INSTRUCTION stringlengths 1 8.43k | RESPONSE stringlengths 75 104k |
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Reformat data objects as keras - compatible tuples. | def keras_tuples(stream, inputs=None, outputs=None):
"""Reformat data objects as keras-compatible tuples.
For more detail: https://keras.io/models/model/#fit
Parameters
----------
stream : iterable
Stream of data objects.
inputs : string or iterable of strings, None
Keys to us... |
Creates histrogram of motif location. | def location(args):
"""
Creates histrogram of motif location.
Parameters
----------
args : argparse object
Command line arguments.
"""
fastafile = args.fastafile
pwmfile = args.pwmfile
lwidth = args.width
if not lwidth:
f = Fasta(fastafile)
lwidth = len(... |
Find location of executable. | def which(fname):
"""Find location of executable."""
if "PATH" not in os.environ or not os.environ["PATH"]:
path = os.defpath
else:
path = os.environ["PATH"]
for p in [fname] + [os.path.join(x, fname) for x in path.split(os.pathsep)]:
p = os.path.abspath(p)
if os.access(... |
Find all files in a directory by extension. | def find_by_ext(dirname, ext):
"""Find all files in a directory by extension."""
# Get all fasta-files
try:
files = os.listdir(dirname)
except OSError:
if os.path.exists(dirname):
cmd = "find {0} -maxdepth 1 -name \"*\"".format(dirname)
p = sp.Popen(cmd, shel... |
Return list of Motif instances from default motif database. | def default_motifs():
"""Return list of Motif instances from default motif database."""
config = MotifConfig()
d = config.get_motif_dir()
m = config.get_default_params()['motif_db']
if not d or not m:
raise ValueError("default motif database not configured")
fname = os.path.join(d, m)
... |
Convert alignment to motif. | def motif_from_align(align):
"""Convert alignment to motif.
Converts a list with sequences to a motif. Sequences should be the same
length.
Parameters
----------
align : list
List with sequences (A,C,G,T).
Returns
-------
m : Motif instance
Motif created from ... |
Convert consensus sequence to motif. | def motif_from_consensus(cons, n=12):
"""Convert consensus sequence to motif.
Converts a consensus sequences using the nucleotide IUPAC alphabet to a
motif.
Parameters
----------
cons : str
Consensus sequence using the IUPAC alphabet.
n : int , optional
Count used to conv... |
Parse motifs in a variety of formats to return a list of motifs. | def parse_motifs(motifs):
"""Parse motifs in a variety of formats to return a list of motifs.
Parameters
----------
motifs : list or str
Filename of motif, list of motifs or single Motif instance.
Returns
-------
motifs : list
List of Motif instances.
"""
if isin... |
Read motifs from a file - like object. | def _read_motifs_from_filehandle(handle, fmt):
"""
Read motifs from a file-like object.
Parameters
----------
handle : file-like object
Motifs.
fmt : string, optional
Motif format, can be 'pwm', 'transfac', 'xxmotif', 'jaspar' or 'align'.
Returns
-------
motifs... |
Read motifs from a file or stream or file - like object. | def read_motifs(infile=None, fmt="pwm", as_dict=False):
"""
Read motifs from a file or stream or file-like object.
Parameters
----------
infile : string or file-like object, optional
Motif database, filename of motif file or file-like object. If infile
is not specified the default... |
Return the total information content of the motif. | def information_content(self):
"""Return the total information content of the motif.
Return
------
ic : float
Motif information content.
"""
ic = 0
for row in self.pwm:
ic += 2.0 + np.sum([row[x] * log(row[x])/log(2) for x in range(4) if r... |
Return the minimum PWM score. | def pwm_min_score(self):
"""Return the minimum PWM score.
Returns
-------
score : float
Minimum PWM score.
"""
if self.min_score is None:
score = 0
for row in self.pwm:
score += log(min(row) / 0.25 + 0.01)
s... |
Return the maximum PWM score. | def pwm_max_score(self):
"""Return the maximum PWM score.
Returns
-------
score : float
Maximum PWM score.
"""
if self.max_score is None:
score = 0
for row in self.pwm:
score += log(max(row) / 0.25 + 0.01)
s... |
Calculate the log - odds score for a specific k - mer. | def score_kmer(self, kmer):
"""Calculate the log-odds score for a specific k-mer.
Parameters
----------
kmer : str
String representing a kmer. Should be the same length as the motif.
Returns
-------
score : float
Log-odd score.
... |
Convert PFM with counts to a PFM with fractions. | def pfm_to_pwm(self, pfm, pseudo=0.001):
"""Convert PFM with counts to a PFM with fractions.
Parameters
----------
pfm : list
2-dimensional list with counts.
pseudo : float
Pseudocount used in conversion.
Returns
-------
p... |
Return motif formatted in MotEvo ( TRANSFAC - like ) format Returns ------- m: str String of motif in MotEvo format. | def to_motevo(self):
"""Return motif formatted in MotEvo (TRANSFAC-like) format
Returns
-------
m : str
String of motif in MotEvo format.
"""
m = "//\n"
m += "NA {}\n".format(self.id)
m += "P0\tA\tC\tG\tT\n"
for i, row in enume... |
Return motif formatted in TRANSFAC format Returns ------- m: str String of motif in TRANSFAC format. | def to_transfac(self):
"""Return motif formatted in TRANSFAC format
Returns
-------
m : str
String of motif in TRANSFAC format.
"""
m = "%s\t%s\t%s\n" % ("DE", self.id, "unknown")
for i, (row, cons) in enumerate(zip(self.pfm, self.to_consensus... |
Return motif formatted in MEME format Returns ------- m: str String of motif in MEME format. | def to_meme(self):
"""Return motif formatted in MEME format
Returns
-------
m : str
String of motif in MEME format.
"""
motif_id = self.id.replace(" ", "_")
m = "MOTIF %s\n" % motif_id
m += "BL MOTIF %s width=0 seqs=0\n"% motif_id
... |
Calculate the information content of one position. | def ic_pos(self, row1, row2=None):
"""Calculate the information content of one position.
Returns
-------
score : float
Information content.
"""
if row2 is None:
row2 = [0.25,0.25,0.25,0.25]
score = 0
for a,b in zip(row1, row2):
... |
Calculate the Pearson correlation coefficient of one position compared to another position. | def pcc_pos(self, row1, row2):
"""Calculate the Pearson correlation coefficient of one position
compared to another position.
Returns
-------
score : float
Pearson correlation coefficient.
"""
mean1 = np.mean(row1)
mean2 = np.mean(row2)
... |
Return the reverse complemented motif. | def rc(self):
"""Return the reverse complemented motif.
Returns
-------
m : Motif instance
New Motif instance with the reverse complement of the input motif.
"""
m = Motif()
m.pfm = [row[::-1] for row in self.pfm[::-1]]
m.pwm = [row[::-1] for ... |
Trim positions with an information content lower than the threshold. | def trim(self, edge_ic_cutoff=0.4):
"""Trim positions with an information content lower than the threshold.
The default threshold is set to 0.4. The Motif will be changed in-place.
Parameters
----------
edge_ic_cutoff : float, optional
Information content threshold.... |
Scan FASTA with the motif as a consensus sequence. | def consensus_scan(self, fa):
"""Scan FASTA with the motif as a consensus sequence.
Parameters
----------
fa : Fasta object
Fasta object to scan
Returns
-------
matches : dict
Dictionaru with matches.
"""
regexp = ... |
Scan sequences with this motif. | def pwm_scan(self, fa, cutoff=0.9, nreport=50, scan_rc=True):
"""Scan sequences with this motif.
Scan sequences from a FASTA object with this motif. Less efficient
than using a Scanner object. By setting the cutoff to 0.0 and
nreport to 1, the best match for every sequence will be ret... |
Scan sequences with this motif. | def pwm_scan_all(self, fa, cutoff=0.9, nreport=50, scan_rc=True):
"""Scan sequences with this motif.
Scan sequences from a FASTA object with this motif. Less efficient
than using a Scanner object. By setting the cutoff to 0.0 and
nreport to 1, the best match for every sequence will be... |
Scan sequences with this motif and save to a GFF file. | def pwm_scan_to_gff(self, fa, gfffile, cutoff=0.9, nreport=50, scan_rc=True, append=False):
"""Scan sequences with this motif and save to a GFF file.
Scan sequences from a FASTA object with this motif. Less efficient
than using a Scanner object. By setting the cutoff to 0.0 and
nrepor... |
Return the average of two motifs. | def average_motifs(self, other, pos, orientation, include_bg=False):
"""Return the average of two motifs.
Combine this motif with another motif and return the average as a new
Motif object. The position and orientatien need to be supplied. The pos
parameter is the position of the second... |
Return string representation of pwm. | def _pwm_to_str(self, precision=4):
"""Return string representation of pwm.
Parameters
----------
precision : int, optional, default 4
Floating-point precision.
Returns
-------
pwm_string : str
"""
if not self.pwm:
return ... |
Return pwm as string. | def to_pwm(self, precision=4, extra_str=""):
"""Return pwm as string.
Parameters
----------
precision : int, optional, default 4
Floating-point precision.
extra_str |: str, optional
Extra text to include with motif id line.
Retur... |
Create a sequence logo using seqlogo. | def to_img(self, fname, fmt="PNG", add_left=0, seqlogo=None, height=6):
"""Create a sequence logo using seqlogo.
Create a sequence logo and save it to a file. Valid formats are: PNG,
EPS, GIF and PDF.
Parameters
----------
fname : str
Output filename.
... |
Create a new motif with shuffled positions. | def randomize(self):
"""Create a new motif with shuffled positions.
Shuffle the positions of this motif and return a new Motif instance.
Returns
-------
m : Motif instance
Motif instance with shuffled positions.
"""
random_pfm = [[c for c in row] for... |
Run the maelstrom method. | def maelstrom(args):
"""Run the maelstrom method."""
infile = args.inputfile
genome = args.genome
outdir = args.outdir
pwmfile = args.pwmfile
methods = args.methods
ncpus = args.ncpus
if not os.path.exists(infile):
raise ValueError("file {} does not exist".format(infile))
... |
Send data e. g. { key: np. ndarray } with metadata | def zmq_send_data(socket, data, flags=0, copy=True, track=False):
"""Send data, e.g. {key: np.ndarray}, with metadata"""
header, payload = [], []
for key in sorted(data.keys()):
arr = data[key]
if not isinstance(arr, np.ndarray):
raise DataError('Only ndarray types can be seri... |
Receive data over a socket. | def zmq_recv_data(socket, flags=0, copy=True, track=False):
"""Receive data over a socket."""
data = dict()
msg = socket.recv_multipart(flags=flags, copy=copy, track=track)
headers = json.loads(msg[0].decode('ascii'))
if len(headers) == 0:
raise StopIteration
for header, payload in ... |
Note: A ZMQStreamer does not activate its stream but allows the zmq_worker to do that. | def iterate(self, max_iter=None):
"""
Note: A ZMQStreamer does not activate its stream,
but allows the zmq_worker to do that.
Yields
------
data : dict
Data drawn from `streamer(max_iter)`.
"""
context = zmq.Context()
if six.PY2:
... |
Mask all lowercase nucleotides with N s | def hardmask(self):
""" Mask all lowercase nucleotides with N's """
p = re.compile("a|c|g|t|n")
for seq_id in self.fasta_dict.keys():
self.fasta_dict[seq_id] = p.sub("N", self.fasta_dict[seq_id])
return self |
Return n random sequences from this Fasta object | def get_random(self, n, l=None):
""" Return n random sequences from this Fasta object """
random_f = Fasta()
if l:
ids = self.ids[:]
random.shuffle(ids)
i = 0
while (i < n) and (len(ids) > 0):
seq_id = ids.pop()
if (... |
Write sequences to FASTA formatted file | def writefasta(self, fname):
""" Write sequences to FASTA formatted file"""
f = open(fname, "w")
fa_str = "\n".join([">%s\n%s" % (id, self._format_seq(seq)) for id, seq in self.items()])
f.write(fa_str)
f.close() |
Clusters a set of sequence motifs. Required arg motifs is a file containing positional frequency matrices or an array with motifs. | def cluster_motifs(motifs, match="total", metric="wic", combine="mean", pval=True, threshold=0.95, trim_edges=False, edge_ic_cutoff=0.2, include_bg=True, progress=True, ncpus=None):
"""
Clusters a set of sequence motifs. Required arg 'motifs' is a file containing
positional frequency matrices or an array w... |
Determine the number of samples in a batch. | def batch_length(batch):
'''Determine the number of samples in a batch.
Parameters
----------
batch : dict
A batch dictionary. Each value must implement `len`.
All values must have the same `len`.
Returns
-------
n : int >= 0 or None
The number of samples in this b... |
Activates a number of streams | def _activate(self):
"""Activates a number of streams"""
self.distribution_ = 1. / self.n_streams * np.ones(self.n_streams)
self.valid_streams_ = np.ones(self.n_streams, dtype=bool)
self.streams_ = [None] * self.k
self.stream_weights_ = np.zeros(self.k)
self.stream_coun... |
Randomly select and create a stream. | def _new_stream(self, idx):
'''Randomly select and create a stream.
Parameters
----------
idx : int, [0:n_streams - 1]
The stream index to replace
'''
# instantiate
if self.rate is not None:
n_stream = 1 + self.rng.poisson(lam=self.rate)
... |
Yields items from the mux and handles stream exhaustion and replacement. | def iterate(self, max_iter=None):
"""Yields items from the mux, and handles stream exhaustion and
replacement.
"""
if max_iter is None:
max_iter = np.inf
# Calls Streamer's __enter__, which calls activate()
with self as active_mux:
# Main sampling... |
StochasticMux chooses its next sample stream randomly | def _next_sample_index(self):
"""StochasticMux chooses its next sample stream randomly"""
return self.rng.choice(self.n_active,
p=(self.stream_weights_ /
self.weight_norm_)) |
Randomly select and create a stream. | def _activate_stream(self, idx):
'''Randomly select and create a stream.
StochasticMux adds mode handling to _activate_stream, making it so that
if we're not sampling "with_replacement", the distribution for this
chosen streamer is set to 0, causing the streamer not to be available
... |
Randomly select and create a new stream. | def _new_stream(self, idx):
'''Randomly select and create a new stream.
Parameters
----------
idx : int, [0:n_streams - 1]
The stream index to replace
'''
# Choose the stream index from the candidate pool
self.stream_idxs_[idx] = self.rng.choice(
... |
ShuffledMux s activate is similar to StochasticMux but there is no n_active since all the streams are always available. | def _activate(self):
"""ShuffledMux's activate is similar to StochasticMux,
but there is no 'n_active', since all the streams are always available.
"""
self.streams_ = [None] * self.n_streams
# Weights of the active streams.
# Once a stream is exhausted, it is set to 0.
... |
ShuffledMux chooses its next sample stream randomly conditioned on the stream weights. | def _next_sample_index(self):
"""ShuffledMux chooses its next sample stream randomly,
conditioned on the stream weights.
"""
return self.rng.choice(self.n_streams,
p=(self.stream_weights_ /
self.weight_norm_)) |
Randomly select and create a new stream. | def _new_stream(self, idx):
'''Randomly select and create a new stream.
Parameters
----------
idx : int, [0:n_streams - 1]
The stream index to replace
'''
# Don't activate the stream if the weight is 0 or None
if self.stream_weights_[idx]:
... |
Rotates through each active sampler by incrementing the index | def _next_sample_index(self):
"""Rotates through each active sampler by incrementing the index"""
# Return the next streamer index where the streamer is not None,
# wrapping around.
idx = self.active_index_
self.active_index_ += 1
if self.active_index_ >= len(self.stream... |
Activate a new stream given the index into the stream pool. | def _new_stream(self, idx):
"""Activate a new stream, given the index into the stream pool.
BaseMux's _new_stream simply chooses a new stream and activates it.
For special behavior (ie Weighted streams), you must override this
in a child class.
Parameters
----------
... |
Called by BaseMux s iterate () when a stream is exhausted. Set the stream to None so it is ignored once exhausted. | def _replace_stream(self, idx=None):
"""Called by `BaseMux`'s iterate() when a stream is exhausted.
Set the stream to None so it is ignored once exhausted.
Parameters
----------
idx : int or None
Raises
------
StopIteration
If all streams are... |
Grab the next stream from the input streamers and start it. | def _new_stream(self):
'''Grab the next stream from the input streamers, and start it.
Raises
------
StopIteration
When the input list or generator of streamers is complete,
will raise a StopIteration. If `mode == cycle`, it
will instead restart itera... |
Shuffle X and Y into n/ len ( paths ) datasets and save them to disk at the locations provided in paths. | def split_and_save_datasets(X, Y, paths):
"""Shuffle X and Y into n / len(paths) datasets, and save them
to disk at the locations provided in paths.
"""
shuffled_idxs = np.random.permutation(np.arange(len(X)))
for i in range(len(paths)):
# Take every len(paths) item, starting at i.
... |
Generate data from an npz file. | def npz_generator(npz_path):
"""Generate data from an npz file."""
npz_data = np.load(npz_path)
X = npz_data['X']
# Y is a binary maxtrix with shape=(n, k), each y will have shape=(k,)
y = npz_data['Y']
n = X.shape[0]
while True:
i = np.random.randint(0, n)
yield {'X': X[i]... |
Current hypergeometric implementation in scipy is broken so here s the correct version | def phyper(k, good, bad, N):
""" Current hypergeometric implementation in scipy is broken, so here's the correct version """
pvalues = [phyper_single(x, good, bad, N) for x in range(k + 1, N + 1)]
return np.sum(pvalues) |
Read input from <bedfile > set the width of all entries to <width > and write the result to <outfile >. Input file needs to be in BED or WIG format. | def write_equalwidth_bedfile(bedfile, width, outfile):
"""Read input from <bedfile>, set the width of all entries to <width> and
write the result to <outfile>.
Input file needs to be in BED or WIG format."""
BUFSIZE = 10000
f = open(bedfile)
out = open(outfile, "w")
lines = f.readlines(BUF... |
Calculate enrichment based on hypergeometric distribution | def calc_motif_enrichment(sample, background, mtc=None, len_sample=None, len_back=None):
"""Calculate enrichment based on hypergeometric distribution"""
INF = "Inf"
if mtc not in [None, "Bonferroni", "Benjamini-Hochberg", "None"]:
raise RuntimeError("Unknown correction: %s" % mtc)
sig = ... |
Provide either a file with one cutoff per motif or a single cutoff returns a hash with motif id as key and cutoff as value | def parse_cutoff(motifs, cutoff, default=0.9):
""" Provide either a file with one cutoff per motif or a single cutoff
returns a hash with motif id as key and cutoff as value
"""
cutoffs = {}
if os.path.isfile(str(cutoff)):
for i,line in enumerate(open(cutoff)):
if line !... |
Detect file type. | def determine_file_type(fname):
"""
Detect file type.
The following file types are supported:
BED, narrowPeak, FASTA, list of chr:start-end regions
If the extension is bed, fa, fasta or narrowPeak, we will believe this
without checking!
Parameters
----------
fname : str
Fil... |
automagically determine input type the following types are detected: - Fasta object - FASTA file - list of regions - region file - BED file | def get_seqs_type(seqs):
"""
automagically determine input type
the following types are detected:
- Fasta object
- FASTA file
- list of regions
- region file
- BED file
"""
region_p = re.compile(r'^(.+):(\d+)-(\d+)$')
if isinstance(seqs, Fasta):
re... |
Return md5 checksum of file. | def file_checksum(fname):
"""Return md5 checksum of file.
Note: only works for files < 4GB.
Parameters
----------
filename : str
File used to calculate checksum.
Returns
-------
checkum : str
"""
size = os.path.getsize(fname)
with open(fname, "r+") as f:
... |
Download gene annotation from UCSC based on genomebuild. | def download_annotation(genomebuild, gene_file):
"""
Download gene annotation from UCSC based on genomebuild.
Will check UCSC, Ensembl and RefSeq annotation.
Parameters
----------
genomebuild : str
UCSC genome name.
gene_file : str
Output file name.
"""
pred_bin = ... |
Check if dir exists if not: give warning and die | def _check_dir(self, dirname):
""" Check if dir exists, if not: give warning and die"""
if not os.path.exists(dirname):
print("Directory %s does not exist!" % dirname)
sys.exit(1) |
Index a single one - sequence fasta - file | def _make_index(self, fasta, index):
""" Index a single, one-sequence fasta-file"""
out = open(index, "wb")
f = open(fasta)
# Skip first line of fasta-file
line = f.readline()
offset = f.tell()
line = f.readline()
while line:
out.write(pack(sel... |
Index all fasta - files in fasta_dir ( one sequence per file! ) and store the results in index_dir | def create_index(self,fasta_dir=None, index_dir=None):
"""Index all fasta-files in fasta_dir (one sequence per file!) and
store the results in index_dir"""
# Use default directories if they are not supplied
if not fasta_dir:
fasta_dir = self.fasta_dir
if not... |
read the param_file index_dir should already be set | def _read_index_file(self):
"""read the param_file, index_dir should already be set """
param_file = os.path.join(self.index_dir, self.param_file)
with open(param_file) as f:
for line in f.readlines():
(name, fasta_file, index_file, line_size, total_size) = line.strip... |
retrieve a number of lines from a fasta file - object starting at offset | def _read_seq_from_fasta(self, fasta, offset, nr_lines):
""" retrieve a number of lines from a fasta file-object, starting at offset"""
fasta.seek(offset)
lines = [fasta.readline().strip() for _ in range(nr_lines)]
return "".join(lines) |
Retrieve multiple sequences from same chr ( RC not possible yet ) | def get_sequences(self, chr, coords):
""" Retrieve multiple sequences from same chr (RC not possible yet)"""
# Check if we have an index_dir
if not self.index_dir:
print("Index dir is not defined!")
sys.exit()
# retrieve all information for this specific sequ... |
Retrieve a sequence | def get_sequence(self, chrom, start, end, strand=None):
""" Retrieve a sequence """
# Check if we have an index_dir
if not self.index_dir:
print("Index dir is not defined!")
sys.exit()
# retrieve all information for this specific sequence
fasta_file =... |
Return the sizes of all sequences in the index or the size of chrom if specified as an optional argument | def get_size(self, chrom=None):
""" Return the sizes of all sequences in the index, or the size of chrom if specified
as an optional argument """
if len(self.size) == 0:
raise LookupError("no chromosomes in index, is the index correct?")
if chrom:
if chrom in sel... |
Returns an instance of a specific tool. | def get_tool(name):
"""
Returns an instance of a specific tool.
Parameters
----------
name : str
Name of the tool (case-insensitive).
Returns
-------
tool : MotifProgram instance
"""
tool = name.lower()
if tool not in __tools__:
raise ValueError("Tool {0} n... |
Returns the binary of a tool. | def locate_tool(name, verbose=True):
"""
Returns the binary of a tool.
Parameters
----------
name : str
Name of the tool (case-insensitive).
Returns
-------
tool_bin : str
Binary of tool.
"""
m = get_tool(name)
tool_bin = which(m.cmd)
if tool_bin:
... |
Get the command used to run the tool. | def bin(self):
"""
Get the command used to run the tool.
Returns
-------
command : str
The tool system command.
"""
if self.local_bin:
return self.local_bin
else:
return self.config.bin(self.name) |
Check if the tool is installed. Returns ------- is_installed: bool True if the tool is installed. | def is_installed(self):
"""
Check if the tool is installed.
Returns
-------
is_installed : bool
True if the tool is installed.
"""
return self.is_configured() and os.access(self.bin(), os.X_OK) |
Run the tool and predict motifs from a FASTA file. | def run(self, fastafile, params=None, tmp=None):
"""
Run the tool and predict motifs from a FASTA file.
Parameters
----------
fastafile : str
Name of the FASTA input file.
params : dict, optional
Optional parameters. For some of the tools require... |
Parse parameters. | def _parse_params(self, params=None):
"""
Parse parameters.
Combine default and user-defined parameters.
"""
prm = self.default_params.copy()
if params is not None:
prm.update(params)
if prm["background"]:
# Absolute path, just to be su... |
Run XXmotif and predict motifs from a FASTA file. | def _run_program(self, bin, fastafile, params=None):
"""
Run XXmotif and predict motifs from a FASTA file.
Parameters
----------
bin : str
Command used to run the tool.
fastafile : str
Name of the FASTA input file.
params : dict,... |
Parse parameters. | def _parse_params(self, params=None):
"""
Parse parameters.
Combine default and user-defined parameters.
"""
prm = self.default_params.copy()
if params is not None:
prm.update(params)
# Background file is essential!
if not prm["background"]... |
Run Homer and predict motifs from a FASTA file. | def _run_program(self, bin, fastafile, params=None):
"""
Run Homer and predict motifs from a FASTA file.
Parameters
----------
bin : str
Command used to run the tool.
fastafile : str
Name of the FASTA input file.
params : dict, o... |
Convert BioProspector output to motifs Parameters ---------- fo: file - like File object containing BioProspector output. | def parse(self, fo):
"""
Convert BioProspector output to motifs
Parameters
----------
fo : file-like
File object containing BioProspector output.
Returns
-------
motifs : list
List of Motif instances.
"""
m... |
Run HMS and predict motifs from a FASTA file. | def _run_program(self, bin, fastafile, params=None):
"""
Run HMS and predict motifs from a FASTA file.
Parameters
----------
bin : str
Command used to run the tool.
fastafile : str
Name of the FASTA input file.
params : dict, opt... |
Convert HMS output to motifs Parameters ---------- fo: file - like File object containing HMS output. | def parse(self, fo):
"""
Convert HMS output to motifs
Parameters
----------
fo : file-like
File object containing HMS output.
Returns
-------
motifs : list
List of Motif instances.
"""
motifs = []
m... |
Run AMD and predict motifs from a FASTA file. | def _run_program(self, bin, fastafile, params=None):
"""
Run AMD and predict motifs from a FASTA file.
Parameters
----------
bin : str
Command used to run the tool.
fastafile : str
Name of the FASTA input file.
params : dict, opt... |
Convert AMD output to motifs Parameters ---------- fo: file - like File object containing AMD output. | def parse(self, fo):
"""
Convert AMD output to motifs
Parameters
----------
fo : file-like
File object containing AMD output.
Returns
-------
motifs : list
List of Motif instances.
"""
motifs = []
... |
Convert Improbizer output to motifs Parameters ---------- fo: file - like File object containing Improbizer output. | def parse(self, fo):
"""
Convert Improbizer output to motifs
Parameters
----------
fo : file-like
File object containing Improbizer output.
Returns
-------
motifs : list
List of Motif instances.
"""
motifs ... |
Run Trawler and predict motifs from a FASTA file. | def _run_program(self, bin, fastafile, params=None):
"""
Run Trawler and predict motifs from a FASTA file.
Parameters
----------
bin : str
Command used to run the tool.
fastafile : str
Name of the FASTA input file.
params : dict,... |
Run Weeder and predict motifs from a FASTA file. | def _run_program(self, bin,fastafile, params=None):
"""
Run Weeder and predict motifs from a FASTA file.
Parameters
----------
bin : str
Command used to run the tool.
fastafile : str
Name of the FASTA input file.
params : dict, o... |
Parse parameters. | def _parse_params(self, params=None):
"""
Parse parameters.
Combine default and user-defined parameters.
"""
prm = self.default_params.copy()
if params is not None:
prm.update(params)
if prm["background_model"]:
# Absolute path, just to... |
Run MotifSampler and predict motifs from a FASTA file. | def _run_program(self, bin, fastafile, params=None):
"""
Run MotifSampler and predict motifs from a FASTA file.
Parameters
----------
bin : str
Command used to run the tool.
fastafile : str
Name of the FASTA input file.
params : ... |
Convert MotifSampler output to motifs Parameters ---------- fo: file - like File object containing MotifSampler output. | def parse(self, fo):
"""
Convert MotifSampler output to motifs
Parameters
----------
fo : file-like
File object containing MotifSampler output.
Returns
-------
motifs : list
List of Motif instances.
"""
mot... |
Convert MotifSampler output to motifs Parameters ---------- fo: file - like File object containing MotifSampler output. | def parse_out(self, fo):
"""
Convert MotifSampler output to motifs
Parameters
----------
fo : file-like
File object containing MotifSampler output.
Returns
-------
motifs : list
List of Motif instances.
"""
... |
Run MDmodule and predict motifs from a FASTA file. | def _run_program(self, bin, fastafile, params=None):
"""
Run MDmodule and predict motifs from a FASTA file.
Parameters
----------
bin : str
Command used to run the tool.
fastafile : str
Name of the FASTA input file.
params : dict... |
Convert MDmodule output to motifs Parameters ---------- fo: file - like File object containing MDmodule output. | def parse(self, fo):
"""
Convert MDmodule output to motifs
Parameters
----------
fo : file-like
File object containing MDmodule output.
Returns
-------
motifs : list
List of Motif instances.
"""
motifs = []... |
Parse parameters. | def _parse_params(self, params=None):
"""
Parse parameters.
Combine default and user-defined parameters.
"""
prm = self.default_params.copy()
if params is not None:
prm.update(params)
return prm |
Run ChIPMunk and predict motifs from a FASTA file. | def _run_program(self, bin, fastafile, params=None):
"""
Run ChIPMunk and predict motifs from a FASTA file.
Parameters
----------
bin : str
Command used to run the tool.
fastafile : str
Name of the FASTA input file.
params : dict... |
Convert ChIPMunk output to motifs Parameters ---------- fo: file - like File object containing ChIPMunk output. | def parse(self, fo):
"""
Convert ChIPMunk output to motifs
Parameters
----------
fo : file-like
File object containing ChIPMunk output.
Returns
-------
motifs : list
List of Motif instances.
"""
#KDIC|6.124... |
Run Posmo and predict motifs from a FASTA file. | def _run_program(self, bin, fastafile, params=None):
"""
Run Posmo and predict motifs from a FASTA file.
Parameters
----------
bin : str
Command used to run the tool.
fastafile : str
Name of the FASTA input file.
params : dict, o... |
Convert Posmo output to motifs Parameters ---------- fo: file - like File object containing Posmo output. | def parse(self, fo, width, seed=None):
"""
Convert Posmo output to motifs
Parameters
----------
fo : file-like
File object containing Posmo output.
Returns
-------
motifs : list
List of Motif instances.
"""
... |
Convert GADEM output to motifs Parameters ---------- fo: file - like File object containing GADEM output. | def parse(self, fo):
"""
Convert GADEM output to motifs
Parameters
----------
fo : file-like
File object containing GADEM output.
Returns
-------
motifs : list
List of Motif instances.
"""
motifs = []
... |
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