automate_make_fastas.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Figure out how to automate the entire generate fasta file process"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_fasta(df_sco, dir_to_intergenic):\n",
    "    \n",
    "    #first, read in single copy ortholog dataframe\n",
    "    df = pd.read_excel(df_sco, dtype=str, na_filter=False)\n",
    "    \n",
    "    #Intialize dataframe to be created\n",
    "    names = []\n",
    "    \n",
    "    for i in df:\n",
    "        names.append(i)\n",
    "        \n",
    "    df_final = pd.DataFrame(columns=names)\n",
    "        \n",
    "    os.chdir(dir_to_intergenic)\n",
    "    \n",
    "    for intergenic_file in os.listdir():\n",
    "        if '.txt' in intergenic_file:\n",
    "            with open(intergenic_file, 'r') as f:\n",
    "                \n",
    "                curr_name = None\n",
    "                \n",
    "                for i in df:\n",
    "                    if str(i) in intergenic_file:\n",
    "                        curr_name = str(i)\n",
    "                \n",
    "                headerList = []\n",
    "                seqList = []\n",
    "                currentSeq = 'placeholder' #place holder skips the first currentseq from being ''\n",
    "                \n",
    "                for line in f:\n",
    "                    if line[0] == \">\":\n",
    "                        headerList.append(line[1:].strip())\n",
    "                        if currentSeq != 'placeholder':\n",
    "                            seqList.append(currentSeq)\n",
    "\n",
    "                        currentSeq = ''\n",
    "\n",
    "                    else:\n",
    "                        currentSeq += line.strip()\n",
    "\n",
    "\n",
    "                seqList.append(currentSeq)\n",
    "                \n",
    "                searchfor_list = []\n",
    "                for value in df[curr_name]: #This will be specific for df column that contains gene IDs of interest\n",
    "                    searchfor_list.append(value) #creates list\n",
    "\n",
    "                new_searchfor_list = []\n",
    "                for item in searchfor_list: \n",
    "                    new_searchfor_list.append(item.split(','))\n",
    "\n",
    "                combined_list = []\n",
    "                for i in range(len(headerList)): \n",
    "                    combined_list.append(headerList[i] +'?'+seqList[i]) #This line can be mod to have seperator between id and seq, maybe '?'\n",
    "                    #keep in mind, this will have > and \\n for LF when written to txt file\n",
    "                combined_list_Series = pd.Series(combined_list)\n",
    "                    \n",
    "    \n",
    "                new_filter_list = []\n",
    "\n",
    "                for value in new_searchfor_list:\n",
    "                    working_list = []\n",
    "                    for items in value: \n",
    "                        y = list(filter(lambda x:items in x, combined_list_Series))\n",
    "                        if items == '':\n",
    "                            working_list.append('')\n",
    "                        elif y: \n",
    "                            working_list.append(y[0])\n",
    "\n",
    "                    new_filter_list.append(working_list)\n",
    "                    \n",
    "            df_final[curr_name] = new_filter_list\n",
    "            \n",
    "    return(df_final)\n",
    "            "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "#df = make_fasta('/Users/alecbrown/Desktop/Rokas_Lab/Population_paper/excel_sheets/single_copy_orthologs/gene_single_copy_orthologs.xlsx', \n",
    "                '/Users/alecbrown/Desktop/Rokas_Lab/Population_paper/FILES_intergenic/1500bp/')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
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       "      <th>Aspergillus_fumigatus_Z5_GCA_001029325.1</th>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5812 rows × 265 columns</p>\n",
       "</div>"
      ],
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       "            Aspergillus_fumigatus_A1163_GCA_000150145.1  \\\n",
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       "3     [DS499597.1_340446..342101..+_jus..1500 ID=gen...   \n",
       "4     [DS499599.1_286520..287678..-_jus..1500 ID=gen...   \n",
       "...                                                 ...   \n",
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       "5811  [DS499603.1_73842..74795..+_jus..1500 ID=gene-...   \n",
       "\n",
       "        Aspergillus_fumigatus_A_2_26s_2_GCA_020503825.1  \\\n",
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       "...                                                 ...   \n",
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       "\n",
       "        Aspergillus_fumigatus_A_2_27s_1_GCA_020503795.1  \\\n",
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       "...                                                 ...   \n",
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       "\n",
       "        Aspergillus_fumigatus_A_2_34L_2_GCA_020501235.1  \\\n",
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       "...                                                 ...   \n",
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       "\n",
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       "...                                                 ...   \n",
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       "\n",
       "        Aspergillus_fumigatus_A_2_35s_1_GCA_020502455.1  \\\n",
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       "...                                                 ...   \n",
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       "\n",
       "        Aspergillus_fumigatus_A_2_36s_3_GCA_020502435.1  \\\n",
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       "...                                                 ...   \n",
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       "\n",
       "        Aspergillus_fumigatus_A_2_43L_2_GCA_020500995.1  \\\n",
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       "...                                                 ...   \n",
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       "\n",
       "        Aspergillus_fumigatus_A_2_44L_2_GCA_020501135.1  \\\n",
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       "...                                                 ...   \n",
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       "\n",
       "        Aspergillus_fumigatus_A_2_45L_5_GCA_020501095.1  ...  \\\n",
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       "\n",
       "     Aspergillus_fumigatus_NRZ_2018_326_GCA_020500205.1  \\\n",
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       "...                                                 ...   \n",
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       "...                                                 ...   \n",
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       "5808  [JAIBSG010000017.1_4137..8069..-_jus..1500 ID=...   \n",
       "5809  [JAIBSG010000067.1_132659..133860..+_jus..1500...   \n",
       "5810  [JAIBSG010000048.1_75647..77913..+_jus..1500 I...   \n",
       "5811  [JAIBSG010000034.1_152451..153404..-_jus..1500...   \n",
       "\n",
       "     Aspergillus_fumigatus_NRZ_2018_646_GCA_020499805.1  \\\n",
       "0     [JAIBSF010000039.1_113778..115528..+_jus..1500...   \n",
       "1     [JAIBSF010000014.1_74881..76394..+_jus..1500 I...   \n",
       "2     [JAIBSF010000121.1_53539..55796..+_jus..1500 I...   \n",
       "3     [JAIBSF010000002.1_582950..585091..-_jus..1500...   \n",
       "4     [JAIBSF010000014.1_175880..177038..+_jus..1500...   \n",
       "...                                                 ...   \n",
       "5807  [JAIBSF010000001.1_297349..297834..+_jus..1500...   \n",
       "5808  [JAIBSF010000008.1_427054..430986..+_jus..1500...   \n",
       "5809  [JAIBSF010000065.1_14084..15285..-_jus..1500 I...   \n",
       "5810  [JAIBSF010000093.1_87273..89548..-_jus..1500 I...   \n",
       "5811  [JAIBSF010000005.1_13626..14579..+_jus..1500 I...   \n",
       "\n",
       "     Aspergillus_fumigatus_NRZ_2018_649_GCA_020499775.1  \\\n",
       "0     [JAIBSD010000034.1_15522..17271..-_jus..1500 I...   \n",
       "1     [JAIBSD010000074.1_52946..54459..+_jus..1500 I...   \n",
       "2     [JAIBSD010000125.1_34613..36870..+_jus..1500 I...   \n",
       "3     [JAIBSD010000050.1_125041..127182..-_jus..1500...   \n",
       "4     [JAIBSD010000041.1_27939..29097..+_jus..1500 I...   \n",
       "...                                                 ...   \n",
       "5807  [JAIBSD010000001.1_327184..327669..-_jus..1500...   \n",
       "5808  [JAIBSD010000115.1_55023..58955..-_jus..1500 I...   \n",
       "5809  [JAIBSD010000147.1_51293..52494..+_jus..1500 I...   \n",
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       "5811  [JAIBSD010000002.1_432337..433290..-_jus..1500...   \n",
       "\n",
       "               Aspergillus_fumigatus_Z5_GCA_001029325.1  \\\n",
       "0     [KQ087375.1_308682..310432..+_jus..1500 ID=gen...   \n",
       "1     [KQ087358.1_433177..434690..-_jus..1500 ID=gen...   \n",
       "2     [KQ087369.1_570647..572904..+_jus..1500 ID=gen...   \n",
       "3     [KQ087363.1_346345..348049..+_jus..1500 ID=gen...   \n",
       "4     [KQ087358.1_332163..333321..-_jus..1500 ID=gen...   \n",
       "...                                                 ...   \n",
       "5807  [KQ087358.1_1898227..1898712..-_jus..1500 ID=g...   \n",
       "5808  [KQ087373.1_597108..601040..-_jus..1500 ID=gen...   \n",
       "5809  [KQ087375.1_959644..960845..-_jus..1500 ID=gen...   \n",
       "5810  [KQ087362.1_2084974..2087240..-_jus..1500 ID=g...   \n",
       "5811  [KQ087365.1_1362144..1363097..+_jus..1500 ID=g...   \n",
       "\n",
       "           Aspergillus_fumigatus_niveus_GCA_000731615.1  \\\n",
       "0     [JHOI01000605.1_134918..136667..-_jus..1500 ID...   \n",
       "1     [JHOI01000528.1_47965..49838..+_jus..1500 ID=g...   \n",
       "2     [JHOI01000632.1_353905..356162..-_jus..1500 ID...   \n",
       "3     [JHOI01000604.1_25096..26751..-_jus..1500 ID=g...   \n",
       "4     [JHOI01000547.1_82881..83237..-_jus..1500 ID=g...   \n",
       "...                                                 ...   \n",
       "5807  [JHOI01000607.1_138950..139435..+_jus..1500 ID...   \n",
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       "5811  [JHOI01000596.1_159455..160475..-_jus..1500 ID...   \n",
       "\n",
       "          Aspergillus_fischeri_NRRL4161_GCA_016748045.1  \\\n",
       "0     [WHVT01000011.1_314845..316598..+_jus..1500 ID...   \n",
       "1     [WHVT01000006.1_357120..358633..-_jus..1500 ID...   \n",
       "2     [WHVT01000014.1_234862..237119..+_jus..1500 ID...   \n",
       "3     [WHVT01000004.1_283686..285373..+_jus..1500 ID...   \n",
       "4     [WHVT01000006.1_255068..256225..-_jus..1500 ID...   \n",
       "...                                                 ...   \n",
       "5807  [WHVT01000012.1_365252..365736..-_jus..1500 ID...   \n",
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       "5811  [WHVT01000008.1_588264..589216..-_jus..1500 ID...   \n",
       "\n",
       "          Aspergillus_fischeri_NRRL_181_GCF_000149645.2  \n",
       "0     [NW_001509773.1_2227384..2229137..-_jus..1500 ...  \n",
       "1     [NW_001509760.1_1857448..1858961..-_jus..1500 ...  \n",
       "2     [NW_001509763.1_667567..669824..+_jus..1500 ID...  \n",
       "3     [NW_001509772.1_2378671..2380358..-_jus..1500 ...  \n",
       "4     [NW_001509760.1_1755396..1756553..-_jus..1500 ...  \n",
       "...                                                 ...  \n",
       "5807  [NW_001509760.1_3483665..3484149..-_jus..1500 ...  \n",
       "5808  [NW_001509760.1_743414..747346..+_jus..1500 ID...  \n",
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       "5811  [NW_001509765.1_132296..133248..+_jus..1500 ID...  \n",
       "\n",
       "[5812 rows x 265 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "os.chdir('/Users/alecbrown/Desktop/Rokas_Lab/Population_paper/excel_sheets/')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "file_name ='gene_sco_fastas.xlsx'\n",
    "\n",
    "writer = pd.ExcelWriter(file_name, engine='xlsxwriter')\n",
    "df.round(2)\n",
    "df.to_excel(writer, index = False, header=True )\n",
    "\n",
    "writer.book.use_zip64()\n",
    "\n",
    "#writer.save()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Let's create the fasta files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_excel('/Users/alecbrown/Desktop/Rokas_Lab/Population_paper/excel_sheets/fasta/gene_sco_fastas.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.replace(r'\\?','\\n', regex=True)\n",
    "df = df.replace(r'\\[','', regex=True)\n",
    "df = df.replace(r'\\]','', regex=True)\n",
    "df = df.replace(r\"\\'\",\"\", regex=True)\n",
    "df = df.replace(r'\\\"','', regex=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "os.chdir('/Users/alecbrown/Desktop/Rokas_Lab/Population_paper/fastas/real_data/noncoding_1500bp/')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "i = 0\n",
    "\n",
    "while i < len(df):\n",
    "    #f = open('testing.txt_'.format(i), 'w')\n",
    "    for row in df[i:1+i].values:\n",
    "        f = open(str(i) + '_upstream.txt', 'w')\n",
    "        for fasta in row:\n",
    "            if fasta.rstrip() == '': #this will skip any empty values\n",
    "                continue\n",
    "            else:\n",
    "                f.write('>' + fasta)\n",
    "                f.write('\\n')\n",
    "    #f.close()\n",
    "    i+=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Next, let's figure out how to reformat these fasta files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "#can use regex to get the part after name= then write a new file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "import re"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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     ]
    }
   ],
   "source": [
    "num = 5812\n",
    "path = '/Users/alecbrown/Desktop/Rokas_Lab/Population_paper/fastas/real_data/noncoding_1500bp/'\n",
    "os.chdir(path)\n",
    "\n",
    "for i in range(0,num):\n",
    "    with open(f'{i}_upstream.txt', 'r') as f, open(f'{i}_fasta.txt', 'w') as nf:\n",
    "        fasta_id = []\n",
    "        seqs = []\n",
    "        for line in f:\n",
    "            if '>' in line:\n",
    "                if 'Name=' in line:\n",
    "                    pattern = re.compile(r'Name=[0-9A-Z_.]+')\n",
    "                    matches = pattern.finditer(line)\n",
    "                                         \n",
    "                    for m in matches:\n",
    "                        if m.group(0)[5:] in fasta_id:\n",
    "                            continue\n",
    "                        fasta_id.append(m.group(0)[5:])\n",
    "                        \n",
    "            else:\n",
    "                seqs.append(line[:-2])\n",
    "                \n",
    "        if len(seqs) != len(fasta_id):\n",
    "            print(len(seqs))\n",
    "            print(len(fasta_id))\n",
    "            continue\n",
    "            \n",
    "        else:\n",
    "            #print(len(seqs))\n",
    "            dct = dict(zip(fasta_id, seqs))\n",
    "            \n",
    "            for k,v in dct.items():\n",
    "                nf.write('>' + k + '\\n')\n",
    "                nf.write(v + '\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Below we are going to id fastas that did not run for some reason"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "os.chdir('/Users/alecbrown/Desktop/Rokas_Lab/Population_paper/fastas/real_data/reformat_noncoding_1500bp/')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "nums = []\n",
    "\n",
    "copy = False\n",
    "\n",
    "for file in os.listdir():\n",
    "    if '.txt' in file:\n",
    "        with open(file, 'r') as f:\n",
    "            copy = True\n",
    "            for line in f:\n",
    "                if '>' in line:\n",
    "                    copy = False\n",
    "                    continue\n",
    "                    \n",
    "            if copy == True:\n",
    "                start, end = file.split('_')\n",
    "                nums.append(int(start))\n",
    "                    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "nums.sort()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
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       " 3512,\n",
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       " 5500,\n",
       " 1997,\n",
       " 4056]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nums"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "#The issue was with the REFORMAT, let's investigate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "num = 5812\n",
    "path = '/Users/alecbrown/Desktop/Rokas_Lab/Population_paper/fastas/real_data/noncoding_1500bp/'\n",
    "os.chdir(path)\n",
    "\n",
    "for i in range(0,num):\n",
    "    if i in nums:\n",
    "        with open(f'{i}_upstream.txt', 'r') as f, open(f'{i}_fasta.txt', 'w') as nf:\n",
    "            fasta_id = []\n",
    "            seqs = []\n",
    "            for line in f:\n",
    "                if '>' in line:\n",
    "                    if 'Name=' in line:\n",
    "                        pattern = re.compile(r'Name=[0-9A-Z_.]+')\n",
    "                        matches = pattern.finditer(line)\n",
    "\n",
    "                        for m in matches:\n",
    "                            if m.group(0)[5:] in fasta_id:\n",
    "                                continue\n",
    "                            fasta_id.append(m.group(0)[5:])\n",
    "\n",
    "                else:\n",
    "                    seqs.append(line[:-2])\n",
    "\n",
    "\n",
    "            dct = dict(zip(fasta_id, seqs))\n",
    "\n",
    "            for k,v in dct.items():\n",
    "                nf.write('>' + k + '\\n')\n",
    "                nf.write(v + '\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    }
   ],
   "source": [
    "for i in range(0,5812):\n",
    "    if i in nums:\n",
    "        print(i)"
   ]
  }
 ],
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