14-RBMY.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Install the PGR-TK package"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If neccessary, install the package into your python environment. For example,\n",
    "```\n",
    "pip install --force /code/pgrtk-0.3.3-cp38-cp38-linux_x86_64.whl\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pgrtk\n",
    "import os\n",
    "import matplotlib.pyplot as plt\n",
    "from IPython.display import SVG\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'pgrtk 0.3.3 (v0.3.3_dev:675e3c7, release build, linux [x86_64] [rustc 1.62.0 (a8314ef7d 2022-06-27)])'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pgrtk.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "os.chdir(\"/results\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Lazy load the the AGCfile for fetching sequences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "ref_db =pgrtk.AGCFile(\"/data/pgr-tk-HGRP-y1-evaluation-set-v0.agc\") # lazy load an agc file of the reference without any SHIMMER index \n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load the index into memory\n",
    "The loads the index into the memory. It takes about one minute."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 19 s, sys: 1min 1s, total: 1min 20s\n",
      "Wall time: 36.9 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "sdb = pgrtk.SeqIndexDB()\n",
    "sdb.load_from_agc_index(\"/data/pgr-tk-HGRP-y1-evaluation-set-v0\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "We can see the specification about how SHIMMERs are computed using the `get_shmmr_spec()` method. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(80, 56, 4, 64, False)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sdb.get_shmmr_spec() # window_size, k_mer_size, hieraical_reduction_factor, min_span, use_k_mer_sketch_other_than_minimizer"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Query the database with the sequence of the region"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "207\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(0.0, 4922553.0)"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ref_file_name, roi_chr, roi_b, roi_e = 'hg38_tagged.fa', 'chrY_hg38', 21311161, 26133714\n",
    "#ref_file_name, roi_chr, roi_b, roi_e = 'hg38_tagged.fa', 'chrY_hg38', 21311161, 21311161 + 1600000\n",
    "\n",
    "padding = 50000\n",
    "roi_len = roi_e - roi_b\n",
    "#get a segment of a reference\n",
    "roi_seq = ref_db.get_sub_seq(ref_file_name, roi_chr, roi_b-padding, roi_e+padding)\n",
    "x, y = pgrtk.get_shmmr_dots(roi_seq, roi_seq, 32, 32, 5, 2)\n",
    "plt.plot(x, y, \".\", markersize=0.5)\n",
    "print(x[0])\n",
    "plt.xlim(0,len(roi_seq))\n",
    "plt.ylim(0,len(roi_seq))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The number of hits is 190\n",
      "The total aligned regions is 264\n"
     ]
    }
   ],
   "source": [
    "#find hits in the pangenomic reference\n",
    "aln_range = pgrtk.query_sdb(sdb, roi_seq, merge_range_tol=1000000)\n",
    "\n",
    "print(\"The number of hits is\", len(aln_range))\n",
    "\n",
    "count = 0\n",
    "for sid, rgns in aln_range.items():\n",
    "    count += len(rgns)\n",
    "\n",
    "print(\"The total aligned regions is\", count)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can examine, the target region sizes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [],
   "source": [
    "rgn_lengths = []\n",
    "for k in list(aln_range.keys()):\n",
    "    b, e = aln_range[k][0][0:2]\n",
    "    #print(sdb.seq_info[k], \"target region\", b, \"-\", e, \"len:\", e-b )\n",
    "    rgn_lengths.append(e-b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'count')"
      ]
     },
     "execution_count": 152,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(rgn_lengths, bins=32);\n",
    "plt.xlabel(\"ROI region size\")\n",
    "plt.ylabel(\"count\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Some mapped regions are larger, let's check the repeat / CNV by quick dot plots. We label the region of the ROI by two vertical grey lines. We observe that there are different number of intersections (~different copy number) of the region the \"dots\" due to the different repeat structures."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1728x1728 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "seq_list = []\n",
    "i = 1\n",
    "plt.figure(figsize=(24, 24))\n",
    "for k in list(aln_range.keys()):\n",
    "    ctg_name, source, _ = sdb.seq_info[k]\n",
    "    seq_id = k\n",
    "    rgns = aln_range[k].copy()\n",
    "\n",
    "    rgns = pgrtk.merge_regions(rgns, tol=1000)\n",
    "\n",
    "    for rgn in rgns:\n",
    "        b, e, length, orientation, aln = rgn\n",
    "        aln.sort()\n",
    "  \n",
    "        if aln[0][0][0] > padding or aln[-1][0][1] < padding + roi_len:\n",
    "            continue\n",
    "        \n",
    "        #for illustration purpose, we only plot with the sequnce spanned through the whole region\n",
    "\n",
    "        #if e-b < 0.75 * (roi_len + 2 * padding):             \n",
    "        #    continue\n",
    "\n",
    "        seq =  sdb.get_sub_seq(source, ctg_name, b, e)\n",
    "  \n",
    "        if orientation == 1:\n",
    "            seq = pgrtk.rc_byte_seq(seq)\n",
    "\n",
    "        seq_list.append((\"{}_{}_{}_{}\".format(ctg_name, b, e, orientation), seq))\n",
    "        x, y = pgrtk.get_shmmr_dots(roi_seq, seq, 128, 32, 6, 1)\n",
    "        \n",
    "        if len(y) == 0:\n",
    "            continue\n",
    "        if i <= 36:\n",
    "            plt.subplot(6,6,i)\n",
    "            plt.plot(x, y, \".\", markersize=0.1)\n",
    "            plt.plot([padding, padding],[0, max(y)], color='grey')\n",
    "            plt.plot([padding+roi_len, padding+roi_len],[0, max(y)], color='grey')\n",
    "        i += 1\n",
    "        \n",
    "        \n",
    "        \n",
    "        "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create a new shimmer database for the detailed study"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [],
   "source": [
    "seq_list = []\n",
    "seq_info = sdb.seq_info.copy()\n",
    "i = 0\n",
    "for k in list(aln_range.keys()):\n",
    "    ctg_name, source, _ = seq_info[k]\n",
    "    seq_id = k\n",
    "    rgns = aln_range[k].copy()\n",
    "    \n",
    "    rgns = pgrtk.merge_regions(rgns,tol=1000)\n",
    "\n",
    "    for rgn in rgns:\n",
    "        b, e, length, orientation, aln = rgn\n",
    "        \n",
    "        #for illustration purpose, we only plot with the sequnce spanned through the whole region\n",
    "\n",
    "        if e-b < 0.75 * (roi_len + 2 * padding):             \n",
    "            continue\n",
    "            \n",
    "        seq =  sdb.get_sub_seq(source, ctg_name, b, e)\n",
    "        if orientation == 1:\n",
    "            seq = pgrtk.rc_byte_seq(seq)\n",
    "  \n",
    "        seq_list.append((\"{}_{}_{}_{}\".format(ctg_name, b, e, orientation), seq))\n",
    "        \n",
    "        i += 1\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a shimmer indext database with smaller window (denser shimmers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_sdb = pgrtk.SeqIndexDB() \n",
    "new_sdb.load_from_seq_list(seq_list, w=128, k=56, r=12, min_span=28)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 156,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(new_sdb.seq_info)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The number of hits is 4\n",
      "The total aligned regions is 4\n"
     ]
    }
   ],
   "source": [
    "#find hits in the pangenomic reference\n",
    "aln_range0 = pgrtk.query_sdb(new_sdb, roi_seq, merge_range_tol=300000)\n",
    "\n",
    "aln_range = aln_range0\n",
    "\n",
    "print(\"The number of hits is\", len(aln_range))\n",
    "\n",
    "count = 0\n",
    "for sid, rgns in aln_range.items():\n",
    "    count += len(rgns)\n",
    "\n",
    "print(\"The total aligned regions is\", count)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's loop through the hits (contigs that has alignments) and see the number of \"copies\"."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [],
   "source": [
    "from collections import Counter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "number of copy: 1, number of haplotypes: 4\n"
     ]
    }
   ],
   "source": [
    "n_copy = {}\n",
    "for k in list(aln_range.keys()):\n",
    "    n_copy[k] = len(aln_range[k])\n",
    "copy_count = Counter(n_copy.values())\n",
    "for nc, nh in copy_count.items():\n",
    "    print(\"number of copy: {}, number of haplotypes: {}\".format(nc, nh))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'count')"
      ]
     },
     "execution_count": 160,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rgn_lengths = []\n",
    "for k in list(aln_range.keys()):\n",
    "    for sid, rgns in aln_range.items():\n",
    "        for rgn in rgns:\n",
    "            b, e = rgn[0:2]\n",
    "            #print(seq_index[k], \"target region\", b, \"-\", e, \"len:\", e-b )\n",
    "            rgn_lengths.append(e-b)\n",
    "plt.hist(rgn_lengths, bins=32);\n",
    "plt.xlabel(\"ROI size\")\n",
    "plt.ylabel(\"count\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [],
   "source": [
    "f0 = open(\"/results/ROI_seq.fa\", \"w\")\n",
    "for ctg, seq in seq_list:\n",
    "    \n",
    "    print(\">{}\".format(ctg), file=f0)\n",
    "    print(pgrtk.u8_to_string(seq), file=f0)\n",
    "       \n",
    "f0.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on built-in function generate_mapg_gfa:\n",
      "\n",
      "generate_mapg_gfa(...) method of builtins.SeqIndexDB instance\n",
      "    Convert the adjecent list of the shimmer graph shimmer_pair -> GFA\n",
      "    \n",
      "    Parameters\n",
      "    ----------\n",
      "    min_count : int\n",
      "        the minimum number of times a pair of shimmers must be observed to be included in the graph\n",
      "    \n",
      "    filenpath : string\n",
      "        the path to the output file\n",
      "    \n",
      "    Returns\n",
      "    -------\n",
      "    \n",
      "    None\n",
      "        The data is written into the file at filepath\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(new_sdb.generate_mapg_gfa)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_sdb = pgrtk.SeqIndexDB() \n",
    "new_sdb.load_from_seq_list(seq_list, w=128, k=56, r=12, min_span=28)\n",
    "new_sdb.generate_mapg_gfa(0, \"/results/ROI_80_56_6.gfa\")\n",
    "\n",
    "new_sdb = pgrtk.SeqIndexDB() \n",
    "new_sdb.load_from_seq_list(seq_list, w=128, k=56, r=2, min_span=28)\n",
    "new_sdb.generate_mapg_gfa(0, \"/results/ROI_80_56_2.gfa\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Construct the genome graphs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [],
   "source": [
    "import networkx as nx\n",
    "from networkx.drawing import nx_pydot "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_graph(seq_list, w=128, k=56, r=4, min_span=28, highlite=0):\n",
    "    new_sdb = pgrtk.SeqIndexDB() \n",
    "    new_sdb.load_from_seq_list(seq_list, w=w, k=k, r=r, min_span=min_span)\n",
    "    new_sdb.generate_mapg_gfa(0, f\"/results/{name}-{w}-{k}-{r}.gfa\")\n",
    "    sid_to_path = {}\n",
    "    spl=new_sdb.get_shmmr_pair_list()\n",
    "    for (k0, k1, sid, p0, p1, o) in spl:\n",
    "        sid_to_path.setdefault(sid,[])\n",
    "        sid_to_path[sid].append((p0, p1, o, k0, k1))\n",
    "    G = nx.DiGraph()\n",
    "    m = new_sdb.get_shmmr_map()\n",
    "    for sid, path in sid_to_path.items():\n",
    "        #print(sid)\n",
    "        path.sort()\n",
    "        v = path[0]\n",
    "        #if sid != 45:\n",
    "        #    continue\n",
    "        for w in path[1:]:\n",
    "            v = tuple(v[-2:])\n",
    "            w = tuple(w[-2:])\n",
    "            color = \"yellow\"\n",
    "            penwidth =  2 + 0.1 * (len(m[v]) * len(m[w])) ** 0.5\n",
    "            G.add_edge(v, w, penwidth = penwidth, color=\"orange\" )\n",
    "            G.add_edge(w, v, penwidth = penwidth, color=\"orange\" )\n",
    "            G.add_node(v, fillcolor=color, style=\"filled\")\n",
    "            #G.add_node(w, size =  len(m[v]))\n",
    "            v = w\n",
    "            \n",
    "    node_to_sid = {}\n",
    "    for v in G.nodes():\n",
    "        node_to_sid.setdefault(v, {})\n",
    "        for sid, path in sid_to_path.items():\n",
    "            node_to_sid[v][sid] = 0\n",
    "            \n",
    "     \n",
    "    for sid, path in sid_to_path.items():\n",
    "        #print(sid)\n",
    "        path.sort()\n",
    "        for v in path:\n",
    "            v = tuple(v[-2:])\n",
    "            node_to_sid[v][sid] = 1\n",
    "    #nx.set_node_attributes(G, node_to_sid)  \n",
    "    return G\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_graph2(seq_list, w=128, k=56, r=4, min_span=28, highlite=0):\n",
    "    new_sdb = pgrtk.SeqIndexDB() \n",
    "    new_sdb.load_from_seq_list(seq_list, w=w, k=k, r=r, min_span=min_span)\n",
    "    new_sdb.generate_mapg_gfa(0, f\"/results/{name}-{w}-{k}-{r}.gfa\")\n",
    "    sid_to_path = {}\n",
    "    spl=new_sdb.get_shmmr_pair_list()\n",
    "    for (k0, k1, sid, p0, p1, o) in spl:\n",
    "        sid_to_path.setdefault(sid,[])\n",
    "        sid_to_path[sid].append((p0, p1, o, k0, k1))\n",
    "    G = nx.DiGraph()\n",
    "    m = new_sdb.get_shmmr_map()\n",
    "    for sid, path in sid_to_path.items():\n",
    "        #print(sid)\n",
    "        path.sort()\n",
    "        v = path[0]\n",
    "        #if sid != 45:\n",
    "        #    continue\n",
    "        for w in path[1:]:\n",
    "            v = tuple(v[-2:])\n",
    "            w = tuple(w[-2:])\n",
    "            color = \"yellow\"\n",
    "            penwidth =  1 + 0.02 * (len(m[v]) * len(m[w])) ** 0.5\n",
    "            G.add_edge(v, w, penwidth = penwidth, color=\"orange\" )\n",
    "            G.add_edge(w, v, penwidth = penwidth, color=\"orange\" )\n",
    "            G.add_node(v, fillcolor=color, style=\"filled\")\n",
    "            #G.add_node(w, size =  len(m[v]))\n",
    "            v = w\n",
    "            \n",
    "    for sid, path in sid_to_path.items():\n",
    "        #print(sid)\n",
    "        path.sort()\n",
    "        v = path[0]\n",
    "        if sid != highlite:\n",
    "            continue\n",
    "        for w in path[1:]:\n",
    "            v = tuple(v[-2:])\n",
    "            w = tuple(w[-2:])\n",
    "            color = \"blue\"\n",
    "            penwidth =  1 + 0.02 * (len(m[v]) * len(m[w])) ** 0.5\n",
    "            G.add_node(v, fillcolor=color, style=\"filled\")\n",
    "            G.add_edge(v, w, penwidth = penwidth, color=color )\n",
    "            G.add_edge(w, v, penwidth = penwidth, color=color )\n",
    "            v = w\n",
    "    return G\n",
    "    "
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "for r in (12,4):\n",
    "    w=80; k=56;\n",
    "    name=\"ROI\"\n",
    "    G = get_graph2(seq_list, w=w, k=k, r=r, highlite=0)\n",
    "    \n",
    "    #nx.write_gexf(G, f\"/results/{name}-{w}-{k}-{r}.gexf\")\n",
    "    nx_pydot.write_dot(G, f\"{name}-{w}-{k}-{r}.dot\")\n",
    "    ## for this version of graphviz, we need to create PDF to get the bounding box right\n",
    "    os.system(f\"\"\"neato -Tpdf {name}-{w}-{k}-{r}.dot -x -Grankdir=LR -Gsize=64,64 \\\n",
    "    -Nfixedsize=true -Nwidth=.5 -Nheight=.5 -Nlabel=\"\" > {name}-{w}-{k}-{r}.pdf\"\"\")\n",
    "    os.system(f\"\"\"pdf2svg {name}-{w}-{k}-{r}.pdf {name}-{w}-{k}-{r}.svg\"\"\")"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "for ht in range(0,12):\n",
    "    w=80; k=56; r=6;\n",
    "    name=\"ROI\"\n",
    "    G = get_graph2(seq_list, w=w, k=k, r=r, highlite=ht)\n",
    "    \n",
    "    #nx.write_gexf(G, f\"/results/{name}-{w}-{k}-{r}.gexf\")\n",
    "    nx_pydot.write_dot(G, f\"{name}-{w}-{k}-{r}-h{ht}.dot\")\n",
    "    ## for this version of graphviz, we need to create PDF to get the bounding box right\n",
    "    os.system(f\"\"\"neato -Tpdf {name}-{w}-{k}-{r}-h{ht}.dot -x -Grankdir=LR -Gsize=64,64 \\\n",
    "    -Nfixedsize=true -Nwidth=.5 -Nheight=.5 -Nlabel=\"\" > {name}-{w}-{k}-{r}-h{ht}.pdf\"\"\")\n",
    "    os.system(f\"\"\"pdf2svg {name}-{w}-{k}-{r}-h{ht}.pdf {name}-{w}-{k}-{r}-h{ht}.svg\"\"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Generate Repeat Pattern Using the Principal Bundles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 167,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(seq_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [],
   "source": [
    "shmmrspec = {\"w\": 80, \"k\":56, \"r\":4, \"min_span\":28 }\n",
    "new_sdb = pgrtk.SeqIndexDB() \n",
    "new_sdb.load_from_seq_list(seq_list, \n",
    "                           w = shmmrspec[\"w\"], \n",
    "                           k = shmmrspec[\"k\"], \n",
    "                           r = shmmrspec[\"r\"], \n",
    "                           min_span = shmmrspec[\"min_span\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "90\n"
     ]
    }
   ],
   "source": [
    "principal_bundles, sid_smps = new_sdb.get_principal_bundle_decomposition(0,8)\n",
    "sid_smps = dict(sid_smps)\n",
    "sid_to_smps = sid_smps # just an alias\n",
    "print(len(principal_bundles))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from matplotlib import cm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colors.LinearSegmentedColormap at 0x7ff72bd1dc40>"
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cmap=plt.get_cmap(\"nipy_spectral\")\n",
    "cmap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 0  7 14 21 28 35 42 49 56 63 70 77 84  1  8 15 22 29 36 43 50 57 64 71\n",
      " 78 85  2  9 16 23 30 37 44 51 58 65 72 79 86  3 10 17 24 31 38 45 52 59\n",
      " 66 73 80 87  4 11 18 25 32 39 46 53 60 67 74 81 88  5 12 19 26 33 40 47\n",
      " 54 61 68 75 82 89  6 13 20 27 34 41 48 55 62 69 76 83]\n"
     ]
    }
   ],
   "source": [
    "lpb = len(principal_bundles)\n",
    "color_theme0 = cmap(np.linspace(0.1, 0.9, lpb))\n",
    "#pseudo-randomize the colors\n",
    "idx = np.array([_ * (8011 * 97) for _ in range(lpb)]) % lpb\n",
    "print(idx)\n",
    "color_theme = color_theme0[idx]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib.colors import to_hex as to_hex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_sdb.generate_principal_mapg_gfa(0, 8, \"/results/RBMY_principal.gfa\")\n",
    "\n",
    "v_to_name = {}\n",
    "v_to_bundle_id = {}\n",
    "with open(\"/results/RBMY_principal.gfa\") as f:\n",
    "    for r in f:\n",
    "        r = r.strip().split(\"\\t\")\n",
    "        if r[0] != \"S\":\n",
    "            continue\n",
    "        n = r[1]\n",
    "        v = r[4].split(\":\")[-1]\n",
    "        v_to_name[v] = n\n",
    "\n",
    "f = open(\"/results/RBMY_principal_color.csv\", \"w\")\n",
    "print(\"Name,Color,Bundle_ID\", file=f)\n",
    "for bundle in principal_bundles:\n",
    "    bundle_id = bundle[0]\n",
    "    for v in bundle[2]:\n",
    "        vertex = tuple(v[:2])\n",
    "        color = to_hex(color_theme[bundle_id])\n",
    "  \n",
    "        print(v_to_name[\"{:016x}_{:016x}\".format(*vertex)], color, bundle_id, file=f, sep=\",\")\n",
    "f.close()\n",
    "\n",
    "\n",
    "new_sdb.generate_mapg_gfa(0, \"/results/RBMY.gfa\")\n",
    "\n",
    "v_to_name = {}\n",
    "v_to_bundle_id = {}\n",
    "with open(\"/results/RBMY.gfa\") as f:\n",
    "    for r in f:\n",
    "        r = r.strip().split(\"\\t\")\n",
    "        if r[0] != \"S\":\n",
    "            continue\n",
    "        n = r[1]\n",
    "        v = r[4].split(\":\")[-1]\n",
    "        v_to_name[v] = n\n",
    "\n",
    "f = open(\"/results/RBMY_color.csv\", \"w\")\n",
    "print(\"Name,Color,Bundle_ID\", file=f)\n",
    "for bundle in principal_bundles:\n",
    "    bundle_id = bundle[0]\n",
    "    for v in bundle[2]:\n",
    "        vertex = tuple(v[:2])\n",
    "        color = to_hex(color_theme[bundle_id])\n",
    "  \n",
    "        print(v_to_name[\"{:016x}_{:016x}\".format(*vertex)], color, bundle_id, file=f, sep=\",\")\n",
    "f.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [],
   "source": [
    "b_vertex_to_position = {}\n",
    "i = 0\n",
    "for bundle in principal_bundles:\n",
    "    for v in bundle[2]:\n",
    "        vertex = tuple(v[:2])\n",
    "        b_vertex_to_position[vertex] = i, bundle[0]\n",
    "        i += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x144 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x144 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x144 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x144 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "seq_info = new_sdb.seq_info.copy()\n",
    "sinfo = list(seq_info.items())\n",
    "sinfo.sort(key=lambda x: x[1][0])\n",
    "\n",
    "#fig = plt.figure(figsize=(24,96))\n",
    "pidx = 1\n",
    "for sid, data in sinfo[:10]:\n",
    "    ctg, _, _ = data\n",
    "    smps = sid_smps[sid]\n",
    "    #print(seq_info[sid])\n",
    "    #print(sid, len(smps))\n",
    "    x, rx = [], []\n",
    "    y, ry = [], []\n",
    "    c, rc = [], []\n",
    "\n",
    "   \n",
    "    for s in smps:\n",
    "        if s[1] is None:\n",
    "            continue\n",
    "        vertex = tuple(s[0][:2])\n",
    "        x.append(s[0][2])\n",
    "        y.append(b_vertex_to_position[vertex][0]) # same direction\n",
    "        c.append(color_theme[s[1][0]])\n",
    "            \n",
    "\n",
    "    fig = plt.figure(figsize=(6,2))\n",
    "    plt.scatter(x, y, marker=\".\", color=c, s=4)\n",
    "    \n",
    "    \n",
    "    plt.xlim(-10000,7000000)\n",
    "    #plt.ylim(150,280)\n",
    "    plt.title(ctg)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [],
   "source": [
    "#ref_file_name, roi1_chr, roi1_b, roi1_e = 'chm13_tagged.fa', 'chrY_chm13', 25622115, 25625511\n",
    "ref_file_name, roi1_chr, roi1_b, roi1_e = 'hg38_tagged.fa', 'chrY_hg38', 22403410,22424870\n",
    "padding = 100\n",
    "roi1_seq = ref_db.get_sub_seq(ref_file_name, roi1_chr, roi1_b-padding, roi1_e+padding)\n",
    "\n",
    "ref_file_name, roi2_chr, roi2_b, roi2_e = 'hg38_tagged.fa', 'chrY_hg38', 26121585, 26133714\n",
    "padding = 100\n",
    "roi2_seq = ref_db.get_sub_seq(ref_file_name, roi2_chr, roi2_b-padding, roi2_e+padding)\n",
    "\n",
    "ref_file_name, roi3_chr, roi3_b, roi3_e = 'hg38_tagged.fa', 'chrY_hg38', 21311161, 21319435\n",
    "padding = 100\n",
    "roi3_seq = ref_db.get_sub_seq(ref_file_name, roi3_chr, roi3_b-padding, roi3_e+padding)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [],
   "source": [
    "gene_matches1 = new_sdb.get_match_positions_with_fragment(roi1_seq)\n",
    "gene_matches2 = new_sdb.get_match_positions_with_fragment(roi2_seq)\n",
    "gene_matches3 = new_sdb.get_match_positions_with_fragment(roi3_seq)\n",
    "gene_matches = [gene_matches1, gene_matches2, gene_matches3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1728x4608 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "seq_info = new_sdb.seq_info.copy()\n",
    "sinfo = list(seq_info.items())\n",
    "sinfo.sort(key=lambda x: x[1][0])\n",
    "\n",
    "fig = plt.figure(figsize=(24,64))\n",
    "pidx = 1\n",
    "for sid, data in sinfo:\n",
    "    ctg, _, _ = data\n",
    "    smps = sid_smps[sid]\n",
    "    #print(seq_info[sid])\n",
    "    #print(sid, len(smps))\n",
    "    x, rx = [], []\n",
    "    y, ry = [], []\n",
    "    c, rc = [], []\n",
    "    for s in smps:\n",
    "        if s[1] is None:\n",
    "            continue\n",
    "        \n",
    "        if s[0][4] == s[1][1]:\n",
    "            x.append(s[0][2])\n",
    "            y.append(0) # same direction\n",
    "            c.append(color_theme[s[1][0]])\n",
    "        else:\n",
    "            rx.append(s[0][2])\n",
    "            ry.append(6)\n",
    "            rc.append(color_theme[s[1][0]])\n",
    "\n",
    "            \n",
    "    y = np.array(y) \n",
    "    ry = np.array(ry)\n",
    "    x.reverse()\n",
    "    c.reverse()\n",
    "    \n",
    "    plt.subplot(len(sid_smps), 1, pidx)\n",
    "    pidx += 1\n",
    "    \n",
    "    #plt.figure(figsize=(24,3))\n",
    "    plt.scatter(x, y, marker=\">\", color=c, s=180)\n",
    "    plt.scatter(rx, ry, marker=\"<\", color=rc, s=180)\n",
    "    \n",
    "    \n",
    "    for mi in range(len(gene_matches)):\n",
    "        if sid not in gene_matches[mi]:\n",
    "            continue\n",
    "        matches = set([(_[0], _[1]) for _ in gene_matches[mi][sid]])\n",
    "        track_x = [_[0] for _ in matches]\n",
    "        plt.scatter(track_x, [-4-mi*2]*len(track_x), marker=\"s\", color=\"black\", s=2)\n",
    "    \n",
    "    #plt.axis(\"off\")\n",
    "    plt.yticks([])\n",
    "    plt.ylim(-16,12)\n",
    "    plt.xlim(-10000,2000000)\n",
    "    plt.text(0, -15, ctg, fontsize=24)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 181,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pidx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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