def ensure_downloaded(callback=None, verbose=True):
"""
Retrieve the taxonomy database if not already downloaded.
"""
serverfiles.localpath_download(
Taxonomy.DOMAIN, Taxonomy.FILENAME,
callback=callback, verbose=verbose)
def ensure_downloaded(callback=None, verbose=True):
"""
Retrieve the taxonomy database if not already downloaded.
"""
serverfiles.localpath_download(Taxonomy.DOMAIN,
Taxonomy.FILENAME,
callback=callback,
verbose=verbose)
def fetch_ncbi_geneinfo(taxid, progress=None):
taxid = gene.NCBIGeneInfo.TAX_MAP.get(taxid, taxid)
sf.localpath_download(
"NCBI_geneinfo",
"gene_info.{taxid}.db".format(taxid=taxid),
callback=progress,
verbose=True,
)
return gene.NCBIGeneInfo(taxid)
def fetch_ppidb(ppisource, taxid, progress=None):
fname = ppisource.sf_filename
if "{taxid}" in fname:
if taxid in ppisource.tax_mapping:
taxid_m = ppisource.tax_mapping[taxid]
if taxid_m is None:
raise ValueError(taxid)
taxid = taxid_m
fname = fname.format(taxid=taxid)
constructor = lambda: ppisource.constructor(taxid)
else:
constructor = ppisource.constructor
sf.localpath_download(ppisource.sf_domain,
fname,
callback=progress,
verbose=True)
return constructor()
def load_miRNA_microCosm(org="mus_musculus", max_pvalue=None, min_score=None):
""" Load miRNA's from microcosm into the global scope (currently
only Mus musculus is supported)
"""
global IDs, LABELS, miRNA_lib, mat_toPre, ACCtoID
global preIDs, premiRNA_lib, preACCtoID, clusters
global num_toClusters, clusters_toNum
file = osf.localpath_download("miRNA", "v5.txt.{org}".format(org=org))
[IDs, LABELS, miRNA_lib, mat_toPre, ACCtoID] = parse_targets_microcosm_v5(file,
max_pvalue=max_pvalue, min_score=min_score)
[preIDs, premiRNA_lib, preACCtoID, clusters] = [], {}, {}, {}
num_toClusters, clusters_toNum = {}, {}
def load_miRNA_microCosm(org="mus_musculus", max_pvalue=None, min_score=None):
""" Load miRNA's from microcosm into the global scope (currently
only Mus musculus is supported)
"""
global IDs, LABELS, miRNA_lib, mat_toPre, ACCtoID
global preIDs, premiRNA_lib, preACCtoID, clusters
global num_toClusters, clusters_toNum
file = osf.localpath_download("miRNA", "v5.txt.{org}".format(org=org))
[IDs, LABELS, miRNA_lib, mat_toPre,
ACCtoID] = parse_targets_microcosm_v5(file,
max_pvalue=max_pvalue,
min_score=min_score)
[preIDs, premiRNA_lib, preACCtoID, clusters] = [], {}, {}, {}
num_toClusters, clusters_toNum = {}, {}
def ensure_downloaded(domain, filename, advance=None):
serverfiles.localpath_download(domain, filename, callback=advance)
def ensure_downloaded(domain, filename, advance=None):
serverfiles.localpath_download(domain, filename, callback=advance)
from __future__ import absolute_import, division
from collections import defaultdict
import math, os, random, re, urllib
import functools
import numpy as np
from orangecontrib.bio.utils import serverfiles as osf
#import statc
from . import gene as ge, go, kegg as kg, utils, taxonomy as obiTaxonomy
op = utils.stats
mirnafile = osf.localpath_download('miRNA','miRNA.txt')
premirnafile = osf.localpath_download('miRNA','premiRNA.txt')
################################################################################################################
################################################################################################################
def __build_lib(filename, labels=True, MATtoPRE=True, ACCtoID=True, clust=False):
"""
build_lib() function takes as input a filename
and gives as output some variables there will be used in
the module.
"""
content = [l.rstrip() for l in open(filename).readlines()][1:]
to_return = []
ids = [l.split('\t')[0] for l in content]
to_return.append(ids)
def __init__(self):
from .ncbi.taxonomy import Taxonomy
# Ensure the taxonomy db is downloaded.
filename = serverfiles.localpath_download(self.DOMAIN, self.FILENAME)
self._tax = Taxonomy(filename)
def __init__(self):
from .ncbi.taxonomy import Taxonomy
# Ensure the taxonomy db is downloaded.
filename = serverfiles.localpath_download(self.DOMAIN, self.FILENAME)
self._tax = Taxonomy(filename)
from __future__ import absolute_import, division
from collections import defaultdict
import math, os, random, re, urllib
import functools
import numpy as np
from orangecontrib.bio.utils import serverfiles as osf
#import statc
from . import gene as ge, go, kegg as kg, utils, taxonomy as obiTaxonomy
op = utils.stats
mirnafile = osf.localpath_download('miRNA', 'miRNA.txt')
premirnafile = osf.localpath_download('miRNA', 'premiRNA.txt')
################################################################################################################
################################################################################################################
def __build_lib(filename,
labels=True,
MATtoPRE=True,
ACCtoID=True,
clust=False):
"""
build_lib() function takes as input a filename
and gives as output some variables there will be used in
the module.
"""
def ensure_downloaded(callback=None, verbose=True):
"""
Retrieve the taxonomy database if not already downloaded.
"""
serverfiles.localpath_download("Taxonomy", "ncbi_taxonomy.tar.gz",
callback=callback, verbose=verbose)
def Load(self):
path = serverfiles.localpath_download("Taxonomy", "ncbi_taxonomy.tar.gz")
self._text = TextDB(os.path.join(path, "ncbi_taxonomy.db"))
self._info = TextDB(os.path.join(path, "ncbi_taxonomy_inf.db"))
