def testGOVolcano(self):
infile = testfile('go_tested.tab')
run_viz('volcano', self.img, infile,
textannot="id",
fc_name="log2fc_s1_over_s2",
fc_corr_p="corrected_p_s1_over_s2",
gosplit=True)
def testPCA(self):
infile = testfile('go_tested.tab')
run_viz('pca',
self.img,
infile,
sinfo=TTEST_SINFO,
calculate_sep=False)
def testBasicTaxBar(self):
infile = testfile('taxonomy_write_simple.tab')
tabfile = testfile('taxonomy_plot_out.tab')
run_viz('bar', self.img, infile, mode='t',
nterms='2', meancol='samp1_mean',
target_rank="genus", barcol="6",
tabfile=tabfile)
self.assertTrue(os.path.exists(tabfile))
os.remove(tabfile)
run_viz('bar', self.img, infile, mode='t',
nterms='2', meancol='samp1_mean',
target_rank="genus", barcol="6")
def testVolcano(self):
infile = testfile('cli_mult_test_out.tab')
run_viz('volcano', self.img, infile,
textannot="id",
fc_corr_p="corrected_p_s1_over_s2",
fc_name="log2fc_s1_over_s2")
# test tabfile
tabfile = testfile('taxonomy_plot_out.tab')
run_viz('volcano', self.img, infile,
textannot="id",
fc_name="log2fc_s1_over_s2",
fc_corr_p="corrected_p_s1_over_s2",
tabfile=tabfile)
self.assertTrue(os.path.exists(tabfile))
os.remove(tabfile)
def testFtDist(self):
infile = testfile('ft_out.tab')
run_viz('ft_dist', self.img, infile,
meancol="s1_mean",
whichway='t_dist',
id="GO:0008150",
target_rank="genus",
nterms="all")
# f dist
run_viz('ft_dist', self.img, infile,
meancol="s1_mean",
whichway='f_dist',
target_onto="bp",
nterms="all", id=209)
# test tabfile
tabfile = testfile("tmp")
run_viz('ft_dist', self.img, infile,
meancol="s1_mean",
whichway='t_dist',
id="GO:0008150",
target_rank="genus",
nterms="all",
tabfile=tabfile)
self.assertTrue(os.path.exists(tabfile))
os.remove(tabfile)
def testFuncBar(self):
infile = testfile('eggnog_out.tab')
tabfile = testfile('viz_f_filt.tab')
# bp
run_viz('bar', self.img, infile, mode='f',
nterms='2', meancol='NS_mean',
target_onto='bp', barcol='1', tabfile=tabfile)
df = pd.read_csv(tabfile, sep='\t')
namespace = df.namespace.unique()
self.assertEqual(namespace, ['biological_process'])
# cc
run_viz('bar', self.img, infile, mode='f',
nterms='2', meancol='NS_mean',
target_onto='cc', barcol='1', tabfile=tabfile)
df = pd.read_csv(tabfile, sep='\t')
namespace = df.namespace.unique()
self.assertEqual(namespace, ['cellular_component'])
# mf
run_viz('bar', self.img, infile, mode='f',
nterms='2', meancol='NS_mean',
target_onto='mf', barcol='1', tabfile=tabfile)
df = pd.read_csv(tabfile, sep='\t')
namespace = df.namespace.unique()
self.assertEqual(namespace, ['molecular_function'])
def cli():
"""
Command line interface; main entry point to metaQuantome
:return: exit code
"""
# initialize logger
logging.basicConfig(level=logging.INFO,
format='%(message)s',
stream=sys.stderr)
args = parse_args_cli()
if args.command == "db":
db_download_handler(args.dbs, args.dir, args.update)
elif args.command == "expand":
expand(mode=args.mode,
sinfo=args.samps,
int_file=args.int_file,
pep_colname_int=args.pep_colname_int,
pep_colname_func=args.pep_colname_func,
pep_colname_tax=args.pep_colname_tax,
data_dir=args.data_dir,
outfile=args.outfile,
func_file=args.func_file,
func_colname=args.func_colname,
ontology=args.ontology,
slim_down=args.slim_down,
tax_file=args.tax_file,
tax_colname=args.tax_colname,
nopep=args.nopep,
nopep_file=args.nopep_file,
ft_tar_rank=args.ft_tar_rank)
elif args.command == "filter":
run_filter(expanded_file=args.expand_file,
sinfo=args.samps,
ontology=args.ontology,
mode=args.mode,
qthreshold=args.qthreshold,
min_child_non_leaf=args.min_children_non_leaf,
min_child_nsamp=args.min_child_nsamp,
min_peptides=args.min_peptides,
min_pep_nsamp=args.min_pep_nsamp,
outfile=args.outfile)
elif args.command == "stat":
stat(infile=args.file,
sinfo=args.samps,
paired=args.paired,
parametric=args.parametric,
ontology=args.ontology,
mode=args.mode,
outfile=args.outfile)
elif args.command == "viz":
run_viz(plottype=args.plottype,
img=args.img,
infile=args.infile,
mode=args.mode,
meancol=args.meancol,
nterms=args.nterms,
strip=args.strip,
target_rank=args.target_rank,
barcol=args.barcol,
textannot=args.textannot,
calculate_sep=args.calculate_sep,
fc_name=args.fc_name,
flip_fc=args.flip_fc,
gosplit=args.gosplit,
sinfo=args.samps,
filter_to_sig=args.filter_to_sig,
alpha=args.alpha,
whichway=args.whichway,
name=args.name,
id=args.id,
target_onto=args.target_onto,
width=args.width,
height=args.height,
tabfile=args.tabfile)
else:
ValueError(
'incorrect mode. please provide one of "db", "expand", "filter", "stat", or "viz".'
)
sys.exit(0)
def testPCABig(self):
infile = testfile('tax_filt_out.tab')
sampfile = testfile('rudney_samples.tab')
run_viz('pca', self.img, infile,
sinfo=sampfile,
calculate_sep=True)
def testHeatmap(self):
infile = testfile('go_expanded_ttest.tab')
run_viz('heatmap', self.img, infile,
sinfo=TTEST_SINFO)