def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if argv is None:
argv = sys.argv
# setup command line parser
parser = E.OptionParser(version="%prog version: $Id$",
usage=globals()["__doc__"])
parser.add_option("-t",
"--test",
dest="test",
type="string",
help="supply help")
parser.add_option("--twin-id-column",
dest="id_column",
type="string",
help="column number or header for twin IDs in "
"input tables")
parser.add_option("--demographics-file",
dest="demo_file",
type="string",
help="tab-separated text file containing twins "
"demographic data")
parser.add_option(
"--demo-id-column",
dest="demo_id_column",
type="string",
help="column header or number that indicates the twin IDs "
"that match to those from the flow cytometry data")
parser.add_option("--task",
dest="task",
type="choice",
choices=[
"merge_flow", "split_zygosity",
"regress_confounding", "kinship"
],
help="choose a task")
parser.add_option("--output-file-pattern",
dest="out_pattern",
type="string",
help="output filename pattern to use where output is "
"multiple files")
parser.add_option("--output-directory",
dest="out_dir",
type="string",
help="directory to output files into")
parser.add_option("--zygosity-column",
dest="zygosity_col",
type="string",
help="column header containing zygosity information")
parser.add_option("--id-columns",
dest="id_headers",
type="string",
help="comma-separated list of column headers used to "
"uniquely identify each sample")
parser.add_option("--family-id-column",
dest="family_id",
type="string",
help="column header containing family IDs")
parser.add_option("--confounding-column",
dest="confounding",
type="string",
help="either a comma-separates list or single value, "
"column number or column header")
parser.add_option("--marker-group",
dest="marker_col",
type="string",
help="column header containing marker IDs to group "
"regression fits by")
parser.add_option("--filter-zero-arrays",
dest="filter_zero",
action="store_true",
help="Filter out arrays where there are no observations")
parser.add_option("--database",
dest="database",
type="string",
help="absolute path to SQLite database")
parser.add_option("--tablename",
dest="table",
type="string",
help="tablename to extract from SQL database")
parser.add_option("--filter-gates",
dest="filt_gate",
type="string",
help="regex to filter out unwanted triboolean gates")
# add common options (-h/--help, ...) and parse command line
(options, args) = E.Start(parser, argv=argv)
parser.set_defaults(filter_zero=True, filt_gate=None)
infile = argv[-1]
if options.task == "merge_flow":
merged_arrays = P52.mergeGateArrays(db=options.database,
table_name=options.table,
filter_zero=options.filter_zero,
filter_gate=options.filt_gate)
all_dfs = P52.mergeArrayWithDemographics(
flow_arrays=merged_arrays,
id_column=options.id_column,
demo_file=options.demo_file,
demo_id_column=options.demo_id_column)
for out_df in all_dfs:
# construct the table names using cell_type, panel and gate
# cell type and statistic should be in the out_pattern
outname = "-".join(
[options.out_pattern, out_df["gate"][0], out_df["panel"][0]])
outname = outname.replace("/", "_")
out_file = "/".join([options.out_dir, outname])
E.info("writing %s data to file" % outname)
# file names may contain '/', replace these with "_"
out_df.to_csv(out_file, sep="\t", index_col="indx")
# memory useage was ballooning from R's amazing ability
# to free up memory after garbage collection.
P52.clearREnvironment()
elif options.task == "split_zygosity":
out_frames = P52.split_zygosity(
infile=infile,
zygosity_column=options.zygosity_col,
id_headers=(options.id_headers).split(","),
pair_header=options.family_id)
# expect keys: MZ and DZ
try:
MZ_frame = out_frames["MZ"]
DZ_frame = out_frames["DZ"]
# output filenames using pattern and zygosity as a prefix
MZ_outfile = "-".join([options.out_pattern, "MZ.tsv"])
MZ_frame.to_csv(MZ_outfile, sep="\t", index_label="indx")
DZ_outfile = "-".join([options.out_pattern, "DZ.tsv"])
DZ_frame.to_csv(DZ_outfile, sep="\t", index_label="indx")
except TypeError:
pass
elif options.task == "regress_confounding":
out_df = P52.regress_out_confounding(
infile=infile,
confounding_column=options.confounding,
group_var=options.marker_col)
out_df.to_csv(options.stdout, sep="\t", index_label="indx")
elif options.task == "kinship":
out_df = P52.make_kinship_matrix(twins_file=infile,
id_column=options.id_headers,
family_column=options.family_id,
zygosity_column=options.zygosity_col)
out_df.to_csv(options.stdout, index_label="indx", sep="\t")
# write footer and output benchmark information.
E.Stop()
def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if argv is None:
argv = sys.argv
# setup command line parser
parser = E.OptionParser(version="%prog version: $Id$",
usage=globals()["__doc__"])
parser.add_option("-t", "--test", dest="test", type="string",
help="supply help")
parser.add_option("--twin-id-column", dest="id_column", type="string",
help="column number or header for twin IDs in "
"input tables")
parser.add_option("--demographics-file", dest="demo_file", type="string",
help="tab-separated text file containing twins "
"demographic data")
parser.add_option("--demo-id-column", dest="demo_id_column", type="string",
help="column header or number that indicates the twin IDs "
"that match to those from the flow cytometry data")
parser.add_option("--task", dest="task", type="choice",
choices=["merge_flow", "split_zygosity",
"regress_confounding", "kinship"],
help="choose a task")
parser.add_option("--output-file-pattern", dest="out_pattern", type="string",
help="output filename pattern to use where output is "
"multiple files")
parser.add_option("--output-directory", dest="out_dir", type="string",
help="directory to output files into")
parser.add_option("--zygosity-column", dest="zygosity_col", type="string",
help="column header containing zygosity information")
parser.add_option("--id-columns", dest="id_headers", type="string",
help="comma-separated list of column headers used to "
"uniquely identify each sample")
parser.add_option("--family-id-column", dest="family_id", type="string",
help="column header containing family IDs")
parser.add_option("--confounding-column", dest="confounding", type="string",
help="either a comma-separates list or single value, "
"column number or column header")
parser.add_option("--marker-group", dest="marker_col", type="string",
help="column header containing marker IDs to group "
"regression fits by")
parser.add_option("--filter-zero-arrays", dest="filter_zero", action="store_true",
help="Filter out arrays where there are no observations")
parser.add_option("--database", dest="database", type="string",
help="absolute path to SQLite database")
parser.add_option("--tablename", dest="table", type="string",
help="tablename to extract from SQL database")
parser.add_option("--filter-gates", dest="filt_gate", type="string",
help="regex to filter out unwanted triboolean gates")
# add common options (-h/--help, ...) and parse command line
(options, args) = E.Start(parser, argv=argv)
parser.set_defaults(filter_zero=True,
filt_gate=None)
infile = argv[-1]
if options.task == "merge_flow":
merged_arrays = P52.mergeGateArrays(db=options.database,
table_name=options.table,
filter_zero=options.filter_zero,
filter_gate=options.filt_gate)
all_dfs = P52.mergeArrayWithDemographics(flow_arrays=merged_arrays,
id_column=options.id_column,
demo_file=options.demo_file,
demo_id_column=options.demo_id_column)
for out_df in all_dfs:
# construct the table names using cell_type, panel and gate
# cell type and statistic should be in the out_pattern
outname = "-".join([options.out_pattern, out_df["gate"][0],
out_df["panel"][0]])
outname = outname.replace("/", "_")
out_file = "/".join([options.out_dir, outname])
E.info("writing %s data to file" % outname)
# file names may contain '/', replace these with "_"
out_df.to_csv(out_file, sep="\t", index_col="indx")
# memory useage was ballooning from R's amazing ability
# to free up memory after garbage collection.
P52.clearREnvironment()
elif options.task == "split_zygosity":
out_frames = P52.split_zygosity(infile=infile,
zygosity_column=options.zygosity_col,
id_headers=(options.id_headers).split(","),
pair_header=options.family_id)
# expect keys: MZ and DZ
try:
MZ_frame = out_frames["MZ"]
DZ_frame = out_frames["DZ"]
# output filenames using pattern and zygosity as a prefix
MZ_outfile = "-".join([options.out_pattern, "MZ.tsv"])
MZ_frame.to_csv(MZ_outfile, sep="\t", index_label="indx")
DZ_outfile = "-".join([options.out_pattern,"DZ.tsv"])
DZ_frame.to_csv(DZ_outfile, sep="\t", index_label="indx")
except TypeError:
pass
elif options.task == "regress_confounding":
out_df = P52.regress_out_confounding(infile=infile,
confounding_column=options.confounding,
group_var=options.marker_col)
out_df.to_csv(options.stdout, sep="\t", index_label="indx")
elif options.task == "kinship":
out_df = P52.make_kinship_matrix(twins_file=infile,
id_column=options.id_headers,
family_column=options.family_id,
zygosity_column=options.zygosity_col)
out_df.to_csv(options.stdout, index_label="indx", sep="\t")
# write footer and output benchmark information.
E.Stop()
