def get_colmap(fns, pattern, single_col=False, antipattern=False):
"""For table files, loops through headers and checks which column(s)
match a passed pattern. Those column(s) names are returned in a map with
filenames as keys"""
colmap = {}
for fn in fns:
header = tsvreader.get_tsv_header(fn)
basefn = os.path.basename(fn)
try:
cols = tsvreader.get_cols_in_file(pattern, header, single_col)
except RuntimeError:
# Columns are not in this file
cols = []
if antipattern:
try:
anticols = tsvreader.get_cols_in_file(antipattern, header,
single_col)
except RuntimeError:
# The filtering "anti"-columns are not in the file,
anticols = []
cols = [col for col in cols if col not in anticols]
if cols:
colmap[basefn] = cols
else:
return False
return colmap
def initialize_input(self):
super().initialize_input()
quantheader = reader.get_tsv_header(self.quantfile)
self.quantfields = reader.get_cols_in_file(self.quantcolpattern,
quantheader)
self.quantacc = reader.get_cols_in_file(self.quantacccolpattern,
quantheader, single_col=True)
self.quantpeptides = reader.generate_tsv_proteins(self.quantfile,
quantheader)
def initialize_input(self):
super().initialize_input()
quantheader = reader.get_tsv_header(self.quantfile)
self.quantfields = reader.get_cols_in_file(self.quantcolpattern,
quantheader)
self.quantacc = reader.get_cols_in_file(self.quantacccolpattern,
quantheader,
single_col=True)
self.quantfeatures = reader.generate_tsv_proteins(
self.quantfile, quantheader)
def initialize_input(self):
super().initialize_input()
self.pepheader = tsvreader.get_tsv_header(self.pepfile)
if self.proteincol:
self.get_column_header_for_number(['proteincol'], self.pepheader)
elif self.pcolpattern:
self.proteincol = tsvreader.get_cols_in_file(
self.pcolpattern, self.pepheader, True)
self.scorecol = tsvreader.get_cols_in_file(self.scorecolpattern,
self.pepheader, True)
def initialize_input(self):
self.oldheader = tsvreader.get_tsv_header(self.fn)
self.get_column_header_for_number(['spectracol'])
self.scorecol = tsvreader.get_cols_in_file(self.scorecolpattern,
self.oldheader, True)
self.precurquantcol = prep.get_quantcols(self.precursorquantcolpattern,
self.oldheader, 'precur')
def get_colmap(fns, pattern, single_col=False, antipattern=False):
"""For table files, loops through headers and checks which column(s)
match a passed pattern. Those column(s) names are returned in a map with
filenames as keys"""
colmap = {}
for fn in fns:
header = tsvreader.get_tsv_header(fn)
basefn = os.path.basename(fn)
cols = tsvreader.get_cols_in_file(pattern, header, single_col)
if antipattern:
anticols = tsvreader.get_cols_in_file(antipattern, header,
single_col)
cols = [col for col in cols if col not in anticols]
if cols:
colmap[basefn] = cols
return colmap
def initialize_input(self):
self.oldheader = tsvreader.get_tsv_header(self.fn)
self.get_column_header_for_number(['spectracol'])
self.scorecol = tsvreader.get_cols_in_file(self.scorecolpattern,
self.oldheader, True)
self.precurquantcol = prep.get_quantcols(self.precursorquantcolpattern,
self.oldheader, 'precur')
def get_colmap(fns, pattern, single_col=False, antipattern=False):
"""For table files, loops through headers and checks which column(s)
match a passed pattern. Those column(s) names are returned in a map with
filenames as keys"""
colmap = {}
for fn in fns:
header = tsvreader.get_tsv_header(fn)
basefn = os.path.basename(fn)
cols = tsvreader.get_cols_in_file(pattern, header, single_col)
if antipattern:
anticols = tsvreader.get_cols_in_file(antipattern, header,
single_col)
cols = [col for col in cols if col not in anticols]
if cols:
colmap[basefn] = cols
return colmap
def prepare(self):
self.oldheader = tsvreader.get_tsv_header(self.fn)
self.get_column_header_for_number(['spectracol'])
self.scorecol = tsvreader.get_cols_in_file(self.scorecolpattern,
self.oldheader, True)
self.precurquantcol = psmtopeptable.get_quantcols(self.precursorquantcolpattern,
self.oldheader, 'precur')
def get_td_proteins_bestpep(self, theader, dheader):
self.header = [self.headeraccfield] + prottabledata.PICKED_HEADER
tscorecol = tsvreader.get_cols_in_file(self.scorecolpattern, theader,
True)
dscorecol = tsvreader.get_cols_in_file(self.scorecolpattern, dheader,
True)
tpeps = tsvreader.generate_split_tsv_lines(self.fn, theader)
dpeps = tsvreader.generate_split_tsv_lines(self.decoyfn, dheader)
targets = proteins.generate_bestpep_proteins(tpeps, tscorecol,
self.minlogscore,
self.headeraccfield,
self.fixedfeatcol)
decoys = proteins.generate_bestpep_proteins(dpeps, dscorecol,
self.minlogscore,
self.headeraccfield,
self.fixedfeatcol)
return targets, decoys
def get_quantcols(pattern, oldheader, coltype):
"""Searches for quantification columns using pattern and header list.
Calls reader function to do regexp. Returns a single column for
precursor quant."""
if pattern is None:
return False
if coltype == 'precur':
return reader.get_cols_in_file(pattern, oldheader, single_col=True)
def get_psms(self):
self.header = self.oldheader[:]
if self.confpattern:
confkey = tsvreader.get_cols_in_file(self.confpattern, self.header,
True)
elif self.confcol:
confkey = self.header[int(self.confcol) - 1]
else:
raise RuntimeError('Must define either --confcol or '
'--confcolpattern')
self.psms = prep.generate_psms(self.fn, self.oldheader, confkey,
self.conflvl, self.lowerbetter)
def set_features(self):
self.header = self.oldheader[:]
if self.confpattern:
confkey = tsvreader.get_cols_in_file(self.confpattern,
self.header, True)
elif self.confcol:
confkey = self.header[int(self.confcol) - 1]
else:
print('Must define either --confcol or --confcolpattern')
sys.exit(1)
self.psms = filtering.filter_psms_conf(self.oldpsms,
confkey,
self.conflvl,
self.lowerbetter)
def get_psms(self):
self.header = self.oldheader[:]
if self.confpattern:
confkey = tsvreader.get_cols_in_file(self.confpattern,
self.header, True)
elif self.confcol:
confkey = self.header[int(self.confcol) - 1]
else:
raise RuntimeError('Must define either --confcol or '
'--confcolpattern')
self.psms = prep.generate_psms(self.fn,
self.oldheader,
confkey,
self.conflvl,
self.lowerbetter)
def initialize_input(self):
self.oldheader = tsvreader.get_tsv_header(self.fn)
self.scorecol = tsvreader.get_cols_in_file(self.scorecolpattern,
self.oldheader, True)
self.qvalcol = tsvreader.get_cols_in_file(self.fdrcolpattern,
self.oldheader, True)
def set_features(self):
qpat = self.quantcolpattern if self.quantcolpattern else '[a-z]+[0-9]+plex_'
header = [x for x in self.oldheader if x != psmh.HEADER_SPECFILE]
try:
isocols = tsvreader.get_columns_by_pattern(header, qpat)
except RuntimeError:
pass
else:
for col in isocols:
header.pop(header.index(col))
if self.precurquantcol:
header = [peph.HEADER_AREA if x == self.precurquantcol
else x for x in header]
header = [peph.HEADER_PEPTIDE, peph.HEADER_LINKED_PSMS] + [
x for x in header if x != psmh.HEADER_PEPTIDE]
switch_map = {old: new for old, new in zip(
[psmh.HEADER_PEPTIDE, psmh.HEADER_PROTEIN, psmh.HEADER_PEPTIDE_Q],
[peph.HEADER_PEPTIDE, peph.HEADER_PROTEINS, peph.HEADER_QVAL])}
self.header = [switch_map[field] if field in switch_map else field
for field in header]
peptides = psmtopeptable.generate_peptides(self.fn, self.oldheader,
switch_map, self.scorecol, self.precurquantcol, self.spectracol)
# Remove quant data if not specified any way to summarize
if self.quantcolpattern and any([self.denomcols, self.denompatterns,
self.mediansweep, self.medianintensity]):
denomcols = False
if self.denomcols is not None:
denomcols = [self.number_to_headerfield(col, self.oldheader)
for col in self.denomcols]
elif self.denompatterns is not None:
denomcolnrs = [tsvreader.get_columns_by_pattern(self.oldheader, pattern)
for pattern in self.denompatterns]
denomcols = set([col for cols in denomcolnrs for col in cols])
quantcols = tsvreader.get_columns_by_pattern(self.oldheader,
self.quantcolpattern)
totalproteome, tpacc, tp_pepacc = False, False, False
if self.totalprotfn:
pep_tp_accs = [psmh.HEADER_MASTER_PROT, psmh.HEADER_SYMBOL,
psmh.HEADER_GENE, peph.HEADER_PROTEINS]
totalphead = tsvreader.get_tsv_header(self.totalprotfn)
totalpfield_found = False
for tpacc, tp_pepacc in zip(proth.TPROT_HEADER_ACCS, pep_tp_accs):
if totalphead[0] == tpacc and tp_pepacc in self.header:
totalpfield_found = True
break
if not totalpfield_found:
print('Could not find correct header field name in the total '
'proteome table passed. '
'Should be one of {}'.format(proth.TPROT_HEADER_ACCS))
sys.exit(1)
totalproteome = tsvreader.generate_split_tsv_lines(self.totalprotfn, totalphead)
mn_factors = False
if self.mednorm_factors:
mnhead = tsvreader.get_tsv_header(self.mednorm_factors)
mn_factors = tsvreader.generate_split_tsv_lines(self.mednorm_factors, mnhead)
nopsms = [isosummarize.get_no_psms_field(qf) for qf in quantcols]
self.header = self.header + quantcols + nopsms + [proth.HEADER_NO_FULLQ_PSMS]
peptides = isosummarize.get_isobaric_ratios(self.fn, self.oldheader,
quantcols, denomcols, self.mediansweep, self.medianintensity,
self.median_or_avg, self.minint, peptides, self.header[0],
psmh.HEADER_PEPTIDE, totalproteome, tpacc, tp_pepacc,
self.logisoquant, self.mediannormalize, mn_factors, self.keepnapsms)
if self.modelqvals:
qix = self.header.index(peph.HEADER_QVAL) + 1
self.header = self.header[:qix] + [peph.HEADER_QVAL_MODELED] + self.header[qix:]
scorecol = tsvreader.get_cols_in_file(self.scorecolpattern,
self.oldheader, True)
peptides = psmtopeptable.recalculate_qvals_linear_model(peptides,
scorecol, self.qvalthreshold, self.minpeptidenr)
self.features = peptides
def initialize_input(self):
super().initialize_input()
self.scorecol = reader.get_cols_in_file(self.scorecolpattern,
self.oldheader, True)
def initialize_input(self):
self.oldheader = tsvreader.get_tsv_header(self.fn)
self.scorecol = tsvreader.get_cols_in_file(self.scorecolpattern,
self.oldheader, True)
self.qvalcol = tsvreader.get_cols_in_file(self.fdrcolpattern,
self.oldheader, True)
def initialize_input(self):
super().initialize_input()
self.scorecol = reader.get_cols_in_file(self.scorecolpattern,
self.oldheader, True)
