def write_out(new_exp, multipeptides, outfile, matrix_outfile, single_outfile):
""" Write the result to disk
"""
# write out the complete original files
writer = csv.writer(open(outfile, "w"), delimiter="\t")
header_first = new_exp.runs[0].header
for run in new_exp.runs:
assert header_first == run.header
writer.writerow(header_first)
print "number of precursors quantified:", len(multipeptides)
for m in multipeptides:
# selected_peakgroups = [p.peakgroups[0] for p in m.get_peptides()]
# if (len(selected_peakgroups)*2.0 / len(new_exp.runs) < fraction_needed_selected) : continue
for p in m.getAllPeptides():
for selected_pg in p.peakgroups:
if single_outfile:
# Only write the newly imputed ones ...
if float(selected_pg.get_value("m_score")) > 1.0:
row_to_write = selected_pg.row
writer.writerow(row_to_write)
else:
row_to_write = selected_pg.row
writer.writerow(row_to_write)
if len(matrix_outfile) > 0:
helper.write_out_matrix_file(matrix_outfile, new_exp.runs, multipeptides, 0.0, style=options.matrix_output_method)
def write_out(new_exp, multipeptides, outfile, matrix_outfile, single_outfile=None):
""" Write the result to disk
This writes all peakgroups to disk (newly imputed ones as previously found
ones) as even some "previously good" peakgroups may have changed location
due to isotopic_transfer.
"""
# write out the complete original files
writer = csv.writer(open(outfile, "w"), delimiter="\t")
header_first = new_exp.runs[0].header
for run in new_exp.runs:
assert header_first == run.header
writer.writerow(header_first)
print("number of precursors quantified:", len(multipeptides))
for m in sorted(multipeptides, key=lambda x: str(x)):
# selected_peakgroups = [p.peakgroups[0] for p in m.get_peptides()]
# if (len(selected_peakgroups)*2.0 / len(new_exp.runs) < fraction_needed_selected) : continue
for p in m.getAllPeptides():
for selected_pg in sorted(p.peakgroups):
if single_outfile is not None:
if single_outfile == selected_pg.get_value("run_id"):
# Only write the values for this run ...
row_to_write = selected_pg.row
writer.writerow(row_to_write)
else:
row_to_write = selected_pg.row
writer.writerow(row_to_write)
if len(matrix_outfile) > 0:
helper.write_out_matrix_file(matrix_outfile, new_exp.runs, multipeptides, 0.0, style=options.matrix_output_method)
def write_out(new_exp, multipeptides, outfile, matrix_outfile, single_outfile=None):
""" Write the result to disk
This writes all peakgroups to disk (newly imputed ones as previously found
ones) as even some "previously good" peakgroups may have changed location
due to isotopic_transfer.
"""
# write out the complete original files
writer = csv.writer(open(outfile, "w"), delimiter="\t")
header_first = new_exp.runs[0].header
for run in new_exp.runs:
assert header_first == run.header
writer.writerow(header_first)
print("number of precursors quantified:", len(multipeptides))
for m in sorted(multipeptides, key=lambda x: str(x)):
# selected_peakgroups = [p.peakgroups[0] for p in m.get_peptides()]
# if (len(selected_peakgroups)*2.0 / len(new_exp.runs) < fraction_needed_selected) : continue
for p in m.getAllPeptides():
for selected_pg in sorted(p.peakgroups):
if single_outfile is not None:
if single_outfile == selected_pg.get_value("run_id"):
# Only write the values for this run ...
row_to_write = selected_pg.row
writer.writerow(row_to_write)
else:
row_to_write = selected_pg.row
writer.writerow(row_to_write)
if len(matrix_outfile) > 0:
helper.write_out_matrix_file(matrix_outfile, new_exp.runs, multipeptides, 0.0, style=options.matrix_output_method)
def write_out(new_exp, multipeptides, outfile, matrix_outfile, single_outfile):
""" Write the result to disk
"""
# write out the complete original files
writer = csv.writer(open(outfile, "w"), delimiter="\t")
header_first = new_exp.runs[0].header
for run in new_exp.runs:
assert header_first == run.header
writer.writerow(header_first)
print "number of precursors quantified:", len(multipeptides)
for m in multipeptides:
# selected_peakgroups = [p.peakgroups[0] for p in m.get_peptides()]
# if (len(selected_peakgroups)*2.0 / len(new_exp.runs) < fraction_needed_selected) : continue
for p in m.getAllPeptides():
for selected_pg in p.peakgroups:
if single_outfile:
# Only write the newly imputed ones ...
if float(selected_pg.get_value("m_score")) > 1.0:
row_to_write = selected_pg.row
writer.writerow(row_to_write)
else:
row_to_write = selected_pg.row
writer.writerow(row_to_write)
if len(matrix_outfile) > 0:
helper.write_out_matrix_file(matrix_outfile, new_exp.runs, multipeptides, 0.0, style=options.matrix_output_method)
def test_matrix_out_2(self):
"""Test the output matrix writers"""
import msproteomicstoolslib.algorithms.alignment.AlignmentHelper as helper
runs = self.exp2.runs
multipeptides = self.multipeptides2
tmpfile = "tmp.output.csv"
helper.write_out_matrix_file(tmpfile, runs, multipeptides, 0.0,
style="full", write_requant=False)
os.remove(tmpfile)
tmpfile = "tmp.output.tsv"
helper.write_out_matrix_file(tmpfile, runs, multipeptides, 0.0,
style="full", write_requant=False)
os.remove(tmpfile)
tmpfile = "tmp.output.xls"
helper.write_out_matrix_file(tmpfile, runs, multipeptides, 0.0,
style="full", write_requant=False)
os.remove(tmpfile)
tmpfile = "tmp.output.xlsx"
helper.write_out_matrix_file(tmpfile, runs, multipeptides, 0.0,
style="full", write_requant=False)
os.remove(tmpfile)
