def download_fasta_and_genbank(identifier, tag, genbank=True, fasta=True):
"""
:param identifier: valid identifier to retrieve from NCBI (genbank) and
ENA (fasta)
:param tag: name of the filename for the genbank and fasta files.
"""
if genbank:
from bioservices import EUtils
eu = EUtils()
data = eu.EFetch(db="nuccore",
id=identifier,
rettype="gbwithparts",
retmode="text")
if isinstance(data, int) and data == 400:
raise ValueError("{} not found on NCBI".format(identifier))
else:
with open("%s.gbk" % tag, "w") as fout:
fout.write(data.decode())
if fasta:
from bioservices import ENA
ena = ENA()
data = ena.get_data(identifier, 'fasta')
if isinstance(data, int) and data == 400:
raise ValueError("{} not found on ENA".format(identifier))
else:
with open("%s.fa" % tag, "w") as fout:
try:
# change in API in v1.7.8
fout.write(data)
except:
fout.write(data.decode())
def __init__(self, dbname):
self.dbname = dbname
self.eutils = EUtils()
self.enadb = ENADownload()
self.category = [
'archaea', 'bacteria', 'fungi', 'invertebrate', 'mitonchondrion',
'other', 'plant', 'plasmid', 'plastid', 'protozoa',
'vertebrate_mammalian', 'vertebrate_other', 'viral'
]
def find_taxon(self, taxid, mode="ncbi"):
taxid = str(taxid)
if mode == "ncbi":
from bioservices import EUtils
self.eutils = EUtils(verbose=False)
res = self.eutils.taxonomy_summary(taxid)
else:
res = self.ensembl.get_taxonomy_by_id(taxid)
return res
"""if "error" in res[taxid]:
def to_genbank(self, retmax=10000):
"""Draft: from a TaxID, uses EUtils to retrieve
the GenBank identifiers
:Inspiration: https://gist.github.com/fjossinet/5673672
"""
from bioservices import EUtils
e = EUtils()
idlist = e.ESearch(db='nucleotide',
term='txid%s[Organism:exp]' % self.taxid,
restart=0,
retmax=retmax)['idlist']
results = e.ESummary(db='nucleotide', id=idlist, retmax=retmax)
return results
def _update_custom_taxonomy_bases(self, taxid):
"""
"""
taxid = str(taxid)
self.eutils = EUtils(verbose=False)
res = self.eutils.taxonomy_summary(taxid)
if "error" in res[taxid]:
print("not found in NCBI (EUtils)")
else:
print("found in NCBI (EUtils) and added to local databases")
with open(self.custom_db, "w") as fout:
data = res[taxid]
fout.write("ID : {}\n".format(taxid))
#fout.write("PARENT ID : {}\n".format(taxid))
fout.write("RANK : {}\n".format(data['rank']))
#fout.write("GC ID : {}\n".format(data['']))
fout.write("SCIENTIFIC NAME : {}\n".format(data['scientificname']))
def findName(accession):
s = EUtils()
theID = None
geneOrProtein = "gene"
# Check gene database
res = s.ESearch("gene", accession)
if len(res["idlist"]) > 0:
# Get the ID in the "gene" database
theID = res["idlist"][0]
# If that fails, check the protein database
if theID == None:
res = s.ESearch("protein", accession)
if len(res["idlist"]) > 0:
theID = res["idlist"][0]
geneOrProtein = "protein"
# Couldn't find in either database
if not theID:
print("ERROR: couldn't find link for %s" % accession)
# Get link to the corresponding ID in the Taxonomy database
link = s.ELink(db="taxonomy",
dbfrom=geneOrProtein,
id=theID,
retmode="json")
taxID = json.loads(link)["linksets"][0]["linksetdbs"][0]["links"][0]
# Download taxonomy record
tax = s.EFetch(db="taxonomy", id=taxID)
#print(tax)
tree = ElementTree.fromstring(tax)
xmlP = parseString(tax)
#print(xmlP.toprettyxml())
taxonTag = tree.find("Taxon")
sciName = taxonTag.find("ScientificName")
return sciName.text
def get_entrez_summary(gene_id):
e = EUtils()
ret = e.ESearch('gene', gene_id)
ret = e.EFetch('gene', ret['idlist'])
return ret.decode("utf-8")
def __init__(self):
from bioservices import EUtils
self.eutils = EUtils()
class EUtilsTools(object):
"""Simple wrapper around EUtils to fetch basic informatino about an accession number
::
>>> from sequana.databases import EUtilsTools
>>> et.accession_to_info("K01711.1")
{'K01711.1': {'accession': '331784',
'comment': 'Measles virus (strain Edmonston), complete genome',
'gi': '331784',
'identifier': 'gi|331784|gb|K01711.1|MEANPCG[331784]',
'taxid': '11234'}}
"""
def __init__(self):
from bioservices import EUtils
self.eutils = EUtils()
def accession_to_info(self, ids):
"""An accession or list of them returns list of dictionaries"""
res = self.eutils.EFetch(db="nuccore",
id=ids,
rettype="docsum",
retmode="dict")
res = res['eSummaryResult']['DocSum']
# if one id provided, it will be a dict, otherwise a list of dicts
try:
res[0]
except:
res = [res]
# now we can loop over all identifiers
records = {}
accessions = [x.strip() for x in ids.split(',')]
for i, entry in enumerate(res):
# first, save the acc number
accession = entry['Id']
# then various info
items = entry['Item']
identifier = [x for x in items
if x['@Name'] == "Extra"][0]['#text']
if "||" in identifier:
# strip content after ||
identifier = identifier.split("||")[0]
title = [x for x in items if x['@Name'] == "Title"][0]['#text']
taxid = [x for x in items if x['@Name'] == "TaxId"][0]['#text']
gi = [x for x in items if x['@Name'] == "Gi"][0]['#text']
record = {
"taxid": taxid,
'accession': accession,
"identifier": identifier,
'gi': gi,
'comment': title
}
records[accessions[i]] = AttrDict(**record)
return records
class Taxon(object):
"""Utility to search for information related to a taxon
Uses HGNC service to fetch information about a taxon.
::
>>> from bioservices.apps.taxonomy import Taxon
>>> t = Taxon()
>>> t.search_by_taxon("9606")
{'Scientific Name': 'H**o sapiens', 'taxon': '9606'}
You can also pop up the Uniprot page using::
t.uniprot_onweb("9606")
A full list of taxons is available here::
http://www.uniprot.org/taxonomy/?query=*&format=*
.. versionadded:: 1.2.0
"""
def __init__(self):
super(Taxon, self).__init__()
# self.df = pd.DataFrame(index=[], columns=["Taxon", "Scientific Name"])
self._eutils_service = EUtils()
self._ensembl_service = Ensembl() # there is a search by name, easier to use than EUtils
def search_by_name(self, name):
"""using ensembl, tries to get the taxon identifier from the given name
::
>>> s.search_by_name('mouse')
10090
"""
res = self._ensembl_service.get_taxonomy_name("mouse")[0]
try:
return res["id"]
except:
return res
def search_by_taxon(self, taxon):
"""
should be a string without comma (only one entry accepted")
"""
assert isinstance(taxon, str)
assert "," not in taxon
ret = self._eutils_service.taxonomy(taxon)
if ret == "\n":
# nothing found
pass
else:
res = {"taxon": taxon, "Scientific Name": ret.Taxon[0].ScientificName}
# self.df.append(res)
return res
def info(self, taxon, lineage=False):
"""Prints information about a Taxon
:param str taxon: taxon identifier
:param bool lineage: prints lineage is set to True
"""
ret = self._eutils_service.taxonomy(taxon)
print("Display Name: %s" % ret.Taxon[0].OtherNames.Name.DispName)
print("GenBank Common name: %s" % ret.Taxon[0].OtherNames.GenbankCommonName)
print("Taxon Id: %s " % ret.Taxon[0].TaxId)
if lineage:
print("Lineage:")
for i, x in enumerate(ret.Taxon[0].Lineage.split(";")):
print(i * " " + x)
def uniprot_onweb(self, taxon):
"""Open Uniprot taxonomy page for a given taxon
:param str taxon: taxon identifier
"""
import webbrowser
try:
from urllib.request import urlopen
from urllib.error import HTTPError, URLError
except:
from urllib2 import urlopen, HTTPError, URLError
try:
urlopen("http://www.uniprot.org/taxonomy/%s" % taxon)
webbrowser.open("http://www.uniprot.org/taxonomy/%s" % taxon)
except HTTPError as err:
print("Invalid taxon")
except URLError as err:
print(err.args)
def __init__(self):
super(Taxon, self).__init__()
# self.df = pd.DataFrame(index=[], columns=["Taxon", "Scientific Name"])
self._eutils_service = EUtils()
self._ensembl_service = Ensembl() # there is a search by name, easier to use than EUtils
class Taxon(object):
"""Utility to search for information related to a taxon
Uses HGNC service to fetch information about a taxon.
::
>>> from bioservices.apps.taxonomy import Taxon
>>> t = Taxon()
>>> t.search_by_taxon("9606")
{'Scientific Name': 'H**o sapiens', 'taxon': '9606'}
You can also pop up the Uniprot page using::
t.uniprot_onweb("9606")
A full list of taxons is available here::
http://www.uniprot.org/taxonomy/?query=*&format=*
.. versionadded:: 1.2.0
"""
def __init__(self):
super(Taxon, self).__init__()
# self.df = pd.DataFrame(index=[], columns=["Taxon", "Scientific Name"])
self._eutils_service = EUtils()
self._ensembl_service = Ensembl() # there is a search by name, easier to use than EUtils
def search_by_name(self, name):
"""using ensembl, tries to get the taxon identifier from the given name
::
>>> s.search_by_name('mouse')
10090
"""
res = self._ensembl_service.get_taxonomy_name("mouse")[0]
try:
return res['id']
except:
return res
def search_by_taxon(self, taxon):
"""
should be a string without comma (only one entry accepted")
"""
assert isinstance(taxon, str)
assert "," not in taxon
ret = self._eutils_service.taxonomy(taxon)
if ret == "\n":
# nothing found
pass
else:
res = {'taxon': taxon, 'Scientific Name': ret.Taxon[0].ScientificName}
# self.df.append(res)
return res
def info(self, taxon, lineage=False):
"""Prints information about a Taxon
:param str taxon: taxon identifier
:param bool lineage: prints lineage is set to True
"""
ret = self._eutils_service.taxonomy(taxon)
print("Display Name: %s" % ret.Taxon[0].OtherNames.Name.DispName)
print("GenBank Common name: %s" % ret.Taxon[0].OtherNames.GenbankCommonName)
print("Taxon Id: %s " % ret.Taxon[0].TaxId)
if lineage:
print("Lineage:")
for i, x in enumerate(ret.Taxon[0].Lineage.split(";")):
print(i*" "+x)
def uniprot_onweb(self, taxon):
"""Open Uniprot taxonomy page for a given taxon
:param str taxon: taxon identifier
"""
import webbrowser
try:
from urllib.request import urlopen
from urllib.error import HTTPError, URLError
except:
from urllib2 import urlopen, HTTPError, URLError
try:
urlopen('http://www.uniprot.org/taxonomy/%s' % taxon)
webbrowser.open("http://www.uniprot.org/taxonomy/%s" % taxon)
except HTTPError as err:
print("Invalid taxon")
except URLError as err:
print(err.args)
class Taxonomy(object):
"""This class should ease the retrieval and manipulation of Taxons
There are many resources to retrieve information about a Taxon.
For instance, from BioServices, one can use UniProt, Ensembl, or
EUtils. This is convenient to retrieve a Taxon (see :meth:`fetch_by_name`
and :meth:`fetch_by_id` that rely on Ensembl). However, you can
also download a flat file from EBI ftp server, which
stores a set or records (2.8M (april 2020).
Note that the Ensembl database does not seem to be as up to date
as the flat files but entries contain more information.
for instance taxon 2 is in the flat file but not available through
the :meth:`fetch_by_id`, which uses ensembl.
So, you may access to a taxon in 2 different ways getting differnt
dictionary. However, 3 keys are common (id, parent, scientific_name)
::
>>> t = taxonomy.Taxonomy()
>>> t.fetch_by_id(9606) # Get a dictionary from Ensembl
>>> t.records[9606] # or just try with the get
>>> t[9606]
>>> t.get_lineage(9606)
"""
def __init__(self,
filename=None,
verbose=True,
online=True,
source="ncbi"):
""".. rubric:: constructor
:param offline: if you do not have internet, the connction to Ensembl
may hang for a while and fail. If so, set **offline** to True
:param from: download taxonomy databases from ncbi
"""
assert source in ['ncbi', 'ena']
self.source = source
if online:
from bioservices import Ensembl, EUtils
self.ensembl = Ensembl(verbose=False)
self.records = {} # empty to start with.
self.verbose = verbose
if filename is None:
self._dbname = "taxonomy.dat"
self.database = sequana_config_path + os.sep + self._dbname
else:
self.database = filename
self._custom_db = sequana_config_path
self._custom_db += "/taxonomy/taxonomy_custom.dat"
def _update_custom_taxonomy_bases(self, taxid):
"""
"""
taxid = str(taxid)
self.eutils = EUtils(verbose=False)
res = self.eutils.taxonomy_summary(taxid)
if "error" in res[taxid]:
print("not found in NCBI (EUtils)")
else:
print("found in NCBI (EUtils) and added to local databases")
with open(self.custom_db, "w") as fout:
data = res[taxid]
fout.write("ID : {}\n".format(taxid))
#fout.write("PARENT ID : {}\n".format(taxid))
fout.write("RANK : {}\n".format(data['rank']))
#fout.write("GC ID : {}\n".format(data['']))
fout.write("SCIENTIFIC NAME : {}\n".format(
data['scientificname']))
def download_taxonomic_file(self, overwrite=False):
"""Loads entire flat file from EBI
Do not overwrite the file by default.
"""
import ftplib
from sequana import sequana_config_path
if os.path.exists(self.database) and overwrite is False:
logger.info(
"Found taxonomy.dat file in sequana your path {}".format(
sequana_config_path))
return
else:
logger.info(
"Downloading and extracting the taxonomy file from the web. Please be patient."
)
if self.source == "ena":
url = 'ftp.ebi.ac.uk'
else:
url = 'ftp.ncbi.nlm.nih.gov'
self.ftp = ftplib.FTP(url)
self.ftp.login()
if self.source == "ena":
# for the EBI ftp only: self.ftp.cwd('databases')
self.ftp.cwd('pub')
self.ftp.cwd('databases')
self.ftp.cwd('taxonomy')
logger.warning(
'Downloading and saving in %s. This is from ebi and may be behind the NCBI taxonomy'
% self.database)
self.ftp.retrbinary('RETR taxonomy.dat',
open(self.database, 'wb').write)
ftp.close()
else:
self.ftp.cwd('pub')
self.ftp.cwd('taxonomy')
logger.warning('Downloading and saving in %s from ncbi ftp' %
self.database)
import tempfile
import shutil
with tempfile.TemporaryDirectory() as tmpdir:
filename = tmpdir + os.sep + "taxdump.tar.gz"
self.ftp.retrbinary('RETR taxdump.tar.gz',
open(filename, "wb").write)
import tarfile
tf = tarfile.open(filename)
assert "nodes.dmp" in tf.getnames()
assert "names.dmp" in tf.getnames()
tf.extract("nodes.dmp", tmpdir)
tf.extract("names.dmp", tmpdir)
ncbi = NCBITaxonomy(tmpdir + os.sep + "names.dmp",
tmpdir + os.sep + "nodes.dmp")
ncbi.create_taxonomy_file(tmpdir + os.sep + "taxonomy.dat")
shutil.move(tmpdir + os.sep + "taxonomy.dat", self.database)
self.ftp.close()
def load_records(self, overwrite=False):
"""Load a flat file and store records in :attr:`records`
Since version 0.8.3 we use NCBI that is updated more often than the ebi
ftp according to their README.
ftp://ncbi.nlm.nih.gov/pub/taxonomy/
"""
self.download_taxonomic_file(overwrite=overwrite)
self.records = {}
# TODO: check if it exists otherwise, load it ?
if os.path.exists(self.database) is False:
self.load()
with open(self.database) as f:
data = f.read().strip()
# This is fast. tried parse package, much slower. cost of progress bar
# is not important.
data = data.split("//\n") # the sep is //\n
self._child_match = re.compile(r'ID\s+\:\s*(\d+)\s*')
self._parent_match = re.compile(r'PARENT ID\s+\:\s*(\d+)\s*')
self._rank_match = re.compile(r'RANK\s+\:\s*([^\n]+)\s*')
self._name_match = re.compile(r'SCIENTIFIC NAME\s+\:\s*([^\n]+)\s*')
from easydev import Progress
pb = Progress(len(data))
logger.info('Loading all taxon records.')
for i, record in enumerate(data[0:]):
dd = {'raw': record}
dd['id'] = int(self._child_match.search(record).group(1))
dd['parent'] = int(self._parent_match.search(record).group(1))
dd['scientific_name'] = self._name_match.search(record).group(1)
dd['rank'] = self._rank_match.search(record).group(1)
self.records[dd["id"]] = dd
if self.verbose:
pb.animate(i + 1)
if self.verbose:
print()
def find_taxon(self, taxid, mode="ncbi"):
taxid = str(taxid)
if mode == "ncbi":
from bioservices import EUtils
self.eutils = EUtils(verbose=False)
res = self.eutils.taxonomy_summary(taxid)
else:
res = self.ensembl.get_taxonomy_by_id(taxid)
return res
"""if "error" in res[taxid]:
print("not found in NCBI (EUtils)")
else:
data = res[taxid]
fout.write("ID : {}\n".format(taxid))
#fout.write("PARENT ID : {}\n".format(taxid))
fout.write("RANK : {}\n".format(data['rank']))
#fout.write("GC ID : {}\n".format(data['']))
fout.write("SCIENTIFIC NAME : {}\n".format(data['scientificname']))
"""
@load_taxons
def fetch_by_id(self, taxon):
"""Search for a taxon by identifier
:return; a dictionary.
::
>>> ret = s.search_by_id('10090')
>>> ret['name']
'Mus Musculus'
"""
res = self.ensembl.get_taxonomy_by_id(taxon)
return res
@load_taxons
def fetch_by_name(self, name):
"""Search a taxon by its name.
:param str name: name of an organism. SQL cards possible e.g.,
_ and % characters.
:return: a list of possible matches. Each item being a dictionary.
::
>>> ret = s.search_by_name('Mus Musculus')
>>> ret[0]['id']
10090
"""
res = self.ensembl.get_taxonomy_by_name(name)
return res
def on_web(self, taxon):
"""Open UniProt page for a given taxon"""
# Should work for python2 and 3
import webbrowser
try:
from urllib.request import urlopen
from urllib.error import HTTPError, URLError
except:
from urllib2 import urlopen, HTTPError, URLError
try:
urlopen('http://www.uniprot.org/taxonomy/%s' % taxon)
webbrowser.open("http://www.uniprot.org/taxonomy/%s" % taxon)
except HTTPError as err:
print("Invalid taxon")
except URLError as err:
print(err.args)
@load_taxons
def get_lineage(self, taxon):
"""Get lineage of a taxon
:param int taxon: a known taxon
:return: list containing the lineage
"""
# important to reinit the second argument to []
taxon = int(taxon)
lineage = self._gen_lineage_and_rank(taxon, [])
lineage = [x[0] for x in lineage]
return lineage
@load_taxons
def _gen_lineage_and_rank(self, taxon, lineage_rank=[]):
# recursively filling the lineage argument
try:
record = self.records[taxon]
except:
return [('unknown_taxon:{}'.format(taxon), 'no rank')]
parent = int(record['parent'])
if taxon == 1:
lineage_rank.append((record['scientific_name'], record['rank']))
lineage_rank.reverse()
return lineage_rank
else:
lineage_rank.append((record['scientific_name'], record['rank']))
return self._gen_lineage_and_rank(parent, lineage_rank)
@load_taxons
def get_parent_taxon(self, taxon):
return self.records[taxon]['parent']
@load_taxons
def get_parent_name(self, taxon):
taxid = self.get_parent_taxon(taxon)
return self.records[taxid]['scientific_name']
@load_taxons
def get_lineage_and_rank(self, taxon):
"""Get lineage and rank of a taxon
:param int taxon:
:return: a list of tuples. Each tuple is a pair of taxon name/rank
The list is the lineage for to the input taxon.
"""
taxon = int(taxon)
lineage = self._gen_lineage_and_rank(taxon, [])
return lineage
@load_taxons
def get_ranks(self):
return Counter([x['rank'] for x in self.records.values()])
@load_taxons
def get_record_for_given_rank(self, rank):
return [x for x in self.records.values() if x['rank'] == rank]
@load_taxons
def get_names_for_given_rank(self, rank):
data = [x for x in self.records.values() if x['rank'] == rank]
return [x['scientific_name'] for x in data]
@load_taxons
def get_children(self, taxon):
taxon = str(taxon)
children = [
self.records[k] for k in self.records.keys()
if self.records[k]['parent'] == taxon
]
children = [child['id'] for child in children]
return children
@load_taxons
def get_family_tree(self, taxon):
"""root is taxon and we return the corresponding tree"""
# should limit the tree size
# uniprot flat files has no record about children, so we would
# need to reconstruct the tree
tree = {}
children = self.get_children(taxon)
if len(children) == 0:
return tree
else:
return [self.get_family_tree(child) for child in children]
@load_taxons
def __getitem__(self, iden):
return self.records[iden]
@load_taxons
def __getitem__(self, iden):
return len(self.records)
def append_existing_database(self, filename):
"""
Taxonomy DB looks like::
ID : 2731450
PARENT ID : 1914233
RANK : genus
SCIENTIFIC NAME : Limnoglobus
//
a = NCBITaxonomy("names.dmp", "nodes.dmp")
a.create_taxonomy_file("taxonomy.dat")
tax = Taxonomy()
tax.append_existing_database("taxonomy.dat")
"""
tax = Taxonomy(filename)
tax.load_records()
self.load_records()
toadd = []
for record in tax.records.keys():
if record not in self.records:
toadd.append(record)
with open(self.database, "a") as fout:
for record in toadd:
fout.write(tax.records[record]['raw'] + "//\n")
class KrakenBuilderBase():
def __init__(self, dbname):
from bioservices import EUtils
self.dbname = dbname
self.eutils = EUtils()
self.enadb = ENADownload()
self.category = [
'archaea', 'bacteria', 'fungi', 'invertebrate', 'mitonchondrion',
'other', 'plant', 'plasmid', 'plastid', 'protozoa',
'vertebrate_mammalian', 'vertebrate_other', 'viral'
]
def download_ncbi_refseq(self, category):
"""Download all files of type *fna* from ncbi FTP.
::
kb = KrakenBuilder()
kb.download_ncbi_refseq("viral")
"""
import ftplib
import os
assert category in self.category, "Please use one of {}".format(
self.category)
ftp = ftplib.FTP("ftp.ncbi.nlm.nih.gov")
ftp.login("anonymous", "*****@*****.**")
ftp.cwd("refseq/release/{}".format(category))
import io
file_mapper = {}
for filename in ftp.nlst():
if "genomic.fna" in filename:
ftp.retrbinary('RETR ' + filename, open(filename, "wb").write)
print(filename)
def download_genomes_from_ncbi(self, email, category):
"""This downloads all genomes on ncbi for a given category looking at
their ftp. This could be highly redundant.
"""
assert category in self.category
ftp = ftplib.FTP("ftp.ncbi.nlm.nih.gov")
ftp.login("anonymous", email)
ftp.cwd("refseq/release/{}".format(category))
file_mapper = {}
for filename in ftp.nlst():
if "genomic.fna" in filename:
ftp.retrbinary('RETR ' + filename, open(filename, "wb").write)
logger.info(filename)
def _download_assembly_report(self, category):
assert category in self.category
ftp = ftplib.FTP("ftp.ncbi.nlm.nih.gov")
ftp.login("anonymous", "anonymous")
ftp.cwd("genomes/refseq/{}".format(category))
filename = "assembly_summary.txt"
ftp.retrbinary(
'RETR ' + filename,
open(filename.replace(".txt", "_{}.txt".format(category)),
"wb").write)
logger.info(filename)
def download_accession_from_ncbi(self, accession):
# a list of accessions in a file
# can be a list, a unique string, a filename with 1-column wit accession
# to retrieve
if isinstance(accession, list):
pass
elif isinstance(accession, str):
if os.path.exists(accession):
with open(accession, "r") as fin:
accessions = fin.read().split()
else:
accessions = [accession]
from easydev import Progress
N = len(accessions)
pb = Progress(N)
logger.info("Fetching {} accession fasta files from NCBI".format(N))
for i, accession in enumerate(accessions):
data = self.eutils.EFetch("nucleotide",
rettype="fasta",
id=accession,
retmode="text")
if isinstance(data, int):
logger.info(
"Could not fetch this accession: {}. continue".format(
accession))
print("Could not fetch this accession: {}. continue".format(
accession))
else:
outname = "{}/library/{}.fa".format(self.dbname, accession)
with open(outname, "wb") as fout:
fout.write(data)
pb.animate(i + 1)
accessions = ["O23729", "O23730", "O23731"]
records = []
for accession in accessions:
handle = ExPASy.get_sprot_raw(accession)
record = SwissProt.read(handle)
EC = record.description.split(";")[1].split("=")[1]
records.append(EC)
"""
"""
import mygene
mg = mygene.MyGeneInfo()
g = mg.getgene(100759423)
"""
#https://www.biostars.org/p/104733/
"""
# dela, ampak zelo pocasi...
kegg.find("genes", '100759423')
#Out[386]: 'cge:100759423\tK18311 N-acetylaspartylglutamate/N-acetylaspartylglutamylglutamate synthase [EC:6.3.2.41 6.3.2.42] | (RefSeq) Rimkla; ribosomal modification protein rimK like family member A\n'
"""
#http://nbviewer.jupyter.org/url/pythonhosted.org//bioservices/_downloads/Entrez_EUtils.ipynb
from bioservices import EUtils
e = EUtils()
db = 'gene'
id_list = '100759423'
results = e.EPost(db, id_list)
# we found enough lines, get out
# Removed this line because it was redundant the while will catch
# it, I left it for history
# if len(lines_found) > lines:
# break
# decrement the block counter to get the
# next X bytes
block_counter -= 1
return lines_found[-lines:]
# Link to NCBI EServices
s = EUtils()
N = 21
bottom = 1
max_height = 4
theta = range(0, 21) #np.linspace(0.0, 2 * np.pi, N, endpoint=False)
my_xticks = [
'BB', 'A', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'K', 'L', 'M', 'N', 'P', 'Q',
'R', 'S', 'T', 'V', 'W', 'Y'
]
for f in os.listdir("."):
fname = f.split(".")
# plot SASA from freesasa calculation
if ".sasa" in f:
def __init__(self):
super(Taxon, self).__init__()
# self.df = pd.DataFrame(index=[], columns=["Taxon", "Scientific Name"])
self._eutils_service = EUtils()
self._ensembl_service = Ensembl() # there is a search by name, easier to use than EUtils
