{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "ee0d797b",
   "metadata": {},
   "source": [
    "# Tissue-specific proteoform inference across five mouse organs\n",
    "\n",
    "This notebook shows how to use ProteoPy for proteoform group inference following a previously established approach that we published in Bludau et al. (2021):\n",
    "\n",
    "> Bludau I, Frank M, Dörig C, Cai Y, Heusel M, Rosenberger G, Picotti P, Collins BC, Röst H, and Aebersold R. **Systematic detection of functional proteoform groups from bottom-up proteomic datasets.** *Nature Communications*, 12:3810, 2021. [doi:10.1038/s41467-021-24030-x](https://doi.org/10.1038/s41467-021-24030-x)\n",
    "\n",
    "In this paper, we introduced COPF (COrrelation-based functional ProteoForm assessment), a data-driven strategy that assigns peptides to co-varying proteoform groups based on peptide correlation patterns. It was applied to SWATH-MS (DIA) data from five mouse tissues (brain, brown adipose tissue, heart, liver, and quadriceps) across eight BXD mice, originally published by Williams et al. (2018):\n",
    "\n",
    "> Williams EG, Wu Y, Wolski W, Kim JY, Lan J, Hasan M, Halter C, Jha P, Ryu D, Auwerx J, and Aebersold R. **Quantifying and Localizing the Mitochondrial Proteome Across Five Tissues in A Mouse Population.** *Molecular & Cellular Proteomics*, 17(9):1766–1777, 2018. [doi:10.1074/mcp.RA118.000554](https://doi.org/10.1074/mcp.RA118.000554)\n",
    "\n",
    "In this notebook, we show how the COPF implementation in ProteoPy can be used to perform the core proteoform inference workflow."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "nqku72pdj79",
   "metadata": {},
   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2bafc259",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/isabell/miniconda3/envs/proteopy/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n"
     ]
    }
   ],
   "source": [
    "import random\n",
    "from pathlib import Path\n",
    "import numpy as np\n",
    "import scanpy as sc\n",
    "import matplotlib as mpl\n",
    "from matplotlib.pyplot import rc_context\n",
    "\n",
    "import proteopy as pr  # Convention: import proteopy as pr\n",
    "from proteopy.utils import is_proteodata\n",
    "\n",
    "# Set random seed for reproducibility\n",
    "random.seed(42)\n",
    "\n",
    "# Create a data directory in your current working directory \n",
    "# to store files downloaded in this notebook.\n",
    "cwd = Path(\".\").resolve()\n",
    "(cwd / 'data').mkdir(parents=True, exist_ok=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "03c559b7",
   "metadata": {},
   "source": [
    "## Reading in the data\n",
    "\n",
    "The Williams et al. (2018) dataset contains peptide-level SWATH-MS intensities from five tissues of eight BXD mice. ProteoPy provides a built-in download function (`pr.download.williams_2018()`) that fetches the dataset from the original supplementary archive, processes it, and saves it as three separate files:\n",
    "\n",
    "- **Intensities** — long-format table with columns `sample_id`, `peptide_id`, and `intensity` (one row per measurement)\n",
    "- **Sample annotation** — maps each `sample_id` to its `tissue` and `mouse_id`\n",
    "- **Peptide annotation** — maps each `peptide_id` to its `protein_id` and `gene_id`\n",
    "\n",
    "This separation into three files mirrors a common data delivery format in proteomics. The files are then read into an AnnData object using `pr.read.long()`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d68b55d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define paths to the data files. These are the same paths that will be used in the download function below.\n",
    "intensities_path = \"data/williams-2018_mouse-tissue_intensities.tsv\"\n",
    "sample_annotation_path = \"data/williams-2018_mouse-tissue_sample_annotation.tsv\"\n",
    "peptide_annotation_path = \"data/williams-2018_mouse-tissue_peptide_annotation.tsv\"\n",
    "\n",
    "pr.download.williams_2018(\n",
    "    intensities_path=intensities_path,\n",
    "    sample_annotation_path=sample_annotation_path,\n",
    "    var_annotation_path=peptide_annotation_path,\n",
    "    force=True,  # Overwrite files if already exist\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "jszc7mlblu9",
   "metadata": {},
   "source": [
    "A quick look at the first rows of each file shows the data format ProteoPy expects for each information layer:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0ede6e75",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sample_id\tpeptide_id\tintensity\n",
      "C57_Brain\tAAAAAAAAAAAAAAAGAAGK\t26302.0\n",
      "DBA_Brain\tAAAAAAAAAAAAAAAGAAGK\t15460.0\n",
      "45_Brain\tAAAAAAAAAAAAAAAGAAGK\t24631.0\n",
      "66_Brain\tAAAAAAAAAAAAAAAGAAGK\t26554.0\n"
     ]
    }
   ],
   "source": [
    "# intensities\n",
    "!head -n5 {intensities_path}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "cfbf3627",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sample_id\ttissue\tmouse_id\n",
      "C57_Brain\tBrain\tC57\n",
      "DBA_Brain\tBrain\tDBA\n",
      "45_Brain\tBrain\t45\n",
      "66_Brain\tBrain\t66\n"
     ]
    }
   ],
   "source": [
    "# sample_annotation\n",
    "!head -n5 {sample_annotation_path}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "b6d872a8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "peptide_id\tprotein_id\tgene_id\n",
      "AAAAAAAAAAAAAAAGAAGK\tP55012\tSlc12a2\n",
      "AAAAADLANR\tQ9JHS4\tClpx\n",
      "AAAADGEPLHNEEER\tQ80WW9\tDdrgk1\n",
      "AAAAEGARPLER\tQ80UM7\tMogs\n"
     ]
    }
   ],
   "source": [
    "# var_annotation\n",
    "!head -n5 {peptide_annotation_path}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "sa0gtgqxej",
   "metadata": {},
   "source": [
    "With the three files on disk, `pr.read.long()` reads the long-format intensities, pivots them into a dense matrix, and merges the sample and peptide annotations into a single AnnData object. Setting `fill_na=0` replaces any missing intensity values with zero."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "981576e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AnnData object with n_obs × n_vars = 40 × 32690\n",
       "    obs: 'sample_id', 'tissue', 'mouse_id'\n",
       "    var: 'peptide_id', 'protein_id', 'protein_id_annotation', 'gene_id'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a peptide level AnnData object from the \n",
    "# downloaded data files and fill missing values with 0.\n",
    "adata = pr.read.long(\n",
    "    intensities=intensities_path,\n",
    "    sample_annotation=sample_annotation_path,\n",
    "    var_annotation=peptide_annotation_path,\n",
    "    level=\"peptide\",\n",
    "    fill_na=0,\n",
    ")\n",
    "\n",
    "adata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "795e2296",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Is proteodata:  (True, 'peptide')\n"
     ]
    }
   ],
   "source": [
    "print(\"Is proteodata: \", is_proteodata(adata))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "95d976af",
   "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",
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       "    }\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>sample_id</th>\n",
       "      <th>tissue</th>\n",
       "      <th>mouse_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>101_Brain</th>\n",
       "      <td>101_Brain</td>\n",
       "      <td>Brain</td>\n",
       "      <td>101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45_Brain</th>\n",
       "      <td>45_Brain</td>\n",
       "      <td>Brain</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66_Brain</th>\n",
       "      <td>66_Brain</td>\n",
       "      <td>Brain</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68_Brain</th>\n",
       "      <td>68_Brain</td>\n",
       "      <td>Brain</td>\n",
       "      <td>68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73_Brain</th>\n",
       "      <td>73_Brain</td>\n",
       "      <td>Brain</td>\n",
       "      <td>73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80_Brain</th>\n",
       "      <td>80_Brain</td>\n",
       "      <td>Brain</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BAT_101</th>\n",
       "      <td>BAT_101</td>\n",
       "      <td>BAT</td>\n",
       "      <td>101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BAT_45</th>\n",
       "      <td>BAT_45</td>\n",
       "      <td>BAT</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BAT_66</th>\n",
       "      <td>BAT_66</td>\n",
       "      <td>BAT</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BAT_68</th>\n",
       "      <td>BAT_68</td>\n",
       "      <td>BAT</td>\n",
       "      <td>68</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           sample_id tissue mouse_id\n",
       "101_Brain  101_Brain  Brain      101\n",
       "45_Brain    45_Brain  Brain       45\n",
       "66_Brain    66_Brain  Brain       66\n",
       "68_Brain    68_Brain  Brain       68\n",
       "73_Brain    73_Brain  Brain       73\n",
       "80_Brain    80_Brain  Brain       80\n",
       "BAT_101      BAT_101    BAT      101\n",
       "BAT_45        BAT_45    BAT       45\n",
       "BAT_66        BAT_66    BAT       66\n",
       "BAT_68        BAT_68    BAT       68"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adata.obs.head(n=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "72b2377c",
   "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>peptide_id</th>\n",
       "      <th>protein_id</th>\n",
       "      <th>protein_id_annotation</th>\n",
       "      <th>gene_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AAAAAAAAAAAAAAAGAAGK</th>\n",
       "      <td>AAAAAAAAAAAAAAAGAAGK</td>\n",
       "      <td>P55012</td>\n",
       "      <td>P55012</td>\n",
       "      <td>Slc12a2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAAAADLANR</th>\n",
       "      <td>AAAAADLANR</td>\n",
       "      <td>Q9JHS4</td>\n",
       "      <td>Q9JHS4</td>\n",
       "      <td>Clpx</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAAADGEPLHNEEER</th>\n",
       "      <td>AAAADGEPLHNEEER</td>\n",
       "      <td>Q80WW9</td>\n",
       "      <td>Q80WW9</td>\n",
       "      <td>Ddrgk1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAAAEGARPLER</th>\n",
       "      <td>AAAAEGARPLER</td>\n",
       "      <td>Q80UM7</td>\n",
       "      <td>Q80UM7</td>\n",
       "      <td>Mogs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAAAKEEAPK</th>\n",
       "      <td>AAAAKEEAPK</td>\n",
       "      <td>Q91XV3</td>\n",
       "      <td>Q91XV3</td>\n",
       "      <td>Basp1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAAANLC(UniMod:4)PGDVILAIDGFGTESMTHADAQDR</th>\n",
       "      <td>AAAANLC(UniMod:4)PGDVILAIDGFGTESMTHADAQDR</td>\n",
       "      <td>O70209</td>\n",
       "      <td>O70209</td>\n",
       "      <td>Pdlim3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAAAYALGR</th>\n",
       "      <td>AAAAYALGR</td>\n",
       "      <td>Q6ZQ73</td>\n",
       "      <td>Q6ZQ73</td>\n",
       "      <td>Cand2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAADLM(UniMod:35)AYC(UniMod:4)EAHAKEDPLLTPVPASENPFR</th>\n",
       "      <td>AAADLM(UniMod:35)AYC(UniMod:4)EAHAKEDPLLTPVPAS...</td>\n",
       "      <td>P63213</td>\n",
       "      <td>P63213</td>\n",
       "      <td>Gng2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAADLMAYC(UniMod:4)EAHAK</th>\n",
       "      <td>AAADLMAYC(UniMod:4)EAHAK</td>\n",
       "      <td>P63213</td>\n",
       "      <td>P63213</td>\n",
       "      <td>Gng2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAADLMAYC(UniMod:4)EAHAKEDPLLTPVPASENPFR</th>\n",
       "      <td>AAADLMAYC(UniMod:4)EAHAKEDPLLTPVPASENPFR</td>\n",
       "      <td>P63213</td>\n",
       "      <td>P63213</td>\n",
       "      <td>Gng2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                                           peptide_id  \\\n",
       "AAAAAAAAAAAAAAAGAAGK                                                             AAAAAAAAAAAAAAAGAAGK   \n",
       "AAAAADLANR                                                                                 AAAAADLANR   \n",
       "AAAADGEPLHNEEER                                                                       AAAADGEPLHNEEER   \n",
       "AAAAEGARPLER                                                                             AAAAEGARPLER   \n",
       "AAAAKEEAPK                                                                                 AAAAKEEAPK   \n",
       "AAAANLC(UniMod:4)PGDVILAIDGFGTESMTHADAQDR                   AAAANLC(UniMod:4)PGDVILAIDGFGTESMTHADAQDR   \n",
       "AAAAYALGR                                                                                   AAAAYALGR   \n",
       "AAADLM(UniMod:35)AYC(UniMod:4)EAHAKEDPLLTPVPASE...  AAADLM(UniMod:35)AYC(UniMod:4)EAHAKEDPLLTPVPAS...   \n",
       "AAADLMAYC(UniMod:4)EAHAK                                                     AAADLMAYC(UniMod:4)EAHAK   \n",
       "AAADLMAYC(UniMod:4)EAHAKEDPLLTPVPASENPFR                     AAADLMAYC(UniMod:4)EAHAKEDPLLTPVPASENPFR   \n",
       "\n",
       "                                                   protein_id  \\\n",
       "AAAAAAAAAAAAAAAGAAGK                                   P55012   \n",
       "AAAAADLANR                                             Q9JHS4   \n",
       "AAAADGEPLHNEEER                                        Q80WW9   \n",
       "AAAAEGARPLER                                           Q80UM7   \n",
       "AAAAKEEAPK                                             Q91XV3   \n",
       "AAAANLC(UniMod:4)PGDVILAIDGFGTESMTHADAQDR              O70209   \n",
       "AAAAYALGR                                              Q6ZQ73   \n",
       "AAADLM(UniMod:35)AYC(UniMod:4)EAHAKEDPLLTPVPASE...     P63213   \n",
       "AAADLMAYC(UniMod:4)EAHAK                               P63213   \n",
       "AAADLMAYC(UniMod:4)EAHAKEDPLLTPVPASENPFR               P63213   \n",
       "\n",
       "                                                   protein_id_annotation  \\\n",
       "AAAAAAAAAAAAAAAGAAGK                                              P55012   \n",
       "AAAAADLANR                                                        Q9JHS4   \n",
       "AAAADGEPLHNEEER                                                   Q80WW9   \n",
       "AAAAEGARPLER                                                      Q80UM7   \n",
       "AAAAKEEAPK                                                        Q91XV3   \n",
       "AAAANLC(UniMod:4)PGDVILAIDGFGTESMTHADAQDR                         O70209   \n",
       "AAAAYALGR                                                         Q6ZQ73   \n",
       "AAADLM(UniMod:35)AYC(UniMod:4)EAHAKEDPLLTPVPASE...                P63213   \n",
       "AAADLMAYC(UniMod:4)EAHAK                                          P63213   \n",
       "AAADLMAYC(UniMod:4)EAHAKEDPLLTPVPASENPFR                          P63213   \n",
       "\n",
       "                                                    gene_id  \n",
       "AAAAAAAAAAAAAAAGAAGK                                Slc12a2  \n",
       "AAAAADLANR                                             Clpx  \n",
       "AAAADGEPLHNEEER                                      Ddrgk1  \n",
       "AAAAEGARPLER                                           Mogs  \n",
       "AAAAKEEAPK                                            Basp1  \n",
       "AAAANLC(UniMod:4)PGDVILAIDGFGTESMTHADAQDR            Pdlim3  \n",
       "AAAAYALGR                                             Cand2  \n",
       "AAADLM(UniMod:35)AYC(UniMod:4)EAHAKEDPLLTPVPASE...     Gng2  \n",
       "AAADLMAYC(UniMod:4)EAHAK                               Gng2  \n",
       "AAADLMAYC(UniMod:4)EAHAKEDPLLTPVPASENPFR               Gng2  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adata.var.head(n=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4da2630a",
   "metadata": {},
   "source": [
    "You can define consistent color schemes and category orders for the different tissues and BXD mice used for all figures created by ProteoPy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "76254f75",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Tissues\n",
    "n_tissues = adata.obs[\"tissue\"].nunique()\n",
    "cmap = mpl.colormaps[\"Set2\"]\n",
    "adata.uns[\"colors_tissue\"] = cmap(range(n_tissues)).tolist()\n",
    "\n",
    "adata.uns[\"order_tissue\"] = [\"Brain\", \"BAT\", \"Heart\", \"Liver\", \"Quad\"]\n",
    "\n",
    "# BXD mice\n",
    "n_mice = adata.obs[\"mouse_id\"].nunique()\n",
    "cmap = mpl.colormaps[\"tab10\"]\n",
    "adata.uns[\"colors_mouse_id\"] = cmap(range(n_mice)).tolist()\n",
    "\n",
    "adata.uns[\"order_mouse_id\"] = sorted(adata.obs[\"mouse_id\"].unique().tolist())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0808aed4",
   "metadata": {},
   "source": [
    "Looking at the sample distribution shows successful data import in agreement with the study design. The dataset includes 5 tissues derived from 8 BXD mice:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f33d3172",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pr.pl.n_samples_per_category(\n",
    "    adata,\n",
    "    category_key=\"tissue\",\n",
    "    order=adata.uns[\"order_tissue\"],\n",
    "    color_scheme=adata.uns[\"colors_tissue\"],\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "17fda9da",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pr.pl.n_samples_per_category(\n",
    "    adata,\n",
    "    category_key=\"mouse_id\",\n",
    "    order=adata.uns[\"order_mouse_id\"],\n",
    "    color_scheme=adata.uns[\"colors_mouse_id\"],\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "afc3a4c6",
   "metadata": {},
   "source": [
    "## Quality control and preprocessing"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d000ae1",
   "metadata": {},
   "source": [
    "Similar to the original analysis, we remove peptides from the iRT protein, which was used for calibration, and A2ASS6, which has extraordinarily many\n",
    "peptides and distorts the analysis.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d94da445",
   "metadata": {},
   "outputs": [],
   "source": [
    "irt_mask = (adata.var[\"protein_id\"] == \"iRT_protein\")\n",
    "adata = adata[:, ~irt_mask]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "1227eeaf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "N peptides for protein A2ASS6: 919\n"
     ]
    }
   ],
   "source": [
    "A2ASS6_mask = (adata.var[\"protein_id\"] == \"A2ASS6\")\n",
    "print(f\"N peptides for protein A2ASS6: {A2ASS6_mask.sum()}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "da282d13",
   "metadata": {},
   "outputs": [],
   "source": [
    "adata = adata[:, ~A2ASS6_mask]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd4bb21d",
   "metadata": {},
   "source": [
    "Next, peptides that differ only by technical modifications or derived from\n",
    "missed cleavages are summarized by summing up their intensities. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "58bbd476",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Stripping modifications: 31760 peptides -> 29862 unique stripped sequences (method='sum').\n"
     ]
    }
   ],
   "source": [
    "pr.pp.summarize_modifications(adata, method=\"sum\", verbose=True)\n",
    "pr.pp.summarize_overlapping_peptides(adata)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e833350d",
   "metadata": {},
   "source": [
    "After these preprocessing steps, the dataset includes approximately 25,000\n",
    "peptides and 3,800 proteins per sample."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "6f8a6601",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Global:\n",
      " mean_count  std_count  median_count  min_count  max_count  mean_pct  std_pct  median_pct  min_pct  max_pct\n",
      "    25184.2      199.1       25258.5      24623      25418      98.8      0.8        99.1     96.6     99.7\n",
      "\n",
      "Per tissue:\n",
      "tissue  mean_count  std_count  median_count  min_count  max_count  mean_pct  std_pct  median_pct  min_pct  max_pct\n",
      "   BAT     25181.2      191.5       25077.5      24997      25418      98.8      0.8        98.4     98.0     99.7\n",
      " Brain     25269.4        7.2       25268.5      25261      25280      99.1      0.0        99.1     99.1     99.1\n",
      " Heart     24860.5      110.9       24858.0      24623      24996      97.5      0.4        97.5     96.6     98.0\n",
      " Liver     25369.6       11.8       25372.0      25352      25386      99.5      0.0        99.5     99.4     99.6\n",
      "  Quad     25240.0       27.7       25240.0      25211      25289      99.0      0.1        99.0     98.9     99.2\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Axes: ylabel='#'>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pr.pl.n_peptides_per_sample(\n",
    "    adata,\n",
    "    zero_to_na=True,\n",
    "    order_by=\"tissue\",\n",
    "    order=adata.uns[\"order_tissue\"],\n",
    "    color_scheme=adata.uns[\"colors_tissue\"],\n",
    "    print_stats=True,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "f336afc9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Global:\n",
      " mean_count  std_count  median_count  min_count  max_count  mean_pct  std_pct  median_pct  min_pct  max_pct\n",
      "     3808.8        5.8        3811.5       3790       3815      99.8      0.2        99.9     99.3     99.9\n",
      "\n",
      "Per tissue:\n",
      "tissue  mean_count  std_count  median_count  min_count  max_count  mean_pct  std_pct  median_pct  min_pct  max_pct\n",
      "   BAT      3807.1        5.3        3805.0       3801       3814      99.7      0.1        99.7     99.6     99.9\n",
      " Brain      3812.1        0.6        3812.0       3811       3813      99.9      0.0        99.9     99.8     99.9\n",
      " Heart      3800.1        4.6        3801.0       3790       3806      99.6      0.1        99.6     99.3     99.7\n",
      " Liver      3814.0        0.5        3814.0       3813       3815      99.9      0.0        99.9     99.9     99.9\n",
      "  Quad      3810.8        1.5        3811.0       3808       3813      99.8      0.0        99.8     99.8     99.9\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Axes: ylabel='#'>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pr.pl.n_proteins_per_sample(\n",
    "    adata,\n",
    "    zero_to_na=True,\n",
    "    order_by=\"tissue\",\n",
    "    order=adata.uns[\"order_tissue\"],\n",
    "    color_scheme=adata.uns[\"colors_tissue\"],\n",
    "    print_stats=True,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b055722",
   "metadata": {},
   "source": [
    "Since proteoform group inference depends on high peptide coverage, we also inspect the distribution of peptides per protein:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "4db161e2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    mean  median  mode  variance  min  max\n",
      "6.680115     4.0     1 70.811955    1  118\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Number of peptide_id per protein_id', ylabel='# protein_id'>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pr.pl.n_peptides_per_protein(adata, print_stats=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d545f18",
   "metadata": {},
   "source": [
    "Note that no log transformation, data normalization or missing value\n",
    "imputation is performed here. This is because of the overall very high data\n",
    "consistency across the dataset and because COPF is based on covariation\n",
    "rather than direct intensity differences across conditions. This is also in\n",
    "agreement with the analysis by Bludau et al. (2021). However, other datasets\n",
    "might require additional preprocessing steps.  "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "510952c2",
   "metadata": {},
   "source": [
    "## Exploratory analysis of peptide-level data\n",
    "\n",
    "Before proteoform inference, ProteoPy can be used to perform classical exploratory data analysis steps, for example to investigate the primary sources of variation in the dataset."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "62956d00",
   "metadata": {},
   "source": [
    "### Sample correlation matrix\n",
    "\n",
    "High intra-tissue correlation and lower inter-tissue correlation show that peptide intensities are strongly driven by the tissue of origin and not by the mouse strain."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "86b0a403",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x700 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pr.pl.sample_correlation_matrix(\n",
    "    adata,\n",
    "    method=\"pearson\",\n",
    "    margin_color=\"tissue\",\n",
    "    color_scheme=adata.uns[\"colors_tissue\"],\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9755834a",
   "metadata": {},
   "source": [
    "### Dimensionality reduction\n",
    "\n",
    "The AnnData-based proteodata object created and used by ProteoPy is directly compatible with other AnnData based python packages such as scanpy (`import scanpy as sc`), which can for example be used for dimensionality reduction and clustering. \n",
    "\n",
    "Here, the PCA and UMAP analyses further confirm that tissue origin is the dominant source of variation in the dataset."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b40530b",
   "metadata": {},
   "source": [
    "#### PCA analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "7810f73a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sc.tl.pca(adata)\n",
    "\n",
    "with rc_context({\"figure.figsize\": (5, 3)}):\n",
    "    sc.pl.pca_variance_ratio(adata, n_pcs=50, log=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "40e61923",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2183.4x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2183.4x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sc.pl.pca(\n",
    "    adata,\n",
    "    color=[\"tissue\", \"tissue\", \"tissue\"],\n",
    "    dimensions=[(0, 1), (1, 2), (2, 3)],\n",
    "    ncols=3,\n",
    "    size=90,\n",
    "    palette=adata.uns[\"colors_tissue\"],\n",
    ")\n",
    "\n",
    "sc.pl.pca(\n",
    "    adata,\n",
    "    color=[\"mouse_id\", \"mouse_id\", \"mouse_id\"],\n",
    "    dimensions=[(0, 1), (1, 2), (2, 3)],\n",
    "    ncols=3,\n",
    "    size=90,\n",
    "    palette=adata.uns[\"colors_mouse_id\"],\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "44d5dd6e",
   "metadata": {},
   "source": [
    "#### UMAP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "c439e33c",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/isabell/miniconda3/envs/proteopy/lib/python3.10/site-packages/sklearn/manifold/_spectral_embedding.py:328: UserWarning: Graph is not fully connected, spectral embedding may not work as expected.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sc.pp.neighbors(adata, n_neighbors=4)\n",
    "sc.tl.umap(adata)\n",
    "\n",
    "sc.pl.umap(\n",
    "    adata,\n",
    "    color=[\"tissue\"],\n",
    "    size=100,\n",
    "    palette=adata.uns[\"colors_tissue\"],\n",
    ")\n",
    "\n",
    "sc.pl.umap(\n",
    "    adata,\n",
    "    color=[\"mouse_id\"],\n",
    "    size=100,\n",
    "    palette=adata.uns[\"colors_mouse_id\"],\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fed12e31",
   "metadata": {},
   "source": [
    "## Proteoform inference\n",
    "\n",
    "ProteoPy includes the core functionality of the COPF workflow: (1) compute pairwise peptide correlations between all peptides of a protein, (2) perform hierarchical clustering on the correlation distances, (3) cut each dendrogram into two clusters representing proteoform groups, and (4) score the between- vs. within-cluster correlation difference. Proteins require at least 4 peptides for meaningful clustering."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "9cf0f468",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Removed 1770 proteins and 2984 peptides.\n"
     ]
    }
   ],
   "source": [
    "# Require ≥4 peptides per protein for COPF analysis\n",
    "pr.pp.filter_proteins_by_peptide_count(adata, min_count=4)\n",
    "pr.pp.remove_zero_variance_vars(adata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "a5c373eb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# COPF pipeline: correlate, cluster, score\n",
    "pr.tl.pairwise_peptide_correlations(adata)\n",
    "pr.tl.peptide_dendograms_by_correlation(adata, method=\"agglomerative-hierarchical-clustering\")\n",
    "pr.tl.peptide_clusters_from_dendograms(adata, n_clusters=2, min_peptides_per_cluster=2)\n",
    "pr.tl.proteoform_scores(adata, min_score=0.1, min_pval_adj=0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "96db936d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove COPF outlier peptides (cluster_id == 1000000)\n",
    "copf_outliers = (adata.var[\"cluster_id\"] == 1000000)\n",
    "adata = adata[:, ~copf_outliers]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34223432",
   "metadata": {},
   "source": [
    "The pseudo-volcano plot shows proteoform scores vs. adjusted p-values (related to Figure 6B in Bludau et al. (2021)). The two highlighted proteins — Ldb3 (Q9JKS4) and Sorbs2 (Q3UTJ2) — are examined in detail below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "2e11160b",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Looks like you are using a tranform that doesn't support FancyArrowPatch, using ax.annotate instead. The arrows might strike through texts. Increasing shrinkA in arrowprops might help.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Proteoform Score', ylabel='adj. p-value'>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bludauI_proteoforms = [\"Q9JKS4\", \"Q3UTJ2\"]\n",
    "pr.pl.proteoform_scores(\n",
    "    adata,\n",
    "    adj=True,\n",
    "    pval_threshold=0.1,\n",
    "    score_threshold=0.1,\n",
    "    highlight_prots=bludauI_proteoforms,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "a3829467",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "65 significant proteoforms inferred.\n"
     ]
    }
   ],
   "source": [
    "pf_df = pr.get.proteoforms_df(adata, only_proteins=True)\n",
    "n_proteoforms = pf_df[pf_df[\"is_proteoform\"] == 1].shape[0]\n",
    "print(f\"{n_proteoforms} significant proteoforms inferred.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "103c871d",
   "metadata": {},
   "source": [
    "## Proteoform exploration\n",
    "\n",
    "ProteoPy also recovered the two exemplary proteins with proteoform groups highlighted in Bludau et al (2021): LIM domain-binding protein 3 (Ldb3, Q9JKS4) and Sorbin and SH3 domain-containing protein 2 (Sorbs2, Q3UTJ2)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "43928958",
   "metadata": {},
   "source": [
    "### LIM domain-binding protein 3 — Ldb3 (Q9JKS4)\n",
    "\n",
    "Ldb3 is a muscle-specific protein. COPF assigns its peptides to two tissue-specific proteoform groups, consistent with known alternative splice variants (reproduces Figure 7A)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "8f50bdb7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pr.pl.proteoform_intensities(\n",
    "    adata,\n",
    "    protein_ids=\"Q9JKS4\",\n",
    "    order_by=\"tissue\",\n",
    "    order=adata.uns[\"order_tissue\"],\n",
    "    xlab_rotation=45,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "ac856b5c",
   "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>protein_id</th>\n",
       "      <th>peptide_id</th>\n",
       "      <th>cluster_id</th>\n",
       "      <th>proteoform_score</th>\n",
       "      <th>proteoform_score_pval</th>\n",
       "      <th>proteoform_score_pval_adj</th>\n",
       "      <th>is_proteoform</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>QYNNPIGLYSAETLR</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.529813</td>\n",
       "      <td>0.002771</td>\n",
       "      <td>0.062994</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>ASSEGAQGSVSPK</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.529813</td>\n",
       "      <td>0.002771</td>\n",
       "      <td>0.062994</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>VLPGPSQPR</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.529813</td>\n",
       "      <td>0.002771</td>\n",
       "      <td>0.062994</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>EMAQMYQMSLR</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.529813</td>\n",
       "      <td>0.002771</td>\n",
       "      <td>0.062994</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>ILAQMTGTEYMQDPDEEALRR</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.529813</td>\n",
       "      <td>0.002771</td>\n",
       "      <td>0.062994</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>IMGEVMHALR</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.529813</td>\n",
       "      <td>0.002771</td>\n",
       "      <td>0.062994</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>QTWHTTCFVCAACK</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.529813</td>\n",
       "      <td>0.002771</td>\n",
       "      <td>0.062994</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>SKRPIPISTTAPPIQSPLPVIPHQK</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.529813</td>\n",
       "      <td>0.002771</td>\n",
       "      <td>0.062994</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>SASYNLSLTLQK</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.529813</td>\n",
       "      <td>0.002771</td>\n",
       "      <td>0.062994</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>SWHPEEFNCAYCK</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.529813</td>\n",
       "      <td>0.002771</td>\n",
       "      <td>0.062994</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>ASGAGLLGGSLPVKDLAVDSASPVYQAVIK</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.529813</td>\n",
       "      <td>0.002771</td>\n",
       "      <td>0.062994</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>TPLCGHCNNVIR</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.529813</td>\n",
       "      <td>0.002771</td>\n",
       "      <td>0.062994</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>TQSKPEDEADEWARR</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.529813</td>\n",
       "      <td>0.002771</td>\n",
       "      <td>0.062994</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>TSLADVCFVEEQNNVYCER</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.529813</td>\n",
       "      <td>0.002771</td>\n",
       "      <td>0.062994</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>AAQSQLSQGDLVVAIDGVNTDTMTHLEAQNK</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.529813</td>\n",
       "      <td>0.002771</td>\n",
       "      <td>0.062994</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>CYEQFFAPICAK</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.529813</td>\n",
       "      <td>0.002771</td>\n",
       "      <td>0.062994</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>LQGGKDFNMPLTISR</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.529813</td>\n",
       "      <td>0.002771</td>\n",
       "      <td>0.062994</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>GAPAYNPTGPQVTPLAR</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.529813</td>\n",
       "      <td>0.002771</td>\n",
       "      <td>0.062994</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>GPFLVAMGR</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.529813</td>\n",
       "      <td>0.002771</td>\n",
       "      <td>0.062994</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   protein_id                       peptide_id  cluster_id  proteoform_score  \\\n",
       "0      Q9JKS4                  QYNNPIGLYSAETLR         0.0          0.529813   \n",
       "1      Q9JKS4                    ASSEGAQGSVSPK         0.0          0.529813   \n",
       "2      Q9JKS4                        VLPGPSQPR         0.0          0.529813   \n",
       "3      Q9JKS4                      EMAQMYQMSLR         0.0          0.529813   \n",
       "4      Q9JKS4            ILAQMTGTEYMQDPDEEALRR         1.0          0.529813   \n",
       "5      Q9JKS4                       IMGEVMHALR         1.0          0.529813   \n",
       "6      Q9JKS4                   QTWHTTCFVCAACK         1.0          0.529813   \n",
       "7      Q9JKS4        SKRPIPISTTAPPIQSPLPVIPHQK         1.0          0.529813   \n",
       "8      Q9JKS4                     SASYNLSLTLQK         1.0          0.529813   \n",
       "9      Q9JKS4                    SWHPEEFNCAYCK         1.0          0.529813   \n",
       "10     Q9JKS4   ASGAGLLGGSLPVKDLAVDSASPVYQAVIK         1.0          0.529813   \n",
       "11     Q9JKS4                     TPLCGHCNNVIR         1.0          0.529813   \n",
       "12     Q9JKS4                  TQSKPEDEADEWARR         1.0          0.529813   \n",
       "13     Q9JKS4              TSLADVCFVEEQNNVYCER         1.0          0.529813   \n",
       "14     Q9JKS4  AAQSQLSQGDLVVAIDGVNTDTMTHLEAQNK         1.0          0.529813   \n",
       "15     Q9JKS4                     CYEQFFAPICAK         1.0          0.529813   \n",
       "16     Q9JKS4                  LQGGKDFNMPLTISR         1.0          0.529813   \n",
       "17     Q9JKS4                GAPAYNPTGPQVTPLAR         1.0          0.529813   \n",
       "18     Q9JKS4                        GPFLVAMGR         1.0          0.529813   \n",
       "\n",
       "    proteoform_score_pval  proteoform_score_pval_adj  is_proteoform  \n",
       "0                0.002771                   0.062994            1.0  \n",
       "1                0.002771                   0.062994            1.0  \n",
       "2                0.002771                   0.062994            1.0  \n",
       "3                0.002771                   0.062994            1.0  \n",
       "4                0.002771                   0.062994            1.0  \n",
       "5                0.002771                   0.062994            1.0  \n",
       "6                0.002771                   0.062994            1.0  \n",
       "7                0.002771                   0.062994            1.0  \n",
       "8                0.002771                   0.062994            1.0  \n",
       "9                0.002771                   0.062994            1.0  \n",
       "10               0.002771                   0.062994            1.0  \n",
       "11               0.002771                   0.062994            1.0  \n",
       "12               0.002771                   0.062994            1.0  \n",
       "13               0.002771                   0.062994            1.0  \n",
       "14               0.002771                   0.062994            1.0  \n",
       "15               0.002771                   0.062994            1.0  \n",
       "16               0.002771                   0.062994            1.0  \n",
       "17               0.002771                   0.062994            1.0  \n",
       "18               0.002771                   0.062994            1.0  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pr.get.proteoforms_df(adata, proteins=\"Q9JKS4\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34ca76a4",
   "metadata": {},
   "source": [
    "### Ldb3 peptide sequence map (reproduces Figure 7C)\n",
    "\n",
    "Mapping detected peptides onto the canonical protein sequence and annotated UniProt alternative sequences confirms that the two proteoform groups correspond to known splice variants."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "eeb34806",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'LIM domain binding protein 3 (Q9JKS4)'}, xlabel='Position'>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Canonical sequence and UniProt alternative sequences for Q9JKS4\n",
    "# Source: https://www.uniprot.org/uniprotkb/Q9JKS4/entry#sequences\n",
    "seq = \"MSYSVTLTGPGPWGFRLQGGKDFNMPLTISRITPGSKAAQSQLSQGDLVVAIDGVNTDTMTHLEAQNKIKSASYNLSLTLQKSKRPIPISTTAPPIQSPLPVIPHQKDPALDTNGSLATPSPSPEARASPGALEFGDTFSSSFSQTSVCSPLMEASGPVLPLGSPVAKASSEGAQGSVSPKVLPGPSQPRQYNNPIGLYSAETLREMAQMYQMSLRGKASGAGLLGGSLPVKDLAVDSASPVYQAVIKTQSKPEDEADEWARRSSNLQSRSFRILAQMTGTEYMQDPDEEALRRSSTPIEHAPVCTSQATSPLLPASAQSPAAASPIAASPTLATAAATHAAAASAAGPAASPVENPRPQASAYSPAAAASPAPSAHTSYSEGPAAPAPKPRVVTTASIRPSVYQPVPASSYSPSPGANYSPTPYTPSPAPAYTPSPAPTYTPSPAPTYSPSPAPAYTPSPAPNYTPTPSAAYSGGPSESASRPPWVTDDSFSQKFAPGKSTTTVSKQTLPRGAPAYNPTGPQVTPLARGTFQRAERFPASSRTPLCGHCNNVIRGPFLVAMGRSWHPEEFNCAYCKTSLADVCFVEEQNNVYCERCYEQFFAPICAKCNTKIMGEVMHALRQTWHTTCFVCAACKKPFGNSLFHMEDGEPYCEKDYINLFSTKCHGCDFPVEAGDKFIEALGHTWHDTCFICAVCHVNLEGQPFYSKKDKPLCKKHAHAINV\"\n",
    "alt_seqs = {\n",
    "    \"Q9JKS4-2_0\": {\"seq_coord\": (107, 227), \"group\": \"alt_2\"},\n",
    "    \"Q9JKS4-3_0\": {\"seq_coord\": (295, 357), \"group\": \"alt_3\"},\n",
    "    \"Q9JKS4-4_0\": {\"seq_coord\": (107, 227), \"group\": \"alt_4\"},\n",
    "    \"Q9JKS4-4_1\": {\"seq_coord\": (295, 357), \"group\": \"alt_4\"},\n",
    "    \"Q9JKS4-5_0\": {\"seq_coord\": (295, 327), \"group\": \"alt_5\"},\n",
    "    \"Q9JKS4-5_1\": {\"seq_coord\": (328, 723), \"group\": \"alt_5\"},\n",
    "    \"Q9JKS4-6_0\": {\"seq_coord\": (107, 227), \"group\": \"alt_6\"},\n",
    "    \"Q9JKS4-6_1\": {\"seq_coord\": (295, 327), \"group\": \"alt_6\"},\n",
    "    \"Q9JKS4-6_2\": {\"seq_coord\": (328, 723), \"group\": \"alt_6\"},\n",
    "}\n",
    "\n",
    "pr.pl.peptides_on_prot_sequence(\n",
    "    adata,\n",
    "    protein_id=\"Q9JKS4\",\n",
    "    group_by=\"proteoform_id\",\n",
    "    ref_sequence=seq,\n",
    "    add_sequences=alt_seqs,\n",
    "    title=\"LIM domain binding protein 3 (Q9JKS4)\",\n",
    "    figsize=(8, 4),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a83f4ac5",
   "metadata": {},
   "source": [
    "### Sorbin and SH3 domain-containing protein 2 — Sorbs2 (Q3UTJ2)\n",
    "\n",
    "Sorbs2 peptides are assigned to two proteoform groups with distinct tissue expression patterns: one group is abundant across brain, heart, and liver, while the other is brain-specific (reproduces Figure 7D)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "fedaba5c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pr.pl.proteoform_intensities(\n",
    "    adata,\n",
    "    protein_ids=\"Q3UTJ2\",\n",
    "    order_by=\"tissue\",\n",
    "    order=adata.uns[\"order_tissue\"],\n",
    "    xlab_rotation=45,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "89a8b435",
   "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>protein_id</th>\n",
       "      <th>peptide_id</th>\n",
       "      <th>cluster_id</th>\n",
       "      <th>proteoform_score</th>\n",
       "      <th>proteoform_score_pval</th>\n",
       "      <th>proteoform_score_pval_adj</th>\n",
       "      <th>is_proteoform</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Q3UTJ2</td>\n",
       "      <td>LAFLVSPVPFR</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.619637</td>\n",
       "      <td>0.000343</td>\n",
       "      <td>0.01393</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Q3UTJ2</td>\n",
       "      <td>ASVVEALDSALKDICDQIK</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.619637</td>\n",
       "      <td>0.000343</td>\n",
       "      <td>0.01393</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Q3UTJ2</td>\n",
       "      <td>QGIFPVSYVEVVKR</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.619637</td>\n",
       "      <td>0.000343</td>\n",
       "      <td>0.01393</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Q3UTJ2</td>\n",
       "      <td>APHYPGIGPVDESGIPTAIR</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.619637</td>\n",
       "      <td>0.000343</td>\n",
       "      <td>0.01393</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Q3UTJ2</td>\n",
       "      <td>SFISSSPSSPSR</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.619637</td>\n",
       "      <td>0.000343</td>\n",
       "      <td>0.01393</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Q3UTJ2</td>\n",
       "      <td>SIFEYEPGK</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.619637</td>\n",
       "      <td>0.000343</td>\n",
       "      <td>0.01393</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Q3UTJ2</td>\n",
       "      <td>AQPARPPPPVQPGEIGEAIAK</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.619637</td>\n",
       "      <td>0.000343</td>\n",
       "      <td>0.01393</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Q3UTJ2</td>\n",
       "      <td>SYSSTLTDLGR</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.619637</td>\n",
       "      <td>0.000343</td>\n",
       "      <td>0.01393</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Q3UTJ2</td>\n",
       "      <td>VGIFPISYVEK</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.619637</td>\n",
       "      <td>0.000343</td>\n",
       "      <td>0.01393</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Q3UTJ2</td>\n",
       "      <td>ADLPGSSSTFTK</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.619637</td>\n",
       "      <td>0.000343</td>\n",
       "      <td>0.01393</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Q3UTJ2</td>\n",
       "      <td>GLGDQSSSR</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.619637</td>\n",
       "      <td>0.000343</td>\n",
       "      <td>0.01393</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   protein_id             peptide_id  cluster_id  proteoform_score  \\\n",
       "0      Q3UTJ2            LAFLVSPVPFR         0.0          0.619637   \n",
       "1      Q3UTJ2    ASVVEALDSALKDICDQIK         0.0          0.619637   \n",
       "2      Q3UTJ2         QGIFPVSYVEVVKR         1.0          0.619637   \n",
       "3      Q3UTJ2   APHYPGIGPVDESGIPTAIR         1.0          0.619637   \n",
       "4      Q3UTJ2           SFISSSPSSPSR         1.0          0.619637   \n",
       "5      Q3UTJ2              SIFEYEPGK         1.0          0.619637   \n",
       "6      Q3UTJ2  AQPARPPPPVQPGEIGEAIAK         1.0          0.619637   \n",
       "7      Q3UTJ2            SYSSTLTDLGR         1.0          0.619637   \n",
       "8      Q3UTJ2            VGIFPISYVEK         1.0          0.619637   \n",
       "9      Q3UTJ2           ADLPGSSSTFTK         1.0          0.619637   \n",
       "10     Q3UTJ2              GLGDQSSSR         1.0          0.619637   \n",
       "\n",
       "    proteoform_score_pval  proteoform_score_pval_adj  is_proteoform  \n",
       "0                0.000343                    0.01393            1.0  \n",
       "1                0.000343                    0.01393            1.0  \n",
       "2                0.000343                    0.01393            1.0  \n",
       "3                0.000343                    0.01393            1.0  \n",
       "4                0.000343                    0.01393            1.0  \n",
       "5                0.000343                    0.01393            1.0  \n",
       "6                0.000343                    0.01393            1.0  \n",
       "7                0.000343                    0.01393            1.0  \n",
       "8                0.000343                    0.01393            1.0  \n",
       "9                0.000343                    0.01393            1.0  \n",
       "10               0.000343                    0.01393            1.0  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pr.get.proteoforms_df(adata, proteins=\"Q3UTJ2\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "578c4daf",
   "metadata": {},
   "source": [
    "### Sorbs2 peptide sequence map (reproduces Figure 7F)\n",
    "\n",
    "The brain-specific proteoform group maps to a region covered by alternative sequences 3, 4 and 5 in UniProt (10 in Bludau et. al. Figure 7F), a brain-specific splice variant."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "27dbceb7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Sorbin and SH3 domain-containing protein 2 (Q3UTJ2)'}, xlabel='Position'>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Canonical sequence and UniProt alternative sequences for Q3UTJ2\n",
    "# Source: https://www.uniprot.org/uniprotkb/Q3UTJ2/entry#sequences\n",
    "seq = \"MNTDSGGCARKRAAMSVTLTSVKRVQSSPNLLAAGRESQSPDSAWRSYNDRNPETLNGDATYSSLAAKGFRSVRPNLQDKRSPTQSQITINGNSGGAVSPVSYYQRPFSPSAYSLPASLNSSIIMQHGRSLDSAETYSQHAQSLDGTMGSSIPLYRSSEEEKRVTVIKAPHYPGIGPVDESGIPTAIRTTVDRPKDWYKTMFKQIHMVHKPGLYNSPYSAQSHPAAKTQTYRPLSKSHSDNGTDAFKEVPSPVPPPHVPPRPRDQSSTLKHDWDPPDRKVDTRKFRSEPRSIFEYEPGKSSILQHERPVSIYQSSIDRSLERPSSSASMAGDFRKRRKSEPAVGPLRGLGDQSSSRTSPGRADLPGSSSTFTKSFISSSPSSPSRAQGGDDSKMCPPLCSYSGLNGTPSGELECCNAYRQHLDVPGDSQRAITFKNGWQMARQNAEIWSSTEETVSPKIKSRSCDDLLNDDCDSFPDPKTKSESMGSLLCEEDSKESCPMTWASPYIQEVCGNSRSRLKHRSAHNAPGFLKMYKKMHRINRKDLMNSEVICSVKSRILQYEKEQQHRGLLHGWSQSSTEEVPRDVVPTRISEFEKLIQKSKSMPNLGDEMLSPITLEPPQNGLCPKRRFSIESLLEEETQVRHPSQGQRSCKSNTLVPIHIEVTSDEQPRTHMEFSDSDQDGVVSDHSDYVHVEGSSFCSESDFDHFSFTSSESFYGSSHHHHHHHHHHRHLISSCKGRCPASYTRFTTMLKHERAKHENMDRPRRQEMDPGLSKLAFLVSPVPFRRKKILTPQKQTEKAKCKASVVEALDSALKDICDQIKAEKRRGSLPDNSILHRLISELLPQIPERNSSLHALKRSPMHQPFHPLPPDGASHCPLYQNDCGRMPHSASFPDVDTTSNYHAQDYGSALSLQDHESPRSYSSTLTDLGRSASRERRGTPEKEKLPAKAVYDFKAQTSKELSFKKGDTVYILRKIDQNWYEGEHHGRVGIFPISYVEKLTPPEKAQPARPPPPVQPGEIGEAIAKYNFNADTNVELSLRKGDRIILLKRVDQNWYEGKIPGTNRQGIFPVSYVEVVKRNAKGAEDYPDPPLPHSYSSDRIYTLSSNKPQRPGFSHENIQGGGEPFQALYNYTPRNEDELELRESDVVDVMEKCDDGWFVGTSRRTKFFGTFPGNYVKRL\"\n",
    "alt_seqs = {\n",
    "    \"Q3UTJ2-2_0\": {\"seq_coord\": (210, 211), \"group\": \"alt_2\"},\n",
    "    \"Q3UTJ2-2_1\": {\"seq_coord\": (307, 308), \"group\": \"alt_2\"},\n",
    "    \"Q3UTJ2-3_0\": {\"seq_coord\": (3, 34), \"group\": \"alt_3\"},\n",
    "    \"Q3UTJ2-3_1\": {\"seq_coord\": (210, 211), \"group\": \"alt_3\"},\n",
    "    \"Q3UTJ2-3_2\": {\"seq_coord\": (387, 914), \"group\": \"alt_3\"},\n",
    "    \"Q3UTJ2-3_3\": {\"seq_coord\": (1125, 1180), \"group\": \"alt_3\"},\n",
    "    \"Q3UTJ2-4_0\": {\"seq_coord\": (3, 34), \"group\": \"alt_4\"},\n",
    "    \"Q3UTJ2-4_1\": {\"seq_coord\": (387, 914), \"group\": \"alt_4\"},\n",
    "    \"Q3UTJ2-5_0\": {\"seq_coord\": (44, 67), \"group\": \"alt_5\"},\n",
    "    \"Q3UTJ2-5_1\": {\"seq_coord\": (210, 211), \"group\": \"alt_5\"},\n",
    "    \"Q3UTJ2-5_2\": {\"seq_coord\": (307, 308), \"group\": \"alt_5\"},\n",
    "    \"Q3UTJ2-5_3\": {\"seq_coord\": (387, 914), \"group\": \"alt_5\"},\n",
    "    \"Q3UTJ2-5_4\": {\"seq_coord\": (1125, 1135), \"group\": \"alt_5\"},\n",
    "    \"Q3UTJ2-6_0\": {\"seq_coord\": (44, 67), \"group\": \"alt_6\"},\n",
    "    \"Q3UTJ2-6_1\": {\"seq_coord\": (210, 211), \"group\": \"alt_6\"},\n",
    "    \"Q3UTJ2-6_2\": {\"seq_coord\": (308, 316), \"group\": \"alt_6\"},\n",
    "    \"Q3UTJ2-6_3\": {\"seq_coord\": (316, 1180), \"group\": \"alt_6\"},\n",
    "    \"Q3UTJ2-7_0\": {\"seq_coord\": (310, 313), \"group\": \"alt_7\"},\n",
    "    \"Q3UTJ2-7_1\": {\"seq_coord\": (313, 1180), \"group\": \"alt_7\"},\n",
    "}\n",
    "\n",
    "pr.pl.peptides_on_prot_sequence(\n",
    "    adata,\n",
    "    protein_id=\"Q3UTJ2\",\n",
    "    group_by=\"proteoform_id\",\n",
    "    ref_sequence=seq,\n",
    "    add_sequences=alt_seqs,\n",
    "    title=\"Sorbin and SH3 domain-containing protein 2 (Q3UTJ2)\",\n",
    "    figsize=(8, 4),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "07253c56",
   "metadata": {},
   "source": [
    "## Proteoform quantification and statistical analysis\n",
    "\n",
    "To test if the inferred proteoform groups are indeed tissue-specific, a one-way ANOVA analysis can be performed directly using ProteoPy functions. In strong agreement with Bludau et al. (2021), our analysis revealed that 59 out of 65 proteoform-containing proteins (90.8%) are expressed in a tissue-specific manner."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "4b851d42",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Aggregate peptide intensities to proteoform level\n",
    "adata_pfs = adata.copy()\n",
    "pr.pp.quantify_proteoforms(adata_pfs, group_by=\"proteoform_id\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "f8b0ccfa",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Retain only significant proteoforms (score >= 0.1, adj. p-value <= 0.1)\n",
    "pf_mask = (\n",
    "    (adata_pfs.var[\"proteoform_score\"].astype(float) >= 0.1)\n",
    "    & (adata_pfs.var[\"proteoform_score_pval_adj\"].astype(float) <= 0.1)\n",
    ")\n",
    "adata_pfs = adata_pfs[:, pf_mask].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "0a75eabd",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Log2 transform for statistical testing\n",
    "adata_pfs.layers[\"raw\"] = adata_pfs.X\n",
    "adata_pfs.X[adata_pfs.X == 0] = np.nan\n",
    "adata_pfs.X = np.log2(adata_pfs.X)\n",
    "adata_pfs.X[np.isnan(adata_pfs.X)] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "696e88c6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saved test results in .varm['anova_oneway;tissue;all']\n"
     ]
    }
   ],
   "source": [
    "# One-way ANOVA across tissues\n",
    "pr.tl.differential_abundance(\n",
    "    adata_pfs,\n",
    "    method=\"anova_oneway\",\n",
    "    multitest_correction=\"bonferroni\",\n",
    "    group_by=\"tissue\",\n",
    "    alpha=0.01,\n",
    "    space=\"log\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "a9f07ae1",
   "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>proteoform_id</th>\n",
       "      <th>test_type</th>\n",
       "      <th>group_by</th>\n",
       "      <th>design</th>\n",
       "      <th>fstat</th>\n",
       "      <th>pval</th>\n",
       "      <th>mean_Brain</th>\n",
       "      <th>mean_BAT</th>\n",
       "      <th>mean_Heart</th>\n",
       "      <th>mean_Liver</th>\n",
       "      <th>mean_Quad</th>\n",
       "      <th>pval_adj</th>\n",
       "      <th>is_diff_abundant</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>O08601_0</td>\n",
       "      <td>anova_oneway</td>\n",
       "      <td>tissue</td>\n",
       "      <td>all</td>\n",
       "      <td>29.998692</td>\n",
       "      <td>7.135979e-11</td>\n",
       "      <td>15.447875</td>\n",
       "      <td>16.438822</td>\n",
       "      <td>13.642355</td>\n",
       "      <td>15.286296</td>\n",
       "      <td>13.226680</td>\n",
       "      <td>9.276772e-09</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>O08601_1</td>\n",
       "      <td>anova_oneway</td>\n",
       "      <td>tissue</td>\n",
       "      <td>all</td>\n",
       "      <td>309.316738</td>\n",
       "      <td>8.846917e-27</td>\n",
       "      <td>17.173194</td>\n",
       "      <td>16.274997</td>\n",
       "      <td>16.297549</td>\n",
       "      <td>19.401295</td>\n",
       "      <td>16.539176</td>\n",
       "      <td>1.150099e-24</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>O54724_0</td>\n",
       "      <td>anova_oneway</td>\n",
       "      <td>tissue</td>\n",
       "      <td>all</td>\n",
       "      <td>12.603239</td>\n",
       "      <td>1.878084e-06</td>\n",
       "      <td>15.879478</td>\n",
       "      <td>13.639894</td>\n",
       "      <td>8.489357</td>\n",
       "      <td>10.545068</td>\n",
       "      <td>11.828292</td>\n",
       "      <td>2.441509e-04</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>O54724_1</td>\n",
       "      <td>anova_oneway</td>\n",
       "      <td>tissue</td>\n",
       "      <td>all</td>\n",
       "      <td>184.250825</td>\n",
       "      <td>5.444913e-23</td>\n",
       "      <td>16.359031</td>\n",
       "      <td>19.356209</td>\n",
       "      <td>18.207868</td>\n",
       "      <td>15.845380</td>\n",
       "      <td>17.226098</td>\n",
       "      <td>7.078387e-21</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>O54749_0</td>\n",
       "      <td>anova_oneway</td>\n",
       "      <td>tissue</td>\n",
       "      <td>all</td>\n",
       "      <td>5.288221</td>\n",
       "      <td>1.938883e-03</td>\n",
       "      <td>13.162980</td>\n",
       "      <td>12.879554</td>\n",
       "      <td>14.428646</td>\n",
       "      <td>13.568651</td>\n",
       "      <td>13.071253</td>\n",
       "      <td>2.520548e-01</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>Q9JKS4_1</td>\n",
       "      <td>anova_oneway</td>\n",
       "      <td>tissue</td>\n",
       "      <td>all</td>\n",
       "      <td>66.936903</td>\n",
       "      <td>6.594055e-16</td>\n",
       "      <td>17.255804</td>\n",
       "      <td>17.226273</td>\n",
       "      <td>19.196674</td>\n",
       "      <td>17.040296</td>\n",
       "      <td>19.944539</td>\n",
       "      <td>8.572271e-14</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>Q9QYR6_0</td>\n",
       "      <td>anova_oneway</td>\n",
       "      <td>tissue</td>\n",
       "      <td>all</td>\n",
       "      <td>14.856602</td>\n",
       "      <td>3.441306e-07</td>\n",
       "      <td>15.506743</td>\n",
       "      <td>12.560879</td>\n",
       "      <td>13.676294</td>\n",
       "      <td>13.230452</td>\n",
       "      <td>13.061866</td>\n",
       "      <td>4.473698e-05</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>Q9QYR6_1</td>\n",
       "      <td>anova_oneway</td>\n",
       "      <td>tissue</td>\n",
       "      <td>all</td>\n",
       "      <td>646.764070</td>\n",
       "      <td>2.861598e-32</td>\n",
       "      <td>20.504493</td>\n",
       "      <td>16.481401</td>\n",
       "      <td>16.861090</td>\n",
       "      <td>17.344528</td>\n",
       "      <td>16.848407</td>\n",
       "      <td>3.720078e-30</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>Q9Z204_0</td>\n",
       "      <td>anova_oneway</td>\n",
       "      <td>tissue</td>\n",
       "      <td>all</td>\n",
       "      <td>75.275766</td>\n",
       "      <td>1.071660e-16</td>\n",
       "      <td>16.117296</td>\n",
       "      <td>12.403909</td>\n",
       "      <td>12.737527</td>\n",
       "      <td>13.374945</td>\n",
       "      <td>12.716591</td>\n",
       "      <td>1.393159e-14</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>Q9Z204_1</td>\n",
       "      <td>anova_oneway</td>\n",
       "      <td>tissue</td>\n",
       "      <td>all</td>\n",
       "      <td>152.715690</td>\n",
       "      <td>1.224770e-21</td>\n",
       "      <td>15.790335</td>\n",
       "      <td>14.611674</td>\n",
       "      <td>13.502690</td>\n",
       "      <td>16.977432</td>\n",
       "      <td>13.218752</td>\n",
       "      <td>1.592201e-19</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>130 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    proteoform_id     test_type group_by design       fstat          pval  \\\n",
       "0        O08601_0  anova_oneway   tissue    all   29.998692  7.135979e-11   \n",
       "1        O08601_1  anova_oneway   tissue    all  309.316738  8.846917e-27   \n",
       "2        O54724_0  anova_oneway   tissue    all   12.603239  1.878084e-06   \n",
       "3        O54724_1  anova_oneway   tissue    all  184.250825  5.444913e-23   \n",
       "4        O54749_0  anova_oneway   tissue    all    5.288221  1.938883e-03   \n",
       "..            ...           ...      ...    ...         ...           ...   \n",
       "125      Q9JKS4_1  anova_oneway   tissue    all   66.936903  6.594055e-16   \n",
       "126      Q9QYR6_0  anova_oneway   tissue    all   14.856602  3.441306e-07   \n",
       "127      Q9QYR6_1  anova_oneway   tissue    all  646.764070  2.861598e-32   \n",
       "128      Q9Z204_0  anova_oneway   tissue    all   75.275766  1.071660e-16   \n",
       "129      Q9Z204_1  anova_oneway   tissue    all  152.715690  1.224770e-21   \n",
       "\n",
       "     mean_Brain   mean_BAT  mean_Heart  mean_Liver  mean_Quad      pval_adj  \\\n",
       "0     15.447875  16.438822   13.642355   15.286296  13.226680  9.276772e-09   \n",
       "1     17.173194  16.274997   16.297549   19.401295  16.539176  1.150099e-24   \n",
       "2     15.879478  13.639894    8.489357   10.545068  11.828292  2.441509e-04   \n",
       "3     16.359031  19.356209   18.207868   15.845380  17.226098  7.078387e-21   \n",
       "4     13.162980  12.879554   14.428646   13.568651  13.071253  2.520548e-01   \n",
       "..          ...        ...         ...         ...        ...           ...   \n",
       "125   17.255804  17.226273   19.196674   17.040296  19.944539  8.572271e-14   \n",
       "126   15.506743  12.560879   13.676294   13.230452  13.061866  4.473698e-05   \n",
       "127   20.504493  16.481401   16.861090   17.344528  16.848407  3.720078e-30   \n",
       "128   16.117296  12.403909   12.737527   13.374945  12.716591  1.393159e-14   \n",
       "129   15.790335  14.611674   13.502690   16.977432  13.218752  1.592201e-19   \n",
       "\n",
       "     is_diff_abundant  \n",
       "0                True  \n",
       "1                True  \n",
       "2                True  \n",
       "3                True  \n",
       "4               False  \n",
       "..                ...  \n",
       "125              True  \n",
       "126              True  \n",
       "127              True  \n",
       "128              True  \n",
       "129              True  \n",
       "\n",
       "[130 rows x 13 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "anova_results = pr.get.differential_abundance_df(adata_pfs, keys=\"anova_oneway;tissue;all\")\n",
    "anova_results.rename(columns={\"var_id\": \"proteoform_id\"}, inplace=True)\n",
    "anova_results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "888c78b1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "59 tissue-specific proteoform groups found via ANOVA.\n"
     ]
    }
   ],
   "source": [
    "# Count proteins with all proteoforms being significantly tissue-specific\n",
    "protein_id_map = adata_pfs.var[[\"protein_id\", \"protein_id_old\"]].set_index(\"protein_id\")[\"protein_id_old\"]\n",
    "anova_results[\"protein_id\"] = anova_results[\"proteoform_id\"].map(protein_id_map)\n",
    "n_tissue_specific_pfs = anova_results.groupby(\"protein_id\")[\"is_diff_abundant\"].all().sum()\n",
    "\n",
    "print(f\"{n_tissue_specific_pfs} tissue-specific proteoform groups found via ANOVA.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ae40c32",
   "metadata": {},
   "source": [
    "## Summary\n",
    "\n",
    "This notebook reproduced the core proteoform inference workflow from Bludau et al. (2021) using ProteoPy. Key results:\n",
    "\n",
    "- **Proteoform detection**: COPF identified 65 proteins with proteoform groups, comparable to the 63 reported in the original study (Figure 6B).\n",
    "- **Biological verification**: The tissue-specific proteoform assignments for Ldb3 (Q9JKS4) and Sorbs2 (Q3UTJ2) match the published findings (Figures 7A, 7C, 7D, 7F), with peptide-to-sequence mappings consistent with known alternative splice variants.\n",
    "- **Tissue specificity**: ANOVA analysis recovered 59 tissue-specific proteoform groups (90.8% of the inferred proteoform groups) — similar to the 56 tissue-specific proteoform groups (88.9% of the inferred proteoform groups) reported by Bludau et al.\n",
    "\n",
    "Minor discrepancies between reported numbers are expected due to implementation details in preprocessing (e.g., peptide modification summarization, overlapping peptide handling) and statistical testing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "3a899aff",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "adjustText==1.3.0\n",
      "anndata==0.11.4\n",
      "anyio==4.12.1\n",
      "appnope==0.1.4\n",
      "argon2-cffi==25.1.0\n",
      "argon2-cffi-bindings==25.1.0\n",
      "array-api-compat==1.14.0\n",
      "arrow==1.4.0\n",
      "asttokens==3.0.1\n",
      "async-lru==2.2.0\n",
      "attrs==25.4.0\n",
      "babel==2.18.0\n",
      "beautifulsoup4==4.14.3\n",
      "biopython==1.86\n",
      "bleach==6.3.0\n",
      "certifi==2026.2.25\n",
      "cffi==2.0.0\n",
      "charset-normalizer==3.4.4\n",
      "comm==0.2.3\n",
      "contourpy==1.3.2\n",
      "cramjam==2.11.0\n",
      "cycler==0.12.1\n",
      "debugpy==1.8.20\n",
      "decorator==5.2.1\n",
      "defusedxml==0.7.1\n",
      "et_xmlfile==2.0.0\n",
      "exceptiongroup==1.3.1\n",
      "executing==2.2.1\n",
      "fastjsonschema==2.21.2\n",
      "fastparquet==2025.12.0\n",
      "fonttools==4.61.1\n",
      "fqdn==1.5.1\n",
      "fsspec==2026.2.0\n",
      "h11==0.16.0\n",
      "h5py==3.15.1\n",
      "httpcore==1.0.9\n",
      "httpx==0.28.1\n",
      "idna==3.11\n",
      "igraph==1.0.0\n",
      "ipykernel==7.2.0\n",
      "ipython==8.38.0\n",
      "isoduration==20.11.0\n",
      "jedi==0.19.2\n",
      "Jinja2==3.1.6\n",
      "joblib==1.5.3\n",
      "json5==0.13.0\n",
      "jsonpointer==3.0.0\n",
      "jsonschema==4.26.0\n",
      "jsonschema-specifications==2025.9.1\n",
      "jupyter-events==0.12.0\n",
      "jupyter-lsp==2.3.0\n",
      "jupyter_client==8.8.0\n",
      "jupyter_core==5.9.1\n",
      "jupyter_server==2.17.0\n",
      "jupyter_server_terminals==0.5.4\n",
      "jupyterlab==4.5.5\n",
      "jupyterlab_pygments==0.3.0\n",
      "jupyterlab_server==2.28.0\n",
      "kiwisolver==1.4.9\n",
      "lark==1.3.1\n",
      "legacy-api-wrap==1.5\n",
      "llvmlite==0.46.0\n",
      "MarkupSafe==3.0.3\n",
      "matplotlib==3.10.8\n",
      "matplotlib-inline==0.2.1\n",
      "mistune==3.2.0\n",
      "natsort==8.4.0\n",
      "nbclient==0.10.4\n",
      "nbconvert==7.17.0\n",
      "nbformat==5.10.4\n",
      "nest-asyncio==1.6.0\n",
      "networkx==3.4.2\n",
      "notebook_shim==0.2.4\n",
      "numba==0.64.0\n",
      "numpy==2.2.6\n",
      "openpyxl==3.1.5\n",
      "overrides==7.7.0\n",
      "packaging @ file:///opt/miniconda3/conda-bld/packaging_1761049079158/work\n",
      "pandas==2.3.3\n",
      "pandocfilters==1.5.1\n",
      "parso==0.8.6\n",
      "patsy==1.0.2\n",
      "pexpect==4.9.0\n",
      "pillow==12.1.1\n",
      "platformdirs==4.9.2\n",
      "pooch==1.9.0\n",
      "prometheus_client==0.24.1\n",
      "prompt_toolkit==3.0.52\n",
      "-e git+https://github.com/UKHD-NP/proteopy.git@7c053b623233c7438b7f881db36737e0fb7eab78#egg=proteopy\n",
      "psutil==7.2.2\n",
      "ptyprocess==0.7.0\n",
      "pure_eval==0.2.3\n",
      "pycparser==3.0\n",
      "Pygments==2.19.2\n",
      "pynndescent==0.6.0\n",
      "pyparsing==3.3.2\n",
      "python-dateutil==2.9.0.post0\n",
      "python-igraph==1.0.0\n",
      "python-json-logger==4.0.0\n",
      "pytz==2025.2\n",
      "PyYAML==6.0.3\n",
      "pyzmq==27.1.0\n",
      "referencing==0.37.0\n",
      "requests==2.32.5\n",
      "rfc3339-validator==0.1.4\n",
      "rfc3986-validator==0.1.1\n",
      "rfc3987-syntax==1.1.0\n",
      "rpds-py==0.30.0\n",
      "scanpy==1.11.5\n",
      "scikit-learn==1.7.2\n",
      "scipy==1.15.3\n",
      "seaborn==0.13.2\n",
      "Send2Trash==2.1.0\n",
      "session-info2==0.4\n",
      "six==1.17.0\n",
      "soupsieve==2.8.3\n",
      "stack-data==0.6.3\n",
      "statsmodels==0.14.6\n",
      "terminado==0.18.1\n",
      "texttable==1.7.0\n",
      "threadpoolctl==3.6.0\n",
      "tinycss2==1.4.0\n",
      "tomli==2.4.0\n",
      "tornado==6.5.4\n",
      "tqdm==4.67.3\n",
      "traitlets==5.14.3\n",
      "typing_extensions==4.15.0\n",
      "tzdata==2025.3\n",
      "umap-learn==0.5.11\n",
      "uri-template==1.3.0\n",
      "urllib3==2.6.3\n",
      "wcwidth==0.6.0\n",
      "webcolors==25.10.0\n",
      "webencodings==0.5.1\n",
      "websocket-client==1.9.0\n"
     ]
    }
   ],
   "source": [
    "!pip freeze"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fabf3d14",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "proteopy",
   "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": "3.10.19"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}