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("--method",
dest="method",
type="choice",
choices=["compensation", "parse_gating"],
help="select method to perform on workspace "
"file.")
parser.add_option("--gating-directory",
dest="gate_dir",
type="string",
help="directory to store gating dummy files")
# add common options (-h/--help, ...) and parse command line
(options, args) = E.Start(parser, argv=argv)
# write footer and output benchmark information.
E.Stop()
infile = argv[-1]
if options.method == "compensation":
split_file = infile.split("/")
infile = split_file[-1]
split_file.remove(infile)
path = "/".join(split_file)
out_df = P52.get_compensation_matrix(path=path, infile=infile)
out_df.to_csv(options.stdout, sep="\t")
elif options.method == "parse_gating":
for dfile in P52.parse_gating_file(infile):
outfile = options.gate_dir + "/" + dfile
P.touch(outfile)
else:
pass
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("--id-column",
dest="id_col",
type="string",
help="column header for sample IDs")
parser.add_option("--matrix-distance",
dest="dist",
type="choice",
choices=["Euclid"],
help="distance metric to use "
"for distance between matrices")
# 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]
# the input file is a list of files
myfunc = lambda x: x.rstrip("\n")
with open(infile, "r") as ifile:
all_files = ifile.readlines()
list_of_files = map(myfunc, all_files)
matrix_list = P52.makeMatrixList(list_of_files=list_of_files,
id_col=options.id_col)
distance_matrix = P52.getMatrixDistances(list_of_matrices=matrix_list,
distance=options.dist)
distance_matrix.to_csv(options.stdout, sep="\t", index_label=None)
# 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("--method", dest="method", type="choice",
choices=["compensation", "parse_gating"],
help="select method to perform on workspace "
"file.")
parser.add_option("--gating-directory", dest="gate_dir", type="string",
help="directory to store gating dummy files")
# add common options (-h/--help, ...) and parse command line
(options, args) = E.Start(parser, argv=argv)
# write footer and output benchmark information.
E.Stop()
infile = argv[-1]
if options.method == "compensation":
split_file = infile.split("/")
infile = split_file[-1]
split_file.remove(infile)
path = "/".join(split_file)
out_df = P52.get_compensation_matrix(path=path,
infile=infile)
out_df.to_csv(options.stdout, sep="\t")
elif options.method == "parse_gating":
for dfile in P52.parse_gating_file(infile):
outfile = options.gate_dir + "/" + dfile
P.touch(outfile)
else:
pass
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("--id-column", dest="id_col", type="string",
help="column header for sample IDs")
parser.add_option("--matrix-distance", dest="dist", type="choice",
choices=["Euclid"], help="distance metric to use "
"for distance between matrices")
# 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]
# the input file is a list of files
myfunc = lambda x: x.rstrip("\n")
with open(infile, "r") as ifile:
all_files = ifile.readlines()
list_of_files = map(myfunc, all_files)
matrix_list = P52.makeMatrixList(list_of_files=list_of_files,
id_col=options.id_col)
distance_matrix = P52.getMatrixDistances(list_of_matrices=matrix_list,
distance=options.dist)
distance_matrix.to_csv(options.stdout, sep="\t", index_label=None)
# 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("--task", dest="task", type="choice",
choices=["heritability", "merge",
"kinship"],
help="task")
parser.add_option("--heritability", dest="equation", type="string",
help="equation used to estimate heritability")
parser.add_option("--monozygote-file", dest="mz_file", type="string",
help="file containing monozygotic twin data")
parser.add_option("--dizygote-file", dest="dz_file", type="string",
help="file containing dizygotic twin data")
# add common options (-h/--help, ...) and parse command line
(options, args) = E.Start(parser, argv=argv)
if options.task == "heritability":
h_df = P52.estimate_heritability(mz_file=options.mz_file,
dz_file=options.dz_file)
# generate scatter plots of each marker
outdir = "/".join(options.dz_file.split("/")[:-1])
plot_out = "-".join(options.dz_file.split("/")[-1].split("-")[1:4])
plot_out = os.path.join(outdir, plot_out)
E.info("plotting correlations to %s" % plot_out)
R('''suppressPackageStartupMessages(library(ggplot2))''')
R('''mz.df <- read.table("%s", sep="\t", h=T, row.names=1)''' % options.mz_file)
R('''dz.df <- read.table("%s", sep="\t", h=T, row.names=1)''' % options.dz_file)
R('''all.dz <- data.frame(rbind(mz.df, dz.df))''')
R('''p_cor <- ggplot(all.dz, aes(x=twin1, y=twin2, '''
'''colour=zygosity)) + '''
'''geom_point(size=1) + stat_smooth(method=lm) + '''
'''facet_wrap( ~ marker, scales="free")''')
R('''png("%s-cors.png", height=720, width=720)''' % plot_out)
R('''print(p_cor)''')
R('''dev.off()''')
options.stdout.write("H^2\n")
for key in h_df.keys():
options.stdout.write("%s: %0.3f\n" % (key, h_df[key]))
elif options.task == "merge":
infiles = argv[-1]
infiles = infiles.split(",")
out_df = P52.merge_heritability(infiles)
out_df.to_csv(options.stdout, 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("--plot-type", dest="plot_type", type="choice",
choices=["histogram", "scatter", "barchart"],
help="type of plot to generate")
parser.add_option("--x-axis", dest="x_axis", type="string",
help="variable to plot on the X-axis."
"This is the default axis for plotting.")
parser.add_option("--y-axis", dest="y_axis", type="string",
help="variable to plot on the Y-axis")
parser.add_option("--split-by", dest="split_by", type="string",
help="varible over which to split up plots")
parser.add_option("--X-title", dest="x_title", type="string",
help="label to attach to X-axis")
parser.add_option("--Y-title", dest="y_title", type="string",
help="label to attach to Y-axis")
parser.add_option("--colour-var", dest="col_var", type="string",
help="variable to colour points by")
parser.add_option("--free-scale", dest="free_scale", type="choice",
choices=["free_x", "free_y", "free"], help="whether to "
"use free scaling on plot axes")
parser.add_option("--outfile", dest="outfile", type="string",
help="file to save plot to")
parser.add_option("--melt-data", dest="melt", action="store_true",
help="melt the dataframe first, requires ID vars")
parser.add_option("--melt-id-vars", dest="id_vars", type="string",
help="comma separated list of id variables for"
" the melted dataframe")
parser.add_option("--merge-frames", dest="merge", action="store_true",
help="merge two input dataframes together")
parser.add_option("--merge-id-vars", dest="merge_vars", type="string",
help="comma separate list of id variables to merge "
"two dataframes on")
# add common options (-h/--help, ...) and parse command line
(options, args) = E.Start(parser, argv=argv)
parser.set_defaults(free_scale="both",
split_by=None,
col_var=None,
melt=False)
infile = argv[-1]
if len(infile.split(",")) == 2:
infiles = infile.split(",")
df1 = pd.read_table(infiles[0], sep=":", index_col=0,
header=0)
df2 = pd.read_table(infiles[1], sep=":", index_col=0,
header=0)
ids = options.merge_vars.split(",")
df1[options.y_axis] = df1.index
df2[options.y_axis] = df2.index
df1.columns = [ids[0], options.y_axis]
df2.columns = [ids[0], options.y_axis]
df = pd.merge(df1, df2, on=options.y_axis)
# these need to not be hard-coded!
df.columns = ["mean_h2", ids[0], "fano_h2"]
else:
df = pd.read_table(infile, sep="\t", index_col=0,
header=0)
# assumes the first column is the index
if options.melt:
mids = options.id_vars.split(",")
if options.y_axis:
_df = pd.melt(df, id_vars=options.x_axis, value_name=options.y_axis,
var_name=options.col_var)
else:
_df = pd.melt(df, id_vars=mids, value_name=options.x_axis,
var_name=options.col_var)
df = _df
else:
pass
# check variables are present
try:
var = df[options.x_axis]
except ValueError:
raise ValueError("no plotting variable found")
if options.col_var:
try:
cols = df[options.col_var]
except ValueError:
E.warn("Colour variable not found in data frame."
"Check the data file is the correct one")
else:
pass
if options.split_by:
try:
splits = df[options.split_by]
except ValueError:
E.warn("Split-by variable not found in the data "
"frame. Check the data file is the correct"
" one.")
else:
pass
try:
assert options.outfile
except AssertionError:
raise IOError("no output file detected")
if options.plot_type == "histogram":
P52.plotHistogram(data=df,
variable=options.x_axis,
save_path=options.outfile,
x_title=options.x_title,
y_title=options.y_title,
colour_var=options.col_var,
scales=options.free_scale,
split_var=options.split_by)
elif options.plot_type == "barchart":
P52.plotBarchart(data=df,
x_variable=options.x_axis,
y_variable=options.y_axis,
save_path=options.outfile,
x_title=options.x_title,
y_title=options.y_title,
colour_var=options.col_var,
split_var=options.split_by)
else:
pass
# 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()
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("--task",
dest="task",
type="choice",
choices=["heritability", "merge", "kinship"],
help="task")
parser.add_option("--heritability",
dest="equation",
type="string",
help="equation used to estimate heritability")
parser.add_option("--monozygote-file",
dest="mz_file",
type="string",
help="file containing monozygotic twin data")
parser.add_option("--dizygote-file",
dest="dz_file",
type="string",
help="file containing dizygotic twin data")
# add common options (-h/--help, ...) and parse command line
(options, args) = E.Start(parser, argv=argv)
if options.task == "heritability":
h_df = P52.estimate_heritability(mz_file=options.mz_file,
dz_file=options.dz_file)
# generate scatter plots of each marker
outdir = "/".join(options.dz_file.split("/")[:-1])
plot_out = "-".join(options.dz_file.split("/")[-1].split("-")[1:4])
plot_out = os.path.join(outdir, plot_out)
E.info("plotting correlations to %s" % plot_out)
R('''suppressPackageStartupMessages(library(ggplot2))''')
R('''mz.df <- read.table("%s", sep="\t", h=T, row.names=1)''' %
options.mz_file)
R('''dz.df <- read.table("%s", sep="\t", h=T, row.names=1)''' %
options.dz_file)
R('''all.dz <- data.frame(rbind(mz.df, dz.df))''')
R('''p_cor <- ggplot(all.dz, aes(x=twin1, y=twin2, '''
'''colour=zygosity)) + '''
'''geom_point(size=1) + stat_smooth(method=lm) + '''
'''facet_wrap( ~ marker, scales="free")''')
R('''png("%s-cors.png", height=720, width=720)''' % plot_out)
R('''print(p_cor)''')
R('''dev.off()''')
options.stdout.write("H^2\n")
for key in h_df.keys():
options.stdout.write("%s: %0.3f\n" % (key, h_df[key]))
elif options.task == "merge":
infiles = argv[-1]
infiles = infiles.split(",")
out_df = P52.merge_heritability(infiles)
out_df.to_csv(options.stdout, 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("--fcs-directory",
dest="fcs_dir",
type="string",
help="path to directory containing .fcs files"
" for processsing")
parser.add_option("--output-format",
dest="out_format",
type="choice",
choices=("summary", "intensity"),
help="output either"
" summary of intensities or raw intensity data")
parser.add_option("--summary-stats",
dest="stats",
type="choice",
choices=("fano", "mean", "std", "var", "median",
"geometric", "regress"),
help="summary statistics to output if "
"out_format == summary")
parser.add_option("--gating-strategy",
dest="gates",
type="string",
help=".tsv of gating strategy. See docs for details")
parser.add_option(
"--compensation-matrix",
dest="comp_matrix",
type="string",
help="text file containing the compensation/spillover matrix")
parser.add_option("--cell-type",
dest="cell_type",
type="string",
help="description of cell type gene expression "
"is measured on. Will be added to output file name")
parser.add_option("--panel-id",
dest="panel",
type="string",
help="ID for marker panel")
parser.add_option("--output-directory",
dest="out_dir",
type="string",
help="output directory path for files")
parser.add_option(
"--fileset-identifier",
dest="fileset_id",
type="string",
help="unique identifier for sets of files/samples processed "
"together. Useful for assigning to batches for processing")
parser.add_option("--database",
dest="database",
type="string",
help="SQLite database to write results to ")
# add common options (-h/--help, ...) and parse command line
(options, args) = E.Start(parser, argv=argv)
E.info("Processing data for %s in panel %s" %
(options.cell_type, options.panel))
if options.cell_type == "CD4_Tmem" and options.panel == "P3":
P52.get_cd4_Tmem_panel3(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "CD8_Tmem" and options.panel == "P3":
P52.get_cd8_Tmem_panel3(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "CD4_Tnaive" and options.panel == "P3":
P52.get_cd4_naive_panel3(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "CD8_Tnaive" and options.panel == "P3":
P52.get_cd8_naive_panel3(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "CD4_Tcell" and options.panel == "P1":
P52.get_cd4_tcells_panel1(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "CD8_Tcell" and options.panel == "P1":
P52.get_cd8_tcells_panel1(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "DN_Tcell" and options.panel == "P1":
P52.get_dn_tcells_panel1(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "DP_Tcell" and options.panel == "P1":
P52.get_dp_tcells_panel1(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "CD4_Tcell" and options.panel == "P2a":
P52.get_cd4_tcells_panel2(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "CD4_Tcell" and options.panel == "P2b":
P52.get_cd4_tcells_panel2(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "CD8_Tcell" and options.panel == "P2a":
P52.get_cd8_tcells_panel2(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "CD8_Tcell" and options.panel == "P2b":
P52.get_cd8_tcells_panel2(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "DN_Tcell" and options.panel == "P2a":
P52.get_dn_tcells_panel2(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "DN_Tcell" and options.panel == "P2b":
P52.get_dn_tcells_panel2(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "DP_Tcell" and options.panel == "P2a":
P52.get_dp_tcells_panel2(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "DP_Tcell" and options.panel == "P2b":
P52.get_dp_tcells_panel2(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
# elif options.cell_type == "early_NK" and options.panel == "P4":
# P52.get_early_nkcells_panel4(fcs_dir=options.fcs_dir,
# out_dir=options.out_dir,
# comp_matrix=options.comp_matrix,
# panel=options.panel,
# setid=options.fileset_id,
# cell_subset=options.cell_type,
# db=options.database)
# elif options.cell_type == "terminal_NK" and options.panel == "P4":
# P52.get_terminal_nkcells_panel4(fcs_dir=options.fcs_dir,
# out_dir=options.out_dir,
# comp_matrix=options.comp_matrix,
# panel=options.panel,
# setid=options.fileset_id,
# cell_subset=options.cell_type,
# db=options.database)
# elif options.cell_type == "mature_NK" and options.panel == "P4":
# P52.get_mature_nkcells_panel4(fcs_dir=options.fcs_dir,
# out_dir=options.out_dir,
# comp_matrix=options.comp_matrix,
# panel=options.panel,
# setid=options.fileset_id,
# cell_subset=options.cell_type,
# db=options.database)
elif options.cell_type == "NKT_early" and options.panel == "P5":
P52.get_early_nktcells_panel5(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "NKT_naive" and options.panel == "P5":
P52.get_naive_nktcells_panel5(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "NKT_terminal" and options.panel == "P5":
P52.get_terminal_nktcells_panel5(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "NKT_effector" and options.panel == "P5":
P52.get_effector_nktcells_panel5(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "Vd1_Tcells" and options.panel == "P5":
P52.get_Vd1_tcells_panel5(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "Vd2p_Vg9dim" and options.panel == "P5":
P52.get_Vd2_vg9dim_panel5(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "Vd2n_Vg9p" and options.panel == "P5":
P52.get_Vd2n_vg9p_panel5(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "hemat_SCs" and options.panel == "P5":
P52.get_hemat_SC_panel5(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "immature_Bcell" and options.panel == "P6":
P52.get_immature_Bcells_panel6(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "mature_Bcell" and options.panel == "P6":
P52.get_mature_Bcells_panel6(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "memory_Bcell" and options.panel == "P6":
P52.get_memory_Bcells_panel6(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "naive_Bcell" and options.panel == "P6":
P52.get_naive_Bcells_panel6(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "IgA_Bmem" and options.panel == "P6":
P52.get_IgA_Bcells_panel6(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "IgG_Bmem" and options.panel == "P6":
P52.get_IgG_Bcells_panel6(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "IgM_Bmem" and options.panel == "P6":
P52.get_IgM_Bcells_panel6(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "IgE_Bmem" and options.panel == "P6":
P52.get_IgE_Bcells_panel6(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "monocytes" and options.panel == "P7":
P52.get_monocytes_panel7(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "M_dendritic" and options.panel == "P7":
P52.get_myeloid_DC_panel7(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "DC_cd123cd11c" and options.panel == "P7":
P52.get_cd123cd11c_DC_panel7(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "P_dendritic" and options.panel == "P7":
P52.get_plasmacytoid_DC_panel7(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "CD8_APCs" and options.panel == "P7":
P52.get_CD8_APC_panel7(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "CD4_APCs" and options.panel == "P7":
P52.get_CD4_APC_panel7(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "CD1cneg_mDC" and options.panel == "P7":
P52.get_CD1cneg_mDC_panel7(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "Inflam_DC" and options.panel == "P7":
P52.get_inflammatory_DC_panel7(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
elif options.cell_type == "CD16neg_DC" and options.panel == "P7":
P52.get_CD16neg_DC_panel7(fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database)
else:
outfile = "%s/%s-%s-%s.tsv" % (options.out_dir, options.fileset_id,
options.panel, options.cell_type)
P.touch(outfile)
# 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(
"--fcs-directory",
dest="fcs_dir",
type="string",
help="path to directory containing .fcs files" " for processsing",
)
parser.add_option(
"--output-format",
dest="out_format",
type="choice",
choices=("summary", "intensity"),
help="output either" " summary of intensities or raw intensity data",
)
parser.add_option(
"--summary-stats",
dest="stats",
type="choice",
choices=("fano", "mean", "std", "var", "median", "geometric", "regress"),
help="summary statistics to output if " "out_format == summary",
)
parser.add_option(
"--gating-strategy", dest="gates", type="string", help=".tsv of gating strategy. See docs for details"
)
parser.add_option(
"--compensation-matrix",
dest="comp_matrix",
type="string",
help="text file containing the compensation/spillover matrix",
)
parser.add_option(
"--cell-type",
dest="cell_type",
type="string",
help="description of cell type gene expression " "is measured on. Will be added to output file name",
)
parser.add_option("--panel-id", dest="panel", type="string", help="ID for marker panel")
parser.add_option("--output-directory", dest="out_dir", type="string", help="output directory path for files")
parser.add_option(
"--fileset-identifier",
dest="fileset_id",
type="string",
help="unique identifier for sets of files/samples processed "
"together. Useful for assigning to batches for processing",
)
parser.add_option("--database", dest="database", type="string", help="SQLite database to write results to ")
# add common options (-h/--help, ...) and parse command line
(options, args) = E.Start(parser, argv=argv)
E.info("Processing data for %s in panel %s" % (options.cell_type, options.panel))
if options.cell_type == "CD4_Tmem" and options.panel == "P3":
P52.get_cd4_Tmem_panel3(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "CD8_Tmem" and options.panel == "P3":
P52.get_cd8_Tmem_panel3(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "CD4_Tnaive" and options.panel == "P3":
P52.get_cd4_naive_panel3(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "CD8_Tnaive" and options.panel == "P3":
P52.get_cd8_naive_panel3(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "CD4_Tcell" and options.panel == "P1":
P52.get_cd4_tcells_panel1(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "CD8_Tcell" and options.panel == "P1":
P52.get_cd8_tcells_panel1(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "DN_Tcell" and options.panel == "P1":
P52.get_dn_tcells_panel1(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "DP_Tcell" and options.panel == "P1":
P52.get_dp_tcells_panel1(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "CD4_Tcell" and options.panel == "P2a":
P52.get_cd4_tcells_panel2(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "CD4_Tcell" and options.panel == "P2b":
P52.get_cd4_tcells_panel2(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "CD8_Tcell" and options.panel == "P2a":
P52.get_cd8_tcells_panel2(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "CD8_Tcell" and options.panel == "P2b":
P52.get_cd8_tcells_panel2(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "DN_Tcell" and options.panel == "P2a":
P52.get_dn_tcells_panel2(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "DN_Tcell" and options.panel == "P2b":
P52.get_dn_tcells_panel2(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "DP_Tcell" and options.panel == "P2a":
P52.get_dp_tcells_panel2(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "DP_Tcell" and options.panel == "P2b":
P52.get_dp_tcells_panel2(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
# elif options.cell_type == "early_NK" and options.panel == "P4":
# P52.get_early_nkcells_panel4(fcs_dir=options.fcs_dir,
# out_dir=options.out_dir,
# comp_matrix=options.comp_matrix,
# panel=options.panel,
# setid=options.fileset_id,
# cell_subset=options.cell_type,
# db=options.database)
# elif options.cell_type == "terminal_NK" and options.panel == "P4":
# P52.get_terminal_nkcells_panel4(fcs_dir=options.fcs_dir,
# out_dir=options.out_dir,
# comp_matrix=options.comp_matrix,
# panel=options.panel,
# setid=options.fileset_id,
# cell_subset=options.cell_type,
# db=options.database)
# elif options.cell_type == "mature_NK" and options.panel == "P4":
# P52.get_mature_nkcells_panel4(fcs_dir=options.fcs_dir,
# out_dir=options.out_dir,
# comp_matrix=options.comp_matrix,
# panel=options.panel,
# setid=options.fileset_id,
# cell_subset=options.cell_type,
# db=options.database)
elif options.cell_type == "NKT_early" and options.panel == "P5":
P52.get_early_nktcells_panel5(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "NKT_naive" and options.panel == "P5":
P52.get_naive_nktcells_panel5(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "NKT_terminal" and options.panel == "P5":
P52.get_terminal_nktcells_panel5(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "NKT_effector" and options.panel == "P5":
P52.get_effector_nktcells_panel5(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "Vd1_Tcells" and options.panel == "P5":
P52.get_Vd1_tcells_panel5(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "Vd2p_Vg9dim" and options.panel == "P5":
P52.get_Vd2_vg9dim_panel5(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "Vd2n_Vg9p" and options.panel == "P5":
P52.get_Vd2n_vg9p_panel5(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "hemat_SCs" and options.panel == "P5":
P52.get_hemat_SC_panel5(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "immature_Bcell" and options.panel == "P6":
P52.get_immature_Bcells_panel6(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "mature_Bcell" and options.panel == "P6":
P52.get_mature_Bcells_panel6(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "memory_Bcell" and options.panel == "P6":
P52.get_memory_Bcells_panel6(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "naive_Bcell" and options.panel == "P6":
P52.get_naive_Bcells_panel6(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "IgA_Bmem" and options.panel == "P6":
P52.get_IgA_Bcells_panel6(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "IgG_Bmem" and options.panel == "P6":
P52.get_IgG_Bcells_panel6(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "IgM_Bmem" and options.panel == "P6":
P52.get_IgM_Bcells_panel6(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "IgE_Bmem" and options.panel == "P6":
P52.get_IgE_Bcells_panel6(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "monocytes" and options.panel == "P7":
P52.get_monocytes_panel7(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "M_dendritic" and options.panel == "P7":
P52.get_myeloid_DC_panel7(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "DC_cd123cd11c" and options.panel == "P7":
P52.get_cd123cd11c_DC_panel7(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "P_dendritic" and options.panel == "P7":
P52.get_plasmacytoid_DC_panel7(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "CD8_APCs" and options.panel == "P7":
P52.get_CD8_APC_panel7(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "CD4_APCs" and options.panel == "P7":
P52.get_CD4_APC_panel7(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "CD1cneg_mDC" and options.panel == "P7":
P52.get_CD1cneg_mDC_panel7(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "Inflam_DC" and options.panel == "P7":
P52.get_inflammatory_DC_panel7(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
elif options.cell_type == "CD16neg_DC" and options.panel == "P7":
P52.get_CD16neg_DC_panel7(
fcs_dir=options.fcs_dir,
out_dir=options.out_dir,
comp_matrix=options.comp_matrix,
panel=options.panel,
setid=options.fileset_id,
cell_subset=options.cell_type,
db=options.database,
)
else:
outfile = "%s/%s-%s-%s.tsv" % (options.out_dir, options.fileset_id, options.panel, options.cell_type)
P.touch(outfile)
# 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()
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("--plot-type",
dest="plot_type",
type="choice",
choices=["histogram", "scatter", "barchart"],
help="type of plot to generate")
parser.add_option("--x-axis",
dest="x_axis",
type="string",
help="variable to plot on the X-axis."
"This is the default axis for plotting.")
parser.add_option("--y-axis",
dest="y_axis",
type="string",
help="variable to plot on the Y-axis")
parser.add_option("--split-by",
dest="split_by",
type="string",
help="varible over which to split up plots")
parser.add_option("--X-title",
dest="x_title",
type="string",
help="label to attach to X-axis")
parser.add_option("--Y-title",
dest="y_title",
type="string",
help="label to attach to Y-axis")
parser.add_option("--colour-var",
dest="col_var",
type="string",
help="variable to colour points by")
parser.add_option("--free-scale",
dest="free_scale",
type="choice",
choices=["free_x", "free_y", "free"],
help="whether to "
"use free scaling on plot axes")
parser.add_option("--outfile",
dest="outfile",
type="string",
help="file to save plot to")
parser.add_option("--melt-data",
dest="melt",
action="store_true",
help="melt the dataframe first, requires ID vars")
parser.add_option("--melt-id-vars",
dest="id_vars",
type="string",
help="comma separated list of id variables for"
" the melted dataframe")
parser.add_option("--merge-frames",
dest="merge",
action="store_true",
help="merge two input dataframes together")
parser.add_option("--merge-id-vars",
dest="merge_vars",
type="string",
help="comma separate list of id variables to merge "
"two dataframes on")
# add common options (-h/--help, ...) and parse command line
(options, args) = E.Start(parser, argv=argv)
parser.set_defaults(free_scale="both",
split_by=None,
col_var=None,
melt=False)
infile = argv[-1]
if len(infile.split(",")) == 2:
infiles = infile.split(",")
df1 = pd.read_table(infiles[0], sep=":", index_col=0, header=0)
df2 = pd.read_table(infiles[1], sep=":", index_col=0, header=0)
ids = options.merge_vars.split(",")
df1[options.y_axis] = df1.index
df2[options.y_axis] = df2.index
df1.columns = [ids[0], options.y_axis]
df2.columns = [ids[0], options.y_axis]
df = pd.merge(df1, df2, on=options.y_axis)
# these need to not be hard-coded!
df.columns = ["mean_h2", ids[0], "fano_h2"]
else:
df = pd.read_table(infile, sep="\t", index_col=0, header=0)
# assumes the first column is the index
if options.melt:
mids = options.id_vars.split(",")
if options.y_axis:
_df = pd.melt(df,
id_vars=options.x_axis,
value_name=options.y_axis,
var_name=options.col_var)
else:
_df = pd.melt(df,
id_vars=mids,
value_name=options.x_axis,
var_name=options.col_var)
df = _df
else:
pass
# check variables are present
try:
var = df[options.x_axis]
except ValueError:
raise ValueError("no plotting variable found")
if options.col_var:
try:
cols = df[options.col_var]
except ValueError:
E.warn("Colour variable not found in data frame."
"Check the data file is the correct one")
else:
pass
if options.split_by:
try:
splits = df[options.split_by]
except ValueError:
E.warn("Split-by variable not found in the data "
"frame. Check the data file is the correct"
" one.")
else:
pass
try:
assert options.outfile
except AssertionError:
raise IOError("no output file detected")
if options.plot_type == "histogram":
P52.plotHistogram(data=df,
variable=options.x_axis,
save_path=options.outfile,
x_title=options.x_title,
y_title=options.y_title,
colour_var=options.col_var,
scales=options.free_scale,
split_var=options.split_by)
elif options.plot_type == "barchart":
P52.plotBarchart(data=df,
x_variable=options.x_axis,
y_variable=options.y_axis,
save_path=options.outfile,
x_title=options.x_title,
y_title=options.y_title,
colour_var=options.col_var,
split_var=options.split_by)
else:
pass
# write footer and output benchmark information.
E.Stop()
