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("--time", dest="timepoints", type="string",
help="a comma-separated list of time points measured")
parser.add_option("--replicates", dest="reps", type="string",
help="a comma-separated list of replicate IDs")
parser.add_option("--conditions", dest="conditions", type="string",
help="a comma-separated list of experimental conditions")
parser.add_option("--orders", dest="orders", type="int",
help="order of polynomial terms to include in"
"maSigPro linear model")
parser.add_option("--fdr", dest="fdr", type="string",
help="FDR for calling DEGs")
parser.add_option("--padjust", dest="padjust", type="string",
help="multiple testing correction to apply to"
"control FDR")
parser.add_option("--stepwise", dest="stepwise", type="string",
help="stepwise regression to use")
parser.add_option("--pinclude", dest="pinclude", type="string",
help="p-value for inclusion in stepwise regression")
parser.add_option("--rsquared", dest="rsquared", type="string",
help="rsquared cut-off for DEG reporting")
parser.add_option("--var-group", dest="vargroup", type="string",
help="variable group reporting. each, all or"
"group")
parser.add_option("--task", dest="task", type="string",
help="analysis task to be executed")
parser.add_option("--infile", dest="infile", type="string",
help="input file path")
parser.add_option("--quantile", dest="quantile", type="int",
help="see pipeline.ini for explanation")
# add common options (-h/--help, ...) and parse command line
(options, args) = E.Start(parser, argv=argv)
infile = argv[-1]
parser.set_defaults(cutHeight=0,
conditions=None,
split=False,
cluster_size=30)
if options.task == "deseq":
timepoints = [int(x) for x in options.timepoints.split(",")]
timepoints.sort()
reps = [x for x in options.reps.split(",")]
if not options.conditions:
conditions = None
else:
conditions = [x for x in options.conditions.split(",")]
data_frame = TS.deseqNormalize(infile=infile,
time_points=timepoints,
reps=reps,
conditions=conditions)
elif options.task == "masigpro":
data_frame = TS.maSigPro(infile=infile,
order_terms=int(options.orders),
fdr=float(options.fdr),
adjust=options.padjust,
stepwise=options.stepwise,
include_p=float(options.pinclude),
rsq=float(options.rsquared),
var_group=options.vargroup)
elif options.task == "sumcovar":
timepoints = [int(x) for x in options.timepoints.split(",")]
reps = [x for x in options.reps.split(",")]
data_frame = TS.covarFilter(infile=infile,
time_points=timepoints,
replicates=reps,
quantile=int(options.quantile))
elif options.task == "average_expression":
data_frame = TS.avTimeExpression(infile)
else:
pass
data_frame.to_csv(options.stdout,
sep="\t",
header=True,
index_label="gene_id")
# 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("--time",
dest="timepoints",
type="string",
help="a comma-separated list of time points measured")
parser.add_option("--replicates",
dest="reps",
type="string",
help="a comma-separated list of replicate IDs")
parser.add_option("--conditions",
dest="conditions",
type="string",
help="a comma-separated list of experimental conditions")
parser.add_option("--orders",
dest="orders",
type="int",
help="order of polynomial terms to include in"
"maSigPro linear model")
parser.add_option("--fdr",
dest="fdr",
type="string",
help="FDR for calling DEGs")
parser.add_option("--padjust",
dest="padjust",
type="string",
help="multiple testing correction to apply to"
"control FDR")
parser.add_option("--stepwise",
dest="stepwise",
type="string",
help="stepwise regression to use")
parser.add_option("--pinclude",
dest="pinclude",
type="string",
help="p-value for inclusion in stepwise regression")
parser.add_option("--rsquared",
dest="rsquared",
type="string",
help="rsquared cut-off for DEG reporting")
parser.add_option("--var-group",
dest="vargroup",
type="string",
help="variable group reporting. each, all or"
"group")
parser.add_option("--task",
dest="task",
type="string",
help="analysis task to be executed")
parser.add_option("--infile",
dest="infile",
type="string",
help="input file path")
parser.add_option("--quantile",
dest="quantile",
type="int",
help="see pipeline.ini for explanation")
(options, args) = E.Start(parser, argv=argv)
infile = argv[-1]
parser.set_defaults(cutHeight=0,
conditions=None,
split=False,
cluster_size=30)
if options.task == "deseq":
timepoints = [int(x) for x in options.timepoints.split(",")]
timepoints.sort()
reps = [x for x in options.reps.split(",")]
if not options.conditions:
conditions = None
else:
conditions = [x for x in options.conditions.split(",")]
data_frame = TS.deseqNormalize(infile=infile,
time_points=timepoints,
reps=reps,
conditions=conditions)
elif options.task == "masigpro":
data_frame = TS.maSigPro(infile=infile,
order_terms=int(options.orders),
fdr=float(options.fdr),
adjust=options.padjust,
stepwise=options.stepwise,
include_p=float(options.pinclude),
rsq=float(options.rsquared),
var_group=options.vargroup)
elif options.task == "sumcovar":
timepoints = [int(x) for x in options.timepoints.split(",")]
reps = [x for x in options.reps.split(",")]
data_frame = TS.covarFilter(infile=infile,
time_points=timepoints,
replicates=reps,
quantile=int(options.quantile))
elif options.task == "average_expression":
data_frame = TS.avTimeExpression(infile)
else:
pass
data_frame.to_csv(options.stdout,
sep="\t",
header=True,
index_label="gene_id")
# Write footer and output benchmark information.
E.Stop()
