def __init__(self,
intervals_file,
fasta_file,
dnase_file,
cell_line=None,
RNAseq_PC_file=None,
mappability_file=None,
use_linecache=True):
# intervals
if use_linecache:
linecache.clearcache()
BT = BedToolLinecache
else:
BT = BedTool
self.bt = BT(intervals_file)
# Fasta
self.fasta_file = fasta_file
self.fasta_extractor = None # initialize later
# DNase
self.dnase_file = dnase_file
self.dnase_extractor = None
# mappability
if mappability_file is None:
# download the mappability file if not existing
common_dl_dir = os.path.join(this_dir, "../../template/downloaded/dataloader_files")
makedir_exist_ok(common_dl_dir)
rf = RemoteFile(url="http://hgdownload.cse.ucsc.edu/goldenPath/hg19/encodeDCC/wgEncodeMapability/wgEncodeDukeMapabilityUniqueness35bp.bigWig",
md5="1d15ddafe2c8df51cf08495db96679e7")
mappability_file = os.path.join(common_dl_dir, "wgEncodeDukeMapabilityUniqueness35bp.bigWig")
if not os.path.exists(mappability_file) or not rf.validate(mappability_file):
# download the path
rf.get_file(mappability_file)
self.mappability_file = mappability_file
self.mappability_extractor = None
# Get the metadata features
if cell_line is None:
if RNAseq_PC_file is None:
raise ValueError("RNAseq_PC_file has to be specified when cell_line=None")
assert os.path.exists(RNAseq_PC_file)
else:
# Using the pre-defined cell-line
output_dir = os.path.join(this_dir, "../../template/downloaded/dataloader_files/RNAseq_features/")
makedir_exist_ok(output_dir)
RNAseq_PC_file = os.path.join(output_dir, cell_line, "meta.txt")
url_template = ('https://s3.eu-central-1.amazonaws.com/kipoi-models/dataloader_files/'
'FactorNet/dataloader_files/RNAseq_features/{}/meta.txt')
# rf = RemoteFile(url=url_template.format(cell_line))
if not os.path.exists(RNAseq_PC_file): # or not rf.validate(mappability_file):
# download the path
download_url(url_template.format(cell_line), os.path.join(output_dir, cell_line), "meta.txt")
# rf.get_file(RNAseq_PC_file)
self.meta_feat = pd.read_csv(RNAseq_PC_file,
sep="\t", header=None)[0].values
def get_file(self, path):
"""Download the remote file to cache_dir and return
the file path to it
"""
if self.md5:
file_hash = self.md5
else:
file_hash = None
root, filename = os.path.dirname(path), os.path.basename(path)
root = os.path.abspath(root)
download_url(self.url, root, filename, file_hash)
return os.path.join(root, filename)
def get_file(self, path):
"""Download the remote file to cache_dir and return
the file path to it
"""
from kipoi.external.torchvision.dataset_utils import download_url
if self.md5:
file_hash = self.md5
else:
file_hash = None
root, filename = os.path.dirname(path), os.path.basename(path)
root = os.path.abspath(root)
download_url(self.url, root, filename, file_hash)
return os.path.join(root, filename)
def __init__(self,
intervals_file,
fasta_file,
dnase_file,
cell_line=None,
RNAseq_PC_file=None,
mappability_file=None,
GENCODE_dir=None,
use_linecache=True):
# intervals
if use_linecache:
linecache.clearcache()
BT = BedToolLinecache
else:
BT = BedTool
self.bt = BT(intervals_file)
# Fasta
self.fasta_file = fasta_file
self.fasta_extractor = None # initialize later
# DNase
self.dnase_file = dnase_file
self.dnase_extractor = None
# mappability
if mappability_file is None:
# download the mappability file if not existing
common_dl_dir = os.path.join(
this_dir, "../../template/downloaded/dataloader_files")
makedir_exist_ok(common_dl_dir)
rf = RemoteFile(
url=
"http://hgdownload.cse.ucsc.edu/goldenPath/hg19/encodeDCC/wgEncodeMapability/wgEncodeDukeMapabilityUniqueness35bp.bigWig",
md5="1d15ddafe2c8df51cf08495db96679e7")
mappability_file = os.path.join(
common_dl_dir, "wgEncodeDukeMapabilityUniqueness35bp.bigWig")
if not os.path.exists(mappability_file) or not rf.validate(
mappability_file):
# download the path
rf.get_file(mappability_file)
self.mappability_file = mappability_file
self.mappability_extractor = None
# Gencode features
if GENCODE_dir is None:
gp = os.path.join(
this_dir,
"../../template/downloaded/dataloader_files/gencode_features/")
else:
gp = GENCODE_dir
download_gencode_dir(gp) # download files
self.gencode_beds = [
("cpg", BedTool(gp + '/cpgisland.bed.gz')),
("cds",
BedTool(gp + '/wgEncodeGencodeBasicV19.cds.merged.bed.gz')),
("intron",
BedTool(gp + '/wgEncodeGencodeBasicV19.intron.merged.bed.gz')),
("promoter",
BedTool(gp + '/wgEncodeGencodeBasicV19.promoter.merged.bed.gz')),
("utr5",
BedTool(gp + '/wgEncodeGencodeBasicV19.utr5.merged.bed.gz')),
("utr3",
BedTool(gp + '/wgEncodeGencodeBasicV19.utr3.merged.bed.gz')),
]
# Overlap beds - could be done incrementally
print("Overlapping all the bed-files")
# The BT() and .fn are there in order to leverage BedToolLinecache
self.overlap_beds = [(b, BT(self.bt.intersect(v, wa=True, c=True).fn))
for b, v in self.gencode_beds]
print("Assesing the file")
assert len(self.overlap_beds[1][1]) == len(self.bt)
# Get the metadata features
if cell_line is None:
if RNAseq_PC_file is None:
raise ValueError(
"RNAseq_PC_file has to be specified when cell_line=None")
assert os.path.exists(RNAseq_PC_file)
else:
# Using the pre-defined cell-line
output_dir = os.path.join(
this_dir,
"../../template/downloaded/dataloader_files/RNAseq_features/")
makedir_exist_ok(output_dir)
RNAseq_PC_file = os.path.join(output_dir, cell_line, "meta.txt")
url_template = (
'https://s3.eu-central-1.amazonaws.com/kipoi-models/dataloader_files/'
'FactorNet/dataloader_files/RNAseq_features/{}/meta.txt')
# rf = RemoteFile(url=url_template.format(cell_line))
if not os.path.exists(
RNAseq_PC_file): # or not rf.validate(mappability_file):
# download the path
download_url(url_template.format(cell_line),
os.path.join(output_dir, cell_line), "meta.txt")
# rf.get_file(RNAseq_PC_file)
self.meta_feat = pd.read_csv(RNAseq_PC_file, sep="\t",
header=None)[0].values
