[98867e]: / ipynb / ksent.ipynb

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{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Use 16kbp chunks for creating more training data \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import glob\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import seaborn as sns; sns.set(color_codes=True)\n",
    "from gensim.models.keyedvectors import KeyedVectors\n",
    "from gensim.models import Word2Vec\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.manifold import TSNE\n",
    "from sklearn import manifold,neighbors\n",
    "from scipy.cluster.hierarchy import dendrogram, linkage, to_tree, fcluster,distance  \n",
    "from matplotlib import pyplot as plt\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "from Bio import SeqIO\n",
    "from Bio.Align import MultipleSeqAlignment\n",
    "from Bio.Phylo.TreeConstruction import DistanceCalculator, DistanceTreeConstructor\n",
    "from Bio import Phylo\n",
    "from tqdm import tqdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "word_vectors = Word2Vec.load_word2vec_format('/data/genomes/embeddings/dna2vec-20190612-1611-k10to10-100d-10c-4870Mbp-sliding-kPR.w2v')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 4715/4715 [00:03<00:00, 1490.95it/s]\n"
     ]
    }
   ],
   "source": [
    "FASTA=\"/data/genomes/dna2vec_train/\"\n",
    "ff = glob.glob(f\"{FASTA}*.fasta\")\n",
    "X = {}\n",
    "for file in tqdm(ff):\n",
    "    for record in SeqIO.parse(file, \"fasta\"):\n",
    "        seq=str(record.seq)\n",
    "        X[record.description]=seq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>ID</th>\n",
       "      <th>genus</th>\n",
       "      <th>len</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ATGGTAATATCGCTCCTTTGGATTGGGTTTCGTCACTTTTATCTTA...</td>\n",
       "      <td>NZ_CAPG01000111.1</td>\n",
       "      <td>Bacillus</td>\n",
       "      <td>22347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>TTTTTATTTATTCAGCAGCCTTAAACGGTCAACCTATAGAAAAAAT...</td>\n",
       "      <td>NZ_LN886493.1</td>\n",
       "      <td>Planktothrix</td>\n",
       "      <td>1670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CCCCCCCCCGCTGGCACAGACCCCACATGATAAGACGAGTCTGATT...</td>\n",
       "      <td>NZ_LDJH01000056.1</td>\n",
       "      <td>Stenotrophomonas</td>\n",
       "      <td>1317</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ATCAGGACAGCGCTGGCTGCCTACTCTCTTGCATCCAAGGCGAATA...</td>\n",
       "      <td>NZ_FQXZ01000009.1</td>\n",
       "      <td>Vibrio</td>\n",
       "      <td>586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>GACCGTGGGGTGGGGTCGTGTCGGGGTGCCCCCGCAGCAAACTGCA...</td>\n",
       "      <td>NZ_JXDG01000067.1</td>\n",
       "      <td>Pseudomonas</td>\n",
       "      <td>72512</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   0                 ID  \\\n",
       "0  ATGGTAATATCGCTCCTTTGGATTGGGTTTCGTCACTTTTATCTTA...  NZ_CAPG01000111.1   \n",
       "1  TTTTTATTTATTCAGCAGCCTTAAACGGTCAACCTATAGAAAAAAT...      NZ_LN886493.1   \n",
       "2  CCCCCCCCCGCTGGCACAGACCCCACATGATAAGACGAGTCTGATT...  NZ_LDJH01000056.1   \n",
       "3  ATCAGGACAGCGCTGGCTGCCTACTCTCTTGCATCCAAGGCGAATA...  NZ_FQXZ01000009.1   \n",
       "4  GACCGTGGGGTGGGGTCGTGTCGGGGTGCCCCCGCAGCAAACTGCA...  NZ_JXDG01000067.1   \n",
       "\n",
       "              genus    len  \n",
       "0          Bacillus  22347  \n",
       "1      Planktothrix   1670  \n",
       "2  Stenotrophomonas   1317  \n",
       "3            Vibrio    586  \n",
       "4       Pseudomonas  72512  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "descr = X.keys()\n",
    "fastas = pd.DataFrame(data=list(X.values()))\n",
    "fastas[\"ID\"] = [x.split()[0] for x in descr]\n",
    "fastas[\"genus\"] = [x.split()[1] for x in descr]\n",
    "fastas[\"len\"] = [len(x) for x in X.values()]\n",
    "fastas.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2130, 4)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "longer = fastas.loc[fastas[\"len\"] > 16000,:];longer.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 2130/2130 [20:54<00:00,  2.17it/s]  \n"
     ]
    }
   ],
   "source": [
    "ksent_len = 16000\n",
    "ksent = {}\n",
    "for i in tqdm(range(longer.shape[0])):\n",
    "    s = longer.iloc[i,0]\n",
    "    vectors = []\n",
    "    for hop in range((len(s) // ksent_len)):\n",
    "        seq = \"\".join(s[hop:hop+ksent_len])\n",
    "        t = [\"\".join(seq[i:i+10]) for i in range(len(seq)-10)]\n",
    "        tokens = list(filter(lambda x: set(x) == {'A', 'C', 'G', 'T'}, t))\n",
    "        vectors.append(np.mean(word_vectors[tokens], axis=0))\n",
    "    ksent[longer.iloc[i,1]] = (longer.iloc[i,2], vectors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sentences = pd.DataFrame(ksent.keys())\n",
    "sentences['vectors'] = [ksent[x][1] for x in ksen.keys()]\n",
    "sentences['genus'] = [ksent[x][0] for x in ksen.keys()]\n",
    "sentences['n'] = [len(ksent[x][1]) for x in ksen.keys()]\n",
    "sentences.sort_values(by=\"n\", ascending=False,inplace=True)\n",
    "sentences.reset_index(drop=True,inplace=True)\n",
    "sentences.to_pickle(\"../data/ksen-sentences.pkl\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>vectors</th>\n",
       "      <th>genus</th>\n",
       "      <th>n</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NZ_AJTN02000197.1</td>\n",
       "      <td>[[-0.040759552, 0.13493565, 0.11740411, 0.0319...</td>\n",
       "      <td>Bacillus</td>\n",
       "      <td>518</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NZ_FOWX01000006.1</td>\n",
       "      <td>[[-0.03424186, 0.10903403, 0.15674573, -0.0431...</td>\n",
       "      <td>Pseudomonas</td>\n",
       "      <td>509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NZ_LGUX01000047.1</td>\n",
       "      <td>[[-0.02221683, 0.16862509, 0.13689668, -0.0279...</td>\n",
       "      <td>Streptomyces</td>\n",
       "      <td>416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NZ_LAQO01000097.1</td>\n",
       "      <td>[[-0.032138012, 0.13535376, 0.11554951, -0.080...</td>\n",
       "      <td>Paenibacillus</td>\n",
       "      <td>408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NZ_JNNU01000024.1</td>\n",
       "      <td>[[-0.09971707, 0.14343369, 0.073053084, -0.051...</td>\n",
       "      <td>Rhizobium</td>\n",
       "      <td>391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NZ_JDSA01000159.1</td>\n",
       "      <td>[[-0.029859722, 0.09358531, 0.117933616, -0.06...</td>\n",
       "      <td>Clostridium</td>\n",
       "      <td>375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>NZ_FULE01000075.1</td>\n",
       "      <td>[[-0.029456131, 0.1513094, 0.16170317, -0.0625...</td>\n",
       "      <td>Vibrio</td>\n",
       "      <td>374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NZ_FWWS01000035.1</td>\n",
       "      <td>[[-0.029456131, 0.1513094, 0.16170317, -0.0625...</td>\n",
       "      <td>Corynebacterium</td>\n",
       "      <td>374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>NZ_JDSA01000158.1</td>\n",
       "      <td>[[0.012553351, 0.058161315, 0.11874426, -0.032...</td>\n",
       "      <td>Clostridium</td>\n",
       "      <td>370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>NZ_JNNU01000023.1</td>\n",
       "      <td>[[-0.07605679, 0.1315616, 0.099155806, -0.0717...</td>\n",
       "      <td>Rhizobium</td>\n",
       "      <td>345</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   0                                            vectors  \\\n",
       "0  NZ_AJTN02000197.1  [[-0.040759552, 0.13493565, 0.11740411, 0.0319...   \n",
       "1  NZ_FOWX01000006.1  [[-0.03424186, 0.10903403, 0.15674573, -0.0431...   \n",
       "2  NZ_LGUX01000047.1  [[-0.02221683, 0.16862509, 0.13689668, -0.0279...   \n",
       "3  NZ_LAQO01000097.1  [[-0.032138012, 0.13535376, 0.11554951, -0.080...   \n",
       "4  NZ_JNNU01000024.1  [[-0.09971707, 0.14343369, 0.073053084, -0.051...   \n",
       "5  NZ_JDSA01000159.1  [[-0.029859722, 0.09358531, 0.117933616, -0.06...   \n",
       "6  NZ_FULE01000075.1  [[-0.029456131, 0.1513094, 0.16170317, -0.0625...   \n",
       "7  NZ_FWWS01000035.1  [[-0.029456131, 0.1513094, 0.16170317, -0.0625...   \n",
       "8  NZ_JDSA01000158.1  [[0.012553351, 0.058161315, 0.11874426, -0.032...   \n",
       "9  NZ_JNNU01000023.1  [[-0.07605679, 0.1315616, 0.099155806, -0.0717...   \n",
       "\n",
       "             genus    n  \n",
       "0         Bacillus  518  \n",
       "1      Pseudomonas  509  \n",
       "2     Streptomyces  416  \n",
       "3    Paenibacillus  408  \n",
       "4        Rhizobium  391  \n",
       "5      Clostridium  375  \n",
       "6           Vibrio  374  \n",
       "7  Corynebacterium  374  \n",
       "8      Clostridium  370  \n",
       "9        Rhizobium  345  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sentences = pd.read_pickle(\"../data/ksen-sentences.pkl\")\n",
    "sentences.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Reduce dimensions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys, os\n",
    "sys.path.append(\".\")\n",
    "from KlsAutoencoder import *\n",
    "e = Encoder(\"../data/models/encoder-3d\",[100,50,3]);e"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualize  longest sequences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x936 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "longest = sentences.iloc[:10,:]\n",
    "data = [(e.transform(x[\"vectors\"]), x[\"genus\"]) for _, x in longest.iterrows()]\n",
    "\n",
    "fig = plt.figure(figsize=(13,13))\n",
    "ax = fig.add_subplot(111,projection=\"3d\")\n",
    "for s, label in data:\n",
    "    ax.scatter(s[:,0],s[:,1],s[:,2], marker=\"o\",s=50, alpha=0.5, label = label)\n",
    "ax.set_xlabel('dim1')\n",
    "ax.set_ylabel('dim2')\n",
    "ax.set_zlabel('dim3')\n",
    "ax.set_title(\"Ksent in space\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Observations\n",
    "\n",
    "- genome has own position in a latent space\n",
    "- all Ksent (k-sentences of lenght 16K) of a genome cluster together\n",
    "- it seems that any Ksent of a genome carries similar information and can serve as an estimate for entire sequence in the latent space"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "IDEA:\n",
    "- sample ksent from sequences and create sentence vectors\n",
    "- make it into a Word2Vec instance\n",
    "- use model.most_similar(positive=['woman', 'king'], negative=['man']) to find related areas of other genomes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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