_summary[\"hdi_94.5%\"],\n",
    "    color=\"tab:blue\",\n",
    "    alpha=0.5,\n",
    "    zorder=5,\n",
    ")\n",
    "sns.scatterplot(\n",
    "    data=res_summary,\n",
    "    y=\"index\",\n",
    "    x=\"real\",\n",
    "    ax=ax,\n",
    "    color=\"tab:orange\",\n",
    "    zorder=20,\n",
    "    label=\"real\",\n",
    ")\n",
    "ax.legend(loc=\"upper left\", bbox_to_anchor=(1, 1))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b17c85f7-97a4-4bb4-aa05-1d9ad669783e",
   "metadata": {},
   "source": [
    "### Posterior predictive distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "8730e90b-7a34-4d99-92ed-e215c82110e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x105b11de0>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 424,
       "width": 401
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "post_pred = (\n",
    "    trace.posterior_predictive[\"y\"]\n",
    "    .to_dataframe()\n",
    "    .reset_index()\n",
    "    .filter_column_isin(\"replicate\", [\"C-0\", \"E-0\"])\n",
    "    .assign(condition=lambda d: [x[0] for x in d[\"replicate\"]])\n",
    ")\n",
    "\n",
    "plot_expr_data = (\n",
    "    expr_data.copy()\n",
    "    .reset_index()\n",
    "    .pivot_longer(\"replicate\", names_to=\"tissue\", values_to=\"expr\")\n",
    "    .assign(condition=lambda d: [x[0] for x in d[\"replicate\"]])\n",
    ")\n",
    "\n",
    "violin_pal = {\"C\": \"#cab2d6\", \"E\": \"#b2df8a\"}\n",
    "point_pal = {\"C\": \"#6a3d9a\", \"E\": \"#33a02c\"}\n",
    "\n",
    "_, ax = plt.subplots(figsize=(5, 7))\n",
    "sns.violinplot(\n",
    "    data=post_pred,\n",
    "    x=\"y\",\n",
    "    y=\"tissue\",\n",
    "    hue=\"condition\",\n",
    "    palette=violin_pal,\n",
    "    linewidth=0.5,\n",
    "    ax=ax,\n",
    ")\n",
    "sns.stripplot(\n",
    "    data=plot_expr_data,\n",
    "    x=\"expr\",\n",
    "    y=\"tissue\",\n",
    "    hue=\"condition\",\n",
    "    palette=point_pal,\n",
    "    dodge=True,\n",
    "    ax=ax,\n",
    ")\n",
    "ax.legend(loc=\"upper left\", bbox_to_anchor=(1, 1), title=\"condition\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6fa6e97c-a538-4006-8f05-2652f5f26362",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "## Session Info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c4a1a983-0bc9-4f64-b0cb-1f62edd5c2b4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Last updated: 2022-11-09\n",
      "\n",
      "Python implementation: CPython\n",
      "Python version       : 3.10.6\n",
      "IPython version      : 8.4.0\n",
      "\n",
      "Compiler    : Clang 13.0.1 \n",
      "OS          : Darwin\n",
      "Release     : 21.6.0\n",
      "Machine     : x86_64\n",
      "Processor   : i386\n",
      "CPU cores   : 4\n",
      "Architecture: 64bit\n",
      "\n",
      "Hostname: JHCookMac.local\n",
      "\n",
      "Git branch: sex-diff-expr-better\n",
      "\n",
      "matplotlib: 3.5.3\n",
      "pandas    : 1.4.4\n",
      "numpy     : 1.21.6\n",
      "arviz     : 0.12.1\n",
      "pymc      : 4.1.5\n",
      "janitor   : 0.22.0\n",
      "seaborn   : 0.11.2\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%load_ext watermark\n",
    "%watermark -d -u -v -iv -b -h -m"
   ]
  }
 ],
 "metadata": {
  "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": "3.10.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}

If it makes sense for the given model, adding hierarchical prior distributions on $a$ and $b$ can improve stability and accuracy.