visualize_aa_diff.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from pyopenms import MSExperiment, MzMLFile\n",
    "from concurrent.futures import ProcessPoolExecutor\n",
    "from tqdm import tqdm\n",
    "from matplotlib import pyplot as plt\n",
    "import pickle\n",
    "\n",
    "from mzml_pdiff import load_from_csv\n",
    "from mzml_pdiff import save_to_csv\n",
    "from mzml_pdiff import process_file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "dir_analyze = \"data/\"\n",
    "\n",
    "amino_acid_masses_delta = {\n",
    "    \"G\": 57.02146,\n",
    "    \"A\": 71.03711,\n",
    "    \"S\": 87.03203,\n",
    "    \"P\": 97.05276,\n",
    "    \"V\": 99.06841,\n",
    "    \"T\": 101.04768,\n",
    "    \"C\": 103.00919,\n",
    "    \"L\": 113.08406,\n",
    "    \"I\": 113.08406,\n",
    "    \"N\": 114.04293,\n",
    "    \"D\": 115.02694,\n",
    "    \"Q\": 128.05858,\n",
    "    \"K\": 128.09496,\n",
    "    \"E\": 129.04259,\n",
    "    \"M\": 131.04049,\n",
    "    \"H\": 137.05891,\n",
    "    \"F\": 147.06841,\n",
    "    \"R\": 156.10111,\n",
    "    \"Y\": 163.06333,\n",
    "    \"W\": 186.07931,\n",
    "    \"C[Carbamidomethyl]\": 57.0215,  # Example for \"C with carbamidomethyl modification\":\n",
    "    \"K[methyl]\": 142.1267,  # Example for \"K with methyl modification\":\n",
    "    \"Q[Pyro-glu]\": 128.0586,  # Example for \"Q with pyro-glu modification\":\n",
    "    \"K[Dimethyl]\": 156.1406,  # Example for \"K with dimethyl modification\":\n",
    "    \"S[Phospho]\": 166.9987,  # Example for \"S with phospho modification\":\n",
    "    \"T[Phospho]\": 181.0147,  # Example for \"T with phospho modification\":\n",
    "    \"Y[Phospho]\": 243.0297,  # Example for \"Y with phospho modification\":\n",
    "    \"K[Trimethyl]\": 170.1545,  # Example for \"K with trimethyl modification\":\n",
    "    \"K[Acetyl]\": 170.1055,  # Example for \"K with acetyl modification\":\n",
    "    \"N[Deamidated]\": 115.0270,  # Example for \"N with deamidated modification\":\n",
    "    \"K[Propionyl]\": 184.1194,  # Example for \"K with propionyl modification\":\n",
    "    \"K[Butyryl]\": 198.1333,  # Example for \"K with butyryl modification\":\n",
    "    \"K[Formyl]\": 168.0892,  # Example for \"K with formyl modification\":\n",
    "    \"K[Oxidation]\": 144.1059,  # Example for \"K with oxidation modification\":\n",
    "    \"K[Malonyl]\": 184.1055,  # Example for \"K with malonyl modification\":\n",
    "    \"K[Succinyl]\": 198.1194,  # Example for \"K with succinyl modification\":\n",
    "    \"R[Methyl]\": 170.0914,  # Example for \"R with methyl modification\":\n",
    "    \"R[Dimethyl]\": 184.1053,  # Example for \"R with dimethyl modification\":\n",
    "    \"R[Trimethyl]\": 198.1192,  # Example for \"R with trimethyl modification\":\n",
    "    \"Q[Deamidated]\": 115.0270,  # Example for \"Q with deamidated modification\":\n",
    "    \"N[Oxidation]\": 115.0269,  # Example for \"N with oxidation modification\":\n",
    "    \"M[Oxidation]\": 147.0354,  # Example for \"M with oxidation modification\":\n",
    "    \"H[Oxidation]\": 153.0192,  # Example for \"H with oxidation modification\":\n",
    "    \"M[Carbamylation]\": 125.0477,  # Example for \"M with carbamylation modification\":\n",
    "    \"N[Amonia-loss]\": 113.0473,  # Example for \"N with ammonia-loss modification\":\n",
    "    \"R[Amonia-loss]\": 129.0426,  # Example for \"R with ammonia-loss modification\":\n",
    "    \"Q[Amonia-loss]\": 114.0429,  # Example for \"Q with ammonia-loss modification\":\n",
    "    \"N[Pyro-glu]\": 128.0586,  # Example for \"N with pyro-glu modification\":\n",
    "    \"K[Pyro-glu]\": 128.0949,  # Example for \"K with pyro-glu modification\":\n",
    "    \"R[Pyro-glu]\": 156.1011,  # Example for \"R with pyro-glu modification\":\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_dict = {}\n",
    "for f in os.listdir(dir_analyze):\n",
    "    if not f.endswith(\"_intensities_aa_delta_single_mod.csv\"):\n",
    "        continue\n",
    "    \n",
    "    df = pd.read_csv(os.path.join(dir_analyze, f))\n",
    "    df.index = map(str, df.index)\n",
    "    df.index = df.index + \"|\" + f\n",
    "    df_dict[f] = df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dia_key = \"LFQ_Orbitrap_AIF_Human_01_intensities_aa_delta_single_mod.csv\"\n",
    "dda_key = \"LFQ_Orbitrap_DDA_Human_01_intensities_aa_delta_single_mod.csv\"\n",
    "\n",
    "# Initialize the figure and axis for the plot\n",
    "plt.figure(figsize=(10, 5))\n",
    "ax = plt.gca()\n",
    "\n",
    "# Lists to store values for plotting the differential\n",
    "indices = []\n",
    "dia_median_list = []\n",
    "dda_median_list = []\n",
    "\n",
    "for i in range(20, len(amino_acid_masses_delta.keys()) + 1):\n",
    "    selected_cols = list(amino_acid_masses_delta.keys())[0:i]\n",
    "\n",
    "    # Calculate the sums of the selected columns\n",
    "    dia_count_all = df_dict[dia_key][selected_cols].sum(axis=1)\n",
    "    dda_count_all = df_dict[dda_key][selected_cols].sum(axis=1)\n",
    "\n",
    "    # Calculate medians for sums greater than 10\n",
    "    dia_median = dia_count_all[dia_count_all > 10].median()\n",
    "    dda_median = dda_count_all[dda_count_all > 10].median()\n",
    "\n",
    "    # Plot each median\n",
    "    plt.scatter(i, dia_median, c=\"red\", label=\"DIA\" if i == 20 else \"\", alpha=0.5, s=15)\n",
    "    plt.scatter(\n",
    "        i, dda_median, c=\"blue\", label=\"DDA\" if i == 20 else \"\", alpha=0.5, s=15\n",
    "    )\n",
    "\n",
    "    dia_median_list.append(dia_median)\n",
    "    dda_median_list.append(dda_median)\n",
    "\n",
    "plt.plot(range(20, len(amino_acid_masses_delta.keys()) + 1), dia_median_list, c=\"red\")\n",
    "plt.plot(range(20, len(amino_acid_masses_delta.keys()) + 1), dda_median_list, c=\"blue\")\n",
    "\n",
    "# Setting the plot limits, labels, title, and legend\n",
    "plt.ylim(0, 1000)\n",
    "plt.xlabel(\"Number of Selected Columns\")\n",
    "plt.ylabel(\"Median of Summed Values\")\n",
    "plt.title(\"Empirical Differential of Summed Values Over Columns\")\n",
    "plt.legend()\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.patches import Patch\n",
    "\n",
    "dia_key = \"LFQ_Orbitrap_AIF_Human_01_intensities_aa_delta_single_mod.csv\"\n",
    "dda_key = \"LFQ_Orbitrap_DDA_Human_01_intensities_aa_delta_single_mod.csv\"\n",
    "\n",
    "# Initialize the figure and axis for the plot\n",
    "plt.figure(figsize=(10, 5))\n",
    "ax = plt.gca()\n",
    "\n",
    "# Lists to store values for plotting the distributions\n",
    "dia_values = []\n",
    "dda_values = []\n",
    "labels = []\n",
    "\n",
    "for i in range(20, len(amino_acid_masses_delta.keys()) + 1):\n",
    "    selected_cols = list(amino_acid_masses_delta.keys())[0:i]\n",
    "\n",
    "    # Calculate the sums of the selected columns\n",
    "    dia_count_all = df_dict[dia_key][selected_cols].sum(axis=1)\n",
    "    dda_count_all = df_dict[dda_key][selected_cols].sum(axis=1)\n",
    "\n",
    "    # Filter sums greater than 10 and collect values\n",
    "    dia_values.append(dia_count_all[dia_count_all > 10].values)\n",
    "    dda_values.append(dda_count_all[dda_count_all > 10].values)\n",
    "\n",
    "    labels.append(str(i))\n",
    "\n",
    "# Plotting boxplots\n",
    "positions_dia = [x - 0.2 for x in range(20, len(amino_acid_masses_delta.keys()) + 1)]\n",
    "positions_dda = [x + 0.2 for x in range(20, len(amino_acid_masses_delta.keys()) + 1)]\n",
    "central_positions = [x for x in range(20, len(amino_acid_masses_delta.keys()) + 1)]\n",
    "\n",
    "ax.boxplot(\n",
    "    dia_values,\n",
    "    positions=positions_dia,\n",
    "    widths=0.4,\n",
    "    patch_artist=True,\n",
    "    boxprops=dict(facecolor=\"red\"),\n",
    "    medianprops=dict(color=\"black\"),\n",
    "    showfliers=False,\n",
    ")\n",
    "ax.boxplot(\n",
    "    dda_values,\n",
    "    positions=positions_dda,\n",
    "    widths=0.4,\n",
    "    patch_artist=True,\n",
    "    boxprops=dict(facecolor=\"blue\"),\n",
    "    medianprops=dict(color=\"black\"),\n",
    "    showfliers=False,\n",
    ")\n",
    "\n",
    "# Custom legend\n",
    "legend_elements = [\n",
    "    Patch(facecolor=\"red\", edgecolor=\"black\", label=\"DIA\"),\n",
    "    Patch(facecolor=\"blue\", edgecolor=\"black\", label=\"DDA\"),\n",
    "]\n",
    "ax.legend(handles=legend_elements, loc=\"upper left\")\n",
    "\n",
    "# Setting the plot limits, labels, title, and x-ticks\n",
    "ax.set_ylim(0, 4000)\n",
    "ax.set_xlabel(\"Number of Selected Columns\")\n",
    "ax.set_ylabel(\"Summed Values\")\n",
    "ax.set_title(\"Empirical Differential of Summed Values Over Columns\")\n",
    "ax.set_xticks(central_positions)\n",
    "ax.set_xticklabels(labels, rotation=45)\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  }
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