sentence1 stringlengths 52 3.87M | sentence2 stringlengths 1 47.2k | label stringclasses 1
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def load_multiple(filters="*.*", text='Select some files, FACEFACE!', default_directory='default_directory'):
"""
Pops up a dialog for opening more than one file. Returns a list of string paths or None.
"""
# make sure the filters contains "*.*" as an option!
if not '*' in filters.split(';'): filter... | Pops up a dialog for opening more than one file. Returns a list of string paths or None. | entailment |
def Dump(self):
"""
Dumps the current prefs to the preferences.txt file
"""
prefs_file = open(self.prefs_path, 'w')
for n in range(0,len(self.prefs)):
if len(list(self.prefs.items())[n]) > 1:
prefs_file.write(str(list(self.prefs.items())[n][0]) + ' = '... | Dumps the current prefs to the preferences.txt file | entailment |
def link(self):
"""Resolve and link all types in the scope."""
type_specs = {}
types = []
for name, type_spec in self.scope.type_specs.items():
type_spec = type_spec.link(self.scope)
type_specs[name] = type_spec
if type_spec.surface is not None:
... | Resolve and link all types in the scope. | entailment |
def install(path, name=None):
"""Compiles a Thrift file and installs it as a submodule of the caller.
Given a tree organized like so::
foo/
__init__.py
bar.py
my_service.thrift
You would do,
.. code-block:: python
my_service = thriftrw.install('my... | Compiles a Thrift file and installs it as a submodule of the caller.
Given a tree organized like so::
foo/
__init__.py
bar.py
my_service.thrift
You would do,
.. code-block:: python
my_service = thriftrw.install('my_service.thrift')
To install ``m... | entailment |
def loads(self, name, document):
"""Parse and compile the given Thrift document.
:param str name:
Name of the Thrift document.
:param str document:
The Thrift IDL as a string.
"""
return self.compiler.compile(name, document).link().surface | Parse and compile the given Thrift document.
:param str name:
Name of the Thrift document.
:param str document:
The Thrift IDL as a string. | entailment |
def load(self, path, name=None):
"""Load and compile the given Thrift file.
:param str path:
Path to the ``.thrift`` file.
:param str name:
Name of the generated module. Defaults to the base name of the
file.
:returns:
The compiled module.... | Load and compile the given Thrift file.
:param str path:
Path to the ``.thrift`` file.
:param str name:
Name of the generated module. Defaults to the base name of the
file.
:returns:
The compiled module. | entailment |
def get_url_implicit_flow_user(client_id, scope,
redirect_uri='https://oauth.vk.com/blank.html', display='page',
response_type='token', version=None, state=None, revoke=1):
"""
https://vk.com/dev/implicit_flow_user
:return: url
"""
url =... | https://vk.com/dev/implicit_flow_user
:return: url | entailment |
def get_url_authcode_flow_user(client_id, redirect_uri, display="page", scope=None, state=None):
"""Authorization Code Flow for User Access Token
Use Authorization Code Flow to run VK API methods from the server side of an application.
Access token received this way is not bound to an ip address but set of... | Authorization Code Flow for User Access Token
Use Authorization Code Flow to run VK API methods from the server side of an application.
Access token received this way is not bound to an ip address but set of permissions that can be granted is limited for security reasons.
Args:
client_id (int): Ap... | entailment |
def get_fake_data(*a):
"""
Called whenever someone presses the "fire" button.
"""
# add columns of data to the databox
d['x'] = _n.linspace(0,10,100)
d['y'] = _n.cos(d['x']) + 0.1*_n.random.rand(100)
# update the curve
c.setData(d['x'], d['y']) | Called whenever someone presses the "fire" button. | entailment |
def setOpts(self, **opts):
"""
Changes the behavior of the SpinBox. Accepts most of the arguments
allowed in :func:`__init__ <pyqtgraph.SpinBox.__init__>`.
"""
#print opts
for k in opts:
if k == 'bounds':
#print opts[k]
... | Changes the behavior of the SpinBox. Accepts most of the arguments
allowed in :func:`__init__ <pyqtgraph.SpinBox.__init__>`. | entailment |
def setMaximum(self, m, update=True):
"""Set the maximum allowed value (or None for no limit)"""
if m is not None:
m = D(asUnicode(m))
self.opts['bounds'][1] = m
if update:
self.setValue() | Set the maximum allowed value (or None for no limit) | entailment |
def selectNumber(self):
"""
Select the numerical portion of the text to allow quick editing by the user.
"""
le = self.lineEdit()
text = asUnicode(le.text())
if self.opts['suffix'] == '':
le.setSelection(0, len(text))
else:
try:
... | Select the numerical portion of the text to allow quick editing by the user. | entailment |
def value(self):
"""
Return the value of this SpinBox.
"""
if self.opts['int']:
return int(self.val)
else:
return float(self.val) | Return the value of this SpinBox. | entailment |
def setValue(self, value=None, update=True, delaySignal=False):
"""
Set the value of this spin.
If the value is out of bounds, it will be clipped to the nearest boundary.
If the spin is integer type, the value will be coerced to int.
Returns the actual value set.
... | Set the value of this spin.
If the value is out of bounds, it will be clipped to the nearest boundary.
If the spin is integer type, the value will be coerced to int.
Returns the actual value set.
If value is None, then the current value is used (this is for resetting
th... | entailment |
def interpret(self):
"""Return value of text. Return False if text is invalid, raise exception if text is intermediate"""
strn = self.lineEdit().text()
suf = self.opts['suffix']
if len(suf) > 0:
if strn[-len(suf):] != suf:
return False
#raise Excep... | Return value of text. Return False if text is invalid, raise exception if text is intermediate | entailment |
def editingFinishedEvent(self):
"""Edit has finished; set value."""
#print "Edit finished."
if asUnicode(self.lineEdit().text()) == self.lastText:
#print "no text change."
return
try:
val = self.interpret()
except:
return
... | Edit has finished; set value. | entailment |
def make_factory(self, cls, count):
""" Get the generators from the Scaffolding class within the model.
"""
field_names = cls._meta.get_all_field_names()
fields = {}
text = []
finalizer = None
scaffold = scaffolding.scaffold_for_model(cls)
for field_name ... | Get the generators from the Scaffolding class within the model. | entailment |
def compute_indel_length(fs_df):
"""Computes the indel length accounting for wether it is an insertion or
deletion.
Parameters
----------
fs_df : pd.DataFrame
mutation input as dataframe only containing indel mutations
Returns
-------
indel_len : pd.Series
length of ind... | Computes the indel length accounting for wether it is an insertion or
deletion.
Parameters
----------
fs_df : pd.DataFrame
mutation input as dataframe only containing indel mutations
Returns
-------
indel_len : pd.Series
length of indels | entailment |
def keep_indels(mut_df,
indel_len_col=True,
indel_type_col=True):
"""Filters out all mutations that are not indels.
Requires that one of the alleles have '-' indicating either an insertion
or deletion depending if found in reference allele or somatic allele
columns, resp... | Filters out all mutations that are not indels.
Requires that one of the alleles have '-' indicating either an insertion
or deletion depending if found in reference allele or somatic allele
columns, respectively.
Parameters
----------
mut_df : pd.DataFrame
mutation input file as a dataf... | entailment |
def keep_frameshifts(mut_df,
indel_len_col=True):
"""Filters out all mutations that are not frameshift indels.
Requires that one of the alleles have '-' indicating either an insertion
or deletion depending if found in reference allele or somatic allele
columns, respectively.
P... | Filters out all mutations that are not frameshift indels.
Requires that one of the alleles have '-' indicating either an insertion
or deletion depending if found in reference allele or somatic allele
columns, respectively.
Parameters
----------
mut_df : pd.DataFrame
mutation input file... | entailment |
def is_frameshift_len(mut_df):
"""Simply returns a series indicating whether each corresponding mutation
is a frameshift.
This is based on the length of the indel. Thus may be fooled by frameshifts
at exon-intron boundaries or other odd cases.
Parameters
----------
mut_df : pd.DataFrame
... | Simply returns a series indicating whether each corresponding mutation
is a frameshift.
This is based on the length of the indel. Thus may be fooled by frameshifts
at exon-intron boundaries or other odd cases.
Parameters
----------
mut_df : pd.DataFrame
mutation input file as a datafra... | entailment |
def get_frameshift_lengths(num_bins):
"""Simple function that returns the lengths for each frameshift category
if `num_bins` number of frameshift categories are requested.
"""
fs_len = []
i = 1
tmp_bins = 0
while(tmp_bins<num_bins):
if i%3:
fs_len.append(i)
tm... | Simple function that returns the lengths for each frameshift category
if `num_bins` number of frameshift categories are requested. | entailment |
def _init_context(self, gene_seq):
"""Initializes attributes defining mutation contexts and their position.
The self.context2pos and self.pos2context dictionaries map from
sequence context to sequence position and sequence position to
sequence context, respectively. These attributes all... | Initializes attributes defining mutation contexts and their position.
The self.context2pos and self.pos2context dictionaries map from
sequence context to sequence position and sequence position to
sequence context, respectively. These attributes allow for randomly
sampling of mutation p... | entailment |
def random_context_pos(self, num, num_permutations, context):
"""Samples with replacement available positions matching the
sequence context.
Note: this method does random sampling only for an individual
sequence context.
Parameters
----------
num : int
... | Samples with replacement available positions matching the
sequence context.
Note: this method does random sampling only for an individual
sequence context.
Parameters
----------
num : int
Number of positions to sample for each permutation. This
i... | entailment |
def random_pos(self, context_iterable, num_permutations):
"""Obtains random positions w/ replacement which match sequence context.
Parameters
----------
context_iterable: iterable containing two element tuple
Records number of mutations in each context. context_iterable
... | Obtains random positions w/ replacement which match sequence context.
Parameters
----------
context_iterable: iterable containing two element tuple
Records number of mutations in each context. context_iterable
should be something like [('AA', 5), ...].
num_permut... | entailment |
def multiprocess_permutation(bed_dict, mut_df, opts, indel_df=None):
"""Handles parallelization of permutations by splitting work
by chromosome.
"""
chroms = sorted(bed_dict.keys(), key=lambda x: len(bed_dict[x]), reverse=True)
multiprocess_flag = opts['processes']>0
if multiprocess_flag:
... | Handles parallelization of permutations by splitting work
by chromosome. | entailment |
def multiprocess_permutation(bed_dict, mut_df, opts):
"""Handles parallelization of permutations by splitting work
by chromosome.
"""
chroms = sorted(bed_dict.keys())
multiprocess_flag = opts['processes']>0
if multiprocess_flag:
num_processes = opts['processes']
else:
num_pro... | Handles parallelization of permutations by splitting work
by chromosome. | entailment |
def retrieve_scores(gname, sdir,
codon_pos, germ_aa, somatic_aa,
default_mga=5., default_vest=0,
no_file_flag=-1):
"""Retrieves scores from pickle files.
Used by summary script.
"""
# get variant types
#var_class = cutils.get_variant_clas... | Retrieves scores from pickle files.
Used by summary script. | entailment |
def read_vest_pickle(gname, score_dir):
"""Read in VEST scores for given gene.
Parameters
----------
gname : str
name of gene
score_dir : str
directory containing vest scores
Returns
-------
gene_vest : dict or None
dict containing vest scores for gene. Returns ... | Read in VEST scores for given gene.
Parameters
----------
gname : str
name of gene
score_dir : str
directory containing vest scores
Returns
-------
gene_vest : dict or None
dict containing vest scores for gene. Returns None if not found. | entailment |
def compute_vest_stat(vest_dict, ref_aa, somatic_aa, codon_pos,
stat_func=np.mean,
default_val=0.0):
"""Compute missense VEST score statistic.
Note: non-missense mutations are intentially not filtered out and will take
a default value of zero.
Parameters
... | Compute missense VEST score statistic.
Note: non-missense mutations are intentially not filtered out and will take
a default value of zero.
Parameters
----------
vest_dict : dict
dictionary containing vest scores across the gene of interest
ref_aa: list of str
list of reference... | entailment |
def compute_mga_entropy_stat(mga_vec, codon_pos,
stat_func=np.mean,
default_val=0.0):
"""Compute MGA entropy conservation statistic
Parameters
----------
mga_vec : np.array
numpy vector containing MGA Entropy conservation scores for resi... | Compute MGA entropy conservation statistic
Parameters
----------
mga_vec : np.array
numpy vector containing MGA Entropy conservation scores for residues
codon_pos : list of int
position of codon in protein sequence
stat_func : function, default=np.mean
function that calculat... | entailment |
def fetch_vest_scores(vest_dict,
ref_aa, somatic_aa, codon_pos,
default_vest=0.0):
"""Get VEST scores from pre-computed scores in dictionary.
Note: either all mutations should be missense or non-missense intended
to have value equal to default.
Parameters
... | Get VEST scores from pre-computed scores in dictionary.
Note: either all mutations should be missense or non-missense intended
to have value equal to default.
Parameters
----------
vest_dict : dict
dictionary containing vest scores across the gene of interest
ref_aa: list of str
... | entailment |
def fetch_mga_scores(mga_vec,
codon_pos,
default_mga=None):
"""Get MGAEntropy scores from pre-computed scores in array.
Parameters
----------
mga_vec : np.array
numpy vector containing MGA Entropy conservation scores for residues
codon_pos: list of ... | Get MGAEntropy scores from pre-computed scores in array.
Parameters
----------
mga_vec : np.array
numpy vector containing MGA Entropy conservation scores for residues
codon_pos: list of int
position of codon in protein sequence
default_mga: float or None, default=None
value ... | entailment |
def read_neighbor_graph_pickle(gname, graph_dir):
"""Read in neighbor graph for given gene.
Parameters
----------
gname : str
name of gene
graph_dir : str
directory containing gene graphs
Returns
-------
gene_graph : dict or None
neighbor graph as dict for gene.... | Read in neighbor graph for given gene.
Parameters
----------
gname : str
name of gene
graph_dir : str
directory containing gene graphs
Returns
-------
gene_graph : dict or None
neighbor graph as dict for gene. Returns None if not found. | entailment |
def compute_ng_stat(gene_graph, pos_ct, alpha=.5):
"""Compute the clustering score for the gene on its neighbor graph.
Parameters
----------
gene_graph : dict
Graph of spatially near codons. keys = nodes, edges = key -> value.
pos_ct : dict
missense mutation count for each codon
... | Compute the clustering score for the gene on its neighbor graph.
Parameters
----------
gene_graph : dict
Graph of spatially near codons. keys = nodes, edges = key -> value.
pos_ct : dict
missense mutation count for each codon
alpha : float
smoothing factor
Returns
-... | entailment |
def count_frameshift_total(mut_df,
bed_path,
use_unmapped=False,
to_zero_based=False):
"""Count frameshifts for each gene.
Parameters
----------
mut_df : pd.DataFrame
mutation input
bed_path : str
path ... | Count frameshifts for each gene.
Parameters
----------
mut_df : pd.DataFrame
mutation input
bed_path : str
path to BED file containing reference tx for genes
use_unmapped : Bool
flag indicating whether to include frameshifts not mapping
to reference tx
to_zero_ba... | entailment |
def _fetch_3ss_fasta(fasta, gene_name, exon_num,
chrom, strand, start, end):
"""Retreives the 3' SS sequence flanking the specified exon.
Returns a string in fasta format with the first line containing
a ">" and the second line contains the two base pairs of 3' SS.
Parameters
... | Retreives the 3' SS sequence flanking the specified exon.
Returns a string in fasta format with the first line containing
a ">" and the second line contains the two base pairs of 3' SS.
Parameters
----------
fasta : pysam.Fastafile
fasta object from pysam
gene_name : str
gene n... | entailment |
def fetch_gene_fasta(gene_bed, fasta_obj):
"""Retreive gene sequences in FASTA format.
Parameters
----------
gene_bed : BedLine
BedLine object representing a single gene
fasta_obj : pysam.Fastafile
fasta object for index retreival of sequence
Returns
-------
gene_fasta ... | Retreive gene sequences in FASTA format.
Parameters
----------
gene_bed : BedLine
BedLine object representing a single gene
fasta_obj : pysam.Fastafile
fasta object for index retreival of sequence
Returns
-------
gene_fasta : str
sequence of gene in FASTA format | entailment |
def _reset_seq(self):
"""Updates attributes for gene represented in the self.bed attribute.
Sequences are always upper case.
"""
exon_seq_list, five_ss_seq_list, three_ss_seq_list = self._fetch_seq()
self.exon_seq = ''.join(exon_seq_list)
self.three_prime_seq = three_ss_... | Updates attributes for gene represented in the self.bed attribute.
Sequences are always upper case. | entailment |
def add_germline_variants(self, germline_nucs, coding_pos):
"""Add potential germline variants into the nucleotide sequence.
Sequenced individuals may potentially have a SNP at a somatic mutation position.
Therefore they may differ from the reference genome. This method updates the gene
... | Add potential germline variants into the nucleotide sequence.
Sequenced individuals may potentially have a SNP at a somatic mutation position.
Therefore they may differ from the reference genome. This method updates the gene
germline gene sequence to match the actual individual.
Parame... | entailment |
def _to_upper(self):
"""Convert sequences to upper case."""
self.exon_seq = self.exon_seq.upper()
self.three_prime_seq = [s.upper() for s in self.three_prime_seq]
self.five_prime_seq = [s.upper() for s in self.five_prime_seq] | Convert sequences to upper case. | entailment |
def _fetch_seq(self):
"""Fetches gene sequence from PySAM fasta object.
Returns
-------
exons : list of str
list of exon nucleotide sequences
five_prime_ss : list of str
list of 5' splice site sequences
three_prime_ss : list of str
lis... | Fetches gene sequence from PySAM fasta object.
Returns
-------
exons : list of str
list of exon nucleotide sequences
five_prime_ss : list of str
list of 5' splice site sequences
three_prime_ss : list of str
list of 3' splice site sequences | entailment |
def correct_chrom_names(chroms):
"""Make sure chromosome names follow UCSC chr convention."""
chrom_list = []
for chrom in chroms:
# fix chrom numbering
chrom = str(chrom)
chrom = chrom.replace('23', 'X')
chrom = chrom.replace('24', 'Y')
chrom = chrom.replace('25', 'M... | Make sure chromosome names follow UCSC chr convention. | entailment |
def fishers_method(pvals):
"""Fisher's method for combining independent p-values."""
pvals = np.asarray(pvals)
degrees_of_freedom = 2 * pvals.size
chisq_stat = np.sum(-2*np.log(pvals))
fishers_pval = stats.chi2.sf(chisq_stat, degrees_of_freedom)
return fishers_pval | Fisher's method for combining independent p-values. | entailment |
def cummin(x):
"""A python implementation of the cummin function in R"""
for i in range(1, len(x)):
if x[i-1] < x[i]:
x[i] = x[i-1]
return x | A python implementation of the cummin function in R | entailment |
def bh_fdr(pval):
"""A python implementation of the Benjamani-Hochberg FDR method.
This code should always give precisely the same answer as using
p.adjust(pval, method="BH") in R.
Parameters
----------
pval : list or array
list/array of p-values
Returns
-------
pval_adj :... | A python implementation of the Benjamani-Hochberg FDR method.
This code should always give precisely the same answer as using
p.adjust(pval, method="BH") in R.
Parameters
----------
pval : list or array
list/array of p-values
Returns
-------
pval_adj : np.array
adjuste... | entailment |
def calc_deleterious_p_value(mut_info,
unmapped_mut_info,
sc,
gs,
bed,
num_permutations,
stop_thresh,
del_threshold,
... | Calculates the p-value for the number of inactivating SNV mutations.
Calculates p-value based on how many simulations exceed the observed value.
Parameters
----------
mut_info : dict
contains codon and amino acid residue information for mutations mappable
to provided reference tx.
... | entailment |
def calc_protein_p_value(mut_info,
unmapped_mut_info,
sc,
gs,
bed,
graph_dir,
num_permutations,
stop_thresh,
min_recurre... | Computes the p-value for clustering on a neighbor graph composed
of codons connected with edges if they are spatially near in 3D protein
structure.
Parameters
----------
Returns
------- | entailment |
def shannon_entropy(p):
"""Calculates shannon entropy in bits.
Parameters
----------
p : np.array
array of probabilities
Returns
-------
shannon entropy in bits
"""
return -np.sum(np.where(p!=0, p * np.log2(p), 0)) | Calculates shannon entropy in bits.
Parameters
----------
p : np.array
array of probabilities
Returns
-------
shannon entropy in bits | entailment |
def normalized_mutation_entropy(counts, total_cts=None):
"""Calculate the normalized mutation entropy based on a list/array
of mutation counts.
Note: Any grouping of mutation counts together should be done before hand
Parameters
----------
counts : np.array_like
array/list of mutation ... | Calculate the normalized mutation entropy based on a list/array
of mutation counts.
Note: Any grouping of mutation counts together should be done before hand
Parameters
----------
counts : np.array_like
array/list of mutation counts
Returns
-------
norm_ent : float
nor... | entailment |
def kl_divergence(p, q):
"""Compute the Kullback-Leibler (KL) divergence for discrete distributions.
Parameters
----------
p : np.array
"Ideal"/"true" Probability distribution
q : np.array
Approximation of probability distribution p
Returns
-------
kl : float
KL... | Compute the Kullback-Leibler (KL) divergence for discrete distributions.
Parameters
----------
p : np.array
"Ideal"/"true" Probability distribution
q : np.array
Approximation of probability distribution p
Returns
-------
kl : float
KL divergence of approximating p w... | entailment |
def js_divergence(p, q):
"""Compute the Jensen-Shannon Divergence between two discrete distributions.
Parameters
----------
p : np.array
probability mass array (sums to 1)
q : np.array
probability mass array (sums to 1)
Returns
-------
js_div : float
js divergen... | Compute the Jensen-Shannon Divergence between two discrete distributions.
Parameters
----------
p : np.array
probability mass array (sums to 1)
q : np.array
probability mass array (sums to 1)
Returns
-------
js_div : float
js divergence between the two distrubtions | entailment |
def js_distance(p, q):
"""Compute the Jensen-Shannon distance between two discrete distributions.
NOTE: JS divergence is not a metric but the sqrt of JS divergence is a
metric and is called the JS distance.
Parameters
----------
p : np.array
probability mass array (sums to 1)
q : n... | Compute the Jensen-Shannon distance between two discrete distributions.
NOTE: JS divergence is not a metric but the sqrt of JS divergence is a
metric and is called the JS distance.
Parameters
----------
p : np.array
probability mass array (sums to 1)
q : np.array
probability ma... | entailment |
def _filter_utr(self, ex):
"""Filter out UTR regions from the exon list (ie retain only coding regions).
Coding regions are defined by the thickStart and thickEnd attributes.
Parameters
----------
ex : list of tuples
list of exon positions, [(ex1_start, ex1_end), ..... | Filter out UTR regions from the exon list (ie retain only coding regions).
Coding regions are defined by the thickStart and thickEnd attributes.
Parameters
----------
ex : list of tuples
list of exon positions, [(ex1_start, ex1_end), ...]
Returns
-------
... | entailment |
def _init_exons(self):
"""Sets a list of position intervals for each exon.
Only coding regions as defined by thickStart and thickEnd are kept.
Exons are stored in the self.exons attribute.
"""
exon_starts = [self.chrom_start + int(s)
for s in self.bed_tupl... | Sets a list of position intervals for each exon.
Only coding regions as defined by thickStart and thickEnd are kept.
Exons are stored in the self.exons attribute. | entailment |
def init_genome_coordinates(self) :
"""Creates the self.seqpos2genome dictionary that converts positions
relative to the sequence to genome coordinates."""
self.seqpos2genome = {}
# record genome positions for each sequence position
seq_pos = 0
for estart, eend in self.e... | Creates the self.seqpos2genome dictionary that converts positions
relative to the sequence to genome coordinates. | entailment |
def query_position(self, strand, chr, genome_coord):
"""Provides the relative position on the coding sequence for a given
genomic position.
Parameters
----------
chr : str
chromosome, provided to check validity of query
genome_coord : int
0-based ... | Provides the relative position on the coding sequence for a given
genomic position.
Parameters
----------
chr : str
chromosome, provided to check validity of query
genome_coord : int
0-based position for mutation, actually used to get relative coding pos
... | entailment |
def start_logging(log_file='', log_level='INFO', verbose=False):
"""Start logging information into the log directory.
If os.devnull is specified as the log_file then the log file will
not actually be written to a file.
"""
if not log_file:
# create log directory if it doesn't exist
... | Start logging information into the log directory.
If os.devnull is specified as the log_file then the log file will
not actually be written to a file. | entailment |
def log_error_decorator(f):
"""Writes exception to log file if occured in decorated function.
This decorator wrapper is needed for multiprocess logging since otherwise
the python multiprocessing module will obscure the actual line of the error.
"""
@wraps(f)
def wrapper(*args, **kwds):
... | Writes exception to log file if occured in decorated function.
This decorator wrapper is needed for multiprocess logging since otherwise
the python multiprocessing module will obscure the actual line of the error. | entailment |
def filter_list(mylist, bad_ixs):
"""Removes indices from a list.
All elements in bad_ixs will be removed from the list.
Parameters
----------
mylist : list
list to filter out specific indices
bad_ixs : list of ints
indices to remove from list
Returns
-------
mylis... | Removes indices from a list.
All elements in bad_ixs will be removed from the list.
Parameters
----------
mylist : list
list to filter out specific indices
bad_ixs : list of ints
indices to remove from list
Returns
-------
mylist : list
list with elements filte... | entailment |
def rev_comp(seq):
"""Get reverse complement of sequence.
rev_comp will maintain the case of the sequence.
Parameters
----------
seq : str
nucleotide sequence. valid {a, c, t, g, n}
Returns
-------
rev_comp_seq : str
reverse complement of sequence
"""
rev_seq =... | Get reverse complement of sequence.
rev_comp will maintain the case of the sequence.
Parameters
----------
seq : str
nucleotide sequence. valid {a, c, t, g, n}
Returns
-------
rev_comp_seq : str
reverse complement of sequence | entailment |
def bed_generator(bed_path):
"""Iterates through a BED file yielding parsed BED lines.
Parameters
----------
bed_path : str
path to BED file
Yields
------
BedLine(line) : BedLine
A BedLine object which has parsed the individual line in
a BED file.
"""
with o... | Iterates through a BED file yielding parsed BED lines.
Parameters
----------
bed_path : str
path to BED file
Yields
------
BedLine(line) : BedLine
A BedLine object which has parsed the individual line in
a BED file. | entailment |
def read_bed(file_path, restricted_genes=None):
"""Reads BED file and populates a dictionary separating genes
by chromosome.
Parameters
----------
file_path : str
path to BED file
filtered_genes: list
list of gene names to not use
Returns
-------
bed_dict: dict
... | Reads BED file and populates a dictionary separating genes
by chromosome.
Parameters
----------
file_path : str
path to BED file
filtered_genes: list
list of gene names to not use
Returns
-------
bed_dict: dict
dictionary mapping chromosome keys to a list of BED... | entailment |
def _fix_mutation_df(mutation_df, only_unique=False):
"""Drops invalid mutations and corrects for 1-based coordinates.
TODO: Be smarter about what coordinate system is put in the provided
mutations.
Parameters
----------
mutation_df : pd.DataFrame
user provided mutations
only_uniqu... | Drops invalid mutations and corrects for 1-based coordinates.
TODO: Be smarter about what coordinate system is put in the provided
mutations.
Parameters
----------
mutation_df : pd.DataFrame
user provided mutations
only_unique : bool
flag indicating whether only unique mutation... | entailment |
def calc_windowed_sum(aa_mut_pos,
germ_aa,
somatic_aa,
window=[3]):
"""Calculate the sum of mutations within a window around a particular mutated
codon.
Parameters
----------
aa_mut_pos : list
list of mutated amino acid posit... | Calculate the sum of mutations within a window around a particular mutated
codon.
Parameters
----------
aa_mut_pos : list
list of mutated amino acid positions
germ_aa : list
Reference amino acid
somatic_aa : list
Somatic amino acid (if missense)
window : list
... | entailment |
def get_all_context_names(context_num):
"""Based on the nucleotide base context number, return
a list of strings representing each context.
Parameters
----------
context_num : int
number representing the amount of nucleotide base context to use.
Returns
-------
a list of st... | Based on the nucleotide base context number, return
a list of strings representing each context.
Parameters
----------
context_num : int
number representing the amount of nucleotide base context to use.
Returns
-------
a list of strings containing the names of the base contexts | entailment |
def get_chasm_context(tri_nuc):
"""Returns the mutation context acording to CHASM.
For more information about CHASM's mutation context, look
at http://wiki.chasmsoftware.org/index.php/CHASM_Overview.
Essentially CHASM uses a few specified di-nucleotide contexts
followed by single nucleotide context... | Returns the mutation context acording to CHASM.
For more information about CHASM's mutation context, look
at http://wiki.chasmsoftware.org/index.php/CHASM_Overview.
Essentially CHASM uses a few specified di-nucleotide contexts
followed by single nucleotide context.
Parameters
----------
tr... | entailment |
def get_aa_mut_info(coding_pos, somatic_base, gene_seq):
"""Retrieves relevant information about the effect of a somatic
SNV on the amino acid of a gene.
Information includes the germline codon, somatic codon, codon
position, germline AA, and somatic AA.
Parameters
----------
coding_pos : ... | Retrieves relevant information about the effect of a somatic
SNV on the amino acid of a gene.
Information includes the germline codon, somatic codon, codon
position, germline AA, and somatic AA.
Parameters
----------
coding_pos : iterable of ints
Contains the base position (0-based) of... | entailment |
def handle_tsg_results(permutation_result):
"""Handles result from TSG results.
Takes in output from multiprocess_permutation function and converts to
a better formatted dataframe.
Parameters
----------
permutation_result : list
output from multiprocess_permutation
Returns
---... | Handles result from TSG results.
Takes in output from multiprocess_permutation function and converts to
a better formatted dataframe.
Parameters
----------
permutation_result : list
output from multiprocess_permutation
Returns
-------
permutation_df : pd.DataFrame
form... | entailment |
def handle_oncogene_results(permutation_result, num_permutations):
"""Takes in output from multiprocess_permutation function and converts to
a better formatted dataframe.
Parameters
----------
permutation_result : list
output from multiprocess_permutation
Returns
-------
permut... | Takes in output from multiprocess_permutation function and converts to
a better formatted dataframe.
Parameters
----------
permutation_result : list
output from multiprocess_permutation
Returns
-------
permutation_df : pd.DataFrame
formatted output suitable to save | entailment |
def handle_hotmaps_results(permutation_result):
"""Takes in output from multiprocess_permutation function and converts to
a better formatted dataframe.
Parameters
----------
permutation_result : list
output from multiprocess_permutation
Returns
-------
permutation_df : pd.DataF... | Takes in output from multiprocess_permutation function and converts to
a better formatted dataframe.
Parameters
----------
permutation_result : list
output from multiprocess_permutation
Returns
-------
permutation_df : pd.DataFrame
formatted output suitable to save | entailment |
def handle_protein_results(permutation_result):
"""Takes in output from multiprocess_permutation function and converts to
a better formatted dataframe.
Parameters
----------
permutation_result : list
output from multiprocess_permutation
Returns
-------
permutation_df : pd.DataF... | Takes in output from multiprocess_permutation function and converts to
a better formatted dataframe.
Parameters
----------
permutation_result : list
output from multiprocess_permutation
Returns
-------
permutation_df : pd.DataFrame
formatted output suitable to save | entailment |
def handle_effect_results(permutation_result):
"""Takes in output from multiprocess_permutation function and converts to
a better formatted dataframe.
Parameters
----------
permutation_result : list
output from multiprocess_permutation
Returns
-------
permutation_df : pd.DataFr... | Takes in output from multiprocess_permutation function and converts to
a better formatted dataframe.
Parameters
----------
permutation_result : list
output from multiprocess_permutation
Returns
-------
permutation_df : pd.DataFrame
formatted output suitable to save | entailment |
def get_frameshift_info(fs_df, bins):
"""Counts frameshifts stratified by a given length.
Parameters
----------
fs_df : pd.DataFrame
indel mutations from non-coding portion
bins : int
number of different length categories for frameshifts
Returns
-------
indel_len : list... | Counts frameshifts stratified by a given length.
Parameters
----------
fs_df : pd.DataFrame
indel mutations from non-coding portion
bins : int
number of different length categories for frameshifts
Returns
-------
indel_len : list
length of specific frameshift length... | entailment |
def set_mutation_type(self, mut_type=''):
"""Sets the mutation type attribute to a single label based on
attribute flags.
Kwargs:
mut_type (str): value to set self.mut_type
"""
if mut_type:
# user specifies a mutation type
self.mutation_type =... | Sets the mutation type attribute to a single label based on
attribute flags.
Kwargs:
mut_type (str): value to set self.mut_type | entailment |
def set_amino_acid(self, aa):
"""Set amino acid change and position."""
aa = aa.upper() # make sure it is upper case
aa = aa[2:] if aa.startswith('P.') else aa # strip "p."
self.__set_mutation_status() # set flags detailing the type of mutation
self.__parse_hgvs_syntax(aa) | Set amino acid change and position. | entailment |
def __set_mutation_type(self, hgvs_string):
"""Interpret the mutation type (missense, etc.) and set appropriate flags.
Args:
hgvs_string (str): hgvs syntax with "p." removed
"""
self.__set_lost_stop_status(hgvs_string)
self.__set_lost_start_status(hgvs_string)
... | Interpret the mutation type (missense, etc.) and set appropriate flags.
Args:
hgvs_string (str): hgvs syntax with "p." removed | entailment |
def __set_missense_status(self, hgvs_string):
"""Sets the self.is_missense flag."""
# set missense status
if re.search('^[A-Z?]\d+[A-Z?]$', hgvs_string):
self.is_missense = True
self.is_non_silent = True
else:
self.is_missense = False | Sets the self.is_missense flag. | entailment |
def __set_lost_start_status(self, hgvs_string):
"""Sets the self.is_lost_start flag."""
# set is lost start status
mymatch = re.search('^([A-Z?])(\d+)([A-Z?])$', hgvs_string)
if mymatch:
grps = mymatch.groups()
if int(grps[1]) == 1 and grps[0] != grps[2]:
... | Sets the self.is_lost_start flag. | entailment |
def __set_frame_shift_status(self):
"""Check for frame shift and set the self.is_frame_shift flag."""
if 'fs' in self.hgvs_original:
self.is_frame_shift = True
self.is_non_silent = True
elif re.search('[A-Z]\d+[A-Z]+\*', self.hgvs_original):
# it looks like so... | Check for frame shift and set the self.is_frame_shift flag. | entailment |
def __set_lost_stop_status(self, hgvs_string):
"""Check if the stop codon was mutated to something other than
a stop codon."""
lost_stop_pattern = '^\*\d+[A-Z?]+\*?$'
if re.search(lost_stop_pattern, hgvs_string):
self.is_lost_stop = True
self.is_non_silent = True
... | Check if the stop codon was mutated to something other than
a stop codon. | entailment |
def __set_premature_stop_codon_status(self, hgvs_string):
"""Set whether there is a premature stop codon."""
if re.search('.+\*(\d+)?$', hgvs_string):
self.is_premature_stop_codon = True
self.is_non_silent = True
# check if it is also a nonsense mutation
... | Set whether there is a premature stop codon. | entailment |
def __set_indel_status(self):
"""Sets flags related to the mutation being an indel."""
# set indel status
if "ins" in self.hgvs_original:
# mutation is insertion
self.is_insertion = True
self.is_deletion = False
self.is_indel = True
sel... | Sets flags related to the mutation being an indel. | entailment |
def __set_unkown_effect(self, hgvs_string):
"""Sets a flag for unkown effect according to HGVS syntax. The
COSMIC database also uses unconventional questionmarks to denote
missing information.
Args:
hgvs_string (str): hgvs syntax with "p." removed
"""
# Stand... | Sets a flag for unkown effect according to HGVS syntax. The
COSMIC database also uses unconventional questionmarks to denote
missing information.
Args:
hgvs_string (str): hgvs syntax with "p." removed | entailment |
def __set_no_protein(self, hgvs_string):
"""Set a flag for no protein expected. ("p.0" or "p.0?")
Args:
hgvs_string (str): hgvs syntax with "p." removed
"""
no_protein_list = ['0', '0?'] # no protein symbols
if hgvs_string in no_protein_list:
self.is_no_... | Set a flag for no protein expected. ("p.0" or "p.0?")
Args:
hgvs_string (str): hgvs syntax with "p." removed | entailment |
def __parse_hgvs_syntax(self, aa_hgvs):
"""Convert HGVS syntax for amino acid change into attributes.
Specific details of the mutation are stored in attributes like
self.intial (prior to mutation), sel.pos (mutation position),
self.mutated (mutation), and self.stop_pos (position of stop... | Convert HGVS syntax for amino acid change into attributes.
Specific details of the mutation are stored in attributes like
self.intial (prior to mutation), sel.pos (mutation position),
self.mutated (mutation), and self.stop_pos (position of stop codon,
if any).
Args:
... | entailment |
def deleterious_permutation(obs_del,
context_counts,
context_to_mut,
seq_context,
gene_seq,
num_permutations=10000,
stop_criteria=100,
... | Performs null-permutations for deleterious mutation statistics
in a single gene.
Parameters
----------
context_counts : pd.Series
number of mutations for each context
context_to_mut : dict
dictionary mapping nucleotide context to a list of observed
somatic base changes.
... | entailment |
def position_permutation(obs_stat,
context_counts,
context_to_mut,
seq_context,
gene_seq,
gene_vest=None,
num_permutations=10000,
stop_criteria=1... | Performs null-permutations for position-based mutation statistics
in a single gene.
Parameters
----------
obs_stat : tuple, (recur ct, entropy, delta entropy, mean vest)
tuple containing the observed statistics
context_counts : pd.Series
number of mutations for each context
cont... | entailment |
def hotmaps_permutation(obs_stat,
context_counts,
context_to_mut,
seq_context,
gene_seq,
window,
num_permutations=10000,
stop_criteria=100,
... | Performs null-permutations for position-based mutation statistics
in a single gene.
Parameters
----------
obs_stat : dict
dictionary mapping codons to the sum of mutations in a window
context_counts : pd.Series
number of mutations for each context
context_to_mut : dict
d... | entailment |
def protein_permutation(graph_score,
num_codons_obs,
context_counts,
context_to_mut,
seq_context,
gene_seq,
gene_graph,
num_permutations=10000,
... | Performs null-simulations for position-based mutation statistics
in a single gene.
Parameters
----------
graph_score : float
clustering score for observed data
num_codons_obs : int
number of codons with missense mutation in observed data
context_counts : pd.Series
number... | entailment |
def effect_permutation(context_counts,
context_to_mut,
seq_context,
gene_seq,
num_permutations=10000,
pseudo_count=0):
"""Performs null-permutations for effect-based mutation statistics
in a single... | Performs null-permutations for effect-based mutation statistics
in a single gene.
Parameters
----------
context_counts : pd.Series
number of mutations for each context
context_to_mut : dict
dictionary mapping nucleotide context to a list of observed
somatic base changes.
... | entailment |
def non_silent_ratio_permutation(context_counts,
context_to_mut,
seq_context,
gene_seq,
num_permutations=10000):
"""Performs null-permutations for non-silent ratio across all genes.
... | Performs null-permutations for non-silent ratio across all genes.
Parameters
----------
context_counts : pd.Series
number of mutations for each context
context_to_mut : dict
dictionary mapping nucleotide context to a list of observed
somatic base changes.
seq_context : Seque... | entailment |
def summary_permutation(context_counts,
context_to_mut,
seq_context,
gene_seq,
score_dir,
num_permutations=10000,
min_frac=0.0,
min_recur=2,
... | Performs null-permutations and summarizes the results as features over
the gene.
Parameters
----------
context_counts : pd.Series
number of mutations for each context
context_to_mut : dict
dictionary mapping nucleotide context to a list of observed
somatic base changes.
... | entailment |
def maf_permutation(context_counts,
context_to_mut,
seq_context,
gene_seq,
num_permutations=10000,
drop_silent=False):
"""Performs null-permutations across all genes and records the results in
a format like a MAF... | Performs null-permutations across all genes and records the results in
a format like a MAF file. This could be useful for examining the null
permutations because the alternative approaches always summarize the results.
With the simulated null-permutations, novel metrics can be applied to create
an empir... | entailment |
def markdown(value, extensions=settings.MARKDOWN_EXTENSIONS,
extension_configs=settings.MARKDOWN_EXTENSION_CONFIGS,
safe=False):
""" Render markdown over a given value, optionally using varios extensions.
Default extensions could be defined which MARKDOWN_EXTENSIONS option.
:retu... | Render markdown over a given value, optionally using varios extensions.
Default extensions could be defined which MARKDOWN_EXTENSIONS option.
:returns: A rendered markdown | entailment |
def editor_js_initialization(selector, **extra_settings):
""" Return script tag with initialization code. """
init_template = loader.get_template(
settings.MARKDOWN_EDITOR_INIT_TEMPLATE)
options = dict(
previewParserPath=reverse('django_markdown_preview'),
**settings.MARKDOWN_EDITO... | Return script tag with initialization code. | entailment |
def preview(request):
""" Render preview page.
:returns: A rendered preview
"""
if settings.MARKDOWN_PROTECT_PREVIEW:
user = getattr(request, 'user', None)
if not user or not user.is_staff:
from django.contrib.auth.views import redirect_to_login
return redirect_... | Render preview page.
:returns: A rendered preview | entailment |
def register():
""" Register markdown for flatpages. """
admin.site.unregister(FlatPage)
admin.site.register(FlatPage, LocalFlatPageAdmin) | Register markdown for flatpages. | entailment |
def main(argv=None):
"""Command line options."""
program_name = __programm_name__
program_version = "v%s" % __version__
program_descrption = __programm_description__
try:
# Setup argument parser
parser = ArgumentParser(prog=program_name, description=program_descrption)
p... | Command line options. | entailment |
def markdown(value, arg=None):
""" Render markdown over a given value, optionally using varios extensions.
Default extensions could be defined which MARKDOWN_EXTENSIONS option.
Syntax: ::
{{value|markdown}}
{{value|markdown:"tables,codehilite"}}
:returns: A rendered markdown
""... | Render markdown over a given value, optionally using varios extensions.
Default extensions could be defined which MARKDOWN_EXTENSIONS option.
Syntax: ::
{{value|markdown}}
{{value|markdown:"tables,codehilite"}}
:returns: A rendered markdown | entailment |
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