{
 "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.\n",
    "\n",
    "## What this notebook reproduces\n",
    "\n",
    "This is a faithful reproduction, not an approximation. Running it end to\n",
    "end recovers **the same 63 proteins** that Bludau et al. report as\n",
    "carrying multiple proteoform groups — the same count *and* the same\n",
    "accessions, including the two the paper singles out, Ldb3 (Q9JKS4) and\n",
    "Sorbs2 (Q3UTJ2) — together with the proteoform score plot of Figure 6B.\n",
    "\n",
    "ProteoPy's COPF implementation is itself tested against the intermediate\n",
    "outputs of the original R code on this very dataset. Given the same\n",
    "peptides, its correlations, dendrograms, cluster assignments and\n",
    "proteoform scores agree with the reference to between 1e-14 and 1e-12,\n",
    "which leaves the peptide set as the one thing this notebook has to get\n",
    "right."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "nqku72pdj79",
   "metadata": {},
   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2bafc259",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:49:28.120552Z",
     "iopub.status.busy": "2026-08-03T06:49:28.120452Z",
     "iopub.status.idle": "2026-08-03T06:49:29.520913Z",
     "shell.execute_reply": "2026-08-03T06:49:29.520255Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ifichtner/miniforge3/envs/proteoform-repro_exp-04/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)\n",
    "\n",
    "# Protein sequences, needed to locate each peptide in its protein.\n",
    "# Shipped alongside this notebook so it runs straight after cloning.\n",
    "FASTA_PATH = \"uniprot_mus-musculus_reviewed_bludau-2021.fasta\""
   ]
  },
  {
   "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": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:49:29.522655Z",
     "iopub.status.busy": "2026-08-03T06:49:29.522408Z",
     "iopub.status.idle": "2026-08-03T06:50:12.106382Z",
     "shell.execute_reply": "2026-08-03T06:50:12.105715Z"
    }
   },
   "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 = (\n",
    "    \"data/williams-2018_mouse-tissue_sample_annotation.tsv\"\n",
    ")\n",
    "peptide_annotation_path = (\n",
    "    \"data/williams-2018_mouse-tissue_peptide_annotation.tsv\"\n",
    ")\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": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:50:12.108553Z",
     "iopub.status.busy": "2026-08-03T06:50:12.108430Z",
     "iopub.status.idle": "2026-08-03T06:50:12.283511Z",
     "shell.execute_reply": "2026-08-03T06:50:12.282400Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sample_id\tpeptide_id\tintensity\r\n",
      "C57_Brain\tAAAAAAAAAAAAAAAGAAGK\t26302.0\r\n",
      "DBA_Brain\tAAAAAAAAAAAAAAAGAAGK\t15460.0\r\n",
      "45_Brain\tAAAAAAAAAAAAAAAGAAGK\t24631.0\r\n",
      "66_Brain\tAAAAAAAAAAAAAAAGAAGK\t26554.0\r\n"
     ]
    }
   ],
   "source": [
    "# intensities\n",
    "!head -n5 {intensities_path}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "cfbf3627",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:50:12.286257Z",
     "iopub.status.busy": "2026-08-03T06:50:12.286158Z",
     "iopub.status.idle": "2026-08-03T06:50:12.476164Z",
     "shell.execute_reply": "2026-08-03T06:50:12.474900Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sample_id\ttissue\tmouse_id\r\n",
      "C57_Brain\tBrain\tC57\r\n",
      "DBA_Brain\tBrain\tDBA\r\n",
      "45_Brain\tBrain\t45\r\n",
      "66_Brain\tBrain\t66\r\n"
     ]
    }
   ],
   "source": [
    "# sample_annotation\n",
    "!head -n5 {sample_annotation_path}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "b6d872a8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:50:12.478082Z",
     "iopub.status.busy": "2026-08-03T06:50:12.477874Z",
     "iopub.status.idle": "2026-08-03T06:50:12.650799Z",
     "shell.execute_reply": "2026-08-03T06:50:12.649620Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "peptide_id\tprotein_id\tgene_id\r\n",
      "AAAAAAAAAAAAAAAGAAGK\tP55012\tSlc12a2\r\n",
      "AAAAADLANR\tQ9JHS4\tClpx\r\n",
      "AAAADGEPLHNEEER\tQ80WW9\tDdrgk1\r\n",
      "AAAAEGARPLER\tQ80UM7\tMogs\r\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."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "981576e9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:50:12.653447Z",
     "iopub.status.busy": "2026-08-03T06:50:12.653260Z",
     "iopub.status.idle": "2026-08-03T06:50:13.534886Z",
     "shell.execute_reply": "2026-08-03T06:50:13.534351Z"
    }
   },
   "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 downloaded files.\n",
    "# `fill_na` is deliberately left unset: see above.\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",
    ")\n",
    "\n",
    "adata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "795e2296",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:50:13.537666Z",
     "iopub.status.busy": "2026-08-03T06:50:13.537554Z",
     "iopub.status.idle": "2026-08-03T06:50:13.550863Z",
     "shell.execute_reply": "2026-08-03T06:50:13.550489Z"
    }
   },
   "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": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:50:13.552010Z",
     "iopub.status.busy": "2026-08-03T06:50:13.551908Z",
     "iopub.status.idle": "2026-08-03T06:50:13.557794Z",
     "shell.execute_reply": "2026-08-03T06:50:13.557519Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "</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",
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       "      <th>101_Brain</th>\n",
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       "      <td>80</td>\n",
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       "    <tr>\n",
       "      <th>BAT_101</th>\n",
       "      <td>BAT_101</td>\n",
       "      <td>BAT</td>\n",
       "      <td>101</td>\n",
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       "    <tr>\n",
       "      <th>BAT_45</th>\n",
       "      <td>BAT_45</td>\n",
       "      <td>BAT</td>\n",
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       "    <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": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:50:13.558795Z",
     "iopub.status.busy": "2026-08-03T06:50:13.558722Z",
     "iopub.status.idle": "2026-08-03T06:50:13.562238Z",
     "shell.execute_reply": "2026-08-03T06:50:13.561974Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<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": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:50:13.562979Z",
     "iopub.status.busy": "2026-08-03T06:50:13.562903Z",
     "iopub.status.idle": "2026-08-03T06:50:13.567483Z",
     "shell.execute_reply": "2026-08-03T06:50:13.567187Z"
    }
   },
   "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": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:50:13.568816Z",
     "iopub.status.busy": "2026-08-03T06:50:13.568721Z",
     "iopub.status.idle": "2026-08-03T06:50:13.645785Z",
     "shell.execute_reply": "2026-08-03T06:50:13.645277Z"
    }
   },
   "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": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:50:13.647413Z",
     "iopub.status.busy": "2026-08-03T06:50:13.647324Z",
     "iopub.status.idle": "2026-08-03T06:50:13.698763Z",
     "shell.execute_reply": "2026-08-03T06:50:13.698461Z"
    }
   },
   "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": [
    "As per the original analysis, we remove one protein by hand: **A2ASS6** (titin), which carries far more peptides than any other and distorts the analysis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "1227eeaf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:50:13.700375Z",
     "iopub.status.busy": "2026-08-03T06:50:13.700279Z",
     "iopub.status.idle": "2026-08-03T06:50:13.702580Z",
     "shell.execute_reply": "2026-08-03T06:50:13.702286Z"
    }
   },
   "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": 14,
   "id": "da282d13",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:50:13.703644Z",
     "iopub.status.busy": "2026-08-03T06:50:13.703549Z",
     "iopub.status.idle": "2026-08-03T06:50:13.713728Z",
     "shell.execute_reply": "2026-08-03T06:50:13.713467Z"
    }
   },
   "outputs": [],
   "source": [
    "adata = adata[:, ~A2ASS6_mask]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd4bb21d",
   "metadata": {},
   "source": [
    "### Summarising redundant peptides\n",
    "\n",
    "Several peptides can report on the same stretch of a protein: missed cleavages produce overlapping sequences, and one sequence can appear in several modified forms introduced during sample preparation or MS analysis. We therefore group peptides by **where they sit in the protein sequence** and keep the most abundant member of each group."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "58bbd476",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:50:13.715887Z",
     "iopub.status.busy": "2026-08-03T06:50:13.715805Z",
     "iopub.status.idle": "2026-08-03T06:50:22.271502Z",
     "shell.execute_reply": "2026-08-03T06:50:22.270495Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "summarize_peptides_by_neighbourhood_union: 31771 -> 25613 peptides across 25613 neighbourhood group(s)\n"
     ]
    }
   ],
   "source": [
    "pr.pp.summarize_peptides_by_neighbourhood_union(\n",
    "    adata,\n",
    "    annotator=FASTA_PATH,\n",
    "    top_n=1,\n",
    "    on_unknown_protein=\"keep\",\n",
    "    on_unlocated_peptide=\"keep\",\n",
    "    keep_var_cols=[\"gene_id\"],\n",
    "    verbose=True,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e833350d",
   "metadata": {},
   "source": [
    "### Filtering\n",
    "\n",
    "In preparation for the COPF algorithm we filter the dataset on three criteria:\n",
    "\n",
    "1. Peptides must be quantified in **every** sample.\n",
    "2. Peptides must have a positive variance.\n",
    "3. A protein needs **at least 2 peptides** to be scorable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "d881ffdd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:50:22.273325Z",
     "iopub.status.busy": "2026-08-03T06:50:22.273107Z",
     "iopub.status.idle": "2026-08-03T06:50:22.379031Z",
     "shell.execute_reply": "2026-08-03T06:50:22.378446Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "137 var removed\n",
      "Removed 928 proteins and 928 peptides.\n",
      "24,534 peptides across 2,885 proteins\n"
     ]
    }
   ],
   "source": [
    "pr.pp.filter_var_completeness(adata, min_fraction=1.0)\n",
    "pr.pp.remove_zero_variance_vars(adata)\n",
    "pr.pp.filter_proteins_by_peptide_count(adata, min_count=2)\n",
    "\n",
    "print(\n",
    "    f\"{adata.n_vars:,} peptides across \"\n",
    "    f\"{adata.var['protein_id'].nunique():,} proteins\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "63fd4546",
   "metadata": {},
   "source": [
    "This leaves **24,534 peptides across 2,885 proteins**. Every peptide is now\n",
    "quantified in all 40 samples, so the exploratory analysis below needs no\n",
    "imputation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "6f8a6601",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:50:22.380710Z",
     "iopub.status.busy": "2026-08-03T06:50:22.380543Z",
     "iopub.status.idle": "2026-08-03T06:50:22.521101Z",
     "shell.execute_reply": "2026-08-03T06:50:22.520578Z"
    }
   },
   "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",
      "    24322.5      158.4       24405.5      23828      24471      99.1      0.6        99.5     97.1     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     24317.8      125.0       24259.5      24188      24471      99.1      0.5        98.9     98.6     99.7\n",
      " Brain     24425.5        5.2       24424.5      24420      24435      99.6      0.0        99.6     99.5     99.6\n",
      " Heart     24053.1      104.8       24050.0      23828      24178      98.0      0.4        98.0     97.1     98.5\n",
      " Liver     24424.9       10.4       24427.0      24409      24441      99.6      0.0        99.6     99.5     99.6\n",
      "  Quad     24391.4       23.4       24389.0      24368      24439      99.4      0.1        99.4     99.3     99.6\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": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:50:22.522811Z",
     "iopub.status.busy": "2026-08-03T06:50:22.522724Z",
     "iopub.status.idle": "2026-08-03T06:50:22.644570Z",
     "shell.execute_reply": "2026-08-03T06:50:22.644126Z"
    }
   },
   "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",
      "     2884.8        0.4        2885.0       2883       2885     100.0      0.0       100.0     99.9    100.0\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      2884.9        0.4        2885.0       2884       2885     100.0      0.0       100.0    100.0    100.0\n",
      " Brain      2885.0        0.0        2885.0       2885       2885     100.0      0.0       100.0    100.0    100.0\n",
      " Heart      2884.4        0.7        2884.5       2883       2885     100.0      0.0       100.0     99.9    100.0\n",
      " Liver      2885.0        0.0        2885.0       2885       2885     100.0      0.0       100.0    100.0    100.0\n",
      "  Quad      2885.0        0.0        2885.0       2885       2885     100.0      0.0       100.0    100.0    100.0\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": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:50:22.646115Z",
     "iopub.status.busy": "2026-08-03T06:50:22.646021Z",
     "iopub.status.idle": "2026-08-03T06:50:22.739672Z",
     "shell.execute_reply": "2026-08-03T06:50:22.739221Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    mean  median  mode  variance  min  max\n",
      "8.503986     6.0     2 80.414426    2  117\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": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:50:22.740744Z",
     "iopub.status.busy": "2026-08-03T06:50:22.740643Z",
     "iopub.status.idle": "2026-08-03T06:50:22.967797Z",
     "shell.execute_reply": "2026-08-03T06:50:22.967453Z"
    }
   },
   "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": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:50:22.969120Z",
     "iopub.status.busy": "2026-08-03T06:50:22.968975Z",
     "iopub.status.idle": "2026-08-03T06:50:23.217767Z",
     "shell.execute_reply": "2026-08-03T06:50:23.217376Z"
    }
   },
   "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)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "40e61923",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:50:23.222970Z",
     "iopub.status.busy": "2026-08-03T06:50:23.222633Z",
     "iopub.status.idle": "2026-08-03T06:50:23.699961Z",
     "shell.execute_reply": "2026-08-03T06:50:23.699582Z"
    }
   },
   "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": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:50:23.700930Z",
     "iopub.status.busy": "2026-08-03T06:50:23.700846Z",
     "iopub.status.idle": "2026-08-03T06:50:31.561744Z",
     "shell.execute_reply": "2026-08-03T06:50:31.561323Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ifichtner/miniforge3/envs/proteoform-repro_exp-04/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 implements the COPF workflow's four main steps:\n",
    "1. compute pairwise correlations between all peptides of a protein\n",
    "2. cluster the correlation distances hierarchically\n",
    "3. cut each dendrogram into two candidate proteoform groups\n",
    "4. score the difference between within- and between-cluster correlation, and compute Benjamini–Hochberg adjusted p-value.\n",
    "\n",
    "These four steps are covered by ProteoPy's test suite against the original R implementation's own intermediate outputs on this dataset, agreeing to between 1e-14 and 1e-12."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "a5c373eb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:50:31.562996Z",
     "iopub.status.busy": "2026-08-03T06:50:31.562893Z",
     "iopub.status.idle": "2026-08-03T06:51:18.801255Z",
     "shell.execute_reply": "2026-08-03T06:51:18.800796Z"
    }
   },
   "outputs": [],
   "source": [
    "# COPF pipeline: correlate, cluster, score\n",
    "pr.tl.pairwise_peptide_correlations(adata)\n",
    "pr.tl.peptide_dendograms_by_correlation(\n",
    "    adata, method=\"agglomerative-hierarchical-clustering\"\n",
    ")\n",
    "pr.tl.peptide_clusters_from_dendograms(\n",
    "    adata, n_clusters=2, min_peptides_per_cluster=2\n",
    ")\n",
    "pr.tl.proteoform_scores(adata, min_score=0.1, min_pval_adj=0.1)"
   ]
  },
  {
   "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 both called significant, and are examined in detail below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "d028e8eb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:51:18.803227Z",
     "iopub.status.busy": "2026-08-03T06:51:18.803138Z",
     "iopub.status.idle": "2026-08-03T06:51:18.809081Z",
     "shell.execute_reply": "2026-08-03T06:51:18.808748Z"
    }
   },
   "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>gene_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>VLPGPSQPR</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>Ldb3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VGIFPISYVEK</th>\n",
       "      <td>Q3UTJ2</td>\n",
       "      <td>Sorbs2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            protein_id gene_id\n",
       "VLPGPSQPR       Q9JKS4    Ldb3\n",
       "VGIFPISYVEK     Q3UTJ2  Sorbs2"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The two proteins the paper singles out, highlighted by gene symbol below.\n",
    "bludauI_proteoforms = [\"Ldb3\", \"Sorbs2\"]\n",
    "\n",
    "adata.var.loc[\n",
    "    adata.var[\"gene_id\"].isin(bludauI_proteoforms),\n",
    "    [\"protein_id\", \"gene_id\"],\n",
    "].drop_duplicates()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "2e11160b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:51:18.810082Z",
     "iopub.status.busy": "2026-08-03T06:51:18.809983Z",
     "iopub.status.idle": "2026-08-03T06:51:19.454582Z",
     "shell.execute_reply": "2026-08-03T06:51:19.453946Z"
    }
   },
   "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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MiKSurq4OK1aswNy5c7FgwQIEg8FB78OSJkRERDSWTIju19tuuw3/7//9PyxbtgwdHR2wWq2D3qe2tha1tbVQFGUUIiQiIiI6N+O+pe7AgQMwm81YtmwZACA3N3dIg/zZUkdERERjSdqTui1btuD6669HcXExBEHAs88+22ef2tpalJWVwWazoaqqCjt27Bjy8Y8cOQKXy4Xrr78eF110Ef7t3/5tGKMnIiIiygxp734NBoMoLy/HHXfc0e+KBU8++SRqamrw2GOPoaqqCuvXr8eqVatw+PBhTJo0CQBQUVEBWZb73Pfll1+GLMt48803sXfvXkyaNAnXXHMNKisrcdVVVw0YF7tf+xpKtzURERGlR0bVqRMEARs3bsTq1auNbVVVVaisrMSjjz4KAFBVFSUlJbjrrrtw7733DnrM7du34/vf/z5eeuklAMDDDz8MALjnnnv63T8SiSASiRi/+3w+lJSUTPg6dURERDS6Uq1Tl/bu14FEo1Hs3r0bK1euNLaJooiVK1di+/btQzpGZWUlWltb0dnZCVVVsWXLFlxwwQVJ93/wwQfh8XiMfyUlJef8PIiIiIhGWkYnde3t7VAUBYWFhQnbCwsL0dzcPKRjmEwm/Nu//Rsuv/xyLFy4EOeddx4++clPJt3/vvvug9frNf7V19ef03MgIiIiGg1pH1M3Gq699lpce+21Q9rXarVy7Fg/ZFnGq6++CgC48soruUwYERFRhsnoK3N+fj4kSUJLS0vC9paWFhQVFaUpqolJ0zTjdcigYZhERET0kYzufrVYLFi0aBE2b95sbFNVFZs3b8bSpUvTGBkRERFRZkl7S10gEMDRo0eN3+vq6rB3717k5uaitLQUNTU1WLt2LRYvXowlS5Zg/fr1CAaDuP3229MYNREREVFmSXtSt2vXLqxYscL4vaamBgCwdu1aPP7441izZg3a2tpw//33o7m5GRUVFdi0aVOfyRNEREREE1nak7rly5cPOkZr3bp1WLdu3ShFRERERDT2ZPSYOiIiIiIamrS31NHYIUlSukMgIiKiJJjU0ZCYzWbccsst6Q6DiIiIkmD3KxEREdE4wKSOiIiIaBxgUpdEbW0t5s6di8rKynSHkhEURcGrr76KV199FYqipDscIiIi6oVJXRLV1dU4ePAgdu7cme5QMoKqqmhoaEBDQwNUVU13OERERNQLkzoiIiKicYBJHREREdE4wKSOiIiIaBxgUkdEREQ0DjCpIyIiIhoHmNQRERERjQNcJiyJ2tpa1NbWsibbR8xmM2699dZ0h0FERERJCJqmaekOIpP5fD54PB54vV643e50h0NEREQTRKo5CLtfiYiIiMYBdr/SkCiKgrfeegsAcNlll0GSpDRHRERERPGY1NGQqKqKU6dOGT8zqSMiIsos7H4lIiIiGgeY1CVRW1uLuXPnorKyMt2hEBEREQ2KSV0S1dXVOHjwIHbu3JnuUIiIiIgGxaSOiIiIaBxgUkdEREQ0DjCpS4Jj6oiIiGgs4YoSg+CKEj00TYMsywAAk8kEQRDSHBEREdH4lmoOwjp1NCSCIMBsNqc7DCIiIkqC3a9ERERE4wCTuiQ4pi6RoijYunUrtm7dCkVR0h0OERER9cKkLgnWqUukqiqOHz+O48ePQ1XVdIdDREREvTCpIyIiIhoHJsREibKyMrjdboiiiJycHLz22muD3qe2tha1tbXsaiQiIqIxYUIkdQCwbds2uFyuIe9fXV2N6upqYzoxERFRJlA1FXVd9QjGujE1azJy7dnpDokyxIRJ6lLFljoiIso0h84cxe8PPgN/NABN02ASJJyXOx1fWnAzrCZrusOjNEv7mLotW7bg+uuvR3FxMQRBwLPPPttnn9raWpSVlcFms6Gqqgo7duxI6TEEQcAVV1yByspKPPHEE0O6DydKEBFRJmnv7sBje/8AkyAh15aNPHsOPDY3Tnob8Kt9f0x3eJQB0t5SFwwGUV5ejjvuuAOf+tSn+tz+5JNPoqamBo899hiqqqqwfv16rFq1CocPH8akSZMAABUVFcZqB/FefvllFBcX46233sKUKVPQ1NSElStXYsGCBVi4cOGAcbGljoiIMsnzx/4Oh9nWZ0Ufu9mGo10n0dZ9BgWOvDRFR5ngrJYJ+/3vf4/HHnsMdXV12L59O6ZNm4b169dj+vTpuPHGG88+GEHAxo0bsXr1amNbVVUVKisr8eijjwLoKa1RUlKCu+66C/fee2/Kj3HPPfdg3rx5uO2224a0P5cJ66FpGiKRCADAarVymTAiolH2o+2PIKbG+r3NG/Hhs3NuwNIpF41yVDSSUs1BUu5+/fnPf46amhpcd9116OrqMlqysrOzsX79+pQDHkg0GsXu3buxcuVKY5soili5ciW2b98+pGMEg0H4/X4AQCAQwKuvvop58+Yl3T8SicDn8yX8o56E22azwWbr+y2RiIhGnlk0IVk7jKJpcFkcoxwRZZqUk7pHHnkEv/rVr/Cd73wHkiQZ2xcvXoz33ntvWINrb2+HoigoLCxM2F5YWIjm5uYhHaOlpQWXXXYZysvLcfHFF+OLX/zigKtEPPjgg/B4PMa/kpKSc3oOREREw+HSKYvhjfr7bNc0DXbJivNzZ6YhKsokKY+pq6urw4UXXthnu9VqRTAYHJaghtOMGTOwb9++Ie9/3333oaamxvjd5/MxsUPPMmG7du0C0JPAxyf0REQ08i4uvgg7mvbhlK8BbqsLgiBAVmX4ogHcOvcfYZbM6Q6R0izlpG769OnYu3cvpk2blrB906ZNuOCCC4YtMADIz8+HJEloaWlJ2N7S0oKioqJhfSyd1WqF1cpp4b2pqooPP/wQAHDRRRcxqSMiGmWSKOGuRbfhrdM7sa1hN6JqDJNdhfjqzM+j1D0l3eFRBkg5qaupqUF1dTXC4TA0TcOOHTvwpz/9CQ8++CB+/etfD2twFosFixYtwubNm43JE6qqYvPmzVi3bt2wPhYREVGmM4kmLC9diuWlS9MdCmWglJO6L3/5y7Db7fjud7+L7u5u3HLLLSguLsZ//ud/4uabb045gEAggKNHjxq/19XVYe/evcjNzUVpaSlqamqwdu1aLF68GEuWLMH69esRDAZx++23p/xYREREROPVWdWp+/znP4/Pf/7z6O7uRiAQMOrFnY1du3ZhxYoVxu/6eLa1a9fi8ccfx5o1a9DW1ob7778fzc3NqKiowKZNm/pMniAiIiKayM6p+LDD4YDDcW5TqJcvX550irZu3bp17G4lIiIiGsBZTZQYqE7Z8ePHzykgIiIiIkpdykndN77xjYTfY7EY3n33XWzatAn33HPPcMVFRERERClIOam7++67+91eW1tr1DGj8cdkMuGmm24yfiYiIqLMkvKKEslce+21+Mtf/jJch6MMIwgCXC4XXC4XlwkjIiLKQMOW1D399NPIzc0drsMRERERUQpS7ke78MILE1pqNE1Dc3Mz2tra8F//9V/DGhxlDkVRsHfvXgBARUUFV5QgIiLKMCkndfrKDjpRFFFQUIDly5fj/PPPH6640q62tha1tbVQFCXdoWQEVVVx8OBBAMDChQuZ1BEREWUYQRusSNwE5/P54PF44PV64Xa70x1O2sRiMWzYsAEAcPPNN8Ns5sLRREREIynVHGRILXU+n2/IAUzkxIeIiIgoXYaU1GVnZw8641HTNAiCwO5KIiIiojQYUlL32muvjXQcRERERHQOhpTUXXHFFSMdBxERERGdg7NeGqC7uxunTp1CNBpN2L5w4cJzDoqIiIiIUpNyUtfW1obbb78dL774Yr+3c0zd+GQymXD99dcbPxMREVFmSXlFiW984xvo6urCO++8A7vdjk2bNuF3v/sdzjvvPPztb38biRjTora2FnPnzkVlZWW6Q8kIgiAgOzt7SJNmiIiIaPSlXKdu8uTJ+Otf/4olS5bA7XZj165dmD17Nv72t7/hoYcewltvvTVSsaYF69QRERFROqSag6TcUhcMBjFp0iQAQE5ODtra2gAACxYswJ49e1I9HI0RiqJg37592LdvH7vYiYiIMlDKSd2cOXNw+PBhAEB5eTl+8YtfoKGhAY899hgmT5487AFSZlBVFfv378f+/fuhqmq6wyEiIqJeUh7xfvfdd6OpqQkA8MADD+Caa67BE088AYvFgscff3y44yMiIiKiIUg5qfvCF75g/Lxo0SKcPHkShw4dQmlpKfLz84c1uHSqra1FbW0tuxqJiIhoTEi5+7X3RAiHw4GLLrpoXCV0AFBdXY2DBw9i586d6Q6FiIiIaFApJ3VXXnklpk+fjn/913/FwYMHRyImIiIiIkpRykldY2MjvvnNb+KNN97A/PnzUVFRgYcffhinT58eifiIiIiIaAhSTury8/Oxbt06bN26FceOHcNnPvMZ/O53v0NZWRmuvPLKkYiRiIiIiAaRcvHh3hRFwYsvvojvfe972L9//7iZWBA/UeLDDz+c8MWHVVVFR0cHACA3NxeimPL3ASIiIkpBqsWHzzqp27p1K5544gk8/fTTCIfDuPHGG/H5z38e11xzzdkcLmNxRQkiIiJKh1RzkJRLmtx3333YsGEDGhsbcdVVV+E///M/ceONN8LhcJxVwERERER07lJO6rZs2YJ77rkHn/3sZ8ddGZN4rFOXSFEUHDp0CABw/vnnQ5KkNEdERERE8c5pTN2f/vQn3HDDDXA6ncMZU0Zh92uPWCyGDRs2AABuvvlmmM3mNEdEREQ0vqWag5zTaPc777wTLS0t53IIIiIiIhoG55TUnePE2YxWW1uLuXPnorKyMt2hEBEREQ1qwtSl6O7uxrRp0/Ctb31rSPtzmTAiIiIaS84pqXvxxRcxZcqU4YplRP3oRz/CxRdfnO4wiIiIiEbEWSd1ra2t0DQNO3bsQGtr63DGNOyOHDmCQ4cO4dprrx3yfdj9SkRERGNJykmd3+/HrbfeiilTpuCKK67AFVdcgSlTpuALX/gCvF5vygFs2bIF119/PYqLiyEIAp599tk++9TW1qKsrAw2mw1VVVXYsWNHSo/xrW99Cw8++GBK92H3KxEREY0lKSd1X/7yl/HOO+/g+eefR1dXF7q6uvD8889j165duPPOO1MOIBgMory8HLW1tf3e/uSTT6KmpgYPPPAA9uzZg/LycqxatSqhdbCiogLz58/v86+xsRF//etfMXv2bMyePTuluNhSl0iSJFx11VW46qqrWKOOiIgoA6Vcp87pdOKll17CZZddlrD9zTffxDXXXINgMHj2wQgCNm7ciNWrVxvbqqqqUFlZiUcffRRAzxqkJSUluOuuu3DvvfcOesz77rsPf/jDHyBJEgKBAGKxGL75zW/i/vvv73f/SCSCSCRi/O7z+VBSUjLh69QREdHwiikx7Gzejx1NewEASyZXoLJoIcwS64BSjxGvU5eXlwePx9Nnu8fjQU5OTqqHG1A0GsXu3buxcuVKY5soili5ciW2b98+pGM8+OCDqK+vx4kTJ/DjH/8YX/nKV5ImdPr+Ho/H+FdSUnLOz4OIiChedyyEB9+pxVOHn0dnuAud4S48dfh5/PuOnyMUC6c7PBqjUk7qvvvd76KmpgbNzc3GtubmZtxzzz343ve+N6zBtbe3Q1EUFBYWJmwvLCxMePzhdN9998Hr9Rr/6uvrR+RxxhpVVXH48GEcPnwYqqqmOxwiooxX72vEo3sex/fe+jF+sPWn+NvRVxCRe3qC/njwWXTHuuGxZkEQBAiCAI81C/5oAH/64K9pjpzGqpTXfv35z3+Oo0ePorS0FKWlpQCAU6dOwWq1oq2tDb/4xS+Mfffs2TN8kQ6D2267bdB9rFYrrFbryAczxiiKYkxQmTFjBkRxwpQ4JCJK2f7Wg/j1/ifhtjphEk3QoGFL/dvY3/oBvrHoDhzuPAan2dHnfnaTDYc6jkJWZZjElC/RNMGl/I6JH+820vLz8yFJUp+lyFpaWlBUVDRqcRAREQ2Vqql48vDzyLG5IQiCsd1lcaIr4sXzx1+FMkCPh6wpiMhRmCxM6ig1Kb9jHnjggZGIo18WiwWLFi3C5s2bjWRSVVVs3rwZ69atG7U4iIiIhuqUrwH+SAC59uw+t7ksThw6cxRWkyXp/W2SFXazbQQjpPEq7V8DAoEAjh49avxeV1eHvXv3Ijc3F6WlpaipqcHatWuxePFiLFmyBOvXr0cwGMTtt9+exqiJiIj6F1Vi0JC8sIQKDZVF5djWsAsuizPhNn80iMunLoEocIgLpS7tSd2uXbuwYsUK4/eamhoAwNq1a/H4449jzZo1aGtrw/3334/m5mZUVFRg06ZNfSZPEBERDSdFVRCWI7CZrJDEodfnLHYVwiL13xInqzImuwpx46yrcSbUiQPtH8IimaFBQ1SRsbBgDq6fddVwPYV+xZQYYqoMu8mW0D1MY1/ak7rly5djsFJ569atY3crERGNiqgSxVOH/xf7Ww8hpsZgkcxYVLgAN82+ZkiTF1wWJyomzcW+1oMJLXGapsEfDeL/zLoakijhK+W3oCXYhp1N+yEIQGVROSY580fseZ3p7sQTHzyLU77TUKEhy+zEVWXLcNnUJSP2mDS60p7UERERZQpVU/Gz3f+NlmA7nBY77OiphrCjaS+ag21Yd9FtQ2rduuWC1QCAvS0HEFFjECEgy+rCVxZ+DlOzJhv7FToL8MlZnxiR5xLPG/Hh33f8HBbJZCSamqbh6cMvIBgNYdWMK0Y8Bhp5TOpoSCRJMrrJuUwYEY1XB9uPoN7fiBxbYpF9p8WBo10ncdJ3GmWewYvSS6KEW+f9I2467xo0BlpglSwocRenbazc80c3QxSQ0NIoCAKybW68emorVkxbmrTLmMaOYXt3/fWvf8X//M//DNfhKMOIooipU6di6tSprFFHROPWtsZd8Fiz+r3NabZhW8PulI7nsjgxO3cGpnmmpnXyw5HOOthM/c+o7ZZDOOVrHOWIaCQM2zvsX/7lXzgjlYiIxjR1wDHewoCzWscqTcO4fF4T0bAldYcOHYKiKMN1OMowqqri2LFjOHbsGJcJI6Jx65Ipi+CLBvq9LRjrxiXFi0Y5ouExI7vUWKKsN4fZhtKs4lGOiEYC+9FoSBRFwbZt27Bt2zYm70Q0bs3Pn4PJzknojoUTtgdjIUz3lAxpPF0mumHWVZA1BbIqJ2z3RvxYXroUVhOXxxwPhjRRYv/+/Zg/fz5EUcT+/fsH3NflcqGkpARms3lYAkyX2tpa1NbWMoEhIppAREHENxZ9CRsOPYcD7YehaApMohkXTZqPT8+5bszWdcu2eXBP5f/BEx88i9O+RmgAnGYHbpx1Na4ouTjd4dEwEbTBisShZ5B8c3MzJk2aBFEUIQjCgLXlPB4PHnvsMaxZs2ZYg00Hn88Hj8cDr9cLt9ud7nDSJhaLYcOGDQCAm2++ecwn7UREg4kpMYTkMBxm+5Dq040VYTmMmCrDZXaO2SR1okg1BxnSu7Surg4FBQXGzwOJRCJ46qmn8C//8i/jIqkjIqKJySyZYZbG3xdYm8kGriw7Pg0pqZs2bVq/Pyfzta99Dbt3pzbtm4iIiIjO3pDH1A3VwoULkZOTg2eeeeasgyIiIiKi1AwpqauoqDDG0Q3W/86JBURERESjb8hj6nTvvvsuvvWtb+Gee+7B0qVLAQDbt2/Hf/zHf+Chhx4amSgp7SRJwuWXX278TERERJkl5TF1n/nMZ/Czn/0M1113nbFt4cKFKCkpwfe+9z2sXr162IOk9BNFcUjjKYmIiCg9Ui4+/N5772H69Ol9tk+fPh0HDx4clqAyQW1tLebOnYvKysp0h0JEREQ0qCHVqYt30UUXYf78+fj1r38Ni8UCAIhGo/jyl7+M999/H3v27BmRQNOFdep6qKqK+vp6AEBJSQlEkYuREBERjaQRqVMX77HHHsP111+PqVOnYuHChQB6ZscKgoDnnnsu9YhpTFAUBVu2bAHQU3yYSR0REVFmSTmpW7JkCY4fP44nnngChw4dAgCsWbMGt9xyC5xO57AHSERERESDO6t1T5xOJ7761a8OdyxEREREdJbOejG7gwcP4tSpU4hGownbb7jhhnMOKhPU1taitraWdfeIiIhoTEg5qTt+/DhuuukmvPfee0ZBYgBGUeLxkgRVV1ejurraGKRIRDTWHO86iReOv4auiA9Okx1XlV2OefmzuYg70TiV8mj3u+++G9OnT0drayscDgcOHDiALVu2YPHixXj99ddHIEQiIkrVKye2YP2u36A52ApZldEZ8eKX+57Ak4c5oY1ovEo5qdu+fTt++MMfIj8/H6IoQhRFXHbZZXjwwQfx9a9/fSRiJCKiFPgifrxw/DXk2rNhEns6ZERBRK49G9sadqHe15jmCIloJKTc/aooCrKysgAA+fn5aGxsxJw5czBt2jQcPnx42ANMF46pSyRJEi655BLjZyLKXFsbdkES+v/OnmV24ZWTb+KOBWtGOSoaToqqYFfzfrx1egeiagwlWcW4bsaVyLVnpzs0SqOUk7r58+dj3759mD59OqqqqvDQQw/BYrHgl7/8JWbMmDESMaYFx9QlEkURM2fOTHcYRDQEnWEvLJKl39vMkgnBaPcoR0TDSVEV/Ne7/4OjXSeRbc2CIAh4v/0wdre8h3+quBWzc8fPtZhSk3L363e/+12oqgoA+OEPf4i6ujosW7YML7zwAn72s58Ne4BERJSaC3JnoTsW6vc2fySI83L7LvVIY8fWhl047j2FHJvbmPRiM1nhtrjwu/efhqqpaY6Q0iXllrpVq1YZP8+aNQuHDh1CR0cHcnJyOKNqHFNVFY2NPeNwiouLuaIEUQZbOOkCuI+6IKuyMaYOAFRNhSgIuHxqVRqjo3P1VsNOuC2uPtsFQYA/GsCJrnrMyJmWhsgo3YblypybmzvuErra2lrMnTsXlZWV6Q4lIyiKgtdeew2vvfYaxxkSZThJlHD3RV+CVbKiM+yFN+JDR7gLqqbh64vugMNsT3eIdA6iSmzAa24gxu71ieqsiw+PdxxTR0RjWZ4jB99d+nWc8jWgIdCCAkcuZmZPg5hkAgWNHfn2bDQH2xJaYXWiKGJKVlEaoqJMwL9uIqJxShAETPNMxSVTFuG8nOlM6MaJT85YCV8kYBT/14XkMGZ5piHPnpOmyCjd+BeeBLtfiYgoE5Vll+DzF9yEbjmMzrAXvkgAXWEfJjsn4cvln0t3eJRGgtY71R9nurq6sHLlSsiyDFmWcffdd+MrX/nKkO+vd796vV643e4RjDSzxWIxbNiwAQBw8803w2w2pzkiIqKJLapEcaD9Q/ijQZyXU4bJrsJ0h0TDLNUcZNyPqcvKysKWLVvgcDgQDAYxf/58fOpTn0JeXl66QyMiIjprFsmCCwvnpzsMyiDjvvtVkiQ4HA4AQCQSgaZpfcYh9Ifdr0RERDSWpD2p27JlC66//noUFxdDEAQ8++yzffapra1FWVkZbDYbqqqqsGPHjpQeo6urC+Xl5Zg6dSruuece5OfnD3qf6upqHDx4EDt37kzpscYrSZKwZMkSLFmyhMuEERERZaC0J3XBYBDl5eWora3t9/Ynn3wSNTU1eOCBB7Bnzx6Ul5dj1apVaG1tNfapqKjA/Pnz+/zTi+VmZ2dj3759qKurwx//+Ee0tLQMGhdb6hKJoog5c+Zgzpw5LDxMRESUgTJqooQgCNi4cSNWr15tbKuqqkJlZSUeffRRAD0rG5SUlOCuu+7Cvffem/JjfO1rX8OVV16JT3/60/3eHolEEIlEjN99Ph9KSkom/EQJIiIiGl2pTpTI6CaXaDSK3bt3Y+XKlcY2URSxcuVKbN++fUjHaGlpgd/vBwB4vV5s2bIFc+bMSbr/gw8+CI/HY/wrKSk5tycxTqiqiubmZjQ3Nxtr/xIRnauwHMbGDzfhga3/ge9seQjrd/0GdV2n0h0W0ZiU0Ulde3s7FEVBYWHiNO3CwkI0NzcP6RgnT57EsmXLUF5ejmXLluGuu+7CggULku5/3333wev1Gv/q6+vP6TmMF4qi4JVXXsErr7zCZcKIaFhE5Age3vELbG3YCQECzJIJZ0IdWL/7N9jd/F66wyMac8Z9SZMlS5Zg7969Q97farXCarWOXEBERAQAeOXkW+iK+JBlcRrbJFFCttWNpz/8X1RMmgtJ5MQsoqHK6Ja6/Px8SJLUZ2JDS0sLioq4th0R0Vj2bsv7CQmdThAEBKJBnPSdTkNURGNXRid1FosFixYtwubNm41tqqpi8+bNWLp0aRojIyKic6VoyYdyaBoQkaOjGA3R2Jf27tdAIICjR48av9fV1WHv3r3Izc1FaWkpampqsHbtWixevBhLlizB+vXrEQwGcfvtt6cxaiIiOleTnZNwytcAs9R32UGryYwSd3EaoiIau9Ke1O3atQsrVqwwfq+pqQEArF27Fo8//jjWrFmDtrY23H///WhubkZFRQU2bdrUZ/IEERGNLTfOuhoPvlOLbNENQRCM7YFoEBWT5sHVT9csESWXUXXqMlGqNWLGq1gshg0bNgAAbr75ZpjNfb9ZExGl6tCZo3ji4LPwRf1QNQ1WyYwLJ83HzRfcwEkSNOGlmoOkvaWOxgZRFHHRRRcZPxMRDYfz82bhh5d9Ew2BZkTkCCa7CuEw29MdFgBA0zTsbtmPzSe3IiRH4LI4cO30FZiXPzvdoRH1iy11g2BLHRHRxKNpGv5w4BnsatmPbGtP97CqqfCG/VhZtgzXz1o5+EGIztG4WlGCiIgoHU76TmNny37k2DzGeD9REJFj92DzybfQGe5Kb4BE/WBSR0Oiqira29vR3t7OZcKIaNzbfHIr3EkmapglE946vWuUIyIaHJM6GhJFUfDiiy/ixRdf5DJhRDTudcdCkIT+J2qYRTN8Uf8oR0Q0OCZ1SdTW1mLu3LmorKxMdyhERDTK5uXPhj8W7Pe2bjmE+flzRjkiosExqUuiuroaBw8exM6dO9MdChERjbJLpiyCRTRDURN7JmJKDNlWNxYUnJ+myIiSY1JHRETUi81kQ83ir8AsmdEZ8uJMqBOdYS881iz88+IvQxR4+aTMwzp1RERE/ZjkzMf3lt6NhkAzOsNeFNhzUeSalO6wiJJiUkdERJSEIAiYmjUZU7MmpzsUokExqSMiIhohYTmMtxvfRb2/EVNdRbi4eBHsZlu6w6JxikkdDYkoili4cKHxMxHReKJpGt5vP4zXTm1HRI6g1FOMVWVXINvmOetjHjpzFL/e/yeomga7yYZ3Ww/g+eOv4ksL1mAulxqjEcBlwgbBZcKIiMY3TdPw6/1/wvvth+GxZkEURIRiYcRUGf9UcSvOy52e8jG7YyF8760fw2V2GCtS6I8ViHbjh5d9E06LYzifBo1DqeYgbKlLora2FrW1tSy0O4Y0B1qx8ehLOO1rgigIOC9nOlaftwpua1a6QyOaMFRNxRuntuPNhp2IyFE4zQ5cVbYMi4sWJiQ356Il0IZnj76EU/5GCND/1q+Gx3p2X7x3Ne/D++2HkRPXKmc32+ANtOKrL9+Li4svhE2yYsnkClxVtgwmcfBL59aGndA0rc9zFgQBggBsOf0Orp2x4qziJUqGLXWDYEtdD03T4PV6AQAej2fYPpyHS13XKfznnt/CaXLALPV84IblCADg3qqvnVMXChENjaZp+OW+J3Co4zjcFicEQej57Ij4sWxqJf5xzj+c82Oc9J7G+t2/gcNkN/7WI3IEqqbh3ou/hhxbdsrHfOidxxCMBRM+1452nsCRzhPQNA1VxRXIs+fAFwlgalYRrpq2DCd9jci35+DCwnmwmqx9jvnrfX/CKX9Dv6VPNE1DkXMS/unCW1OOlSaWVHMQDo6iIZFlGc899xyee+45yLKc7nD6+OMHz8JtcRkf8gBgM1khCiL+fPh/0xgZ0cRxuOMYDp45Ao/VZSRIgiAg2+bGmw070RHqOufHeOKDZ5FlcSb8rVtNVphECU8eev6sjhlVIgkJXVSJ4VjXSdhNVoiCYHxBNIkSNhx6Dv/v7Uew5fTbePLQc/jumw9jb8uBPsec7JqE7lio38frlkMoZmkUGgFM6mjM6wp70R7q7PcbsUUy42hnHdggTTTy3qh/G26Lq9/bzKIJWxt2ndPxvREf2rrP9Pu3bpbMONZ14qz+1vPsOZDVj7+sNgfboB9FA+C2ZkHTNLzTtBdW0YyusBcOsx0eWxYcZjv++/2ncCbUmXDMy0uqoGhqv/HIqoLlpUtTjpNoMEzqaMyLKjEAyT/IVU2DNsDtRDQ8Iko06UoLJtGEkNx/y9VQxZSBewk0TYOqqSkf9x9mfgL+yMfrvMbUGEQAsqbAbXUhy+JEe6gTYTkCSZSgxn2eCIIAu8mKTXWvJxwzy+LCLReshjfiN1rsQnIYXWEf1sy5/qzH/xENhBMlaMzLs+fAJvVf90nTNOTZs7mkD9EoWJA/B88d2wy3tW9rXXcsjPJJc8/p+Dk2Dxym5H/rOTYPJFFK+bil7ilYc8H1eObDFyFrCpwmB0JyBB6rGxfkzkJUiaIz7IVJlBBVYih0FCTc32ayoinQ2ue4lZPLcV5OGTaf3IqmYAsKHQVYWXbZWY37IxoKJnVJcPbr2CGJEpaXLMWmE6/DEzfTVdM0dEa8uHPO59MYHdHEccmUxXjl5FuQVTlhhmhYjqDQmY/ZOTPO6fiSKGFF6SX432OvwmNLnNXeGfbiywtvPutjXzJlMS4qnI+9LQfRFupAQ6AZzd1t2NG8FwIEAAKicgxWsxkzckoT7iurMlwWZ7/HzbZ58I9zrjvruIhSweaLJKqrq3Hw4EHs3Lkz3aHQEFw9/XJ8ovQyhGJhY+HtmCrj8+ffhHkFc9IdHtGEYDVZ8c3FX4XL4kJX2IczoS54I35McRXhG4u+NCyz5j8x7TJcPf1yhOQIOsJd6Ah1IarE8LkLbsTCc2wJtJlsqCq+EEc6j2N2zgwUOQogQISiqYjKUbSF2lFZWA6rZEm4ny8axNVly87psYmGA1vqaFwQBAGfnPUJXD19GRr8zZBECVNcRWfVFUNEZy/PkYN7q76G9u4O+KJ+5Nqyh7WkkCAIuHbGCnxi2qUj8rd+vOsUTvoakWNzY1HRAkSUKLpjIZhFM5qCLWgOtsFutsFmskJWZfiiQSybUonpntLBD040wpjU0ZCIooi5c+caP2cqi2TB9Gx+uBKlW74jF/mO3BE7/kj9re9u2Q9HXN05q2QxWuZmmcvgMNlR4i5GU6AVTosDV5ctw4zsacMeB9HZYFKXBMfUJZIkCYsWLUp3GEREI8osmhNmt8bToMFty8Itc1ePblBEQ5S5TS5pxjF1REQTzyVTFhnFhnvzRvy4fGrVKEdENHRM6mhINE1DIBBAIBBgIV+iYfDMM89g0aJFqKiowPnnn48rr7wSqppajbXvf//7+MY3vpHSff71X/8V559/PsrLy7F48WK89NJLKd1/vCt0FuCiwgXwRRI/6/zRIKZ7SnBB3qw0Rkc0MHa/0pDIsoyNGzcCAG6++WaYzeY0R0Q0djU1NeGrX/0qdu/ejWnTesZj7dmzJ6XZoWe7XN+yZcvwve99D3a7Hfv27cPll1+OxsZGOJ39l+TIJJqm4bS/CSe9p5Fjz8b5uTNHZDLUF+f9Iza7CvFmw04Eot2wmixYNnUJPjnzE6x5SRmNSV0SHFNHRCOlpaUFkiQhN/fjiQQXXXQRAGDXrl34+te/jkAgAJvNhp/+9Ke49NJLceLECVRUVODOO+/EK6+8gi9+8YsAgPr6elx55ZVobGzEeeedh8cffxx5eXl47rnn8J3vfAeiKEKWZfzoRz/CjTfeiGuvvdZ4zAULFkDTNLS1tY1KUheRe9ZYtfQqCdKfQDSIN+rfxilfA4pdhVhcVI7fH3gGTcEWSIIIRdPgMNnwxfn/iAvyzhvWOAVBwMqyZVhZtgyapg1LKRai0SBo7EsbkM/ng8fjgdfrhds9cZd1icVi2LBhAwC21A2XQDSIzrAXbquLSwZNMKqq4jOf+Qxee+01XHHFFbjkkktwyy23oKCgALNmzcKvfvUrrFq1Cm+99RY+/elP4+jRo2hvb8f06dPxu9/9zkjovv/97+O//uu/sH//fhQVFeFrX/saZFnGL3/5S5SXl+Oxxx7D0qVLoaoqfD4fsrOzE+L4zW9+g0ceeQTvvvvuiCYuB9oO49mjL6Ej3AVoAoqzCrFmzvWY6p7c7/77Ww/i8fefhigIcJodCMa6sa1hN2bnTEdZdomxn6Zp8Eb9uH/pN5Brz+73WERjWao5CNuRiUZZKBbGY3v/gAe2/gQ/3vlLfH/rT/GTnb+EN+JLd2g0SkRRxF/+8hds27YN11xzDbZu3Yp58+bh8OHDEEURq1atAgBcdtllKCwsxN69ewEAZrMZX/jCFxKO9Q//8A8oKioCAHz1q1/F3//+dwDAJz7xCdx999146KGHsH///j4J3ebNm/GDH/wATz755IgmdO+2vI9f7HsCUSWGLIsLWVYnusJe/HjXL9AYaO6zf3cshN+9/xdkWZxwWZwQBAExRYaiqTjUcTxhEoMgCLBJlj7rrhJNVOM+qauvr8fy5csxd+5cLFy4EE899dSQ7ldbW4u5c+eisrJyhCOkiUTTNPxsz29R5z2FLIsTOTY3PNYsnAl14sc7fomoEk13iDSKzj//fNx555149tlncfHFF+OZZ57ps098wuVwOAatE6nv/5Of/AT//d//DYfDgbVr1+Khhx4y9nnjjTdw++2347nnnsOcOSO34oqmaXj2yEvIsXkSnockSsgyO/H04Rf73Oet0zsSngcAnAl3QhJESKKIE97TCfvbTDY0+Psmh0QT0bhP6kwmE9avX4+DBw/i5Zdfxje+8Q0Eg8FB78eSJjQSjnaeQGOgBfZei5KbJTMC0SB2Nu1LU2Q0mhoaGrB161bj987OTtTV1aGiogKqquKVV14BAGzbtg3Nzc2oqKjocwx95MwLL7yAlpYWAMCvf/1rrFy5EgBw6NAhzJs3D+vWrcM//dM/4e233wYAbNmyBbfeeiv++te/ory8fCSfJs6EOuGN+PttCZRECfW+hj6z6U8HmuEwJ/592CQbVKgwiSb4o4GE21RNhS2uWDDRRDbuJ0pMnjwZkyf3jNsoKipCfn4+Ojo6Bh0UzIkSNBL2tLwHh9ne721uqwt7Wt7HpVPZOjzeybKMH/7wh6irq4PD4YAsy1i7di1uvPFGTJkyBV//+tfxzW9+EzabDU8//TRcLhfa29uN+x89ehRdXV0Aemaz3nLLLWhoaDAmSgA9pUsOHz4Mi8UCh8OBn//85wCAL33pS4hEIrj99tuN4/3+97/HggULhv15atCAgXp2+7mtNKsY77cdhtvqMrYVufJx8IyIqBKF2zUpYX9v2I/Pzrl+mCImGtvSntRt2bIFDz/8MHbv3o2mpiZs3LgRq1evTtintrYWDz/8MJqbm1FeXo5HHnkES5YsSfmxdu/eDUVRUFJSMui+1dXVqK6uNgYpTnSiKGL27NnGz3R2rJIViqoA/VRhUDUVZokTUCaCadOmJa0Pt3jxYmzbtq3P9rKyMiOR27FjB2666SYsXrw46WP015ULAEeOHEk94LOUb89FlsXV722KqqDYVdSnFe/SKZV48fhrCbNOTaIJF+Sdhz0t72GKs2f8oKqp6Ir4UFE4D/PyZ4/sEyEaI9J+dQ4GgygvL0dtbW2/tz/55JOoqanBAw88gD179qC8vByrVq1Ca2ursU9FRQXmz5/f519jY6OxT0dHB774xS/il7/85Yg/p/FIkiRUVVWhqqoKkjT8daEmikunLkZUifV7my8awPKSi0c5IhprTp06hfz8fNjt/bf4ZhJBEPDJGZ9AZ9ib0M2qair80SD+8bxr+9zHbrbhSwtvRiDWDX8kCEVVEIgG4bFm4d+vuA/n58+CVbIg2+rGlxaswe3zP8uSI0QfyaiSJoIg9Gmpq6qqQmVlJR599FEAPaUASkpKcNddd+Hee+8d0nEjkQiuuuoqfOUrX8Gtt946pPvEd79++OGHE76kCQ2fPx58Fjub98JtyTIuRv5oADM80/C1C7/ICxQN6KmnnsI111yDrKysdIcyZLua9+P5Y3+HL9IzHq7AkYc1538SM7KnJb1PdyyEt07vQL2/EcWuIiybugQuS+YXSCYaTqmWNEl79+tAotEodu/ejfvuu8/YJooiVq5cie3btw/pGJqm4bbbbsOVV145pIQuEokgEong1ltvxa233gqfzzek7trxTtM0RCI9pQSsVisTj3PwuQtuRKm7GK+d2o5ANAibyYqV05bh6rLLeV5pQK2trbDZbGMqoQOAxUULsahwAfzRACRBgtPiGPQ+DrMdV0+/YhSiIxo/Mjqpa29vh6IoKCwsTNheWFiIQ4cODekYW7duxZNPPomFCxfi2WefBTDwoOAHH3wQP/jBD84p7vFIlmWjHAyLD58bQRBw2dQluGxq6uNCaWDeiA/PH92MY94TECBibv55uKZs+ZCSiLFg27ZtWLZsWbrDGJLT/iY8d/QVtHSfgVmUcEnxIiwrqYJJzOjLDtGYNu7/ui677LKUFsm+7777UFNTY/zOljqisaE12I6Hdz4GSRBhM9kAKHin8V3sbn4f91b9E9zWsdW61VtXVxcURUFeXl66QxnUuy3v47/f/zPcFhdMoglRJYa/Hfs79rQcwN2L72BiRzRC0j5RYiD5+fmQJMmowaRraWkxKqgPN6vVCrfbnfCPiDLf/xx4GjbJ+lFC16OnfIyKDYf+lr7Ahsn27duxdOnSdIcxKFmV8eSh55Bj9RjJmyAI8FizcNrfhK2nd6U5QqLxK6OTOovFgkWLFmHz5s3GNlVVsXnz5jHx4UZEoyMY7UZjoBWS2HdmtkWy4GjnCajaxy32siqjwd+MlmBbn+K3mSgYDMLr9aK4uHjI99E0DW3dZ9Dgbx7VlUqOdp5AdyzU7/hQt9WF7Y27Ry0Wookm7W3ggUAAR48eNX6vq6vD3r17kZubi9LSUtTU1GDt2rVYvHgxlixZgvXr1yMYDCYUziSiiS2iRAdMzhRVgaIqEEQBm+pexxv1byMkRyAA8NjcWDPnk5ibQbXOumMhvFj3Gt5vOwwVKtz1ZixfMPSxdMe7TuL3BzaiM9wFDRpskhUXF1+EG8+7GqIwst/lg7HupBN+BEFATJVH9PGJJrK0J3W7du3CihUrjN/18Wxr167F448/jjVr1qCtrQ3333+/sVzOpk2b+kyeIKKJy2PNgr3X0lI6TdPgtrlhEk14se41vHLiTXisWcbSUpqm4Rf7nkDN4q9gmmfqaIbdr2C0G/++4+cIxUJwWhwQIMB3xovfN/0V2VNyMTOuDEhnuAsvHn8dJ3ynYRJMuGxqJcqypuBnu/8bbqsL2baPh4+81bATsirjM+d/ckTjL/OUJE0co0oMM7Inj+jjE01kae9+Xb58OTRN6/NPX+oGANatW4eTJ08iEongnXfeQVVVVfoCJqKMI4kSLptaCV+vdUEBoCvixzXTroCsynjj1Dvw9JowIQgC3BYXNh7pf4WH0fbXoy8jIkcSZuwK5Q54bFn4w8GNRotkXdcp/N9tP8P+toOIKlEEY0H8+fBz+MZrP4DdZO2TWGVZnHinaS9CsfCIxp9nz8HsnOnojoUStmuahmAshE/O+MSIPj7RRJb2pI7GBlEUMWPGDMyYMYPLhFFGunb6ClxavBiBaDfOhDrREepCdyyE66avQNWUC9HS3Y6w0n9CI4kSmoOt/d422g6eOdK31VEQIAgCOkNdaOs+0/PF9/2n4LI4jIkhgiAg2+rGKV8DTvub+j12RIngdKD/24bTlxbejOnZpfBG/OgIdeFMqBMxVcZXF34ORb3WbiWi4ZP27lcaGyRJwqWXXpruMGgMiykxnPY3QRAETM2aPOxlLQRBwD/OuQ7XzliBOm89BAAzs6fB+lE3q0mQBlxbfqTHmg2VrMow9TPhA/ioCLgSRUOgGZ0RH3JtfdeltkoWnA60YGZOWb/HMAkjv8yfRbLgnypuRWe4C/W+JjjMdszILs2Yc0w0XjGpI6IR98qJLfj7ia3olnsG0TtNDlw9fRlWlA7/FwWH2d7vAu+FzgJkWbISForXRZQoZudMH/ZYzka+Ixe+iL/fBMhmtmKSIw8nfQ3QtP7rbxY6C1DfT0udpmlwmR0odU8Z9piTybFlI8eWPWqPRzTR8WsTDYmmaYjFYojFYmOiBARljrdO78D/HnsVdrMVefYc5NqyYTVZ8OyRV/BOw7ujFocgCFhz/ifRFfEllDfRZ85+anbfxeXT4foZK9EV9vf5O/NHg1hSVAGryYpCZz7MYv+ruszwlCLL7ERY/rirWdVUdIa9WD3rmn7LvhDR+MCkjoZElmVs2LABGzZsgCyzJAENjaZpePnElj6TEwAg25qFF0+8NqpfEuYXnI+7F92BbKsboVgYESWK83Km476Lq+GxZkah8Tl5M/H5uasRVWM4E+pEe6gTgWgQlZPLcdPsawAAHqsb5+fN7DMZAQC6lRAeXv6vmJ9/PqJKDKFYGC6LE/904a2omnLhaD8dIhpF7H4lohETiAURjHYjy+rqc5sgCPBFAwjJ4Y9WfhgdM7Knoabyq6P2eGejqvhCLC5aiJO+05BVBVOzJvc5R2vnfRq/2v8nHOk8AUkQoGgqLKIZn5nzSZQXzkN54bw0RU9E6cKkLona2lrU1tZCUZR0h0I0ZpkEEwaanSBCSDopYKKTRAkz4mrS9WY1WbHuotvQGmzHhx3HjbGE+sQQIpp4mNQlUV1djerqavh8Png8fWeYEdHg7GYbil1F6Ap7+4zlklUZJVnFsEiWNEU3Pkxy5mOSM3/YjierMjrDXthMVmRZ+rawElHm4pg6IhpRt1xwI7rlcML6oxEliogSxS0XrE5fYIMoKyvD3r17B9zn05/+tFEo/bbbbsP69ev73a+2thYLFixARUUF5s+fj5/97GfDG+wwUDUVfzv6Mr775sP4t7cfwQNbf4KHdvwcLYG2dIdGREPEpI6IRtRkVyH+tWodZmaXQf5oDdbZOdPxrxevQ4EzL93hjYovfOELeO+997B3715s27YNP/7xj/Huu6M383co/nz4ebxe/zZsJis8VjfcFhf8kQAe3vkYvBFfusMjoiFg9ysRjbg8Rw6+tPDmdIdxzg4dOoQ77rgDXq8X5513Hrq7uxNu379/Py655BK0t7dj6dKleOyxx2C32xOGcASDQcRisdEOfUCBaBA7G/fC3WtCiyRKMIkS/vfYq7hl7ur0BEdEQ8aWOhoSURRRWlqK0tJSLhNGE9att96KL33pSzhw4AD+7//9v3jjjTcSbn/nnXfw0ksv4YMPPkBHRwd++tOfGrc9/fTTmDdvHsrKyvCtb30LF16YOeVFjnWdREztv1SRzWTD0a4ToxsQEZ0VXp1pSCRJwhVXXIErrrgCksTZijTx+Hw+7N27F7fddhsAYMGCBbjssssS9vnsZz+LrKwsSJKEL33pS/j73/9u3PbpT38aBw4cwOHDh/GHP/wBhw8fHs3wByQJEgaqFsjlvYjGBv6lEo0hUSWKY50ncKzzBGJKZnXhTUS9lxsbyu1lZWWoqqrC888/P1Jhpey8nDLYTP3PQg5Eg1hYcMEoR0REZ4NJXRK1tbWYO3cuKisr0x0KETRNw0vH38D33vwx1u/+Ldbv/i2+++bDePnEG4PfmYaF2+3GhRdeiP/5n/8BABw4cABvvfVWwj5PP/00AoEAFEXBf//3f2PlypUAgIMHDxr7tLW14dVXX8XChQtHL/hBWE1WXFW2DF1hX8IKHxE5ArvJjpXTLhvg3kSUKQSNC3kOSK9T5/V64XZnxjJC6RCLxbBhwwYAwM033wyzuf91J2lkvHl6B/5y+AVk2xLfg11hHz5z/j/g0in88jHcysrKEAqFEt7rGzZswD333AO/34/zzjsPwWAQt9xyCz73uc/h3nvvhdfrxeHDh9HW1pYwUeLOO+/Em2++CYvFAk3TcOedd+JrX/taGp9d/3Y27cOmutfQFfHDJEg4P28mPjPnk3BZnOkOjWhCSjUHYVI3CCZ1PZjUpY+mabh/639AhNCnO0//8/3+pTWDdgXSyDl+/Diam5txySWXpDuUYaGoCkRB5HuKKM1SzUHY/UqU4YKxbgSj3f1eYAVBgD8a7Hdhdxo99fX1KCkpSXcYw0YSJSZ0RGMQkzqiDGcWTRAHuMCKggCzxJKT6dTU1ITJkyenOwwimuCY1BFlOKvJiimuIsj91BHj+qnpp2kaFEWByTT8ibWmaVA1ddiPS0TjE7/eJ1FbW4va2looipLuUM6apmkIh8Pw+XqW+PF4PLDZbGmOavzRNA2n/U0IyWEUOQvgtmYN67EB4AtzP4WHdv4ciqrAarIC6JmZKKtKRq+fOhG0t7cjPz9/WI/ZGe7ChkPP4XjXKaiainx7Dm6YeRXmFcwZ1schovGFEyUGMVYnSqiqioaGBoRCIYiiCE3ToGkaHA4HpkyZkvJ4GU6U6N+Rjjr8z4G/wBfxQ4UKs2jG3LzzsHb+p2GWzv4cNQVa8NThF1DvbwA0oNhViKvKLseelvdwrOskAGBm9jTcMOsqZNs8gxxt7OkKexFTZeTasiGJmVnsWtM0nAl14oP3DiLXlYN58+YNy3G7wl7829uPwiyajPeQpmnoCvvw+bk3YUlxxbA8DhFlvlRzELbUjVNtbW0Ih8N9uoRCoRDa2towadKklI4niiKmTJli/ExAe3cHat/9HTzWLOTYP06sDnccw2/eexL/p+ILZ3Xc074m/MeuX8JldsBpdgAAOsJd+PX+P+Hri27HF+d/eljiz0R1Xafwxw+eRXuoE4AGu8mO5aUX46ppl2fUwP1dzfvxt6MvwxcJwHFEgHmWE6vzNVxYOP+cj73xyCZIopTwpUAQBGTb3PjrsZexePJCrvBARP1iUjcOqaoKv9/f73JekiTB7/ejoKAgpYukJEm48sorhzPMlBzpqMPLJ7YgEAsix5aNf5hxJaZkFaUtHgB4/tjfYTfb+pxHp8WBw2eOoiPUhVx7dsrHffLwc3CZHQktVJIowW114clDz+O+i6vPNfSM1BRowX/u+S3cFhc8cV3YLx5/HbKq4LoZ6Xv/xXu35X38z4G/IMfq7qkbWCRDswn47/eegkmUsOAcV1842nkC1n7GSAqCgEAkiMZAC6ZmDd+kDE3TcKjjKP5+4i10yyEUOQtw3YwrUeDIG7bHIKLRwaQuibE8pk5VVQzUq66qKlRVzbg1XMNyGGE5giyLKyGheebDF/Haqe3ItmZBEiX4vPX4/975L1wz/Qosm7pkWMewpeJ0oLnfiy8AqNBwrOsEcu0VKR0zqkTRFGjpt9irKIhoC51BMNoNp8VxNiFD1VS82/I+ttTvgKzKmJVThpVllyHL4jqr4yUTkSMIyWE4zY4hd0M/e+QluMyOPq1QHmsW3qh/B1dNW3ZOXdrnQlZlbGvYja2nd+KVU2/BZXLAmjcTTrMdKDBBAJBjc+OvR14556RuwPEwGgadOBFTYmgKtsIX8WNb4x60BttglsxYNrUKVZMrAADeiB89LaE2/OXDF7GjaS88H/19Heo4hj0t7+O2+Z8ZlpZHIho9TOqSqK6uRnV1tdGfPZaI4sBFQwVByKguVF/Ej98ffAZ1XaegaBpskgVVky/EDeddhffbDuPPh55DviMPwkcX+6ZgK452nsRbDTtxSfEiFLsK8bkLbsCM7GmjGrdJkBDTYv2eaw0aHKbUEy9N0wa9qCta/180OkJd2HjkRRzrOgVN0zAlqwifmn0Nil09LZqKquDRPY/juLce2dYsCIKAbY27sLVhJ/558VfOqeVT0zRsa9iFl05swY6mffBFfSh0TMKs7FIsKlqIT8+5DiZx4I+b0/6mpElbSA6hIdCMMs/o14KTVRnrd/0GDf5m2EwWhGIhxJQo3qx/B4uLFiLPnoOT3tM46W+AN+zHzub9yLI4MDVrMgqdBbhx1lUpvTeLXYVoDrb2e77sZhsmO/sfOqGoCn6y81d49ujLOBPqREe4Ex5rFq4svRRFzgI8eeg5/P7AXyBCwHvthxCUQxAAaBqwZHK58UXKKllgEc3448FnMS9/NmdWE40hmXNlp2EjiiIcDke/rYyqqsLpdJ7VRIk//vGP+OMf/4hYbPgWkg/LYTy04zE0+JvhsjjhsbpgNVnwev123Pr83fjma/8PR7tOYWfTPrx6civ2thzEwfYjEAUBNskCb8SHiBLBz3b/Fqd9TcMW11BcXHwRfNFAn+2apsEu2TA7d3rKx7SarMixevptadU0DW6rq99WtTPdnXjw7UdxrOskLJIZVpMFzcFWPPTOz3H8o4kVr53ahhO+08ixuY3X32l2wGG24zfvbRiwdXcwGz74G5489BzerH8HgagfZsGE5mALDp45gp1N+/DY3j8MenxhwHFiAiQhPS3Lr5/ajoZAMzy2LKMVURIkWE1W7Gv9AO+2HMChzuOIyTG0dLejtbsNR7tO4oMzR3GmuxP/ufu32N96cJBH+dinZl+DQLS7T4ucN+LHipJLkia+39/6E/zxg2fhj/jRFGxBKBZBS7AdT3/4Atq6z6A52Io3T+/A66ffBgBkmZ3oDPvQHGjDjqZ9aAy0GMcSBAExVcbe1gOpni4iSiMmdUnU1tZi7ty5qKwcm2tqFhYWwmw2Q5ZlY+arLMswm80oLCw8q2MqijLs3dFb6t9BdywES68L1aGOYzjccRyKpsBltsNuskIUROxo3mtcWE2ChJAchiiIsJts+PV7G9AabD+n5CQVl05ZjGJnYUJip6gKOiM+fOq8a8+6q3D1eVejs9fC6gDQFfHhkzNX9puQ//nwc7BIloRWFZNogtuahT998DcAwPbGPXD3kxCKgoiOUCeag60px6ppGg60f4hXTr4JfzSIkByBSTRBEARYJQvaQ52IqBEc6axDg795wGOdl1OGiBzp9zGyLI60jaF8u+ld47yZJTOcZgc0TYMAwB8N4JS/ETbJgvZwJ0ySCVbJAptkQXOwDd1yCNlWN5768IUB35etwXYc6azDmVAnil1F+Pqi22GVLPBG/PBG/IgpMXxyxidw9fTL+71/S6ANr5x4EyE5jOZge8/wClGEKIiIyBE8d+zvqPc1IiSH0R3r/riLW9MgiSKCsW4c6jiG+BDNkgkdIe9wnUYiGgXsfk1iLHe/Aj0TG6ZNmwa/359Qp87lcmXULMJ9bR8gq9f4sWC0G11hL8ySCQI0RNUYLKIZMVUGNOBMuAuTnQWIaTJybR6813YITYFWRJQouiJe5NqysXbepzHNM3VEYzdLZnxj8Zfw95NvYWfzPsiqggJHHu5YsAbTs0vP+rjzC87H7Qs+g2ePvPTR2CfAZXbilgtWY3HRwj77a5qGY10nIasKtJgGtyUL0kfd66Ig4kyo86MWzShMScqDKJqGQKw7pTiPdNThiQ82Ynfze2gItKAz3AW7yQarKQ/6O8wqmXHCexrz8mZjU93rWFG6FJOc+f22Nq4+bxX+rf0IokrMSPI1TUNXxIdbLlidthmfMTWxi31e/my83bQHVtECXyyAbKsHqqbBHw2iJKvY2M8imVHnrUf5pAvgC/vRGGjpk5h2hLrwq/1/RFOgFYqmQhIklLon4yvlt+A7S7+OrrAXUSWGjlAXtjS8g4N7jmBBwflYWnyRUa8QALacfgchOYxANNhnzVZJNKEj7IXH6kZUicEU1+Jplnr+rsJyBFE5iu7Yx+M1o4qMmaM8pIGIzg2TunFMEAS43e4xVV8PADrDH7UOaBomuwpxrOuk0TIiCgKiShSqpsIiWtAa7EBr6AyskhmCICLb6u4ZA7X7N/je0rvPavZpKsySGdfOWIFrZ6wY1uNeWDgfFZPm4UyoExo05Ntzkybjr5/aji3170AQBGgAzKIZ0z0lmJk9DYLQM74vpsjItmbBFw30mxyZRQmTUpjt2BJoQ+27j8NjdcMqWeA02eAXJfgiPa2W+rEECAjGQtjasAsH2j/E/rYPYBbNOD9vFtbO/8eElkWP1Y37Lq7Gk4eew7Guk1A+Krr71Tm3pLXoboE9L2GMW47Ng6WTF+GDjqNQFQUiRDjMdkzJKoLN9PHzESBAUXtatjWoiKmJwxaiShT/seuXEICeWbQfaQ914Ke7fo3vLv063NYs/Gb/BrzfdhhuqwuiIOKvR1/Gyye24JuLv4o8Rw6AniEXgVg3BEGEWez7PhE/WiNY1RRYzB8XIM+zZSMQDfa8t4SPJ2nEFBl59mzMyikbhjNIRKOF3a9JjPXu17FiceEC+KPBhG0WyQINgCYImJo1GUsmV0CBCkVToGk9XZyCIKKi4AK0htphlcxQNBU5H10YRUGETbLguWN/T8MzGj6CICDfkYsCR17ShG5P8/t49uhLyLK6YJOscJhsMIsSjnadwElfPQDAYbYj156Na2dcia6wr88xQrEwzsuZDo916Mn/s0dfgtPsgCAIKHIVIKrKcFuyAEGDPxqA8tF4sG45jLZgO2JqDHNyZyDXno0sqxNHOo/jF3uf6HPcbJsHd1Z8Af9+xb/i4eXfwX0Xr0v7Kgo3zLoKvmggofs02+bGwvwL8Pl5n8KlUxfh4uILkWfLThgHF1WimOzqmdRgk6x9JjjsaNyL7lioz4SIiBzFjqZ9+OmuX+Mvh1/A++0fIsfugSRKEAQBHmsWREHAL/f/0bjPFVMv7knWNQ2SKMEkmIx4VU1FltkFEQJMognZlo9fZ7NkRr4jFzaTDaqqQdNUdIa9sJms+PpFt2dUqz4RDW5CJHU33XQTcnJy8OlPD71oa3V1NQ4ePIidO3eOYGR06dRKeKxZCMthY1u+IweqpqDYWQibyYocmwdXll6CiwrnY3budMzNm40rplYhqslQNRWqpkJWFVyQe55xDKvJilO+hnQ8pVGjaRr+9/jfkW11Y07ODISVqHEht0kWHOs6ha6wDyunXQpREDEvfzaun7US/mgQXWEfAtEgOsNeFDoLcPuCz6b02I3BFmPMYJ4tB1kWJ2wmCyyiBTFVQUSJQlEVBGLdsJqsmOTIR5b14y5Xh9mOY10n0RJs6/f4giBkTIHdUvcUfHHepxGWo+gIedEZ9sIb8WNGdgm+u/Qu5NlyEFGimJM7ExEl1jN+VVNgN9lQ6CyAL+LHJcWLE7pLAWBf+wcJYxw1TcOelvextWEX2kMdePXkNvxk169w+MxRKGripImQHMZ7bR9gV9M+aJqGfEcurp/5CYTVnveAy+KEJEg9XfKaBo8tCzNySnHRpPmAIBjvE0VT4TQ7cEXJxfhaxRdxzYzluOui2/HdpV8flyuVEI13E6L79e6778Ydd9yB3/3ud+kOhXqxSBbcs+T/YMMHf8Ohjp6Ll91sw+3zP4sPzhxDTInBLJkhQIDVZMVNs6/B8qkX47njmxGWw4gqMnJtOZifPxtOiz3h2OI4b2WIqTF0hX3IsrowyZmPhQXn43DHMYSV6Ef1zDRcUVKF5SWXGPe5quxyXDqlEu+2vI9ArBvz8mZjqjv1QrYiROjFVwRBQNXkC7G39QBkVUFToBWhWBh2mxV59mxMzZqMOTkz+hxDEkUcbP8Qhc6Csz8Jo2Rx0UJUTJqLDzuOIxjrxozsaciz93R91lR+Bb/Z/yRO+upxXk7ZR8WDrTg/bxYicgRXlFyMG2Zd3eeYNskKRVNgEno+ho901qEt1AGbyYqYKsNlccAX9cMXC+JA+4dYOOl8hOUIdjXvhz8aRFgO45F3H0eZeyq+Wv55PLz8u6jznsau5v2QVQU2sxUFljzMy52FQlcBfrriAexr+wB/OvQ37G7ah5AcQbbVjcVF5fj0nOv6Ha9JRGPLhEjqli9fjtdffz2l+4zl4sMjQRAEY9bscHfJOMx23LFwDRRVQUyNwSpZIQgCGv3NeO7Y39HafQZmkxlXTVuGpVMWQRIlLCyci+5oNx7Y9tOeArC9+CNBrCy7bFjjHEw0GoUsyzCZTLBYRr62lyRICWVApmQVodhVCH80CO2j/64q67u8lsNsx6VT+x9WoGkaotEoFEWB2WxOusbvgoLzsb1htzGo3iyZUDm5HGE5Al80gO9f8s9wW114ZPfjCMSC/b5nZFWB3dT3tcsUvV9Pk2jC3PzZffZzWZy4e/Ed8EZ86Ar74LFmISSHEVNlFDkLktZ5u7L0Eqzf9QFy7D0lbOr9TbCKPedbURVMc0/BmVAnYkoMLd1tkNVZeLvxXSiaArvJCkEAipwF0KBh/e7f4AeX1uCPn3wEj7//FA60H4aGnskapVnFuGPhGtjMNlQVX4glkysgqzIiShQaNLjMqZc4IqLMlPakbsuWLXj44Yexe/duNDU1YePGjVi9enXCPrW1tXj44YfR3NyM8vJyPPLII1iyZMmIxjXWZ78ON5PJhKuv7tvaEIvFEIlEIIoi7Hb7OV0cJFFKWEmiOKsIdw6wfqrD4sANs67CU4eeR7bNbXTXBWPdRpftaIjFYmhoaEA02tP1JQgCLBaL8b6x2Wyw2fouJ3auJFFCmWcqmgKtMEs9f8qCIMBtdUHVVLjMzn5XpkgmEomgqanJeB6iKMJqtaK4uLjPGsLXTl+BfW0f9LTIfTTwXtVUdMfCuG3eZzDJmQ8AWDZ1CTYceg7Ztr6rfphFE8onzT3bp59AURSEQiEIggC73X5OxbVlWUZDQwMikUjC6zllypSkSS7QM9FDH5eYjcE/M8o8JagonIt9rR/AZXZAVmWIkgVhOYJSdzEcZjume0qxv+0DCBDQGGhFSA7DbrJCVmXkWD2wmz4+91tOv4Nrpi/HP114q9G17ra6+oyVFAQBZsmcttU5iGjkpD2pCwaDKC8vxx133IFPfepTfW5/8sknUVNTg8ceewxVVVVYv349Vq1ahcOHDxuL0ldUVECW5T73ffnll1FcXNxn+1D0bqmLxWL9Ft0VRTFhua2BCvMKgpBwcUxlX73e3GjuCyDhIha/r6ZpaG5uRjAYNLZZLBYUFRXB5XJBURSoavLljOKPO9i+JpPJSIh673tx4YXINmVh04nX0RHywmSSUFlUjhtmXQWTYBrwHA903M7OTvh8PmM5tby8PHg8HgiCkLCvpmk4ceKEkQQJgoBYLAav14u2tjZkZWVB0zQjKei9NJskSUYCoqrqgC3D/e37mVn/gJ/s+jU0VYP1o4t0TJHRrYRxZ/kXEvbVNM1IVOKTTEmSelqK6nsmVgiCYNwWCoVw8uRJlJaWJsRgN9vw7cX/B3878goOnjkCWZWR58jB52bfiFk5ZYjFYhBFEZWTy7GtcTdO+5vgMfeMH1M1Fd6wH9fNvBImSMa++rnRayomE7+vqqpoamqC3+83XhNJkpCdnY3c3NyUjyuKIk6dOgVFURLOQyQSQV1dHcrKyowVWYb6dz/Qvl84/1OY5d6DLfXvwKyZYBMsmFMwA5NdPa3iUxyTEMjy45i3Hu2BM7DABFmW4TDZcVHBx0t4ZVmc+LDtOD4x9VIAgFWwoMheYDxeOj4jBtt3tD4jMnHf+L/lVPY9m8+ITN6399/yUPdN5TMiE/YFzv4zItVi/4I2WpVah0AQhD4tdVVVVaisrMSjjz4KoOeFLykpwV133YV77713yMd+/fXX8eijj+Lpp58ecL9IJIJI5OMCqD6fDyUlJfjFL34Bu71vV9GUKVMSFrr/4x//mPSNWVhYmNDa9ec//znhseLl5eXhuuuuM35/5plnEAwG+93X4/HghhtuMH7/29/+Bq+3/6KhTqczIXl+4YUXcObMmX73tVqt+OxnPx5A//LLL6OlpaXffUVRxMUXXwxFUVBaWopt27ahoSH5RIVbb73V+Pn11183Eor+3HzzzcYH/NatW3H8+PGk+37mM5+BzdbTevHOO+/gww8/TLrvTTfdBJerJ9HYvXs3Dh5MXvV/wYIFmDx5MgoLC7Fv3z7s378/6b7Tpk2Dw9FToDYQCOD06dNJ973qqqtQVNRTu+zw4cPYsWNH0n1XrFiBqVN7au8dO3YM27ZtS7pvxZILsWBOz0X/5MmT2LJlS9J9L7nkEmRnZ6OjowNerxcffPBB0n2XLFmC2bNnIxQKoaGhAW+//XbSfS+66CLMmzcPsirjhfc2w7s/eXHjhQsXory8HADQ1dWF5557Lum+c+fOxaJFi4b03GbPno2qqioAQDgcxlNPPZV03xkzZmDBggVobm6GIAgDPrfS0lJcccUVxu+///3vk+4b/xmhKAo2bNiQ9CIesITRMtVv/F52Ig+S2n+rY9gaQ8OULgA9S5nNbpgMIcnnfyZ8RkiShFtuucX4/dVXXx3yZ8Qbb7yBU6dOJd03Ez4jrr/+emRnZwPAoJ8R1157LfLze1qzDxw4gD179iTdd6Q+Iy6//HJMm9ZTh3AonxEzZ84EAJw+fRqvvfZa0n2XLFmCOXN6Zqw3NzfjlVdeSbqv/hkBAO3t7XjxxReT7nu2nxGBQAAbN25Mum+qnxGXXtrzxSkWi2HDhg1J9z3bzwggMY8IhUK488474fV6h1SeLDOmlyURjUaxe/durFy50tgmiiJWrlyJ7du3j8hjPvjgg/B4PMa/kpLRX2syE8ViMbS2DrzigN6CkewC0JuqqmhoaEiarGYSk8kEr9c7pG9NeguPKIoDfpMbSe647s5QKDTo/t3d3UPqspRlGXV1dTh9+nTSpCBeLBZDe2s7yoTUJ2MMRlVV+P3+wXdMQSAQ6NOaeq78fj+6u7shyzJOnDgx4L4WyYyusA+qpkLTNKgDrwT88WNEgrD1ml1LRBNPRrfUNTY2YsqUKdi2bRuWLl1q7Pftb38bb7zxBt55550hHXflypXYt28fgsEgcnNz8dRTTyUcL16ylrr29vZ+s+SJ0v0a/61k1apVaG9v7zO+SD8PgiCgtLR00K6VxsZGBIM9g+jjY5BlGcXFxXA4egbhj2Z3SVNTE8LhcJ/xb6IoQlVVo1tPP25zc3NCQqQnOvpzMpvNxvOQZRkFBQUJYzRHowukrq7O6ILrTdM0zJw5E01NTcb7vvc5UxQF2dnZyMvLw8mTJ42kVdM0qKpq/L+srKzP30JDQ4Oxv36OTSYTSkpKEpLIs+nWiEajOHjwoBG3HpMkSUa398yZM4336VCO297eDr/fD0EQEs5DJBJBKBSCJElwOp2w2+0JYw1jsRi6u7vR0NAAURSNVVz045jNZtjtdkiS1Od10MftlZWVQdVUHOo6ijdP74SmaVg8aSEuLJxnrHu7+cRb2HTidWPVEEVQ4Y34sbhwIW6ecwOSYfdrZu3L7tce7H4dfF+fz4f8/Pwht9SlfUzdaPj734dehNZqtcJq7fuNd6CZgL33G6pU9u09UD0d++qsViskSeq3RUMfW5bsdp2iKAgGg/3uI4oivF5vvxNUBjvuue4rCEK/F17g4wt0/HHz8/NRX19v/C5JkvHBpGkaHA5HwoeA1WpN+rrrY7qGYqj76h88yV5nWZahKApycnJw+vRpmM3mPudM0zTk5eUhHA4bSRkA41wBPa+n3+9HQUGBcZ/Tp08b4wyBj99rqqqiq6sr6RrEgiAM6W+ju7sbkUikz3PTNA3d3d3IyspKuG0ox83JyYHX64XJZDKeWzgcRigU6qn/5nLBZDIhGo3ixIkTKCsrg8lkgtlshtfrhdVqRVdXV8I51L8Q+P1+uFwuo+svnp4MWS1WlE+ah/JJ8/qN75rzVmBmfhlePP4auiI+ZJkcuGnWNagonJfSRJxM+DwZ6b/l8bjvSHxGjMV9h/oZkSn7AmefG6RyPyDDk7r8/HxIktRnjEZLS4sxxoBGn56o6C0M8fQEYTD6gP3+6JMN0sHlcqGtra3fi5OqqnA6E2eT2mw2ZGVlwe/3Q5Ik2Gw2BAIBYzJCfEInimKf+4+GwS72giDA4XDA5XIZibbe6qW/nmazGR0dHUk/dCVJSujm1ScW9XceRVFEIBBImtQNldfrhdls7vM+0t8/Fosl5RnH+qxlr9drvHbd3T1r4tpsNuP5iKIIRVFw5swZ43nEYjGj1aX3edI0zZio0l9SB/RtIU3mvJzpOG/R9JSeFxFNDBk9ps5isWDRokXYvHmzsU1VVWzevDlp9ymNjsLCQsiynDALVJZlWK1WY7DwQAb7ZpquulkOhwPhcBg+n88o7QH0vO8sFkufpEwQBBQVFaGwsBCSJMFsNsNqtcJutxvdrnq3QlFR0TmV2jgbeomP/hKGWCyGaDSKM2fOIBQKYfLkySgoKIAoitA0DSaTydgGoN8ESqe3YMb/PpBURn2oqopYLNbnmLIsG92s8cfTfx7K+7A3WZaN8ZDhcNj48uFyuYwB8zpJkvqMBx2sey7Z7aIojkptQyIa39LeUhcIBHD06FHj97q6Ouzduxe5ubkoLS1FTU0N1q5di8WLF2PJkiVYv349gsEgbr/99jRGnbn0RMtkMo1oApGVlYVp06ahvb3dGK+Vk5OD7OzsIT2uxWKByWRK2tp3Nhfkc9XW1obOzk5YrVYEg0F4vV6Iogi32w2Hw4Hi4uKk3bL6xBoAxqzXzs5OqKoKu92OvLy8tF20CwsLceLECSiKYrSw+v1+RKNRuN1uBAIB+Hw+2Gw2TJ06NWlLq8fjQXt7O0KhUEINN32sWG5urrGv2WxOmpjrYw0Ho6pqQtkcvaWzoKAAwWDQGI/pdrsRDoeN96HFYjGS61T4fD5j5qsoijCbzZBlGXa7fUjHcrlcaG9vh6qqCeVQ9HF+drsd3d3dfd7ziqLA4/GMesJPRONP2pO6Xbt2YcWKFcbvNTU1AIC1a9fi8ccfx5o1a9DW1ob7778fzc3NqKiowKZNm86562a8iUQiaG5uTigc63a7UVBQMGKtXnoScDb0Fi59IL3eOqQoCiwWC/Ly8oY52oHpSZjevZadnQ1FUYyVFVKZBS0IArKyspCV1bfgbjqYTCaUlZWhvb0d3d3dRmKRk5NjtK6JoohoNIrm5uaktR318XH6DFF9jKHP50Nubm5CyR99soLeLR1PUZRB/371unmxWCzh/l6vF83NzcYQgEAggHA4DLvdbiSjehKVShItyzKam5sTxlPqX4w6Ojpgs9n6JF16wg7ASDJDoVBC17Meu97CO2XKFASDQWN4QfzfKRHRuUp7Urd8+fJBu2LWrVuHdevWjVJEY48sy6ivr08YuA70XAAVRcHkyedeTkIQBCPRGq4k0eFwoKysDK2trUarS25urlE0djR1dHT0WxhYkiTIsoxIJJJyy89w0BPLc215NZlMKCoqgqZpOH78eL+voSiK6O7u7ndMGACjxSw7OxvhcNho+XO5XFBVtc+EjMLCQqiqimAwmFAYuKCgoE9Xpk7TNITDYfj9foRCIaO1TI8pGAwaE1HsdjtkWUY0GkV3d7eRRAmCgMmTJ6f0Pu3s7ExoXdO7zAVBgNVqRXd3d0LM+ozf/Px8hMNhNDQ0QJIk5OTkIBQKwev1IhqNwmazwe12G+/t/Px84znqE2eGu4QKEU1caU/q6NydOXPGaJ2LJ0mSMSPxbGa5xjOZTAnFkIdLIBAwBtjrsyI1TUN+fv6ojqvTx1L1R18PdaCkTv9iMlwxy7JslFfp3fU40GupKAp8Ph9isRjsdjtcLldCTHoykiyR0JOz/lq59Fmd/c36kmUZXq83oYVVEAQUFxdDlmWj7IvD4UianAaDQTQ3N0NRFAQCAaPVWX9MPcG1Wq0Ih8Mwm83IyspCLBZDKBRCNBrF1KlT4fF4Uk6U9KXuACQ8tk4fl6gnp/oKIVar1Zj9rJ9nh8MBh8OBaDSKSCSCvLw8ZGdnG+dM77ImIhpuTOrGCEVR4PV6EQwGIYoicnJyjLVWu7u7k17ENE1DMBjMyPVrfT6fMdM0/kLf2dkJURRHtQtWb5FLNmYu2RiwSCSC1tZWhMNhAD0X+/z8/HOa5aooCk6ePGkkNLIsG93DTU1NyM3NRV5eXp/uXZ/Ph5aWFmPMlp6ETZ06FYIgoKOjA9FoFKFQKGly1bu1N178IH9N0xCLxYznbTKZktZsMplMg9ZXikQiRmuXXu8rvuaZxWIxkqpoNJqQdOrlhkRRTBjXlwqr1YpQKGQkh71b7VRVxeTJk42xgvHvh/iEMJ7FYoEoisjKykq5LAER0dngyNwxQF938syZM4hGowiHwzh9+jSampr6nWgQL/7ilGna29uhKIpRb0y/gJtMJqPFbrTk5OQY66Pq3XmRSMQoHNtfK10kEsHJkycRjUYTumobGhoQCATOOhav12t0N+otb7IsG79Ho1E0NjYmrOigj4cTRdHohtRb9I4cOYK6ujoEAgEjUdITvHj6GLFkSZ3T6TSKDft8Pvj9fsiyDFmWjYklAxUP1ePs6OhAZ2dnQhJ45syZhJp2+oxW/Tnr73O9xa6/2nTn0o2Zk5MDVVURiUT6tGzqLWsdHR3GJIx4QykZQ0Q0GpjUZThN09DY2JhQFFev+K7PWnS5XEkvpoIgDEttNFmW8cwzz+CZZ54ZlqWvIpEIzpw5Y3S/6i1ReqKhKMqo1qrLysoyLtw+nw+hUAg+nw+dnZ3weDz9XphbW1v7FCrWX6fW1tazTkr9fr/R8qPXSNMfQ6/BZjKZ0N7ebjxG76RIpxd5ju+e1wvo+nw+I0mTZRmSJA04/jI7O9uYKKEoSsLj6S1lzc3N/d5X0zQ0NDTgxIkTaG9vR1tbG44fP260LPZu7dKTtPiSMvrtvVcg0Z/nUOojJmMymYyVQvRzoj+Gy+UyVrDoT7KSMWczYYOI6Fwwqctw0WjU6A7qTZIkdHZ2GrMY4xM7/UKdnZ09LAOx9W5cPUE412Ppi9zrVcT1C7bf7zcukKM5WUJvpcnKyjJWfXC5XMjJycGZM2f6JJj6YPferTp696Y+LutsxB+zd5dw/Ng9RVGMJbJisVi/5ysUCvVZg1YvweJwOIzB+oWFhZg2bdqA7xW9K1dv7dMTIJPJZJTk6O7u7vcLRmtrqzGZIf6f1+tFV1dXn0RNr9umv68jkYhxvvWZ0noMsVgMHo8n4ctLNBpFe3t7v6+dTh+jp8vKyoLH44HdbofZbIbNZkN2draRlCVrcZs0aRKAvt3T+rJwbKkjotHCMXUZbrD1YfVB79OmTUNLS4tRrkKSJEyaNCnpWLpoNApZloe8/Nlw0hc4772ElX5h7+7uhsfjOefJHUMRiUTQ0tICv99vrKbgcDgSulsVRUFraytycnKM+nq9ybKckJBqmoYTJ05g8uTJQ1qvL57H40FTU5PRWhm/liKAfruC9USndwIRP+s0niAIxmoYqZQHslgsxvPR33v9lfqIfzxZltHW1oZYLGbUqLPb7cZycp2dncjOzkZ7e7txbvVagXoLoz5+VD9efNKXm5trrNIQjUbR0NCAcDhsHOvMmTPIyspCUVGRMQa1tbXViMdisaCgoAAOh8PoXu19HvUvSP0xmUyYNm0aWltbjeXELBYLioqK0rKCCBFNXEzqkqitrUVtbe2gY4RG2kBLHelV//Ukrri42GjB0Iux9l6WKBKJoKmpyZjdp48XKi4u7nPh12cVDme1+0AggLq6OmPsUjQaRSwWg9VqNbrzYrHYqNQhjEQiOHXqlLE2Z/zsR32ZLz1Z8/l8CAQCRnf25MmTYbFYjBYwv9/fZwayyWRCU1MTbDbbkM+f/toFAgFjJqreNWmxWIxkCEhchSAvLw/19fV9Es74Lks9fj0xVVU16ZJVyegtZXo3s16TLX4MX++VJU6dOpUwmScSiSASicDtdsNkMhnFd/WCyPrz0lf10L906O9tfU1XvTaeXh9O7y7Xz5deK08fqnDmzBk4HA6cPn06Yb1NRVHQ0NCA4uJiTJo0CY2NjQmtx3qtwoEm7pjNZkyZMsWIk61zRJQOgjaao9HHIJ/PZ6wFmWqLy3A5efKkUS1fURSj+ysUCsFut8NiscBisSAnJwednZ1GiRO9G9FqtRozIE+cOAHg41Y+fRC61WpFWVmZsb2pqalPV+uOHTsAADfffPNZte7FYjGcOHHC6KLUW+b0JaD0Aq9Wq9WYMZibm2sslq5PntBnmJ5r3biGhgYjaQ2Hw8bMYp3H40FXVxcAGOUzgJ5ERV8O7dSpU0broj4GTFGUhGXC9NUohsLr9aKlpQWSJMHr9RrJnZ7AO51OuN1uqKqKvLy8hESjtbUVXV1dRkKit/R1dXUldL+KomjUT5s1a1bCc47FYujo6EA4HDZmkzocjoQkpa2tDW1tbQiFQsb7Ua/pVlRUhJkzZxr7t7W1GS3I/XXt6hMUZs6cCU3TjPevXpZFf+5AT+ud2+02livTx/Xpibfe8gvA+BvR6+Lp99G7c3snXXpCXlZWhkgkgvb2dmPYg8vlQm5uLuvJEdGoSzUHYUvdGDBlyhR8+OGH8Hq9xsVKnwEoSRIikQhkWcapU6cgSRKsVquR9OktUPX19UYyIIqi0Sqi8/v98Hg8yM3NRVNTE0KhUEKrT3xS0NXVZbS06V1fQ2mZ6OjoAACjmCsAo+VIn2UaCoVgtVqNVkZ9hmf8RJFQKISTJ09i8uTJ57Rqg57QAT0tovFLOKmqasxg1VvtdIIgoL293Uh69VmgelKnvyZ66Y1UupH1Ish6wu1wOIzESW+58/l8KCsr6zMxYNKkScjKykJHRwcURYHT6UR7e3tC0qU/n+7ubmRlZSW8bl1dXUYCpr/PGhsb4fF4UFZWZpwDj8djrPYQP2sZAJqbmxGLxTBnzhx4vV6jNIveMhx/PvTyJPoEDH2pOX2caDAYNBIr/TH0xEr/YtC7S1Qfd6f/k2UZra2tyMvLM1oF+3s99H0VRTmnlVKIiNKJSd0YoFfvB3q69GKxGMxms1Huwmq1Ghckvcq/XusrEonAYrFA0zSjFUdPQuJbaPRuMr07q/eFL/7i397ebnT71dfXw+VyDamCfyQSSVg2SV8MXb+f3+9HVlaWkTzoS1f5/X7k5uYa++ndfy0tLX2K654tvTBu/ALt+nhGvep/d3e3UVBWT0L15aq6urqMgr/x5zUSifRZ9H0genLY3d2dMNNZT0iysrKMWPt73na73egG7OzsNNavjZ9cAPQkR3rrpMvlMpIffaJD/HPo6urCBx98AKfTCUEQjPdPNBo1viTELxvW1tYGn89ntIqZTCbYbDaEw2FEIhHjvOr3jV+CTS/nYjKZjCLD+uutJ6MOhwOBQMAYr6YnfnrNvP7WVvX5fMjJyRnwvcJOCyIa65jUjQF6V5CenPXultLHEOkXPr1ump4UhEIhuFwuY4ZkfzMl9bFSA5Xi0Ls79YRR/zkQCMDr9fY7kFyfNevz+YylwCwWC2w2G8xms5FE6DXSei8fpV/U9ecQH69e466/wej6jEm9q7S/7mK73Z7QWtc7Jr3VU5+lqSdFepd1IBCA2Ww2Whr11p7e4+f0WIfSfRc/jkt/PeNfD30MZTgcHnQ8XFtbmxGXHodO76rUk7rOzk6jJbB3d6yejMVPbuk901N/P+oJob6sViwWgyzLxrhCfaynfi5kWcaBAwdQXFyMKVOmIBQKGWP19DVS9eegz1DW/+nd23pXc39lRfTnrQ9f0L8A9df9ajab2cVKRGMak7oMF991pRd6ja+jlWwFBH1ma3xi4Ha7cebMmaSPoy9tlKw1Y/r06UarTDy9pap3UheNRo0xdFarFYIgwOv1GmOj9IHseoLU39JJ8QVo+7ut93ZN09Dc3IyWlhaje1lfgaOkpCQh4crPzzfGxMW3AtpsNkyaNAmCIBitV/Hdsvo5NplMxmodZrMZ0WjUGMemx6Wv3BCfhAwkKysLXq/XSET0blD9PESj0YSF4pPR11zVE9D+Xrf4rkh9NnQ8fZKG/nzj33u9H6t3kqe/NhaLBZFIxOhCju8a1VsgAaClpQVAT2KtjyXUXws9idNfA/19rb8uVqvVmNyiT3qJj0P/guN0OpGTk2NMlIjvjlYUBYWFhZzgQERjGuvUZZhoNIqWlhZjxQC9i0pP6PQLon5h1VtJgMS6bvG36xewSZMm9VsoVZ+koF8w9dag3vvorV696S1R8Y/d0tKCAwcOoKurC6FQyBis73Q6E7ok9bFjBQUFCffX/+mzNJONg+rdWtXU1ISmpiajG1N/7h0dHThx4kRCnFarFSUlJUZXdvxg/5ycHLjdblit1n5XGdDvo8+6BHomU8QvBK8vRq+vbdubnrDHJ1P5+fnGjGc9mdcTKbPZbLReDVQqQ5ZlHD16NGHMpF7PLf59YbPZ4PF4jNdVv01/reMTSn27ft4Hot+ut47FJ7zxiZaeYOtJVSAQgM1mM9aJjT+eXnpHn0Sjf0nQW3L1kid6YqfHIEmSUULF5XLB4XBgypQpxuofegtqcXFxn1ZiIqKxhi11GUJVVZw4ccKYTKCPQ9IvZvHJiN4aoV9s9YuYnvzoF009ITCbzcjPz4fJZML06dMRCoWMC7w+u0/vlsrNzYXFYkFDQ0OfsViSJCVtTYtPutrb29HV1dWnyzEUCsHpdCI7O9sYM+Z0OpGfnw9JknD8+HGEQiGj2xT4eJZu7+RNn2Ea3/Kmz/TsPSZMP053dzc6OzuRn59vbLfZbCgtLTXOb3xCoI/30mdi6olV74RHb1GLRqPGaxZ/buJb7vRt+lJZ8QvEFxUVwWazoaSkxChroifyemuf/pokS6y6urqM1tH4Fis94dHPjSiKyM7ORn19vZHcBAIBo2s+vhW0v67KgeiPq3ePx8egJ2hWq9VI9PTb/X4/vF6v0U2r768ng3oLnaqqcDgcxnmXZRkulwuhUAjhcNionae3aOr765NqnE4nnE6n8djsciWi8YJJXRKjWadOVVUcOXLESOj0bbFYzLgQ6eOMABhdaXoLj36h1H+Or5eWk5ODqVOnGsmYvipAa2trwtg4RVFgtVqNlQHKysrQ3t5uJBJutxsHDhzAiRMnUF5eblws9S45PVFSVdUYnN+7e1ivlaYPoNdr1OkX/kAgYEzSiK8hZrFYjLFV+nH02nrxgsFg0iXM9GQgGAwiNzfXGLAfn2T0lyjpzz1+HFZ7e7txXyAxadJbufTH0zQNLpcLXV1dxmvZ3t6Ozs5OmEymhDF0p06dwrRp04z6d/pMUf2x9Akweuz6fh0dHUbLpz4TWk9s9Nco/r1hNpvhdDqNZc70bvf4Vt/492H8c0lF75a9+Bbl+Ikg8bG1t7fDZrPBZrMZJVP0Flf9Pafv7/F4jDI0egKuj+/UXxdVVeF0Oo2hA/GYzBHReMOkLonq6mpUV1cbNWJGUmNjI1paWvrUEtMTOb2lTu/a02+3Wq3GxVa/+IqiaKxioM+UlGUZgUDAqC1mMpmMbli9xcnj8RiJmV4nDOjposzLyzMuxACMiQR6QidJEg4dOgRRFI2WrN7lMvSuxvgyH4IgGMVi9RYZvRVKT7L0Ash6XTu9BSYcDqO7uxs5OTnIy8vrd2UDAAmD+vXuy3fffddIfvRxWx6PBwUFBcjKyjJmb+otiQCMCST6c9Jbk/Tnpbcm6YmqnljrEy9UVUVOTg6sViu6urr6nV0siiLa29tRXFxslPPoPQlBH7MXiURw7NgxNDU1JRxHPz96d6Re1FlPjvQJD/prCfTMktVj6P2a6f8/l5mh/XXl6+dHb1nWW+GsVqsx1k/vDtUn9+j3iS+o7HA4MGPGDGObXsrnzJkzUFUV2dnZcLvdHCtHRBMCk7o0i0ajOH78eJ8WJr3FR5992Js+cF1vtXI4HEaC1d3djUmTJiEQCOD48eMJ65DqA9T1MU164qcPTter+OstQ3a7HYFAIGGFB70Gm36Bja9Vpicd+uQIPRHRx47FJ0Gtra19JgLotcv0Y+txx3fp6a06giCgubkZZrPZGOSux6a3cMXP/tTPpT5OT++i1se8hcNhI1HT79PS0mKsKBA/1kxP2OKTLj1OvUVNlmXjeH6/H11dXcZsWn1SSfxsUr0Isn7+4sfAxb8vTCYT9u3b1+/asvr5A3oST311ht7d2v3RXwe9y14/h8MhfoJE/Ng6vSVWP58WiyWhNI+eWOuJp15WRb9vQUFBn/F3DodjSJNSiIjGGyZ1aXbkyJGkXYYDiS8mq7eAxY9bCgaDxuzH3jMT9VY2/YLtdDoRjUaNsh16sgJ8PA7u6NGjxjH0wenxkzfiVzHQE069pbF3gVo9kemv9Ud/TqFQyJho0Humb3wXnF7eo76+3likPhqNGt2R8S048d2R8V2K+ngyvdiwXpdOP696V7K+bJiehMV3Cfd+bfrrttfHmOmJrf784s+j/tjJujv1eAdKzgAY7wd9/1Rb2pK9PmcrvqtaLy6td3/qNekcDgc0radAcWFhIVpaWozZtzk5OQlfHCRJQmFh4Yi3ohMRjSVM6tIoHA6jra3trO+vX+QikYjRRatfyPtr3dPFt3r5fD6jOzW+tSl+hq0+IF2nJy29u+f0REYvNKsnVr2Tg2TJgt5apR+vd0tUf8eJj9nr9aKoqKjPWCm9S1dvYYtvfYp/DnpCHF/EVj+2npj2Xtc0FfH7x3d/xpNlGcePHx+wu3Coj3surWzDmdDp9PeU3vWuT3KJLwqsT9ax2WyYNm2akdzq5z2+65ZdqkREiZjUJTEaEyVOnTqVcmKQzLlcwHu3FPYeQ9X7At/f7FJ9Pz0OvaUn1QtvKuejv67JpqYmo+VQTxwsFovRnTnQ6znY2LH+ujtHykgkVecivqWt9/ahxBo/O1vv1o9EIgmTdVRVhcViSWh96/0+6+99R0REPQQt064eGSbVxXRTsWPHDqPLL9PpCRMATJ48mRfXCSI+aRtqAtf7vvETG6xWK3JycmAymYx1fvUWUpfL1WeMHBHRRJZqDsKWujTRl0EaS1gCYmKJ79LvzW63J4wd7F2+RJ/Zmp2dDUmS4Pf7oapqwkzUadOmGWVeiIjo3DGpS5MTJ05kXBfbQERRRFFRUbrDoFGgz3zW6wPGFyHW3wf6eEx9JrNec89kMhkrPsQfr6ysDB6PJ2FCCMfEERENLyZ1aXIuEySIhkP8pBSgZ9avXvh30qRJ8Pv9RrkXfbJCcXGxsbSYz+dDKBQyJri4XC44nc4Bu0/jV9sgIqLhxaQuiZGcKBE/oYBoqOIXqz9XJpPJKP+iKAqcTieysrIgSRLy8/PhdrtRUFBg1NrT6yHqCZu+zJheb4+IiNKPEyUGMVITJV599dVhO9Zo0DTNaF0sKChg19koEwQBF154Ierq6tDV1ZW0636wxM9isSA3N9co8WK1WjFlyhRjbV2WCiEiyhycKDEGnE2x4XSLb108m1IldG6mTZuG7OxslJeX4/Tp0zh9+nTC0ll6slZcXAxN09DS0oJoNApJkuDxeIyl2VwuF2eXEhGNU0zqkhjJ7teurq5hPyaNPWazOaEbXl+VQ1/GTF8i67zzzjPWoBVFEaWlpSgpKUlY8SJ+PV0AnFVKRDQBsft1ECPR/Xr48GE0NDQMy7FGC+vU9TCZTLDb7QB6ytLo50EvtqwnYzabDW63G7IsIxgMQpIkOJ1O2Gw25OTkGEtl6clYJBIxxq2xFZSIiAB2vxKdM70Yrj4zVG9Bc7vdmDp1Kjwej9HKFg6HIUkSbDZbyomunhwCPckiERHRueCVJImR7H7V17ykzKF3e+qJm9PphNfrRTQaNcar9U68zGYzS3QQEVHGmBDdr88//zy++c1vQlVV/Mu//Au+/OUvD/m+I9H9euLECRw/fnxYjjVaMqX71e12w2azGYVv41cy0Gus5eTkwOFwQBRFOBwOCIIAk8nEBIyIiMYUdr/2Issyampq8Nprr8Hj8WDRokW46aabkJeXl7aYwuFw2h77XIxUIqePPes9aUBRFKiqCkmS4HA4MGPGDDidTqiqCrPZbEwUsNlsCSsYEBERTUTjPqnbsWMH5s2bhylTpgAArr32Wrz88sv43Oc+N+D9RrL7daytoaq3gk2dOnXA82E2m41WMVVVjUkDek00TdOM++tFbqdPnw6TyQRJkozb9dUL4s9Tfwml3W5PGJdGREQ0kWV8UrdlyxY8/PDD2L17N5qamrBx40asXr06YZ/a2lo8/PDDaG5uRnl5OR555BEsWbIEANDY2GgkdAAwZcqUIc08ra6uRnV1tdH0OZwcDsewHu9c6LMw+ytYKwgCsrKyUFFRYSRq3d3dOHPmDKLRKAAYi7YDPV20DocDNpvtrGdwcsIAERHR2cn4K2gwGER5eTnuuOMOfOpTn+pz+5NPPomamho89thjqKqqwvr167Fq1SocPnwYkyZNOuvHHcmWuuFcmeJs6Auz2+12VFRUoKmpCQ0NDYhEIsZKBaIoIj8/H7NnzzYSLX19T5fLlTCWjSU4iIiI0i/jk7prr70W1157bdLbf/KTn+ArX/kKbr/9dgDAY489hv/93//Fb3/7W9x7770oLi5OaJlraGgwWvH6E4lEEIlEcOutt+LWW2+Fz+dDSUnJ8D0hpLelThAEY5WB2bNnw2KxYNq0aZg6dSoCgQAikQhsNhscDkdCq5ksy8bSZldeeSVb1IiIiDLMmL4yR6NR7N69G/fdd5+xTRRFrFy5Etu3bwcALFmyBO+//z4aGhrg8Xjw4osv4nvf+17SYz744IP4wQ9+MKJx6+PJ2tvbz+k4ei213ttsNhssFgtcLhesViskSTLKb+gtdFarNaGFTU/0ktGXntJ/JiIioswyppO69vZ2KIqCwsLChO2FhYU4dOgQgJ4xWv/xH/+BFStWQFVVfPvb3x5w5ut9992Hmpoa4/eRaKkDgPPPPx87duwwxqYNhdVqRU5ODpxOJ3JycuD1eqFpGvLy8hImDLBLlIiIaOIZ00ndUN1www244YYbhrSv1WodlfIYFosFixYtwqFDh+D3+40xanoJD33cm96ClpWVhdzcXNhsNmNWaLrH5hEREVHmGNNJXX5+PiRJMroFdS0tLSgqKkpTVENnt9tx4YUXJpTxAHrq2CmKAqvVyoK5RERENCRjelV2vbVr8+bNxjZVVbF582YsXbo0jZGlRpIkmEwmo9vUbrfD5XIxoSMiIqIhy/iWukAggKNHjxq/19XVYe/evcjNzUVpaSlqamqwdu1aLF68GEuWLMH69esRDAaN2bBEREREE0HGJ3W7du3CihUrjN/1SQxr167F448/jjVr1qCtrQ33338/mpubUVFRgU2bNvWZPEHnbqythEFERDSRCBrrUwwo1cV0iYiIiIZDqjnImB5TR0REREQ9mNQRERERjQMZP6aOMoOiKHjjjTcAAFdccQXH1xEREWUYJnU0JKqqGmvo6gWSiYiIKHOw+5WIiIhoHGBSl0RtbS3mzp2LysrKdIdCRERENCgmdUlUV1fj4MGD2LlzZ7pDISIiIhoUkzoiIiKicYBJHREREdE4wNmvg9AX3PD5fGmOJL1isRhCoRCAnnNhNpvTHBEREdH4puceQ138i8uEDeL06dMoKSlJdxhEREQ0QdXX12Pq1KmD7sekbhCqqqKxsRFZWVkQBGHYj+/z+VBSUoL6+nquLTuMeF6HH8/p8OM5HX48p8OP53T4DfWcapoGv9+P4uJiiOLgI+bY/ToIURSHlB2fK7fbzT+WEcDzOvx4Tocfz+nw4zkdfjynw28o59Tj8Qz5eJwoQURERDQOMKkjIiIiGgeY1KWZ1WrFAw88AKvVmu5QxhWe1+HHczr8eE6HH8/p8OM5HX4jdU45UYKIiIhoHGBLHREREdE4wKSOiIiIaBxgUkdEREQ0DjCpGwW1tbUoKyuDzWZDVVUVduzYMeD+Tz31FM4//3zYbDYsWLAAL7zwwihFOnakck5/9atfYdmyZcjJyUFOTg5Wrlw56GswUaX6XtVt2LABgiBg9erVIxvgGJTqOe3q6kJ1dTUmT54Mq9WK2bNn8zOgl1TP6fr16zFnzhzY7XaUlJTgn//5nxEOh0cp2sy3ZcsWXH/99SguLoYgCHj22WcHvc/rr7+Oiy66CFarFbNmzcLjjz8+4nGOJame02eeeQZXXXUVCgoK4Ha7sXTpUrz00kupP7BGI2rDhg2axWLRfvvb32oHDhzQvvKVr2jZ2dlaS0tLv/tv3bpVkyRJe+ihh7SDBw9q3/3udzWz2ay99957oxx55kr1nN5yyy1abW2t9u6772offPCBdtttt2kej0c7ffr0KEee2VI9r7q6ujptypQp2rJly7Qbb7xxdIIdI1I9p5FIRFu8eLF23XXXaW+99ZZWV1envf7669revXtHOfLMleo5feKJJzSr1ao98cQTWl1dnfbSSy9pkydP1v75n/95lCPPXC+88IL2ne98R3vmmWc0ANrGjRsH3P/48eOaw+HQampqtIMHD2qPPPKIJkmStmnTptEJeAxI9Zzefffd2r//+79rO3bs0D788EPtvvvu08xms7Znz56UHpdJ3QhbsmSJVl1dbfyuKIpWXFysPfjgg/3u/9nPflb7h3/4h4RtVVVV2p133jmicY4lqZ7T3mRZ1rKysrTf/e53IxXimHQ251WWZe2SSy7Rfv3rX2tr165lUtdLquf05z//uTZjxgwtGo2OVohjTqrntLq6WrvyyisTttXU1GiXXnrpiMY5Vg0lAfn2t7+tzZs3L2HbmjVrtFWrVo1gZGPXUM5pf+bOnav94Af/f3v3HxN1/ccB/HmAB8cPRUVATHCinGgoBYhIjfzR+GGBtoINAjTBlZK1QNOsjjD80ajNldVMh60ZCE0XCVORZOGFSQiIiqf8UPsBGmUTNOHg3t8/mp+vJ1x1p3BwPh/bbfL+vN+fz/Pz2sm99vncHe8YtYa3XwdQd3c3qqursXDhQmnMysoKCxcuRGVlZb9rKisr9eYDQHh4uMH5DxpTanq3mzdvQqvVYsyYMQMVc9gxta5ZWVlwdXXF8uXLByPmsGJKTYuKihASEoJVq1bBzc0NDz/8MDZt2oTe3t7Bij2kmVLTuXPnorq6WrpF29zcjJKSEkRFRQ1KZkvE16mBp9Pp0NHRYfTrFP/26wBqb29Hb28v3Nzc9Mbd3Nxw7ty5fte0tbX1O7+trW3Acg4nptT0bq+//jo8PDz6/FJ6kJlS12PHjmHXrl2ora0dhITDjyk1bW5uxrfffouEhASUlJSgsbERK1euhFarhUqlGozYQ5opNY2Pj0d7ezsee+wxCCHQ09ODF198EW+88cZgRLZIhl6nrl+/jr/++gsKhcJMySxHTk4OOjs7ERsba9Q6XqmjB8qWLVuQn5+P/fv3w87Oztxxhq2Ojg4kJibis88+g4uLi7njWAydTgdXV1fs2LEDAQEBiIuLw4YNG/Dpp5+aO9qwVV5ejk2bNuHjjz/GyZMnsW/fPhQXF2Pjxo3mjkbUry+//BLvvPMOCgoK4OrqatRaXqkbQC4uLrC2tsaVK1f0xq9cuQJ3d/d+17i7uxs1/0FjSk1vy8nJwZYtW3DkyBHMnDlzIGMOO8bWtampCRcvXsTTTz8tjel0OgCAjY0NNBoNvL29Bzb0EGfKc3X8+PEYMWIErK2tpTFfX1+0tbWhu7sbcrl8QDMPdabU9K233kJiYiJSUlIAAH5+frhx4wZWrFiBDRs2wMqK1zaMZeh1auTIkbxKd4/y8/ORkpKCwsJCk+4m8dk8gORyOQICAlBWViaN6XQ6lJWVISQkpN81ISEhevMBoLS01OD8B40pNQWA9957Dxs3bsTBgwcRGBg4GFGHFWPrOm3aNNTX16O2tlZ6REdHY968eaitrcXEiRMHM/6QZMpzNTQ0FI2NjVKDDADnz5/H+PHjH/iGDjCtpjdv3uzTuN1umgX/SqZJ+Do1MPLy8rBs2TLk5eVh0aJFpu3E6I9jkFHy8/OFra2t2L17tzh79qxYsWKFcHZ2Fm1tbUIIIRITE8W6deuk+Wq1WtjY2IicnBzR0NAgVCoVv9LkLsbWdMuWLUIul4uvvvpKtLa2So+Ojg5zncKQZGxd78ZPv/ZlbE0vX74snJycRFpamtBoNOLAgQPC1dVVvPvuu+Y6hSHH2JqqVCrh5OQk8vLyRHNzszh8+LDw9vYWsbGx5jqFIaejo0PU1NSImpoaAUB88MEHoqamRly6dEkIIcS6detEYmKiNP/2V5qsWbNGNDQ0iO3bt/MrTe5ibE337NkjbGxsxPbt2/Vep/7880+jjsumbhB8+OGHwtPTU8jlcjF79mxx/PhxaVtYWJhITk7Wm19QUCB8fHyEXC4XM2bMEMXFxYOceOgzpqZeXl4CQJ+HSqUa/OBDnLHP1TuxqeufsTX9/vvvRXBwsLC1tRWTJ08W2dnZoqenZ5BTD23G1FSr1YrMzEzh7e0t7OzsxMSJE8XKlSvFtWvXBj/4EHX06NF+f0fermNycrIICwvrs8bf31/I5XIxefJkkZubO+i5hzJjaxoWFvaP8/8rmRC8/kxEREQ03PE9dUREREQWgE0dERERkQVgU0dERERkAdjUEREREVkANnVEREREFoBNHREREZEFYFNHREREZAHY1BERERFZADZ1RET/wblz5zBnzhzY2dnB39/f3HGIiPpgU0dEg27p0qWQyWSQyWSQy+WYMmUKsrKy0NPTc8/7Xbx48f0JeReVSgUHBwdoNJo+f8zcXPbv3485c+Zg1KhRcHJywowZM/Dqq6+aOxYRmYmNuQMQ0YMpIiICubm56OrqQklJCVatWoURI0Zg/fr1feZ2d3dDLpebIeX/NTU1YdGiRfDy8jJ5H/fzPMrKyhAXF4fs7GxER0dDJpPh7NmzKC0tvS/7709vby9kMhmsrHg9gGgo4v9MIjILW1tbuLu7w8vLCy+99BIWLlyIoqIiAP+/4padnQ0PDw8olUoAQH19PebPnw+FQoGxY8dixYoV6OzsBABkZmbi888/x9dffy1dBSwvLwcA/PTTT4iNjYWzszPGjBmDmJgYXLx4Ucqi0+mQlZWFhx56CLa2tvD398fBgwel7TKZDNXV1cjKyoJMJkNmZua/5jF0HhcvXoRMJkNBQQEef/xxKBQKBAUF4fz586iqqkJgYCAcHR0RGRmJ3377zWD9vvnmG4SGhmLNmjVQKpXw8fHB4sWLsX379j7zgoKCYGdnBxcXFyxZskTadu3aNSQlJWH06NGwt7dHZGQkLly4IG3fvXs3nJ2dUVRUhOnTp8PW1haXL19GV1cXMjIyMGHCBDg4OCA4OFiqNRGZD5s6IhoSFAoFuru7pZ/Lysqg0WhQWlqKAwcO4MaNGwgPD8fo0aNRVVWFwsJCHDlyBGlpaQCAjIwMxMbGIiIiAq2trWhtbcXcuXOh1WoRHh4OJycnVFRUQK1Ww9HREREREdLxtm3bhvfffx85OTk4deoUwsPDER0dLTU4ra2tmDFjBtLT09Ha2oqMjIx/zWPoPG5TqVR48803cfLkSdjY2CA+Ph5r167Ftm3bUFFRgcbGRrz99tsG6+Xu7o4zZ87g9OnTBucUFxdjyZIliIqKQk1NDcrKyjB79mxp+9KlS/Hjjz+iqKgIlZWVEEIgKioKWq1WmnPz5k1s3boVO3fuxJkzZ+Dq6oq0tDRUVlYiPz8fp06dwnPPPYeIiAi9hpCIzEAQEQ2y5ORkERMTI4QQQqfTidLSUmFraysyMjKk7W5ubqKrq0tas2PHDjF69GjR2dkpjRUXFwsrKyvR1tbWZ7+3ffHFF0KpVAqdTieNdXV1CYVCIQ4dOiSEEMLDw0NkZ2frrQsKChIrV66Ufp41a5ZQqVRG57n7PFpaWgQAsXPnTmksLy9PABBlZWXS2ObNm4VSqTRYw87OThEVFSUACC8vLxEXFyd27dolbt26Jc0JCQkRCQkJ/a4/f/68ACDUarU01t7eLhQKhSgoKBBCCJGbmysAiNraWmnOpUuXhLW1tfjll1/09rdgwQKxfv16g3mJaODxPXVEZBYHDhyAo6MjtFotdDod4uPjpduaAODn56f3/rOGhgbMmjULDg4O0lhoaCh0Oh00Gg3c3Nz6PU5dXR0aGxvh5OSkN37r1i00NTXh+vXr+PXXXxEaGqq3PTQ0FHV1dQbz/9c8d5/HbTNnzpT+fefcO8euXr1q8PgODg4oLi5GU1MTjh49iuPHjyM9PR3btm1DZWUl7O3tUVtbi9TUVIP5bWxsEBwcLI2NHTsWSqUSDQ0N0phcLtfLWl9fj97eXvj4+Ojtr6urC2PHjjWYl4gGHps6IjKLefPm4ZNPPoFcLoeHhwdsbPR/Hd3ZLN2Lzs5OBAQEYM+ePX22jRs37r4c458YOo8RI0ZI/5bJZP2O6XS6f92/t7c3vL29kZKSgg0bNsDHxwd79+7FsmXLoFAo7jH937fFb+cD/q6ntbU1qqurYW1trTfX0dHxno9HRKbje+qIyCwcHBwwZcoUeHp69mno+uPr64u6ujrcuHFDGlOr1bCyspI+SCGXy9Hb26u37tFHH8WFCxfg6uqKKVOm6D1GjRqFkSNHwsPDA2q1Wm+dWq3G9OnT7ynPYJs0aRLs7e2lTDNnzjT49Su+vr7o6enBDz/8II39/vvv0Gg0/3jejzzyCHp7e3H16tU+9XR3d7+/J0RERmFTR0TDQkJCAuzs7JCcnIzTp0/j6NGjePnll5GYmCjdvpw0aRJOnToFjUaD9vZ2aLVaJCQkwMXFBTExMaioqEBLSwvKy8uxevVq/PzzzwCANWvWYOvWrdi7dy80Gg3WrVuH2tpavPLKK/eUZyBlZmZi7dq1KC8vR0tLC2pqavDCCy9Aq9XiySefBPD3hzHy8vKgUqnQ0NCA+vp6bN26FQAwdepUxMTEIDU1FceOHUNdXR2ef/55TJgwATExMQaP6+Pjg4SEBCQlJWHfvn1oaWnBiRMnsHnzZhQXFw/4eRORYWzqiGhYsLe3x6FDh/DHH38gKCgIzz77LBYsWICPPvpImpOamgqlUonAwECMGzcOarUa9vb2+O677+Dp6YlnnnkGvr6+WL58OW7duoWRI0cCAFavXo3XXnsN6enp8PPzw8GDB1FUVISpU6feU56BFBYWhubmZiQlJWHatGmIjIxEW1sbDh8+LF0pfOKJJ1BYWIiioiL4+/tj/vz5OHHihLSP3NxcBAQE4KmnnkJISAiEECgpKdG7Ddyf3NxcJCUlIT09HUqlEosXL0ZVVRU8PT0H9JyJ6J/JhBDC3CGIiIiI6N7wSh0RERGRBWBTR0RERGQB2NQRERERWQA2dUREREQWgE0dERERkQVgU0dERERkAdjUEREREVkANnVEREREFoBNHREREZEFYFNHREREZAHY1BERERFZADZ1RERERBbgf05AHirAe6YGAAAAAElFTkSuQmCC",
      "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": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "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",
    "    protein_id_key=\"gene_id\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "9e574f48",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:51:19.455526Z",
     "iopub.status.busy": "2026-08-03T06:51:19.455437Z",
     "iopub.status.idle": "2026-08-03T06:51:19.476014Z",
     "shell.execute_reply": "2026-08-03T06:51:19.475541Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "63 significant proteoforms inferred.\n"
     ]
    }
   ],
   "source": [
    "pf_df = pr.get.proteoforms_df(adata, only_proteins=True)\n",
    "sig_df = pf_df[pf_df[\"is_proteoform\"] == 1]\n",
    "n_proteoforms = sig_df.shape[0]\n",
    "print(f\"{n_proteoforms} significant proteoforms inferred.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bcea2dcb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:51:19.477279Z",
     "iopub.status.busy": "2026-08-03T06:51:19.477186Z",
     "iopub.status.idle": "2026-08-03T06:51:19.481181Z",
     "shell.execute_reply": "2026-08-03T06:51:19.480871Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "peptides analysed         : 24,534\n",
      "proteins analysed         : 2,885\n",
      "proteins scored (BH n)    : 1,272\n",
      "\n",
      "significant proteins      : 63   (published: 63)\n",
      "recovered of the published: 63\n",
      "missed                    : 0\n",
      "false positives           : 0\n",
      "IDENTICAL SET             : True\n",
      "\n",
      "Sorbs2 (Q3UTJ2) recovered : True\n",
      "Ldb3   (Q9JKS4) recovered : True\n"
     ]
    }
   ],
   "source": [
    "# The 63 accessions Bludau et al. (2021) report for this dataset, taken\n",
    "# from a run of the authors' original R workflow on the same input\n",
    "# https://github.com/ibludau/ProteoformAnanlysis/blob/main/MouseTissue/GetMouseTissueProteoforms_paper.R.\n",
    "PUBLISHED_63 = {\n",
    "    \"O08601\",\n",
    "    \"O54724\",\n",
    "    \"O54749\",\n",
    "    \"O54754\",\n",
    "    \"O88844\",\n",
    "    \"O88986\",\n",
    "    \"P02088\",\n",
    "    \"P07356\",\n",
    "    \"P08226\",\n",
    "    \"P09671\",\n",
    "    \"P10852\",\n",
    "    \"P13541\",\n",
    "    \"P16125\",\n",
    "    \"P16332\",\n",
    "    \"P19096\",\n",
    "    \"P37040\",\n",
    "    \"P41216\",\n",
    "    \"P50431\",\n",
    "    \"P51660\",\n",
    "    \"P58281\",\n",
    "    \"P63030\",\n",
    "    \"P63318\",\n",
    "    \"Q00623\",\n",
    "    \"Q04447\",\n",
    "    \"Q3THK7\",\n",
    "    \"Q3UTJ2\",\n",
    "    \"Q5IRJ6\",\n",
    "    \"Q5RKZ7\",\n",
    "    \"Q60598\",\n",
    "    \"Q61207\",\n",
    "    \"Q62261\",\n",
    "    \"Q71LX4\",\n",
    "    \"Q7TNG8\",\n",
    "    \"Q80X90\",\n",
    "    \"Q8BMS1\",\n",
    "    \"Q8BWF0\",\n",
    "    \"Q8BYI9\",\n",
    "    \"Q8C165\",\n",
    "    \"Q8CI94\",\n",
    "    \"Q8VDD5\",\n",
    "    \"Q8VEM8\",\n",
    "    \"Q8VIJ6\",\n",
    "    \"Q91VN4\",\n",
    "    \"Q91WD5\",\n",
    "    \"Q924X2\",\n",
    "    \"Q99J39\",\n",
    "    \"Q99JB8\",\n",
    "    \"Q99KK7\",\n",
    "    \"Q99LC5\",\n",
    "    \"Q9CPQ1\",\n",
    "    \"Q9CQR4\",\n",
    "    \"Q9D0K2\",\n",
    "    \"Q9D5T0\",\n",
    "    \"Q9DBH5\",\n",
    "    \"Q9DBM2\",\n",
    "    \"Q9ES97\",\n",
    "    \"Q9ET01\",\n",
    "    \"Q9JI39\",\n",
    "    \"Q9JKS4\",\n",
    "    \"Q9QYR6\",\n",
    "    \"Q9QZ47\",\n",
    "    \"Q9Z204\",\n",
    "    \"Q9Z2Z6\",\n",
    "}\n",
    "\n",
    "significant = set(sig_df[\"protein_id\"])\n",
    "\n",
    "print(f\"peptides analysed         : {adata.n_vars:,}\")\n",
    "print(f\"proteins analysed         : {adata.var['protein_id'].nunique():,}\")\n",
    "print(f\"proteins scored (BH n)    : {len(pf_df):,}\")\n",
    "print()\n",
    "print(\n",
    "    f\"significant proteins      : {len(significant)}   (published: {len(PUBLISHED_63)})\"\n",
    ")\n",
    "print(f\"recovered of the published: {len(significant & PUBLISHED_63)}\")\n",
    "print(f\"missed                    : {len(PUBLISHED_63 - significant)}\")\n",
    "print(f\"false positives           : {len(significant - PUBLISHED_63)}\")\n",
    "print(f\"IDENTICAL SET             : {significant == PUBLISHED_63}\")\n",
    "print()\n",
    "print(f\"Sorbs2 (Q3UTJ2) recovered : {'Q3UTJ2' in significant}\")\n",
    "print(f\"Ldb3   (Q9JKS4) recovered : {'Q9JKS4' in significant}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4569a215",
   "metadata": {},
   "source": [
    "### Cleaning up before the downstream sections\n",
    "\n",
    "COPF marks peptides that fit neither cluster as outliers. They played their\n",
    "part in the scoring above and are removed here so the per-proteoform\n",
    "sections that follow work with cluster members only. Note this also drops\n",
    "the proteins that could not be scored at all, so the object is smaller from\n",
    "this point on."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "96db936d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:51:19.482084Z",
     "iopub.status.busy": "2026-08-03T06:51:19.482002Z",
     "iopub.status.idle": "2026-08-03T06:51:19.491922Z",
     "shell.execute_reply": "2026-08-03T06:51:19.491556Z"
    }
   },
   "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": "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": "code",
   "execution_count": 30,
   "id": "843207d8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:51:19.493227Z",
     "iopub.status.busy": "2026-08-03T06:51:19.493135Z",
     "iopub.status.idle": "2026-08-03T06:51:19.580715Z",
     "shell.execute_reply": "2026-08-03T06:51:19.580315Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_3009267/1804092523.py:5: ImplicitModificationWarning: Trying to modify attribute `.var` of view, initializing view as actual.\n",
      "  adata.var[\"peptide_sequence\"] = adata.var[\"peptide_id\"].str.replace(\n"
     ]
    }
   ],
   "source": [
    "# Summarisation keeps each surviving peptide's own identifier, modifications\n",
    "# included, as the reference does. The sequence maps below need the bare\n",
    "# amino-acid sequence to locate peptides on the protein, so derive it into a\n",
    "# separate column rather than rewriting the identifiers.\n",
    "adata.var[\"peptide_sequence\"] = adata.var[\"peptide_id\"].str.replace(\n",
    "    r\"\\(UniMod:\\d+\\)\", \"\", regex=True\n",
    ")"
   ]
  },
  {
   "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": 31,
   "id": "8f50bdb7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:51:19.581726Z",
     "iopub.status.busy": "2026-08-03T06:51:19.581641Z",
     "iopub.status.idle": "2026-08-03T06:51:19.761916Z",
     "shell.execute_reply": "2026-08-03T06:51:19.761517Z"
    }
   },
   "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",
    "    color_scheme=[\"#ff7f0e\", \"#1f77b4\"],\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "ac856b5c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:51:19.763082Z",
     "iopub.status.busy": "2026-08-03T06:51:19.762987Z",
     "iopub.status.idle": "2026-08-03T06:51:19.775726Z",
     "shell.execute_reply": "2026-08-03T06:51:19.775402Z"
    }
   },
   "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>VLPGPSQPR</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.56289</td>\n",
       "      <td>0.00166</td>\n",
       "      <td>0.055571</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>QYNNPIGLYSAETLR</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.56289</td>\n",
       "      <td>0.00166</td>\n",
       "      <td>0.055571</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>EMAQMYQMSLR</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.56289</td>\n",
       "      <td>0.00166</td>\n",
       "      <td>0.055571</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>ASSEGAQGSVSPK</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.56289</td>\n",
       "      <td>0.00166</td>\n",
       "      <td>0.055571</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>ASGAGLLGGSLPVK</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.56289</td>\n",
       "      <td>0.00166</td>\n",
       "      <td>0.055571</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>TSLADVC(UniMod:4)FVEEQNNVYC(UniMod:4)ER</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.56289</td>\n",
       "      <td>0.00166</td>\n",
       "      <td>0.055571</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>TQSKPEDEADEWAR</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.56289</td>\n",
       "      <td>0.00166</td>\n",
       "      <td>0.055571</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>TPLC(UniMod:4)GHC(UniMod:4)NNVIR</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.56289</td>\n",
       "      <td>0.00166</td>\n",
       "      <td>0.055571</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>SWHPEEFNC(UniMod:4)AYC(UniMod:4)K</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.56289</td>\n",
       "      <td>0.00166</td>\n",
       "      <td>0.055571</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>SKRPIPISTTAPPIQSPLPVIPHQK</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.56289</td>\n",
       "      <td>0.00166</td>\n",
       "      <td>0.055571</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>SASYNLSLTLQK</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.56289</td>\n",
       "      <td>0.00166</td>\n",
       "      <td>0.055571</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>QTWHTTC(UniMod:4)FVC(UniMod:4)AAC(UniMod:4)K</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.56289</td>\n",
       "      <td>0.00166</td>\n",
       "      <td>0.055571</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>LQGGKDFNMPLTISR</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.56289</td>\n",
       "      <td>0.00166</td>\n",
       "      <td>0.055571</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>IMGEVMHALR</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.56289</td>\n",
       "      <td>0.00166</td>\n",
       "      <td>0.055571</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>ILAQMTGTEYMQDPDEEALRR</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.56289</td>\n",
       "      <td>0.00166</td>\n",
       "      <td>0.055571</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>GPFLVAMGR</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.56289</td>\n",
       "      <td>0.00166</td>\n",
       "      <td>0.055571</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>GAPAYNPTGPQVTPLAR</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.56289</td>\n",
       "      <td>0.00166</td>\n",
       "      <td>0.055571</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>C(UniMod:4)YEQFFAPIC(UniMod:4)AK</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.56289</td>\n",
       "      <td>0.00166</td>\n",
       "      <td>0.055571</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Q9JKS4</td>\n",
       "      <td>AAQSQLSQGDLVVAIDGVNTDTMTHLEAQNK</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.56289</td>\n",
       "      <td>0.00166</td>\n",
       "      <td>0.055571</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   protein_id                                    peptide_id  cluster_id  \\\n",
       "0      Q9JKS4                                     VLPGPSQPR         0.0   \n",
       "1      Q9JKS4                               QYNNPIGLYSAETLR         0.0   \n",
       "2      Q9JKS4                                   EMAQMYQMSLR         0.0   \n",
       "3      Q9JKS4                                 ASSEGAQGSVSPK         0.0   \n",
       "4      Q9JKS4                                ASGAGLLGGSLPVK         0.0   \n",
       "5      Q9JKS4       TSLADVC(UniMod:4)FVEEQNNVYC(UniMod:4)ER         1.0   \n",
       "6      Q9JKS4                                TQSKPEDEADEWAR         1.0   \n",
       "7      Q9JKS4              TPLC(UniMod:4)GHC(UniMod:4)NNVIR         1.0   \n",
       "8      Q9JKS4             SWHPEEFNC(UniMod:4)AYC(UniMod:4)K         1.0   \n",
       "9      Q9JKS4                     SKRPIPISTTAPPIQSPLPVIPHQK         1.0   \n",
       "10     Q9JKS4                                  SASYNLSLTLQK         1.0   \n",
       "11     Q9JKS4  QTWHTTC(UniMod:4)FVC(UniMod:4)AAC(UniMod:4)K         1.0   \n",
       "12     Q9JKS4                               LQGGKDFNMPLTISR         1.0   \n",
       "13     Q9JKS4                                    IMGEVMHALR         1.0   \n",
       "14     Q9JKS4                         ILAQMTGTEYMQDPDEEALRR         1.0   \n",
       "15     Q9JKS4                                     GPFLVAMGR         1.0   \n",
       "16     Q9JKS4                             GAPAYNPTGPQVTPLAR         1.0   \n",
       "17     Q9JKS4              C(UniMod:4)YEQFFAPIC(UniMod:4)AK         1.0   \n",
       "18     Q9JKS4               AAQSQLSQGDLVVAIDGVNTDTMTHLEAQNK         1.0   \n",
       "\n",
       "    proteoform_score  proteoform_score_pval  proteoform_score_pval_adj  \\\n",
       "0            0.56289                0.00166                   0.055571   \n",
       "1            0.56289                0.00166                   0.055571   \n",
       "2            0.56289                0.00166                   0.055571   \n",
       "3            0.56289                0.00166                   0.055571   \n",
       "4            0.56289                0.00166                   0.055571   \n",
       "5            0.56289                0.00166                   0.055571   \n",
       "6            0.56289                0.00166                   0.055571   \n",
       "7            0.56289                0.00166                   0.055571   \n",
       "8            0.56289                0.00166                   0.055571   \n",
       "9            0.56289                0.00166                   0.055571   \n",
       "10           0.56289                0.00166                   0.055571   \n",
       "11           0.56289                0.00166                   0.055571   \n",
       "12           0.56289                0.00166                   0.055571   \n",
       "13           0.56289                0.00166                   0.055571   \n",
       "14           0.56289                0.00166                   0.055571   \n",
       "15           0.56289                0.00166                   0.055571   \n",
       "16           0.56289                0.00166                   0.055571   \n",
       "17           0.56289                0.00166                   0.055571   \n",
       "18           0.56289                0.00166                   0.055571   \n",
       "\n",
       "    is_proteoform  \n",
       "0             1.0  \n",
       "1             1.0  \n",
       "2             1.0  \n",
       "3             1.0  \n",
       "4             1.0  \n",
       "5             1.0  \n",
       "6             1.0  \n",
       "7             1.0  \n",
       "8             1.0  \n",
       "9             1.0  \n",
       "10            1.0  \n",
       "11            1.0  \n",
       "12            1.0  \n",
       "13            1.0  \n",
       "14            1.0  \n",
       "15            1.0  \n",
       "16            1.0  \n",
       "17            1.0  \n",
       "18            1.0  "
      ]
     },
     "execution_count": 32,
     "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": 33,
   "id": "eeb34806",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:51:19.776882Z",
     "iopub.status.busy": "2026-08-03T06:51:19.776779Z",
     "iopub.status.idle": "2026-08-03T06:51:19.832380Z",
     "shell.execute_reply": "2026-08-03T06:51:19.831986Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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JEwp0m8/8xihOJTF2Ud/9qCgUxx2gsr/XM2fO1N13351rG3d391v2UdTfj/vvv1+PPPKIVqxYcctg4evrKylnmM3++Tx48KD69euX67YHDx6UJJugWb16dUVHRys+Pl6nT59WnTp1FBAQoMDAQNWtW7dAtdevX18bN25URESEOnfurN27d9/y6IWbm5vatWundu3aqUqVKpo6daq+/PJLDR06VM8//7zatWunsLAwa8jMPhqRlJSkxMTEHKHuwoULNnewA0CwAHCHadu2rYKDg7Vjxw69+eabhdo2+57/8fHx6tSpk3X5tWvXdOLECZsPTiEhITp48KCysrJs/kKZfWpSUT0/YMeOHUpOTtYXX3xhvYBXkk6cOFEk/RdEfHy8OnbsaP360qVLSkpKUo8ePUz3XZg5NzvO9u3bdfnyZZujFrndoepWzMxFSEhIrn9Nv/k9k9dfsbPvMvTXowb2lpGRoaysrHyPnN11112Scr5v27RpIy8vLy1fvlwvvvhirsEn+65VAwcOzLGuTp061qNIhw8fVlJSkqKiogpcf8uWLbV69Wr17NlTnTt31q5du3Ic/cpNixYtJN0IDZKUmJiokydP5nqkqk+fPvL09Mxx56yifH8DZQXXWAC4o1gsFr377ruaPHlyoR+k1qJFC/n5+WnevHm6evWqdfnixYtzfCjo0aOHTp8+rU8//dS67Pr163rvvffk7u6u9u3bm9qPbNkftP76F+WrV6/q/fffL5L+C2L+/Pk2d5CaO3eurl+/bnO//9tVmDk3o2vXrrp27ZrNQ82ysrL0n//8p1D9mJmLHj166Pvvv9eePXusy9LT0zV//nyFhoZa/3pfqVIlSTlv4dq8eXPVqlVLb7/9dq7XNfzxxx+F2pfCSElJyfUuYh9++KGk//9BOy/Vq1dXUFBQjqdQu7m56fnnn1dcXJxefPHFHNtt2LBBixcvVu/evdWoUaM8+8/KytLzzz8vNze3HNfb5CciIkKffPKJjh49qm7dutmcbrh169Zct8m+pib79Kn58+dr1apVNq9nnnlGkvT2229r2bJlNtunpqbq2LFjuu+++wpVK1DWccQCQJFauHChNm3alGP56NGjC9xH37591bdv30KPXbFiRb322mt68skn1alTJw0aNEgnTpzQokWLcpzv/8QTT+iDDz5QVFSU9u/fr9DQUP3vf//T7t27NWvWrFtejFoY9913n7y9vTV06FCNGjVKFotFS5cuLZHTmLJdvXpVEREReuCBBxQXF6f3339fbdu2VZ8+fUz3XZg5N6Nfv35q2bKlnn32WR09elR33XWX1q5da31mSEHPdTczFxMnTtQnn3yi7t27a9SoUfLx8dGSJUt04sQJrVy50nrkq1atWvLy8tK8efNUuXJlVapUSa1atVJYWJg+/PBDde/eXQ0aNNCwYcNUvXp1/fbbb9q+fbs8PDyst2Qtajt27NCoUaP097//XXXq1NHVq1e1a9cuffHFF2rRooUefvjhfPvo27evVq1alePagueff16xsbF68803tWfPHg0YMECurq6Kjo7Wxx9/rAYNGuR4zsjo0aP1559/6u6779a1a9e0fPlyff/991qyZEmu15Hkp3///lqwYIGGDx+uPn36aNOmTXJxcVHfvn0VFham3r17q1atWkpPT9fXX3+tdevW6Z577rE+iK9Lly45+swOhu3bt88RvL7++msZhnFb/04BZRnBAkCRmjt3bq7LC3N6gxlPPPGEMjMzNXPmTD333HNq1KiR1q5dq5dfftmmnaurq3bs2KGJEydqyZIlSktLU7169bRo0aIirdXX11fr16/Xs88+q5deekne3t56+OGHFRERkeOuQ8Vlzpw5WrZsmV555RVdu3ZNgwcP1rvvvltkF54WdM7NqFChgjZs2KDRo0dryZIlcnBwUP/+/TV58mS1adOmwE/0NjMX/v7++vbbbzVhwgS99957+vPPP9W4cWOtW7fO5sFsFStW1JIlSzRp0iQ99dRTun79uhYtWqSwsDB16NBBe/bs0bRp0zRnzhxdunRJAQEBatWqlZ588snbnp/8NGrUSB07dtSaNWuUlJQkwzBUq1YtvfLKK3ruuecK9OT14cOHa86cOdq9e7fNnbEqVKigFStWqEePHlqwYIFeeukl6wXbkZGR2rBhQ47+mzZtqlmzZmnZsmVycHBQy5YttXXrVpvT1KT/f6SvINfhDBs2TOfPn9f48eM1cOBArVq1Sh9++KHWrFmjzz77TL///rsMw1DNmjX14osvasKECXk+eyM/n3/+udq2bXvLh+gB5ZHFKMk/mwEAUIRWr16t/v37Kzo6Wm3atMmz3eLFizVs2DDt27cv39N+kLeIiAgFBgZq6dKlt2x37do19e7dW1u3btW6devUrVu32xpv7dq16tu3r77++mtFRETcVh9F7fTp0woLC9OKFSs4YgHchGssAAClws3PN8jMzNR7770nDw+PHE+ERvF444039Omnn+a4HfPNKlasqJUrV+ruu+/WwIEDdeDAgdsab9++fZJ0x9wdTrrxdO5GjRoRKoBccCoUAKBUeOaZZ3TlyhW1bt1aGRkZ+uKLL/Ttt9/qjTfeKJbbwyKn7AdAFkSlSpWswaCwvvrqK+3cuVPvvPOOOnfurGrVqt1WP8VhxowZ9i4BuGMRLAAApUKnTp30zjvvaP369frzzz9Vu3Ztvffeexo5cqS9S0MRmz59ug4cOKA+ffpozpw59i4HQAFxjQUAAAAA07jGAgAAAIBpBAsAAAAAphEsSoBhGEpLSyvRB2IBAAAAJYlgUQIuXrwoT09P6wODAAAAgLKGYAEAAADANIIFAAAAANMIFgAAAABMI1gAAAAAMI1gAQAAAMA0ggUAAAAA0wgWAAAAAEwjWAAAAAAwjWABAAAAwDSCBQAAAADTCBYAAAAATCNYAAAAADCNYAEAAADANEd7FwDY09973q/08xftXQZMquRTWf/b8IW9y7Are76XK/lUliR+lgCgjPpyz5YCtSNYoFxLP39RC9q/Yu8yYNI/dr5q7xLszp7v5ez552cJAMo3ToUCAAAAYBrBAgAAAIBpBAsAAAAAphEsAAAAAJhGsAAAAABgWpkOFgkJCbJYLIqNjbV3KQAAAECZVqaDxc127Nghi8WilJSUQm3322+/6eGHH5avr69cXV3VqFEjxcTEFE+RAAAAQCnEcyzyceHCBbVp00YdO3bUl19+KT8/P8XHx8vb29vepQEAAAB3jFJ/xGLTpk1q27atvLy85Ovrq169eunYsWM52iUkJKhjx46SJG9vb1ksFkVFReXb/5tvvqmgoCAtWrRILVu2VFhYmLp06aJatWoV9a4AAAAApVapDxbp6ekaN26cYmJitHXrVjk4OKh///7KysqyaRcUFKSVK1dKkuLi4pSUlKTZs2fn2//atWvVokULDRw4UFWrVlXTpk21YMGCW26TkZGhtLQ0mxcAAABQlpX6U6EGDBhg8/XChQvl5+enw4cPy93d3bq8QoUK8vHxkSRVrVpVXl5eBer/+PHjmjt3rsaNG6cXXnhB+/bt06hRo+Tk5KShQ4fmus306dM1derU29shAAAAoBQq9Ucs4uPjNXjwYNWsWVMeHh4KDQ2VJCUmJhZJ/1lZWWrWrJneeOMNNW3aVE888YT+8Y9/aN68eXluM2nSJKWmplpfp06dKpJaAAAAgDtVqT9i0bt3b4WEhGjBggUKDAxUVlaWGjZsqKtXrxZJ/9WqVVP9+vVtloWHh1tPq8qNs7OznJ2di2R8AAAAoDQo1cEiOTlZcXFxWrBggdq1aydJio6OzrO9k5OTJCkzM7PAY7Rp00ZxcXE2y3755ReFhITcRsUAAABA2VSqT4Xy9vaWr6+v5s+fr6NHj2rbtm0aN25cnu1DQkJksVi0fv16/fHHH7p06VK+Y4wdO1Z79+7VG2+8oaNHj2r58uWaP3++RowYUZS7AgAAAJRqpTpYODg4aMWKFdq/f78aNmyosWPHaubMmXm2r169uqZOnaqJEyfK399fI0eOzHeMe+65R6tWrdInn3yihg0batq0aZo1a5aGDBlSlLsCAAAAlGql+lQoSYqMjNThw4dtlhmGkev/S9LLL7+sl19+uVBj9OrVS7169br9IgEAAIAyrlQfsQAAAABwZyjXwSIxMVHu7u55vorqlrUAAABAWVfqT4UyIzAwULGxsbdcDwAAACB/5TpYODo6qnbt2vYuAwAAACj1yvWpUAAAAACKRrk+YgFU8qmsf+x81d5lwKRKPpXtXYLd2fO9nD3//CwBQNn0pbYUqJ3FuPl+rChyaWlp8vT0VGpqqjw8POxdDgAAAFDkOBUKAAAAgGkECwAAAACmESwAAAAAmEawAAAAAGAawQIAAACAaQQLAAAAAKYRLAAAAACYRrAAAAAAYBrBAgAAAIBpBAsAAAAApjnauwAAgHm9u3XVhXN/2GVs7yp+kmS38QEAxSs65kCB2hEsAKAMuHDuD/WvFWiXsVcd+12S7DY+AODOwKlQAAAAAEwjWAAAAAAwjWABAAAAwDSCBQAAAADTCBYAAAAATCvTwSIhIUEWi0WxsbH2LgUAAAAo08p0sLjZjh07ZLFYlJKSUuBtpkyZIovFYvO66667iq9IAAAAoBTiORYF0KBBA3399dfWrx0dmTYAAADgr0r9EYtNmzapbdu28vLykq+vr3r16qVjx47laJeQkKCOHTtKkry9vWWxWBQVFVWgMRwdHRUQEGB9ValSpSh3AQAAACj1Sn2wSE9P17hx4xQTE6OtW7fKwcFB/fv3V1ZWlk27oKAgrVy5UpIUFxenpKQkzZ49u0BjxMfHKzAwUDVr1tSQIUOUmJh4y/YZGRlKS0uzeQEAAABlWak/p2fAgAE2Xy9cuFB+fn46fPiw3N3drcsrVKggHx8fSVLVqlXl5eVVoP5btWqlxYsXq169ekpKStLUqVPVrl07/fTTT6pcuXKu20yfPl1Tp069vR0CAAAASqFSf8QiPj5egwcPVs2aNeXh4aHQ0FBJyveoQkF1795dAwcOVOPGjdW1a1dt3LhRKSkp+uyzz/LcZtKkSUpNTbW+Tp06VSS1AAAAAHeqUn/Eonfv3goJCdGCBQsUGBiorKwsNWzYUFevXi2W8by8vFS3bl0dPXo0zzbOzs5ydnYulvEBAACAO1GpPmKRnJysuLg4vfTSS4qIiFB4eLguXLiQZ3snJydJUmZm5m2PeenSJR07dkzVqlW77T4AAACAsqZUBwtvb2/5+vpq/vz5Onr0qLZt26Zx48bl2T4kJEQWi0Xr16/XH3/8oUuXLuU7xvjx47Vz504lJCTo22+/Vf/+/VWhQgUNHjy4KHcFAAAAKNVKdbBwcHDQihUrtH//fjVs2FBjx47VzJkz82xfvXp1TZ06VRMnTpS/v79GjhyZ7xi//vqrBg8erHr16umBBx6Qr6+v9u7dKz8/v6LcFQAAAKBUsxiGYdi7iLIuLS1Nnp6eSk1NlYeHh73LAVAGtW3RTP1rBdpl7FXHfpcku40PAChez366vkDtSvURCwAAAAB3hnIdLBITE+Xu7p7nq6huWQsAAACUdaX+drNmBAYGKjY29pbrAQAAAOSvXAcLR0dH1a5d295lAAAAAKVeuT4VCgAAAEDRKNdHLACgrPCu4me9O5M9xpZkt/EBAMXr2QK243azJYDbzQIAAKCs41QoAAAAAKYRLAAAAACYRrAAAAAAYBrBAgAAAIBpBAsAAAAAphEsAAAAAJhGsAAAAABgGsECAAAAgGkECwAAAACmESwAAAAAmOZo7wIAe+rTo79Ski/auwyY5OVbWWs3rrJ3GXZV3t7LfM8B4M5DsEC5lpJ8UYOavmDvMmDSpz+8Ye8S7K68vZf5ngPAnYdToQAAAACYRrAAAAAAYBrBAgAAAIBpBAsAAAAAphEsAAAAAJhWpoNFQkKCLBaLYmNj7V0KAAAAUKaV6WBxsx07dshisSglJeW2tp8xY4YsFovGjBlTpHUBAAAApV25ChZm7Nu3Tx988IEaN25s71IAAACAO06pDxabNm1S27Zt5eXlJV9fX/Xq1UvHjh3L0S4hIUEdO3aUJHl7e8tisSgqKqpAY1y6dElDhgzRggUL5O3tXZTlAwAAAGVCqQ8W6enpGjdunGJiYrR161Y5ODiof//+ysrKsmkXFBSklStXSpLi4uKUlJSk2bNnF2iMESNGqGfPnoqMjCxQ+4yMDKWlpdm8AAAAgLLM0d4FmDVgwACbrxcuXCg/Pz8dPnxY7u7u1uUVKlSQj4+PJKlq1ary8vIqUP8rVqzQgQMHtG/fvgLXNH36dE2dOrXA7QEAAIDSrtQfsYiPj9fgwYNVs2ZNeXh4KDQ0VJKUmJhouu9Tp05p9OjRWrZsmVxcXAq83aRJk5Sammp9nTp1ynQtAAAAwJ2s1B+x6N27t0JCQrRgwQIFBgYqKytLDRs21NWrV033vX//fp09e1bNmjWzLsvMzNQ333yjOXPmKCMjQxUqVMixnbOzs5ydnU2PDwAAAJQWpTpYJCcnKy4uTgsWLFC7du0kSdHR0Xm2d3JyknQjHBRERESEDh06ZLNs2LBhuuuuuzRhwoRcQwUAAABQHpXqYOHt7S1fX1/Nnz9f1apVU2JioiZOnJhn+5CQEFksFq1fv149evSQq6urzXUYN6tcubIaNmxos6xSpUry9fXNsRwAAAAoz0r1NRYODg5asWKF9u/fr4YNG2rs2LGaOXNmnu2rV6+uqVOnauLEifL399fIkSNLsFoAAACg7CrVRywkKTIyUocPH7ZZZhhGrv8vSS+//LJefvnl2x5vx44dt70tAAAAUFaV6iMWAAAAAO4M5TpYJCYmyt3dPc9XUdyyFgAAACgPSv2pUGYEBgYqNjb2lusBAAAA5K9cBwtHR0fVrl3b3mUAAAAApV65PhUKAAAAQNEo10csAC/fyvr0hzfsXQZM8vKtbO8S7K68vZf5ngPAncdi3Hw/VhS5tLQ0eXp6KjU1VR4eHvYuBwAAAChynAoFAAAAwDSCBQAAAADTCBYAAAAATCNYAAAAADCNYAEAAADANIIFAAAAANMIFgAAAABMI1gAAAAAMI1gAQAAAMA0ggUAAAAA0xztXQAAwLwBkZ2Vfua0vcsoMZX8A7Ty6y32LgMA8BcECwAoA9LPnNa/r123dxklZmw5ClEAUFpwKhQAAAAA0wgWAAAAAEwjWAAAAAAwjWABAAAAwDSCBQAAAADTynSwSEhIkMViUWxsrL1LAQAAAMq0Mh0sbrZjxw5ZLBalpKQUeJu5c+eqcePG8vDwkIeHh1q3bq0vv/yy+IoEAAAASqFyFSxuR40aNTRjxgzt379fMTEx6tSpk/r27auff/7Z3qUBAAAAd4xSHyw2bdqktm3bysvLS76+vurVq5eOHTuWo11CQoI6duwoSfL29pbFYlFUVFS+/ffu3Vs9evRQnTp1VLduXb3++utyd3fX3r17i3pXAAAAgFKr1AeL9PR0jRs3TjExMdq6dascHBzUv39/ZWVl2bQLCgrSypUrJUlxcXFKSkrS7NmzCzVWZmamVqxYofT0dLVu3TrPdhkZGUpLS7N5AQAAAGWZo70LMGvAgAE2Xy9cuFB+fn46fPiw3N3drcsrVKggHx8fSVLVqlXl5eVV4DEOHTqk1q1b688//5S7u7tWrVql+vXr59l++vTpmjp1auF2BAAAACjFSv0Ri/j4eA0ePFg1a9aUh4eHQkNDJUmJiYlFNka9evUUGxur7777Tk8//bSGDh2qw4cP59l+0qRJSk1Ntb5OnTpVZLUAAAAAd6JSf8Sid+/eCgkJ0YIFCxQYGKisrCw1bNhQV69eLbIxnJycVLt2bUlS8+bNtW/fPs2ePVsffPBBru2dnZ3l7OxcZOMDAAAAd7pSHSySk5MVFxenBQsWqF27dpKk6OjoPNs7OTlJunGthBlZWVnKyMgw1QcAAABQlpTqYOHt7S1fX1/Nnz9f1apVU2JioiZOnJhn+5CQEFksFq1fv149evSQq6urzXUYuZk0aZK6d++u4OBgXbx4UcuXL9eOHTu0efPmot4dAAAAoNQq1ddYODg4aMWKFdq/f78aNmyosWPHaubMmXm2r169uqZOnaqJEyfK399fI0eOzHeMs2fP6tFHH1W9evUUERGhffv2afPmzercuXNR7goAAABQqlkMwzDsXURZl5aWJk9PT6WmpsrDw8Pe5QAog7o1aqR/X7tu7zJKzNiKjtp06JC9ywAA/EWpPmIBAAAA4M5QroNFYmKi3N3d83wV5S1rAQAAgLKsVF+8bVZgYKBiY2NvuR4AAABA/sp1sHB0dLQ+nwIAAADA7SvXp0IBAAAAKBoECwAAAACmletToQCgrKjkH6CxZ07bu4wSU8k/wN4lAABuwnMsSgDPsQAAAEBZx6lQAAAAAEwjWAAAAAAwjWABAAAAwDSCBQAAAADTCBYAAAAATCNYAAAAADCNYAEAAADANIIFAAAAANMIFgAAAABMI1gAAAAAMM3R3gUA9tS5b2edSTlj7zJgkr+Xv7as2WLvMgAAKNcIFijXzqSckTHcsHcZMOnMQsIhAAD2xqlQAAAAAEwjWAAAAAAwjWABAAAAwDSCBQAAAADTynSwSEhIkMViUWxsrL1LAQAAAMq0Mh0sbrZjxw5ZLBalpKQUeJvp06frnnvuUeXKlVW1alX169dPcXFxxVckAAAAUAqVq2BxO3bu3KkRI0Zo79692rJli65du6YuXbooPT3d3qUBAAAAd4xSHyw2bdqktm3bysvLS76+vurVq5eOHTuWo11CQoI6duwoSfL29pbFYlFUVFSB+o+KilKDBg3UpEkTLV68WImJidq/f39R7woAAABQapX6YJGenq5x48YpJiZGW7dulYODg/r376+srCybdkFBQVq5cqUkKS4uTklJSZo9e3ahx0tNTZUk+fj4mC8eAAAAKCNK/ZO3BwwYYPP1woUL5efnp8OHD8vd3d26vEKFCtYwULVqVXl5eRV6rKysLI0ZM0Zt2rRRw4YN82yXkZGhjIwM69dpaWmFHgsAAAAoTUr9EYv4+HgNHjxYNWvWlIeHh0JDQyVJiYmJRT7WiBEj9NNPP2nFihW3bDd9+nR5enpaX0FBQUVeCwAAAHAnKfXBonfv3jp//rwWLFig7777Tt99950k6erVq0U6zsiRI7V+/Xpt375dNWrUuGXbSZMmKTU11fo6depUkdYCAAAA3GlK9alQycnJiouL04IFC9SuXTtJUnR0dJ7tnZycJEmZmZkFHsMwDD3zzDNatWqVduzYobCwsHy3cXZ2lrOzc4HHAAAAAEq7Uh0svL295evrq/nz56tatWpKTEzUxIkT82wfEhIii8Wi9evXq0ePHnJ1dbW5DiM3I0aM0PLly7VmzRpVrlxZp0+fliR5enrK1dW1SPcHAAAAKK1K9alQDg4OWrFihfbv36+GDRtq7NixmjlzZp7tq1evrqlTp2rixIny9/fXyJEj8x1j7ty5Sk1NVYcOHVStWjXr69NPPy3KXQEAAABKNYthGIa9iyjr0tLS5OnpqdTUVHl4eNi7HPxF4/aNZQznR6C0syy06ODOg/YuAwCAcq1UH7EAAAAAcGco18EiMTFR7u7ueb6K45a1AAAAQFlUqi/eNiswMFCxsbG3XA8AAAAgf+U6WDg6Oqp27dr2LgMAAAAo9cr1qVAAAAAAigbBAgAAAIBp5fpUKMDfy19nFp6xdxkwyd/L394lAABQ7vEcixLAcywAAABQ1nEqFAAAAADTCBYAAAAATCNYAAAAADCNYAEAAADANIIFAAAAANMIFgAAAABMI1gAAAAAMI1gAQAAAMA0ggUAAAAA0wgWAAAAAExztHcByN+gXp105XxSobdz9ammT9dvK7L+zHL1qSZJhRr7+K9nVLOGf3GVlOccoXwr6p+5ourf7LgAcmf2Z/J2fgYLO2Z+vw9v5/dlUf2OLUw/N89VQefhdmrl38aSR7AoBa6cT9LaLr8Xers+XxVtf2Zl11OYsZt/mFGsteY1Ryjfivpnrqj6NzsugNyZ/Zm8nZ/Bwo6Z3+/D2/l9WVS/YwvTz81zVdB5uJ1a+bex5HEqFAAAAADTCBYAAAAATCNYAAAAADCNYAEAAADANIIFAAAAANNMB4tTp05p+PDhCgwMlJOTk0JCQjR69GglJydb25w5c0ZRUVEKDAyUm5ubunXrpvj4eJt+QkNDNWvWrDy/NgxD48ePl4eHh3bs2CFJ+vHHH9WnTx9VrVpVLi4uCg0N1aBBg3T27NkcdSYnJ6tGjRqyWCxKSUkp0L4lJSXpoYceUt26deXg4KAxY8YUdFoAAACAcsVUsDh+/LhatGih+Ph4ffLJJzp69KjmzZunrVu3qnXr1jp//rwMw1C/fv10/PhxrVmzRj/88INCQkIUGRmp9PT0Ao2TmZmpxx57TB999JG2b9+uDh066I8//lBERIR8fHy0efNmHTlyRIsWLVJgYGCu/T722GNq3LhxofYvIyNDfn5+eumll9SkSZNCbQsAAACUJ6aeYzFixAg5OTnpq6++kqurqyQpODhYTZs2Va1atfTiiy9q7Nix2rt3r3766Sc1aNBAkjR37lwFBATok08+0eOPP37LMTIyMjR48GDFxMRo165dqlevniRp9+7dSk1N1YcffihHxxu7ERYWpo4dO+boY+7cuUpJSdErr7yiL7/8ssD7FxoaqtmzZ0uSFi5cWODtAAAAgPLmto9YnD9/Xps3b9Y///lPa6jIFhAQoCFDhujTTz9VRkaGJMnFxeX/D+rgIGdnZ0VHR99yjEuXLqlnz546fPiwdu/ebQ0V2WNcv35dq1atkmEYefZx+PBhvfrqq/roo4/k4MAlJQAAAEBxuO1P2vHx8TIMQ+Hh4bmuDw8P14ULF1S1alUFBwdr0qRJunDhgq5evao333xTv/76q5KSbv0I92nTpik2Nla7du1SUFCQzbp7771XL7zwgh566CFVqVJF3bt318yZM3XmzBlrm+yjHTNnzlRwcPDt7mqhZWRkKC0tzeYFAAAAlGWm/4R/q6MFkuTs7KwvvvhCv/zyi3x8fOTm5qbt27ere/fu+R5B6NKli9LT0/XGG2/kuv7111/X6dOnNW/ePDVo0EDz5s3TXXfdpUOHDkmSJk2apPDwcD388MO3t3O3afr06fL09LS+bg5FAAAAQFlz28Gidu3aslgsOnLkSK7rjxw5Ij8/P3l5eal58+aKjY1VSkqKkpKStGnTJiUnJ6tmzZq3HCMiIkJr1qzRvHnzNHr06Fzb+Pr6auDAgXr77bd15MgRBQYG6u2335Ykbdu2TZ9//rkcHR3l6OioiIgISVKVKlU0efLk2931fE2aNEmpqanW16lTp4ptLAAAAOBOcNsXb/v6+qpz5856//33NXbsWJvrLE6fPq1ly5ZpxIgRNtt4enpKunEaVUxMjKZNm5bvOF26dNG6devUp08fGYahd999N8+2Tk5OqlWrlvWuUCtXrtSVK1es6/ft26fhw4dr165dqlWrVqH2tzCcnZ3l7OxcbP0DAAAAdxpTd4WaM2eO7rvvPnXt2lWvvfaawsLC9PPPP+u5555T3bp19corr0iSPv/8c/n5+Sk4OFiHDh3S6NGj1a9fP3Xp0qVA40RGRmr9+vXq3bu3srKyNGfOHK1fv14rVqzQgw8+qLp168owDK1bt04bN27UokWLJClHeDh37pykG9d/eHl5FWjs2NhYSTcuJP/jjz8UGxsrJycn1a9fv0DbAwAAAOWBqWBRp04d7du3T1OmTNEDDzygs2fPyjAM3X///Vq6dKnc3Nwk3XjQ3Lhx43TmzBlVq1ZNjz76qF5++WWbvrKysqy3jc1Np06dtGHDBvXq1UuGYWjcuHFyc3PTs88+q1OnTsnZ2Vl16tTRhx9+qEceecTMbtlo2rSp9f/379+v5cuXKyQkRAkJCUU2BgAAAFDamQoW0o1nPSxevNj69eTJk/Wvf/1LBw8e1L333itJGjVqlEaNGpVnH5mZmUpOTlZAQIB1WW4f3Dt06KBLly5Zv54/f36hau3QoUO+F5vfrLDtAQAAgPLIdLC42dSpUxUaGqq9e/eqZcuW+d756ddff9VHH32kzMxMtW3btqjLAQAAAFACijxYSNKwYcMK3Pbuu++Wr6+vli5danPEoiQ0aNBAJ0+ezHXdBx98oCFDhpRoPQAAAEBpVSzBojCyL6i2h40bN+ratWu5rvP39y/hagAAAIDSy+7Bwp5CQkLsXQIAAABQJph+8jYAAAAAECwAAAAAmFauT4UqLVx9qqnPV7e3XVH2Z1Z2PYUZO8PhjPp8VXzXu+Q1Ryjfivpnrqj6NzsugNyZ/Zm8nZ/Bwo6Z3+/D2/l9WVS/YwvTz81zVdB5uJ1a+bex5FkMHtRQ7NLS0uTp6anU1FR5eHjYuxwAAACgyHEqFAAAAADTCBYAAAAATCNYAAAAADCNYAEAAADANIIFAAAAANMIFgAAAABMI1gAAAAAMI1gAQAAAMA0ggUAAAAA0wgWAAAAAExztHcBAIpfZM9+On0+rcDtT/+aqIAawabbmN0uwMdDX29YXej6/7otAAAoGQQLoBw4fT5Nl9o/W+D2V5aOzbd9QdqY3e70zndu/LeQ9f91WwAAUDI4FQoAAACAaQQLAAAAAKYRLAAAAACYRrAAAAAAYBrBAgAAAIBpRRIsTp06peHDhyswMFBOTk4KCQnR6NGjlZycbG1z5swZRUVFKTAwUG5uburWrZvi4+Nt+gkNDdWsWbPy/NowDI0fP14eHh7asWOHJOnHH39Unz59VLVqVbm4uCg0NFSDBg3S2bNnc9SZnJysGjVqyGKxKCUlpcD7t2PHDjVr1kzOzs6qXbu2Fi9eXOBtAQAAgPLAdLA4fvy4WrRoofj4eH3yySc6evSo5s2bp61bt6p169Y6f/68DMNQv379dPz4ca1Zs0Y//PCDQkJCFBkZqfT09AKNk5mZqccee0wfffSRtm/frg4dOuiPP/5QRESEfHx8tHnzZh05ckSLFi1SYGBgrv0+9thjaty4caH278SJE+rZs6c6duyo2NhYjRkzRo8//rg2b95cqH4AAACAssz0cyxGjBghJycnffXVV3J1dZUkBQcHq2nTpqpVq5ZefPFFjR07Vnv37tVPP/2kBg0aSJLmzp2rgIAAffLJJ3r88cdvOUZGRoYGDx6smJgY7dq1S/Xq1ZMk7d69W6mpqfrwww/l6HhjV8LCwtSxY8ccfcydO1cpKSl65ZVX9OWXXxZ4/+bNm6ewsDC9886Ne+KHh4crOjpa//73v9W1a9cC9wMAAACUZaaOWJw/f16bN2/WP//5T2uoyBYQEKAhQ4bo008/VUZGhiTJxcXl/w/s4CBnZ2dFR0ffcoxLly6pZ8+eOnz4sHbv3m0NFdljXL9+XatWrZJhGHn2cfjwYb366qv66KOP5OBQuF3es2ePIiMjbZZ17dpVe/bsKVQ/AAAAQFlmKljEx8fLMAyFh4fnuj48PFwXLlxQ1apVFRwcrEmTJunChQu6evWq3nzzTf36669KSkq65RjTpk1TbGysdu3apaCgIJt19957r1544QU99NBDqlKlirp3766ZM2fqzJkz1jbZRztmzpyp4ODgQu/j6dOn5e/vb7PM399faWlpunLlSq7bZGRkKC0tzeYFAAAAlGVFcvH2rY4WSJKzs7O++OIL/fLLL/Lx8ZGbm5u2b9+u7t2753sEoUuXLkpPT9cbb7yR6/rXX39dp0+f1rx589SgQQPNmzdPd911lw4dOiRJmjRpksLDw/Xwww/f3s7dhunTp8vT09P6ujkQAQAAAGWNqWBRu3ZtWSwWHTlyJNf1R44ckZ+fn7y8vNS8eXPFxsYqJSVFSUlJ2rRpk5KTk1WzZs1bjhEREaE1a9Zo3rx5Gj16dK5tfH19NXDgQL399ts6cuSIAgMD9fbbb0uStm3bps8//1yOjo5ydHRURESEJKlKlSqaPHlyvvsYEBBgcwREunGHKw8Pjxynf2WbNGmSUlNTra9Tp07lOw4AAABQmpm6eNvX11edO3fW+++/r7Fjx9p80D59+rSWLVumESNG2Gzj6ekp6cZpVDExMZo2bVq+43Tp0kXr1q1Tnz59ZBiG3n333TzbOjk5qVatWta7Qq1cudLmlKV9+/Zp+PDh2rVrl2rVqpXv2K1bt9bGjRttlm3ZskWtW7fOcxtnZ2c5Ozvn2zcAAABQVpi+K9ScOXN03333qWvXrnrttdcUFhamn3/+Wc8995zq1q2rV155RZL0+eefy8/PT8HBwTp06JBGjx6tfv36qUuXLgUaJzIyUuvXr1fv3r2VlZWlOXPmaP369VqxYoUefPBB1a1bV4ZhaN26ddq4caMWLVokSTnCw7lz5yTduP7Dy8sr33GfeuopzZkzR88//7yGDx+ubdu26bPPPtOGDRsKMUsAAABA2WY6WNSpU0f79u3TlClT9MADD+js2bMyDEP333+/li5dKjc3N0lSUlKSxo0bpzNnzqhatWp69NFH9fLLL9v0lZWVZb1tbG46deqkDRs2qFevXjIMQ+PGjZObm5ueffZZnTp1Ss7OzqpTp44+/PBDPfLII2Z3TdKN29du2LBBY8eO1ezZs1WjRg19+OGH3GoWAAAA+AvTwUK68YTsvz6NevLkyfrXv/6lgwcP6t5775UkjRo1SqNGjcqzj8zMTCUnJysgIMC6LCEhIUe7Dh066NKlS9av58+fX6haO3TokO/F5rlt88MPPxRqGwAAAKA8KZJgcbOpU6cqNDRUe/fuVcuWLfO989Ovv/6qjz76SJmZmWrbtm1xlAQAAACgGBVLsJCkYcOGFbjt3XffLV9fXy1dutTmiEVJaNCggU6ePJnrug8++EBDhgwp0XoAAACA0qjYgkVhZF9QbQ8bN27UtWvXcl1384PxAAAAAOTujggW9hQSEmLvEgAAAIBSr0ievA0AAACgfCNYAAAAADCt3J8KBZQHAT4eOr3znQK3v+SQJfd82hekjdntAnw8rP8tTP1/3RYAAJQMi1HYhzqg0NLS0uTp6anU1FR5ePBhBwAAAGUPp0IBAAAAMI1gAQAAAMA0ggUAAAAA0wgWAAAAAEwjWAAAAAAwjWABAAAAwDSCBQAAAADTCBYAAAAATCNYAAAAADCNYAEAAADANEd7F1CeLFu2TK6urvYuAwAAACgwZ2dnDR48ON92BIsS1LRpU7m7u9u7DAAAAKDAYmJiCtSOU6EAAAAAmEawAAAAAGAawQIAAACAaQQLAAAAAKaVeLDYvXu3GjVqpIoVK6pfv34lPTwAAACAYlCoYBEVFSWLxSKLxaKKFSsqLCxMzz//vP78888C9zFu3DjdfffdOnHihBYvXlzYegEAAADcgQp9u9lu3bpp0aJFunbtmvbv36+hQ4fKYrHozTffLND2x44d01NPPaUaNWoUuthsV69elZOT021vDwAAAKBoFfpUKGdnZwUEBCgoKEj9+vVTZGSktmzZIknKysrS9OnTFRYWJldXVzVp0kT/+9//JEkJCQmyWCxKTk7W8OHDZbFYrEcsfvrpJ3Xv3l3u7u7y9/fXI488onPnzlnH7NChg0aOHKkxY8aoSpUq6tq1a4G3GzVqlJ5//nn5+PgoICBAU6ZMsdmflJQUPfnkk/L395eLi4saNmyo9evXW9dHR0erXbt2cnV1VVBQkEaNGqX09PTCThsAAABQppm6xuKnn37St99+az16MH36dH300UeaN2+efv75Z40dO1YPP/ywdu7cqaCgICUlJcnDw0OzZs1SUlKSBg0apJSUFHXq1ElNmzZVTEyMNm3apDNnzuiBBx6wGWvJkiVycnLS7t27NW/evEJtV6lSJX333Xd666239Oqrr9oEoe7du2v37t36+OOPdfjwYc2YMUMVKlSQdOPoSrdu3TRgwAAdPHhQn376qaKjozVy5Egz0wYAAACUORbDMIyCNo6KitLHH38sFxcXXb9+XRkZGXJwcNBnn32mXr16ycfHR19//bVat25t3ebxxx/X5cuXtXz5ckmSl5eXZs2apaioKEnSa6+9pl27dmnz5s3WbX799VcFBQUpLi5OdevWVYcOHZSWlqYDBw5Y2xR0u8zMTO3atcvapmXLlurUqZNmzJihr776St27d9eRI0dUt27dHPv7+OOPq0KFCvrggw+sy6Kjo9W+fXulp6fLxcUl13nKyMhQRkaG9eu0tDQFBQVpz549PHkbAAAApUpMTIz1s/utFPoai44dO2ru3LlKT0/Xv//9bzk6OmrAgAH6+eefdfnyZXXu3Nmm/dWrV9W0adM8+/vxxx+1ffv2XD9wHzt2zPqBv3nz5re1XePGjW3WVatWTWfPnpUkxcbGqkaNGrmGiuwxDh48qGXLllmXGYahrKwsnThxQuHh4bluN336dE2dOjWvXQYAAADKnEIHi0qVKql27dqSpIULF6pJkyb673//q4YNG0qSNmzYoOrVq9ts4+zsnGd/ly5dUu/evXO9+LtatWo2497OdhUrVrRZZ7FYlJWVJUlydXXNs67sMZ588kmNGjUqx7rg4OA8t5s0aZLGjRtn/Tr7iAUAAABQVhU6WPyVg4ODXnjhBY0bN06//PKLnJ2dlZiYqPbt2xe4j2bNmmnlypUKDQ2Vo2PBy7nd7f6qcePG+vXXX/XLL7/ketSiWbNmOnz4sDVIFZSzs/MtwxQAAABQ1ph+QN7AgQOt1yGMHz9eY8eO1ZIlS3Ts2DEdOHBA7733npYsWZLn9iNGjND58+c1ePBg7du3T8eOHdPmzZs1bNgwZWZmFvl2f9W+fXv97W9/04ABA7RlyxadOHFCX375pTZt2iRJmjBhgr799luNHDlSsbGxio+P15o1a7h4GwAAALiJqSMWkuTo6KiRI0fqrbfe0okTJ+Tn56fp06fr+PHj8vLyUrNmzfTCCy/kuX1gYKB2796tCRMmqEuXLsrIyFBISIi6desmB4e8c8/tbnezlStXavz48Ro8eLDS09NVu3ZtzZgxQ9KNIxo7d+7Uiy++qHbt2skwDNWqVUuDBg0q+AQBAAAA5UCh7gqF25OWliZPT0/uCgUAAIBSp6B3hTJ9KhQAAAAAECwAAAAAmEawAAAAAGAawQIAAACAaQQLAAAAAKYRLAAAAACYZvo5Fii4H374Qa6urvYuAwAAACgwZ2fnArXjORYlIPs5FqmpqfLw8LB3OQAAAECR41QoAAAAAKYRLAAAAACYRrAAAAAAYBrBAgAAAIBpBAsAAAAAphEsAAAAAJhGsAAAAABgGsECAAAAgGkECwAAAACmESwAAAAAmEawAAAAAGCao70LKA8Mw5AkpaWl2bkSAAAAoPAqV64si8VyyzYEixKQnJwsSQoKCrJzJQAAAEDhpaamysPD45ZtCBYlwMfHR5KUmJgoT09PO1dTvqSlpSkoKEinTp3K94cBRY/5tx/m3r6Yf/th7u2L+bef4p77ypUr59uGYFECHBxuXMri6enJD5mdeHh4MPd2xPzbD3NvX8y//TD39sX82489556LtwEAAACYRrAAAAAAYBrBogQ4Oztr8uTJcnZ2tncp5Q5zb1/Mv/0w9/bF/NsPc29fzL/93AlzbzGy74UKAAAAALeJIxYAAAAATCNYAAAAADCNYAEAAADANIJFMfvPf/6j0NBQubi4qFWrVvr+++/tXVKp980336h3794KDAyUxWLR6tWrbdYbhqFXXnlF1apVk6urqyIjIxUfH2/T5vz58xoyZIg8PDzk5eWlxx57TJcuXSrBvSidpk+frnvuuUeVK1dW1apV1a9fP8XFxdm0+fPPPzVixAj5+vrK3d1dAwYM0JkzZ2zaJCYmqmfPnnJzc1PVqlX13HPP6fr16yW5K6XS3Llz1bhxY+s9ylu3bq0vv/zSup65LzkzZsyQxWLRmDFjrMuY/+IzZcoUWSwWm9ddd91lXc/cF6/ffvtNDz/8sHx9feXq6qpGjRopJibGup7fu8UnNDQ0x3vfYrFoxIgRku7A976BYrNixQrDycnJWLhwofHzzz8b//jHPwwvLy/jzJkz9i6tVNu4caPx4osvGl988YUhyVi1apXN+hkzZhienp7G6tWrjR9//NHo06ePERYWZly5csXaplu3bkaTJk2MvXv3Grt27TJq165tDB48uIT3pPTp2rWrsWjRIuOnn34yYmNjjR49ehjBwcHGpUuXrG2eeuopIygoyNi6dasRExNj3HvvvcZ9991nXX/9+nWjYcOGRmRkpPHDDz8YGzduNKpUqWJMmjTJHrtUqqxdu9bYsGGD8csvvxhxcXHGCy+8YFSsWNH46aefDMNg7kvK999/b4SGhhqNGzc2Ro8ebV3O/BefyZMnGw0aNDCSkpKsrz/++MO6nrkvPufPnzdCQkKMqKgo47vvvjOOHz9ubN682Th69Ki1Db93i8/Zs2dt3vdbtmwxJBnbt283DOPOe+8TLIpRy5YtjREjRli/zszMNAIDA43p06fbsaqy5eZgkZWVZQQEBBgzZ860LktJSTGcnZ2NTz75xDAMwzh8+LAhydi3b5+1zZdffmlYLBbjt99+K7Hay4KzZ88akoydO3cahnFjritWrGh8/vnn1jZHjhwxJBl79uwxDONGMHRwcDBOnz5tbTN37lzDw8PDyMjIKNkdKAO8vb2NDz/8kLkvIRcvXjTq1KljbNmyxWjfvr01WDD/xWvy5MlGkyZNcl3H3BevCRMmGG3bts1zPb93S9bo0aONWrVqGVlZWXfke59ToYrJ1atXtX//fkVGRlqXOTg4KDIyUnv27LFjZWXbiRMndPr0aZt59/T0VKtWrazzvmfPHnl5ealFixbWNpGRkXJwcNB3331X4jWXZqmpqZIkHx8fSdL+/ft17do1m/m/6667FBwcbDP/jRo1kr+/v7VN165dlZaWpp9//rkEqy/dMjMztWLFCqWnp6t169bMfQkZMWKEevbsaTPPEu/9khAfH6/AwEDVrFlTQ4YMUWJioiTmvritXbtWLVq00MCBA1W1alU1bdpUCxYssK7n927JuXr1qj7++GMNHz5cFovljnzvEyyKyblz55SZmWnzjZQkf39/nT592k5VlX3Zc3ureT99+rSqVq1qs97R0VE+Pj58bwohKytLY8aMUZs2bdSwYUNJN+bWyclJXl5eNm1vnv/cvj/Z63Brhw4dkru7u5ydnfXUU09p1apVql+/PnNfAlasWKEDBw5o+vTpOdYx/8WrVatWWrx4sTZt2qS5c+fqxIkTateunS5evMjcF7Pjx49r7ty5qlOnjjZv3qynn35ao0aN0pIlSyTxe7ckrV69WikpKYqKipJ0Z/6741jkPQIoF0aMGKGffvpJ0dHR9i6lXKlXr55iY2OVmpqq//3vfxo6dKh27txp77LKvFOnTmn06NHasmWLXFxc7F1OudO9e3fr/zdu3FitWrVSSEiIPvvsM7m6utqxsrIvKytLLVq00BtvvCFJatq0qX766SfNmzdPQ4cOtXN15ct///tfde/eXYGBgfYuJU8csSgmVapUUYUKFXJcmX/mzBkFBATYqaqyL3tubzXvAQEBOnv2rM3669ev6/z583xvCmjkyJFav369tm/frho1aliXBwQE6OrVq0pJSbFpf/P85/b9yV6HW3NyclLt2rXVvHlzTZ8+XU2aNNHs2bOZ+2K2f/9+nT17Vs2aNZOjo6McHR21c+dOvfvuu3J0dJS/vz/zX4K8vLxUt25dHT16lPd+MatWrZrq169vsyw8PNx6Khq/d0vGyZMn9fXXX+vxxx+3LrsT3/sEi2Li5OSk5s2ba+vWrdZlWVlZ2rp1q1q3bm3Hysq2sLAwBQQE2Mx7WlqavvvuO+u8t27dWikpKdq/f7+1zbZt25SVlaVWrVqVeM2liWEYGjlypFatWqVt27YpLCzMZn3z5s1VsWJFm/mPi4tTYmKizfwfOnTI5pfMli1b5OHhkeOXF/KXlZWljIwM5r6YRURE6NChQ4qNjbW+WrRooSFDhlj/n/kvOZcuXdKxY8dUrVo13vvFrE2bNjluK/7LL78oJCREEr93S8qiRYtUtWpV9ezZ07rsjnzvF/nl4LBasWKF4ezsbCxevNg4fPiw8cQTTxheXl42V+aj8C5evGj88MMPxg8//GBIMv71r38ZP/zwg3Hy5EnDMG7c9s7Ly8tYs2aNcfDgQaNv37653vauadOmxnfffWdER0cbderU4bZ3BfD0008bnp6exo4dO2xuf3f58mVrm6eeesoIDg42tm3bZsTExBitW7c2WrdubV2ffeu7Ll26GLGxscamTZsMPz8/bvtYABMnTjR27txpnDhxwjh48KAxceJEw2KxGF999ZVhGMx9SfvrXaEMg/kvTs8++6yxY8cO48SJE8bu3buNyMhIo0qVKsbZs2cNw2Dui9P3339vODo6Gq+//roRHx9vLFu2zHBzczM+/vhjaxt+7xavzMxMIzg42JgwYUKOdXfae59gUczee+89Izg42HBycjJatmxp7N27194llXrbt283JOV4DR061DCMG7e+e/nllw1/f3/D2dnZiIiIMOLi4mz6SE5ONgYPHmy4u7sbHh4exrBhw4yLFy/aYW9Kl9zmXZKxaNEia5srV64Y//znPw1vb2/Dzc3N6N+/v5GUlGTTT0JCgtG9e3fD1dXVqFKlivHss88a165dK+G9KX2GDx9uhISEGE5OToafn58RERFhDRWGwdyXtJuDBfNffAYNGmRUq1bNcHJyMqpXr24MGjTI5jkKzH3xWrdundGwYUPD2dnZuOuuu4z58+fbrOf3bvHavHmzISnHnBrGnffetxiGYRT9cRAAAAAA5QnXWAAAAAAwjWABAAAAwDSCBQAAAADTCBYAAAAATCNYAAAAADCNYAEAAADANIIFAAAAANMIFgAAAABMI1gAAEqdHTt2yGKxKCUl5ZbtQkNDNWvWrBKpCQDKO4IFAKDYREVFyWKxyGKxyMnJSbVr19arr76q69evm+r3vvvuU1JSkjw9PSVJixcvlpeXV452+/bt0xNPPGFqLABAwTjauwAAQNnWrVs3LVq0SBkZGdq4caNGjBihihUratKkSbfdp5OTkwICAvJt5+fnd9tjAAAKhyMWAIBi5ezsrICAAIWEhOjpp59WZGSk1q5dqwsXLujRRx+Vt7e33Nzc1L17d8XHx1u3O3nypHr37i1vb29VqlRJDRo00MaNGyXZngq1Y8cODRs2TKmpqdajI1OmTJGU81SoxMRE9e3bV+7u7vLw8NADDzygM2fOWNdPmTJFd999t5YuXarQ0FB5enrqwQcf1MWLF0tkrgCgNCNYAABKlKurq65evaqoqCjFxMRo7dq12rNnjwzDUI8ePXTt2jVJ0ogRI5SRkaFvvvlGhw4d0ptvvil3d/cc/d13332aNWuWPDw8lJSUpKSkJI0fPz5Hu6ysLPXt21fnz5/Xzp07tWXLFh0/flyDBg2yaXfs2DGtXr1a69ev1/r167Vz507NmDGjeCYDAMoQToUCAJQIwzC0detWbd68Wd27d9fq1au1e/du3XfffZKkZcuWKSgoSKtXr9bAgQOVmJioAQMGqFGjRpKkmjVr5tqvk5OTPD09ZbFYbnl61NatW3Xo0CGdOHFCQUFBkqSPPvpIDRo00L59+3TPPfdIuhFAFi9erMqVK0uSHnnkEW3dulWvv/56kc0FAJRFHLEAABSr9evXy93dXS4uLurevbsGDRqkqKgoOTo6qlWrVtZ2vr6+qlevno4cOSJJGjVqlF577TW1adNGkydP1sGDB03VceTIEQUFBVlDhSTVr19fXl5e1jGlG6dPZYcKSapWrZrOnj1ramwAKA8IFgCAYtWxY0fFxsYqPj5eV65c0ZIlS2SxWPLd7vHHH9fx48f1yCOP6NChQ2rRooXee++9Yq+3YsWKNl9bLBZlZWUV+7gAUNoRLAAAxapSpUqqXbu2goOD5eh44wzc8PBwXb9+Xd999521XXJysuLi4lS/fn3rsqCgID311FP64osv9Oyzz2rBggW5juHk5KTMzMxb1hEeHq5Tp07p1KlT1mWHDx9WSkqKzZgAgNtDsAAAlLg6deqob9+++sc//qHo6Gj9+OOPevjhh1W9enX17dtXkjRmzBht3rxZJ06c0IEDB7R9+3aFh4fn2l9oaKguXbqkrVu36ty5c7p8+XKONpGRkWrUqJGGDBmiAwcO6Pvvv9ejjz6q9u3bq0WLFsW6vwBQHhAsAAB2sWjRIjVv3ly9evVS69atZRiGNm7caD0VKTMzUyNGjFB4eLi6deumunXr6v3338+1r/vuu09PPfWUBg0aJD8/P7311ls52lgsFq1Zs0be3t7629/+psjISNWsWVOffvppse4nAJQXFsMwDHsXAQAAAKB044gFAAAAANMIFgAAAABMI1gAAAAAMI1gAQAAAMA0ggUAAAAA0wgWAAAAAEwjWAAAAAAwjWABAAAAwDSCBQAAAADTCBYAAAAATCNYAAAAADCNYAEAAADAtP8H2aRpG2NoOmIAAAAASUVORK5CYII=",
      "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": 33,
     "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",
    "    alt_pep_sequence_key=\"peptide_sequence\",\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": 34,
   "id": "fedaba5c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:51:19.833700Z",
     "iopub.status.busy": "2026-08-03T06:51:19.833595Z",
     "iopub.status.idle": "2026-08-03T06:51:20.003969Z",
     "shell.execute_reply": "2026-08-03T06:51:20.003566Z"
    }
   },
   "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": 35,
   "id": "89a8b435",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:51:20.005710Z",
     "iopub.status.busy": "2026-08-03T06:51:20.005622Z",
     "iopub.status.idle": "2026-08-03T06:51:20.018102Z",
     "shell.execute_reply": "2026-08-03T06:51:20.017716Z"
    }
   },
   "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>0.015562</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Q3UTJ2</td>\n",
       "      <td>ASVVEALDSALKDIC(UniMod:4)DQIK</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.619637</td>\n",
       "      <td>0.000343</td>\n",
       "      <td>0.015562</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</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>0.015562</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</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>0.015562</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</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>0.015562</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</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>0.015562</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</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>0.015562</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</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>0.015562</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</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>0.015562</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</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>0.015562</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</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>0.015562</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  ASVVEALDSALKDIC(UniMod:4)DQIK         0.0          0.619637   \n",
       "2      Q3UTJ2                    VGIFPISYVEK         1.0          0.619637   \n",
       "3      Q3UTJ2                    SYSSTLTDLGR         1.0          0.619637   \n",
       "4      Q3UTJ2                      SIFEYEPGK         1.0          0.619637   \n",
       "5      Q3UTJ2                   SFISSSPSSPSR         1.0          0.619637   \n",
       "6      Q3UTJ2                 QGIFPVSYVEVVKR         1.0          0.619637   \n",
       "7      Q3UTJ2                      GLGDQSSSR         1.0          0.619637   \n",
       "8      Q3UTJ2          AQPARPPPPVQPGEIGEAIAK         1.0          0.619637   \n",
       "9      Q3UTJ2           APHYPGIGPVDESGIPTAIR         1.0          0.619637   \n",
       "10     Q3UTJ2                   ADLPGSSSTFTK         1.0          0.619637   \n",
       "\n",
       "    proteoform_score_pval  proteoform_score_pval_adj  is_proteoform  \n",
       "0                0.000343                   0.015562            1.0  \n",
       "1                0.000343                   0.015562            1.0  \n",
       "2                0.000343                   0.015562            1.0  \n",
       "3                0.000343                   0.015562            1.0  \n",
       "4                0.000343                   0.015562            1.0  \n",
       "5                0.000343                   0.015562            1.0  \n",
       "6                0.000343                   0.015562            1.0  \n",
       "7                0.000343                   0.015562            1.0  \n",
       "8                0.000343                   0.015562            1.0  \n",
       "9                0.000343                   0.015562            1.0  \n",
       "10               0.000343                   0.015562            1.0  "
      ]
     },
     "execution_count": 35,
     "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). The blue peptides assigned to proteoform group 0 map to a region previously described as brain-specific and exclusive to neurons."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "27dbceb7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:51:20.019370Z",
     "iopub.status.busy": "2026-08-03T06:51:20.019277Z",
     "iopub.status.idle": "2026-08-03T06:51:20.075666Z",
     "shell.execute_reply": "2026-08-03T06:51:20.075320Z"
    }
   },
   "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": 36,
     "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",
    "    alt_pep_sequence_key=\"peptide_sequence\",\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 58 out of 63 proteoform-containing proteins (92.1%) are expressed in a tissue-specific manner."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "4b851d42",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:51:20.076786Z",
     "iopub.status.busy": "2026-08-03T06:51:20.076702Z",
     "iopub.status.idle": "2026-08-03T06:51:22.798542Z",
     "shell.execute_reply": "2026-08-03T06:51:22.797984Z"
    }
   },
   "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": 38,
   "id": "f8b0ccfa",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:51:22.800423Z",
     "iopub.status.busy": "2026-08-03T06:51:22.800303Z",
     "iopub.status.idle": "2026-08-03T06:51:22.877309Z",
     "shell.execute_reply": "2026-08-03T06:51:22.876875Z"
    }
   },
   "outputs": [],
   "source": [
    "# Retain only significant proteoforms (score >= 0.1, adj. p-value <= 0.1)\n",
    "pf_mask = (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": 39,
   "id": "0a75eabd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:51:22.878867Z",
     "iopub.status.busy": "2026-08-03T06:51:22.878777Z",
     "iopub.status.idle": "2026-08-03T06:51:22.880747Z",
     "shell.execute_reply": "2026-08-03T06:51:22.880513Z"
    }
   },
   "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": 40,
   "id": "696e88c6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:51:22.881657Z",
     "iopub.status.busy": "2026-08-03T06:51:22.881581Z",
     "iopub.status.idle": "2026-08-03T06:51:22.889985Z",
     "shell.execute_reply": "2026-08-03T06:51:22.889682Z"
    }
   },
   "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": 41,
   "id": "a9f07ae1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:51:22.890838Z",
     "iopub.status.busy": "2026-08-03T06:51:22.890747Z",
     "iopub.status.idle": "2026-08-03T06:51:22.898232Z",
     "shell.execute_reply": "2026-08-03T06:51:22.897960Z"
    }
   },
   "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>25.846223</td>\n",
       "      <td>5.018276e-10</td>\n",
       "      <td>14.604930</td>\n",
       "      <td>16.265425</td>\n",
       "      <td>12.130302</td>\n",
       "      <td>14.243520</td>\n",
       "      <td>11.643799</td>\n",
       "      <td>6.323028e-08</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>280.923208</td>\n",
       "      <td>4.532385e-26</td>\n",
       "      <td>17.073096</td>\n",
       "      <td>16.195556</td>\n",
       "      <td>16.293561</td>\n",
       "      <td>19.305650</td>\n",
       "      <td>16.558551</td>\n",
       "      <td>5.710805e-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>2.366386e-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>179.779144</td>\n",
       "      <td>8.197678e-23</td>\n",
       "      <td>16.042224</td>\n",
       "      <td>19.217817</td>\n",
       "      <td>18.051066</td>\n",
       "      <td>15.596972</td>\n",
       "      <td>16.924093</td>\n",
       "      <td>1.032907e-20</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>2.442993e-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>121</th>\n",
       "      <td>Q9QZ47_1</td>\n",
       "      <td>anova_oneway</td>\n",
       "      <td>tissue</td>\n",
       "      <td>all</td>\n",
       "      <td>91.893665</td>\n",
       "      <td>4.637443e-18</td>\n",
       "      <td>15.004601</td>\n",
       "      <td>15.819740</td>\n",
       "      <td>14.530142</td>\n",
       "      <td>14.795794</td>\n",
       "      <td>19.128501</td>\n",
       "      <td>5.843178e-16</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</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>1.350292e-14</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</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>1.543210e-19</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>Q9Z2Z6_0</td>\n",
       "      <td>anova_oneway</td>\n",
       "      <td>tissue</td>\n",
       "      <td>all</td>\n",
       "      <td>15.374666</td>\n",
       "      <td>2.380911e-07</td>\n",
       "      <td>13.995002</td>\n",
       "      <td>14.484431</td>\n",
       "      <td>13.383277</td>\n",
       "      <td>13.692943</td>\n",
       "      <td>12.821110</td>\n",
       "      <td>2.999948e-05</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>Q9Z2Z6_1</td>\n",
       "      <td>anova_oneway</td>\n",
       "      <td>tissue</td>\n",
       "      <td>all</td>\n",
       "      <td>112.326552</td>\n",
       "      <td>1.853570e-19</td>\n",
       "      <td>16.554941</td>\n",
       "      <td>19.275779</td>\n",
       "      <td>18.310678</td>\n",
       "      <td>18.047013</td>\n",
       "      <td>16.098757</td>\n",
       "      <td>2.335499e-17</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>126 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   25.846223  5.018276e-10   \n",
       "1        O08601_1  anova_oneway   tissue    all  280.923208  4.532385e-26   \n",
       "2        O54724_0  anova_oneway   tissue    all   12.603239  1.878084e-06   \n",
       "3        O54724_1  anova_oneway   tissue    all  179.779144  8.197678e-23   \n",
       "4        O54749_0  anova_oneway   tissue    all    5.288221  1.938883e-03   \n",
       "..            ...           ...      ...    ...         ...           ...   \n",
       "121      Q9QZ47_1  anova_oneway   tissue    all   91.893665  4.637443e-18   \n",
       "122      Q9Z204_0  anova_oneway   tissue    all   75.275766  1.071660e-16   \n",
       "123      Q9Z204_1  anova_oneway   tissue    all  152.715690  1.224770e-21   \n",
       "124      Q9Z2Z6_0  anova_oneway   tissue    all   15.374666  2.380911e-07   \n",
       "125      Q9Z2Z6_1  anova_oneway   tissue    all  112.326552  1.853570e-19   \n",
       "\n",
       "     mean_Brain   mean_BAT  mean_Heart  mean_Liver  mean_Quad      pval_adj  \\\n",
       "0     14.604930  16.265425   12.130302   14.243520  11.643799  6.323028e-08   \n",
       "1     17.073096  16.195556   16.293561   19.305650  16.558551  5.710805e-24   \n",
       "2     15.879478  13.639894    8.489357   10.545068  11.828292  2.366386e-04   \n",
       "3     16.042224  19.217817   18.051066   15.596972  16.924093  1.032907e-20   \n",
       "4     13.162980  12.879554   14.428646   13.568651  13.071253  2.442993e-01   \n",
       "..          ...        ...         ...         ...        ...           ...   \n",
       "121   15.004601  15.819740   14.530142   14.795794  19.128501  5.843178e-16   \n",
       "122   16.117296  12.403909   12.737527   13.374945  12.716591  1.350292e-14   \n",
       "123   15.790335  14.611674   13.502690   16.977432  13.218752  1.543210e-19   \n",
       "124   13.995002  14.484431   13.383277   13.692943  12.821110  2.999948e-05   \n",
       "125   16.554941  19.275779   18.310678   18.047013  16.098757  2.335499e-17   \n",
       "\n",
       "     is_diff_abundant  \n",
       "0                True  \n",
       "1                True  \n",
       "2                True  \n",
       "3                True  \n",
       "4               False  \n",
       "..                ...  \n",
       "121              True  \n",
       "122              True  \n",
       "123              True  \n",
       "124              True  \n",
       "125              True  \n",
       "\n",
       "[126 rows x 13 columns]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "anova_results = pr.get.differential_abundance_df(\n",
    "    adata_pfs, keys=\"anova_oneway;tissue;all\"\n",
    ")\n",
    "anova_results.rename(columns={\"var_id\": \"proteoform_id\"}, inplace=True)\n",
    "anova_results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "888c78b1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:51:22.899080Z",
     "iopub.status.busy": "2026-08-03T06:51:22.898998Z",
     "iopub.status.idle": "2026-08-03T06:51:22.904178Z",
     "shell.execute_reply": "2026-08-03T06:51:22.903919Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "58 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(\n",
    "    \"protein_id\"\n",
    ")[\"protein_id_old\"]\n",
    "anova_results[\"protein_id\"] = anova_results[\"proteoform_id\"].map(\n",
    "    protein_id_map\n",
    ")\n",
    "n_tissue_specific_pfs = (\n",
    "    anova_results.groupby(\"protein_id\")[\"is_diff_abundant\"].all().sum()\n",
    ")\n",
    "\n",
    "print(\n",
    "    f\"{n_tissue_specific_pfs} tissue-specific proteoform groups found via ANOVA.\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ae40c32",
   "metadata": {},
   "source": [
    "## Summary\n",
    "\n",
    "This notebook reproduced the proteoform inference workflow of Bludau et al. (2021) with ProteoPy:\n",
    "\n",
    "- **Proteoform detection**: COPF called **63** proteins as carrying multiple proteoform groups - the same count and the **same 63 accessions** as the paper, checked above: 0 missed, 0 false positives.\n",
    "- **Biological verification**: the tissue-specific 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 recovered 58 tissue-specific proteoform groups (92.1 %), against the 56 (88.9 %) reported by Bludau et al.\n",
    "\n",
    "Underneath all of this, ProteoPy's COPF implementation is tested directly against the original R implementation's intermediate outputs on this dataset — pairwise correlations, dendrograms, cluster assignments and proteoform scores — agreeing to between 1e-14 and 1e-12. That is what lets this notebook treat the peptide set as the only thing it needs to get right."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "3a899aff",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-03T06:51:22.904983Z",
     "iopub.status.busy": "2026-08-03T06:51:22.904911Z",
     "iopub.status.idle": "2026-08-03T06:51:23.341181Z",
     "shell.execute_reply": "2026-08-03T06:51:23.340396Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "adjustText==1.3.0\r\n",
      "alabaster==1.0.0\r\n",
      "anndata==0.11.4\r\n",
      "anyio==4.14.2\r\n",
      "argon2-cffi==25.1.0\r\n",
      "argon2-cffi-bindings==25.1.0\r\n",
      "array-api-compat==1.15.0\r\n",
      "arrow==1.4.0\r\n",
      "asttokens==3.0.2\r\n",
      "async-lru==2.3.0\r\n",
      "attrs==26.1.0\r\n",
      "babel==2.18.0\r\n",
      "beautifulsoup4==4.15.0\r\n",
      "biopython==1.86\r\n",
      "bleach==6.4.0\r\n",
      "certifi==2026.7.22\r\n",
      "cffi==2.1.0\r\n",
      "charset-normalizer==3.4.9\r\n",
      "comm==0.2.3\r\n",
      "contourpy==1.3.2\r\n",
      "coverage==7.15.2\r\n",
      "cycler==0.12.1\r\n",
      "debugpy==1.8.21\r\n",
      "decorator==5.3.1\r\n",
      "defusedxml==0.7.1\r\n",
      "docutils==0.21.2\r\n",
      "et_xmlfile==2.0.0\r\n",
      "exceptiongroup==1.3.1\r\n",
      "executing==2.2.1\r\n",
      "fastjsonschema==2.22.1\r\n",
      "flake8==7.3.0\r\n",
      "fonttools==4.63.0\r\n",
      "fqdn==1.5.1\r\n",
      "h11==0.16.0\r\n",
      "h5py==3.16.0\r\n",
      "httpcore==1.0.9\r\n",
      "httpx==0.28.1\r\n",
      "idna==3.18\r\n",
      "igraph==1.0.0\r\n",
      "imagesize==2.0.0\r\n",
      "iniconfig==2.3.0\r\n",
      "ipykernel==7.2.0\r\n",
      "ipython==8.39.0\r\n",
      "isoduration==20.11.0\r\n",
      "jedi==0.20.0\r\n",
      "Jinja2==3.1.6\r\n",
      "joblib==1.5.3\r\n",
      "json5==0.15.0\r\n",
      "jsonpointer==3.1.1\r\n",
      "jsonschema==4.26.0\r\n",
      "jsonschema-specifications==2025.9.1\r\n",
      "jupyter-events==0.12.1\r\n",
      "jupyter-lsp==2.3.1\r\n",
      "jupyter_client==8.9.1\r\n",
      "jupyter_core==5.9.1\r\n",
      "jupyter_server==2.20.0\r\n",
      "jupyter_server_terminals==0.5.4\r\n",
      "jupyterlab==4.5.6\r\n",
      "jupyterlab_pygments==0.3.0\r\n",
      "jupyterlab_server==2.28.0\r\n",
      "kiwisolver==1.5.0\r\n",
      "lark==1.3.1\r\n",
      "latexcodec==3.0.1\r\n",
      "legacy-api-wrap==1.5\r\n",
      "llvmlite==0.46.0\r\n",
      "markdown-it-py==3.0.0\r\n",
      "MarkupSafe==3.0.3\r\n",
      "matplotlib==3.10.8\r\n",
      "matplotlib-inline==0.2.2\r\n",
      "mccabe==0.7.0\r\n",
      "mdit-py-plugins==0.6.1\r\n",
      "mdurl==0.1.2\r\n",
      "mistune==3.3.4\r\n",
      "myst-parser==4.0.1\r\n",
      "natsort==8.4.0\r\n",
      "nbclient==0.11.0\r\n",
      "nbconvert==7.17.1\r\n",
      "nbformat==5.10.4\r\n",
      "nbsphinx==0.9.8\r\n",
      "nest-asyncio==1.6.0\r\n",
      "networkx==3.4.2\r\n",
      "notebook_shim==0.2.4\r\n",
      "numba==0.64.0\r\n",
      "numpy==2.2.6\r\n",
      "numpydoc==1.10.0\r\n",
      "openpyxl==3.1.5\r\n",
      "overrides==7.7.0\r\n",
      "packaging @ file:///home/conda/feedstock_root/build_artifacts/bld/rattler-build_packaging_1777103621/work\r\n",
      "pandas==2.3.3\r\n",
      "pandoc==2.4\r\n",
      "pandocfilters==1.5.1\r\n",
      "parso==0.8.7\r\n",
      "patsy==1.0.2\r\n",
      "pexpect==4.9.0\r\n",
      "pillow==12.3.0\r\n",
      "platformdirs==4.11.0\r\n",
      "pluggy==1.6.0\r\n",
      "plumbum==2.0.2\r\n",
      "ply==3.11\r\n",
      "pooch==1.9.0\r\n",
      "prometheus_client==0.26.0\r\n",
      "prompt_toolkit==3.0.53\r\n",
      "-e git+https://github.com/UKHD-NP/proteopy.git@cbec4335d4607bcc0eb0a3b4b6341ca916325fb6#egg=proteopy\r\n",
      "psutil==7.2.2\r\n",
      "ptyprocess==0.7.0\r\n",
      "pure_eval==0.2.3\r\n",
      "pyarrow==23.0.1\r\n",
      "pybtex==0.26.1\r\n",
      "pybtex-docutils==1.0.3\r\n",
      "pycodestyle==2.14.0\r\n",
      "pycparser==3.0\r\n",
      "pyflakes==3.4.0\r\n",
      "Pygments==2.20.0\r\n",
      "pynndescent==0.6.0\r\n",
      "pyparsing==3.3.2\r\n",
      "pytest==9.1.1\r\n",
      "pytest-cov==7.1.0\r\n",
      "python-dateutil==2.9.0.post0\r\n",
      "python-json-logger==4.1.0\r\n",
      "pytz==2026.3.post1\r\n",
      "PyYAML==6.0.3\r\n",
      "pyzmq==27.1.0\r\n",
      "referencing==0.37.0\r\n",
      "requests==2.34.2\r\n",
      "rfc3339-validator==0.1.4\r\n",
      "rfc3986-validator==0.1.1\r\n",
      "rfc3987-syntax==1.1.0\r\n",
      "rpds-py==0.30.0\r\n",
      "scanpy==1.11.5\r\n",
      "scikit-learn==1.7.2\r\n",
      "scipy==1.15.3\r\n",
      "seaborn==0.13.2\r\n",
      "Send2Trash==2.1.0\r\n",
      "session-info2==0.4.1\r\n",
      "six==1.17.0\r\n",
      "snowballstemmer==3.1.1\r\n",
      "soupsieve==2.9.1\r\n",
      "Sphinx==8.1.3\r\n",
      "sphinx-autodoc-typehints==3.0.1\r\n",
      "sphinx-copybutton==0.5.2\r\n",
      "sphinx_design==0.6.1\r\n",
      "sphinx_rtd_theme==3.1.0\r\n",
      "sphinxcontrib-applehelp==2.0.0\r\n",
      "sphinxcontrib-bibtex==2.7.0\r\n",
      "sphinxcontrib-devhelp==2.0.0\r\n",
      "sphinxcontrib-htmlhelp==2.1.0\r\n",
      "sphinxcontrib-jquery==4.1\r\n",
      "sphinxcontrib-jsmath==1.0.1\r\n",
      "sphinxcontrib-qthelp==2.0.0\r\n",
      "sphinxcontrib-serializinghtml==2.0.0\r\n",
      "stack-data==0.6.3\r\n",
      "statsmodels==0.14.6\r\n",
      "terminado==0.18.1\r\n",
      "texttable==1.7.0\r\n",
      "threadpoolctl==3.6.0\r\n",
      "tinycss2==1.5.1\r\n",
      "tomli==2.4.1\r\n",
      "tornado==6.5.7\r\n",
      "tqdm==4.70.0\r\n",
      "traitlets==5.16.0\r\n",
      "typing_extensions==4.16.0\r\n",
      "tzdata==2026.3\r\n",
      "umap-learn==0.5.12\r\n",
      "uri-template==1.3.0\r\n",
      "urllib3==2.7.0\r\n",
      "wcwidth==0.8.2\r\n",
      "webcolors==25.10.0\r\n",
      "webencodings==0.5.1\r\n",
      "websocket-client==1.9.0\r\n"
     ]
    }
   ],
   "source": [
    "!pip freeze"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3.10 (proteoform-repro exp_04/05)",
   "language": "python",
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
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