def test_plot_rank_abundance_graphs(self):
"""plot_rank_abundance_graphs works with any number of samples"""
self.otu_table = otu_table_fake.split("\n")
self.dir = get_tmp_filename(tmp_dir=self.tmp_dir, prefix="test_plot_rank_abundance", suffix="/")
create_dir(self.dir)
self._dirs_to_remove.append(self.dir)
# test empty sample name
self.assertRaises(ValueError, plot_rank_abundance_graphs, "", iter(self.otu_table), self.dir)
# test invalid sample name
self.assertRaises(ValueError, plot_rank_abundance_graphs, "Invalid_sample_name", iter(self.otu_table), self.dir)
# test with two samples
file_type = "pdf"
plot_rank_abundance_graphs("S3,S5", iter(self.otu_table), self.dir, file_type=file_type)
tmp_file = abspath(self.dir + "rank_abundance_cols_0_2." + file_type)
self.assertTrue(exists(tmp_file))
self.files_to_remove.append(tmp_file)
# test with all samples
plot_rank_abundance_graphs("*", iter(self.otu_table), self.dir, file_type=file_type)
tmp_file = abspath(self.dir + "rank_abundance_cols_0_1_2." + file_type)
self.files_to_remove.append(tmp_file)
self.assertTrue(exists(tmp_file))
def setUp(self):
""" """
self.test_data = get_test_data_fps()
self.files_to_remove = []
self.dirs_to_remove = []
# Create example output directory
tmp_dir = get_qiime_temp_dir()
self.test_out = get_tmp_filename(tmp_dir=tmp_dir,
prefix='core_qiime_analyses_test_',
suffix='',
result_constructor=str)
self.dirs_to_remove.append(self.test_out)
create_dir(self.test_out)
self.qiime_config = load_qiime_config()
self.params = parse_qiime_parameters(params_f1)
# suppress stderr during tests (one of the systems calls in the
# workflow prints a warning, and we can't suppress that warning with
# warnings.filterwarnings) here because it comes from within the code
# executed through the system call. Found this trick here:
# http://stackoverflow.com/questions/9949633/suppressing-print-as-stdout-python
self.saved_stderr = sys.stderr
sys.stderr = StringIO()
initiate_timeout(180)
def setUp(self):
""" """
self.test_data = get_test_data_fps()
self.files_to_remove = []
self.dirs_to_remove = []
# Create example output directory
tmp_dir = get_qiime_temp_dir()
self.test_out = get_tmp_filename(tmp_dir=tmp_dir,
prefix='core_qiime_analyses_test_',
suffix='',
result_constructor=str)
self.dirs_to_remove.append(self.test_out)
create_dir(self.test_out)
self.qiime_config = load_qiime_config()
self.params = parse_qiime_parameters(params_f1)
# suppress stderr during tests (one of the systems calls in the
# workflow prints a warning, and we can't suppress that warning with
# warnings.filterwarnings) here because it comes from within the code
# executed through the system call. Found this trick here:
# http://stackoverflow.com/questions/9949633/suppressing-print-as-stdout-python
self.saved_stderr = sys.stderr
sys.stderr = StringIO()
initiate_timeout(180)
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
out_dir = opts.output_dir
create_dir(out_dir)
if opts.type == 'gradient':
subset_fn = choose_gradient_subset
elif opts.type == 'cluster':
subset_fn = choose_cluster_subsets
subset_otu_table, subset_map_str = subset_fn(open(opts.otu_table_fp, 'U'),
open(opts.map_fp, 'U'), opts.category, opts.num_total_samples)
subset_otu_table_fp = join(out_dir, basename(opts.otu_table_fp))
subset_otu_table_f = open(subset_otu_table_fp, 'w')
subset_otu_table.getBiomFormatJsonString('choose_data_subset.py '
'(microbiogeo)',
subset_otu_table_f)
subset_otu_table_f.close()
subset_map_fp = join(out_dir, basename(opts.map_fp))
subset_map_f = open(subset_map_fp, 'w')
subset_map_f.write(subset_map_str)
subset_map_f.close()
def split_otu_table_on_taxonomy_to_files(otu_table_fp,
level,
output_dir,
md_identifier='taxonomy',
md_processor=process_md_as_list):
""" Split OTU table by taxonomic level, writing otu tables to output dir
"""
results = []
otu_table = parse_biom_table(open(otu_table_fp, 'U'))
create_dir(output_dir)
def split_f(obs_md):
try:
result = md_processor(obs_md, md_identifier, level)
except KeyError:
raise KeyError,\
"Metadata identifier (%s) is not associated with all (or any) observerations. You can modify the key with the md_identifier parameter." % md_identifier
except TypeError:
raise TypeError,\
"Can't correctly process the metadata string. If your input file was generated from QIIME 1.4.0 or earlier you may need to pass --md_as_string."
except AttributeError:
raise AttributeError,\
"Metadata category not found. If your input file was generated from QIIME 1.4.0 or earlier you may need to pass --md_identifier \"Consensus Lineage\"."
return result
for bin, sub_otu_table in otu_table.binObservationsByMetadata(split_f):
output_fp = '%s/otu_table_%s.biom' % (output_dir, bin)
output_f = open(output_fp, 'w')
output_f.write(format_biom_table(sub_otu_table))
output_f.close()
results.append(output_fp)
return results
def main():
option_parser, opts, args =\
parse_command_line_parameters(**script_info)
mapping_fp = opts.mapping_fp
fasta_dir = opts.fasta_dir
output_dir = opts.output_dir
count_start = int(opts.count_start)
filename_column = opts.filename_column
# Check input filepaths
try:
test_mapping_f = open(mapping_fp, "U")
except IOError:
raise IOError,("Cannot open mapping filepath "+\
"%s, please check filepath and permissions." % mapping_fp)
if not isdir(fasta_dir):
raise IOError, ("Specified fasta dir " +
"%s, does not exist" % fasta_dir)
# Create output directory, check path/access to mapping file
create_dir(output_dir)
add_qiime_labels(open(mapping_fp, "U"), fasta_dir, filename_column,
output_dir, count_start)
def test_create_dir(self):
"""create_dir creates dir and fails meaningful."""
tmp_dir_path = get_random_directory_name()
tmp_dir_path2 = get_random_directory_name(suppress_mkdir=True)
tmp_dir_path3 = get_random_directory_name(suppress_mkdir=True)
self.dirs_to_remove.append(tmp_dir_path)
self.dirs_to_remove.append(tmp_dir_path2)
self.dirs_to_remove.append(tmp_dir_path3)
# create on existing dir raises OSError if fail_on_exist=True
self.assertRaises(OSError,
create_dir,
tmp_dir_path,
fail_on_exist=True)
self.assertEquals(
create_dir(tmp_dir_path,
fail_on_exist=True,
handle_errors_externally=True), 1)
# return should be 1 if dir exist and fail_on_exist=False
self.assertEqual(create_dir(tmp_dir_path, fail_on_exist=False), 1)
# if dir not there make it and return always 0
self.assertEqual(create_dir(tmp_dir_path2), 0)
self.assertEqual(create_dir(tmp_dir_path3, fail_on_exist=True), 0)
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
output_dir = opts.output_dir
if output_dir:
create_dir(output_dir)
else:
if isfile(opts.input_dir):
# if output_dir is empty after the split, then a relative path was
# passed, and the input file is in the current directory
output_dir = split(opts.input_dir)[0] or '.'
else: # opts.input_dir is a directory
output_dir = opts.input_dir
if opts.no_trim and not opts.use_sfftools:
raise ValueError(
"When using the --no_trim option you must have the sfftools installed and must also pass the --use_sfftools option")
prep_sffs_in_dir(
opts.input_dir,
output_dir,
make_flowgram=opts.make_flowgram,
convert_to_flx=opts.convert_to_FLX,
use_sfftools=opts.use_sfftools,
no_trim=opts.no_trim)
def main():
option_parser, opts, args =\
parse_command_line_parameters(**script_info)
fasta_fp = opts.fasta_fp
mapping_fp = opts.mapping_fp
output_dir = opts.output_dir
truncate_option = opts.truncate_option
primer_mismatches = int(opts.primer_mismatches)
create_dir(output_dir)
if truncate_option not in ['truncate_only', 'truncate_remove']:
raise ValueError('-z option must be either truncate_only or ' +
'truncate_remove')
try:
fasta_f = open(fasta_fp, "U")
fasta_f.close()
except IOError:
raise IOError("Unable to open fasta file, please check path/" +
"permissions.")
try:
mapping_f = open(fasta_fp, "U")
mapping_f.close()
except IOError:
raise IOError("Unable to open mapping file, please check path/" +
"permissions.")
truncate_reverse_primer(fasta_fp, mapping_fp, output_dir, truncate_option,
primer_mismatches)
def setUp(self):
self._files_to_remove = []
self.fasta_file_path = get_tmp_filename(prefix='fastq_', \
suffix='.fastq')
fastq_file = open(self.fasta_file_path, 'w')
fastq_file.write(fastq_test_string)
fastq_file.close()
#Error testing files
false_fasta_file = '/'
false_qual_file = '/'
self.read_only_output_dir = get_tmp_filename(prefix = 'read_only_', \
suffix = '/')
create_dir(self.read_only_output_dir)
chmod(self.read_only_output_dir, 0577)
self.output_dir = get_tmp_filename(prefix = 'convert_fastaqual_fastq_',\
suffix = '/')
self.output_dir += sep
create_dir(self.output_dir)
self._files_to_remove.append(self.fasta_file_path)
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
output_dir = opts.output_dir
create_dir(output_dir)
otu_table_fp = opts.otu_table
otu_table_fh = open(otu_table_fp, 'U')
otu_table = parse_biom_table(otu_table_fh)
otu_table_fh.close()
tree_fh = open(opts.tree_file, 'U')
tree = DndParser(tree_fh)
tree_fh.close()
mapping_fp = opts.mapping_fp
if mapping_fp:
mapping_f = open(mapping_fp, 'U')
input_map_basename = splitext(split(mapping_fp)[1])[0]
else:
mapping_f = None
input_map_basename = None
input_table_basename = splitext(split(otu_table_fp)[1])[0]
simsam_range_to_files(otu_table,
tree,
simulated_sample_sizes=map(int, opts.num.split(',')),
dissimilarities=map(float, opts.dissim.split(',')),
output_dir=output_dir,
mapping_f=mapping_f,
output_table_basename=input_table_basename,
output_map_basename=input_map_basename)
def main():
option_parser, opts, args = \
parse_command_line_parameters(suppress_verbose=True, **script_info)
input_dir = opts.input_dir
paired_data = opts.paired_data
parameter_fp = opts.parameter_fp
read1_indicator = opts.read1_indicator
read2_indicator = opts.read2_indicator
leading_text = opts.leading_text
trailing_text = opts.trailing_text
include_input_dir_path = opts.include_input_dir_path
output_dir = abspath(opts.output_dir)
remove_filepath_in_name = opts.remove_filepath_in_name
print_only = opts.print_only
if remove_filepath_in_name and not include_input_dir_path:
option_parser.error("If --remove_filepath_in_name is enabled, "
"--include_input_dir_path must also be enabled.")
if opts.parameter_fp:
with open(opts.parameter_fp, 'U') as parameter_f:
params_dict = parse_qiime_parameters(parameter_f)
params_str = get_params_str(params_dict['extract_barcodes'])
else:
params_dict = {}
params_str = ""
create_dir(output_dir)
all_files = []
extensions = ['.fastq.gz', '.fastq', '.fq.gz', '.fq']
for root, dir, fps in walk(input_dir):
for fp in fps:
for extension in extensions:
if fp.endswith(extension):
all_files += [abspath(join(root, fp))]
if paired_data:
all_files, bc_pairs = get_pairs(all_files, read1_indicator,
read2_indicator)
commands = create_commands_eb(all_files, paired_data, output_dir,
params_str, leading_text, trailing_text, include_input_dir_path,
remove_filepath_in_name)
qiime_config = load_qiime_config()
if print_only:
command_handler = print_commands
else:
command_handler = call_commands_serially
logger = WorkflowLogger(generate_log_fp(output_dir),
params=params_dict,
qiime_config=qiime_config)
# Call the command handler on the list of commands
command_handler(commands,
status_update_callback = no_status_updates,
logger=logger,
close_logger_on_success=True)
def test_make_plots(self):
"""make_plots: tests whether the average plots are generated and if
dictionary for the html generation is properly formatted"""
filename1='/tmp/test/testSampleIDSample1_ave.png'
filename2='/tmp/test/testSampleIDSample1_raw.png'
folder1='/tmp/test/'
self._paths_to_clean_up = [filename1,filename2]
self._folders_to_cleanup=[folder1]
exp1={'SampleID': {'Sample1': {'test': {'ave': [' 7.000', ' 2.052'], 'err': [' nan', ' 0.000']}}}}
exp2={'test': {'groups': {'SampleID': {'Sample1': {'groupcolor': '#0000ff', 'raw_link': 'html_plots/testSampleIDSample1_raw.png', 'groupsamples': ['Sample1'], 'ave_link': 'html_plots/testSampleIDSample1_ave.png'}}}, 'samples': {'Sample1': {'color': '#0000ff', 'link': 'html_plots/testSample1.png'}}}}
create_dir('/tmp/test/',False)
obs1,obs2 = make_plots(self.background_color,self.label_color, \
self.rare_data,self.ymax, self.xmax,'/tmp/test/', \
self.resolution, self.imagetype,self.groups,\
self.colors,self.data_colors,self.metric_name,\
self.labelname,self.rarefaction_data_mat, \
self.rarefaction_legend_mat,self.sample_dict, \
self.data_colors,self.colors2)
self.assertEqual(obs1,exp1)
self.assertEqual(obs2,exp2)
self.assertTrue(exists(filename1))
self.assertTrue(exists(filename2))
self.assertTrue(exists(folder1))
def main():
option_parser, opts, args =\
parse_command_line_parameters(**script_info)
mapping_fp = opts.mapping_fp
fasta_dir = opts.fasta_dir
output_dir = opts.output_dir
count_start = int(opts.count_start)
filename_column = opts.filename_column
# Check input filepaths
try:
test_mapping_f = open(mapping_fp, "U")
except IOError:
raise IOError,("Cannot open mapping filepath "+\
"%s, please check filepath and permissions." % mapping_fp)
if not isdir(fasta_dir):
raise IOError,("Specified fasta dir "+
"%s, does not exist" % fasta_dir)
# Create output directory, check path/access to mapping file
create_dir(output_dir)
add_qiime_labels(open(mapping_fp, "U"), fasta_dir, filename_column,
output_dir, count_start)
def split_otu_table_on_taxonomy_to_files(otu_table_fp,
level,
output_dir,
md_identifier='taxonomy',
md_processor=process_md_as_list):
""" Split OTU table by taxonomic level, writing otu tables to output dir
"""
results = []
otu_table = parse_biom_table(open(otu_table_fp,'U'))
create_dir(output_dir)
def split_f(obs_md):
try:
result = md_processor(obs_md,md_identifier,level)
except KeyError:
raise KeyError,\
"Metadata identifier (%s) is not associated with all (or any) observerations. You can modify the key with the md_identifier parameter." % md_identifier
except TypeError:
raise TypeError,\
"Can't correctly process the metadata string. If your input file was generated from QIIME 1.4.0 or earlier you may need to pass --md_as_string."
except AttributeError:
raise AttributeError,\
"Metadata category not found. If your input file was generated from QIIME 1.4.0 or earlier you may need to pass --md_identifier \"Consensus Lineage\"."
return result
for bin, sub_otu_table in otu_table.binObservationsByMetadata(split_f):
output_fp = '%s/otu_table_%s.biom' % (output_dir,bin)
output_f = open(output_fp,'w')
output_f.write(format_biom_table(sub_otu_table))
output_f.close()
results.append(output_fp)
return results
def main():
option_parser, opts, args =\
parse_command_line_parameters(**script_info)
otu_table_fp = opts.biom_fp
map_fp = opts.map_fp
output_dir = opts.output_dir
scolors = opts.scolors.split(',')
ocolors = opts.ocolors.split(',')
sshapes = opts.sshapes.split(',')
oshapes = opts.oshapes.split(',')
ssizes = opts.ssizes.split(',')
osizes = opts.osizes.split(',')
md_fields = opts.md_fields.split(',')
# check that the otu fields asked for are available
shared_options = ['NodeType', 'Abundance']
if not all(
[i in md_fields + shared_options for i in ocolors + oshapes + osizes]):
option_parser.error('The fields specified for observation colors, '
'sizes, or shapes are not in either the shared '
'options (NodeType,Abundance) or the supplied '
'md_fields. These fields must be a subset of the '
'union of these sets. Have you passed ocolors, '
'osizes or oshapes that are not in the md_fields?')
# check that the sample fields asked for are available. mapping file
# elements should all have same metadata keys
sopts = parse_mapping_file_to_dict(map_fp)[0].items()[0][1].keys()
if not all(
[i in sopts + shared_options for i in scolors + sshapes + ssizes]):
option_parser.error('The fields specified for sample colors, sizes, '
'or shapes are not in either the shared options '
'(NodeType,Abundance) or the supplied mapping '
'file. These fields must be a subset of the union '
'of these sets. Have you passed scolors, ssizes '
'or sshapes that are not in the mapping file '
'headers?')
# actual compuation begins
try:
create_dir(output_dir, fail_on_exist=True)
except OSError:
option_parser.error('Directory already exists. Will not overwrite.')
bt = load_table(otu_table_fp)
pmf = parse_mapping_file_to_dict(map_fp)[0] # [1] is comments, don't need
sample_node_table = make_sample_node_table(bt, pmf)
otu_node_table = make_otu_node_table(bt, opts.observation_md_header_key,
md_fields)
node_attr_table = make_node_attr_table(otu_node_table, sample_node_table,
scolors, ocolors, ssizes, osizes,
sshapes, oshapes)
edge_table = make_edge_table(bt)
_write_table(sample_node_table,
os.path.join(output_dir, 'SampleNodeTable.txt'))
_write_table(otu_node_table, os.path.join(output_dir, 'OTUNodeTable.txt'))
_write_table(node_attr_table, os.path.join(output_dir,
'NodeAttrTable.txt'))
_write_table(edge_table, os.path.join(output_dir, 'EdgeTable.txt'))
def setUp(self):
# create the temporary input files that will be used
self.iupac = {
'A': 'A',
'T': 'T',
'G': 'G',
'C': 'C',
'R': '[AG]',
'Y': '[CT]',
'S': '[GC]',
'W': '[AT]',
'K': '[GT]',
'M': '[AC]',
'B': '[CGT]',
'D': '[AGT]',
'H': '[ACT]',
'V': '[ACG]',
'N': '[ACGT]'
}
self.output_dir = get_random_directory_name(prefix='/tmp/')
self.output_dir += '/'
create_dir(self.output_dir)
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
create_dir(opts.output_dir)
generate_passwords(open(opts.personal_ids_fp, 'U'), opts.results_dir,
opts.password_dir, opts.output_dir)
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
output_dir = opts.output_dir
create_dir(output_dir)
otu_table_fp = opts.otu_table
otu_table = load_table(otu_table_fp)
tree_fh = open(opts.tree_file, 'U')
tree = DndParser(tree_fh)
tree_fh.close()
mapping_fp = opts.mapping_fp
if mapping_fp:
mapping_f = open(mapping_fp, 'U')
input_map_basename = splitext(split(mapping_fp)[1])[0]
else:
mapping_f = None
input_map_basename = None
input_table_basename = splitext(split(otu_table_fp)[1])[0]
simsam_range_to_files(otu_table,
tree,
simulated_sample_sizes=map(int, opts.num.split(',')),
dissimilarities=map(float, opts.dissim.split(',')),
output_dir=output_dir,
mapping_f=mapping_f,
output_table_basename=input_table_basename,
output_map_basename=input_map_basename)
def main():
option_parser, opts, args =\
parse_command_line_parameters(**script_info)
otu_table_fp = opts.otu_table_fp
mapping_fp = opts.mapping_fp
mapping_field = opts.mapping_field
output_dir = opts.output_dir
otu_table_base_name = splitext(split(otu_table_fp)[1])[0]
mapping_data, headers, comments = parse_mapping_file(open(mapping_fp,'U'))
try:
field_index = headers.index(mapping_field)
except ValueError:
option_parser.error("Field is not in mapping file (search is case "+\
"and white-space sensitive). \n\tProvided field: "+\
"%s. \n\tValid fields: %s" % (mapping_field,' '.join(headers)))
mapping_values = set([e[field_index] for e in mapping_data])
create_dir(output_dir)
for v in mapping_values:
v_fp_str = v.replace(' ','_')
otu_table_output_fp = join(output_dir,'%s_%s.txt' % (otu_table_base_name, v_fp_str))
mapping_output_fp = join(output_dir,'mapping_%s.txt' % v_fp_str)
filter_otus_and_map(open(mapping_fp,'U'),
open(otu_table_fp,'U'),
open(mapping_output_fp,'w'),
open(otu_table_output_fp,'w'),
valid_states_str="%s:%s" % (mapping_field,v),
num_seqs_per_otu=1)
def main():
option_parser, opts, args = \
parse_command_line_parameters(suppress_verbose=True, **script_info)
input_dir = opts.input_dir
parameter_fp = opts.parameter_fp
read1_indicator = opts.read1_indicator
read2_indicator = opts.read2_indicator
match_barcodes = opts.match_barcodes
barcode_indicator = opts.barcode_indicator
leading_text = opts.leading_text
trailing_text = opts.trailing_text
include_input_dir_path = opts.include_input_dir_path
output_dir = abspath(opts.output_dir)
remove_filepath_in_name = opts.remove_filepath_in_name
print_only = opts.print_only
if remove_filepath_in_name and not include_input_dir_path:
option_parser.error("If --remove_filepath_in_name is enabled, "
"--include_input_dir_path must also be enabled.")
if opts.parameter_fp:
with open(opts.parameter_fp, 'U') as parameter_f:
params_dict = parse_qiime_parameters(parameter_f)
params_str = get_params_str(params_dict['join_paired_ends'])
else:
params_dict = {}
params_str = ""
create_dir(output_dir)
all_files = []
extensions = ['.fastq.gz', '.fastq', '.fq.gz', '.fq']
for root, dir, fps in walk(input_dir):
for fp in fps:
for extension in extensions:
if fp.endswith(extension):
all_files += [abspath(join(root, fp))]
pairs, bc_pairs = get_pairs(all_files, read1_indicator, read2_indicator,
match_barcodes, barcode_indicator)
commands = create_commands_jpe(pairs, output_dir,
params_str, leading_text, trailing_text, include_input_dir_path,
remove_filepath_in_name, match_barcodes, bc_pairs)
qiime_config = load_qiime_config()
if print_only:
command_handler = print_commands
else:
command_handler = call_commands_serially
logger = WorkflowLogger(generate_log_fp(output_dir),
params=params_dict,
qiime_config=qiime_config)
# Call the command handler on the list of commands
command_handler(commands,
status_update_callback=no_status_updates,
logger=logger,
close_logger_on_success=True)
def split_otu_table_on_taxonomy_to_files(otu_table_fp, level, output_dir,
md_identifier='taxonomy',
md_processor=process_md_as_list):
""" Split OTU table by taxonomic level, writing otu tables to output dir
"""
results = []
otu_table = load_table(otu_table_fp)
create_dir(output_dir)
def split_f(id_, obs_md):
try:
result = md_processor(obs_md, md_identifier, level)
except KeyError:
raise KeyError("Metadata identifier (%s) is not associated with "
"all (or any) observerations. You can modify the "
"key with the md_identifier parameter." %
md_identifier)
except TypeError:
raise TypeError("Can't correctly process the metadata string. If "
"your input file was generated from QIIME 1.4.0 or"
" earlier you may need to pass --md_as_string.")
except AttributeError:
raise AttributeError("Metadata category not found. If your input "
"file was generated from QIIME 1.4.0 or "
"earlier you may need to pass --md_identifier"
" \"Consensus Lineage\".")
return result
for bin, sub_otu_table in otu_table.partition(split_f, axis='observation'):
output_fp = '%s/otu_table_%s.biom' % (output_dir, bin)
write_biom_table(sub_otu_table, output_fp)
results.append(output_fp)
return results
def copy_support_files(file_path):
"""Copy the support files to a named destination
file_path: path where you want the support files to be copied to
Will raise EmperorSupportFilesError if a problem is found whilst trying to
copy the files.
"""
file_path = join(file_path, 'emperor_required_resources')
if exists(file_path) == False:
create_dir(file_path, False)
# shutil.copytree does not provide an easy way to copy the contents of a
# directory into another existing directory, hence the system call.
# use double quotes for the paths to escape any invalid chracter(s)/spaces
cmd = 'cp -R "%s/"* "%s"' % (get_emperor_support_files_dir(),
abspath(file_path))
cmd_o, cmd_e, cmd_r = qiime_system_call(cmd)
if cmd_e:
raise EmperorSupportFilesError, "Error found whilst trying to copy " +\
"the support files:\n%s\n Could not execute: %s" % (cmd_e, cmd)
return
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
otu_table_fp = opts.otu_table_fp
mapping_fp = opts.mapping_fp
mapping_field = opts.mapping_field
output_dir = opts.output_dir
# column_rename_ids = opts.column_rename_ids
# include_repeat_cols = opts.include_repeat_cols
create_dir(output_dir)
# split mapping file
mapping_f = open(mapping_fp, 'U')
for fp_str, sub_mapping_s in split_mapping_file_on_field(mapping_f, mapping_field):
mapping_output_fp = join(output_dir, 'mapping_%s.txt' % fp_str)
open(mapping_output_fp, 'w').write(sub_mapping_s)
# split otu table
otu_table_base_name = splitext(split(otu_table_fp)[1])[0]
mapping_f = open(mapping_fp, 'U')
otu_table_f = open(otu_table_fp, 'U')
for fp_str, sub_otu_table_s in split_otu_table_on_sample_metadata(
otu_table_f,
mapping_f,
mapping_field):
otu_table_output_fp = join(
output_dir, '%s_%s.biom' %
(otu_table_base_name, fp_str))
open(otu_table_output_fp, 'w').write(sub_otu_table_s)
def setUp(self):
self._files_to_remove = []
self.fasta_file_path = get_tmp_filename(prefix='fastq_', \
suffix='.fastq')
fastq_file = open(self.fasta_file_path, 'w')
fastq_file.write(fastq_test_string)
fastq_file.close()
#Error testing files
false_fasta_file = '/'
false_qual_file = '/'
self.read_only_output_dir = get_tmp_filename(prefix = 'read_only_', \
suffix = '/')
create_dir(self.read_only_output_dir)
chmod(self.read_only_output_dir, 0577)
self.output_dir = get_tmp_filename(prefix = 'convert_fastaqual_fastq_',\
suffix = '/')
self.output_dir += sep
create_dir(self.output_dir)
self._files_to_remove.append(self.fasta_file_path)
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
otu_table_fp = opts.otu_table_fp
mapping_fp = opts.mapping_fp
mapping_field = opts.mapping_field
output_dir = opts.output_dir
# column_rename_ids = opts.column_rename_ids
# include_repeat_cols = opts.include_repeat_cols
create_dir(output_dir)
# split mapping file
mapping_f = open(mapping_fp, 'U')
for fp_str, sub_mapping_s in split_mapping_file_on_field(mapping_f, mapping_field):
mapping_output_fp = join(output_dir, 'mapping_%s.txt' % fp_str)
open(mapping_output_fp, 'w').write(sub_mapping_s)
# split otu table
otu_table_base_name = splitext(split(otu_table_fp)[1])[0]
mapping_f = open(mapping_fp, 'U')
otu_table = load_table(otu_table_fp)
try:
for fp_str, sub_otu_table_s in split_otu_table_on_sample_metadata(
otu_table,
mapping_f,
mapping_field):
otu_table_output_fp = join(output_dir, '%s_%s.biom' % (
otu_table_base_name, fp_str))
write_biom_table(sub_otu_table_s, otu_table_output_fp)
except OTUTableSplitError as e:
option_parser.error(e)
def __call__(self,
query_fasta_fp,
database_fasta_fp,
output_dir,
observation_metadata_fp=None,
params=None,
HALT_EXEC=False):
if params is None:
params = {}
""" Call the DatabaseMapper """
create_dir(output_dir)
raw_output_fp = self._get_raw_output_fp(output_dir,
params)
output_observation_map_fp = '%s/observation_map.txt' % output_dir
output_biom_fp = '%s/observation_table.biom' % output_dir
log_fp = '%s/observation_table.log' % output_dir
self._assign_dna_reads_to_database(
query_fasta_fp=query_fasta_fp,
database_fasta_fp=database_fasta_fp,
raw_output_fp=raw_output_fp,
temp_dir=get_qiime_temp_dir(),
params=params,
HALT_EXEC=HALT_EXEC)
self._process_raw_output(raw_output_fp,
log_fp,
output_observation_map_fp)
self._generate_biom_output(output_observation_map_fp,
output_biom_fp,
observation_metadata_fp)
def copy_support_files(file_path):
"""Copy the support files to a named destination
file_path: path where you want the support files to be copied to
Will raise EmperorSupportFilesError if a problem is found whilst trying to
copy the files.
"""
file_path = join(file_path, "emperor_required_resources")
if exists(file_path) == False:
create_dir(file_path, False)
# shutil.copytree does not provide an easy way to copy the contents of a
# directory into another existing directory, hence the system call.
# use double quotes for the paths to escape any invalid chracter(s)/spaces
cmd = 'cp -R "%s/"* "%s"' % (get_emperor_support_files_dir(), abspath(file_path))
cmd_o, cmd_e, cmd_r = qiime_system_call(cmd)
if cmd_e:
raise EmperorSupportFilesError, "Error found whilst trying to copy " + "the support files:\n%s\n Could not execute: %s" % (
cmd_e,
cmd,
)
return
def main():
option_parser, opts, args =\
parse_command_line_parameters(**script_info)
fasta_fp = opts.fasta_fp
mapping_fp = opts.mapping_fp
output_dir = opts.output_dir
truncate_option = opts.truncate_option
primer_mismatches = int(opts.primer_mismatches)
create_dir(output_dir)
if truncate_option not in ['truncate_only', 'truncate_remove']:
raise ValueError('-z option must be either truncate_only or ' +
'truncate_remove')
try:
fasta_f = open(fasta_fp, "U")
fasta_f.close()
except IOError:
raise IOError("Unable to open fasta file, please check path/" +
"permissions.")
try:
mapping_f = open(fasta_fp, "U")
mapping_f.close()
except IOError:
raise IOError("Unable to open mapping file, please check path/" +
"permissions.")
truncate_reverse_primer(fasta_fp, mapping_fp, output_dir, truncate_option,
primer_mismatches)
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
output_dir = opts.output_dir
if output_dir:
create_dir(output_dir)
else:
if isfile(opts.input_dir):
# if output_dir is empty after the split, then a relative path was
# passed, and the input file is in the current directory
output_dir = split(opts.input_dir)[0] or '.'
else: # opts.input_dir is a directory
output_dir = opts.input_dir
if opts.no_trim and not opts.use_sfftools:
raise ValueError(
"When using the --no_trim option you must have the sfftools installed and must also pass the --use_sfftools option"
)
prep_sffs_in_dir(opts.input_dir,
output_dir,
make_flowgram=opts.make_flowgram,
convert_to_flx=opts.convert_to_FLX,
use_sfftools=opts.use_sfftools,
no_trim=opts.no_trim)
def test_truncate_fasta_qual(self):
""" Test for overall module functionality """
base_pos = 80
output_dir = '/tmp/truncate_fasta_qual_test/'
create_dir(output_dir)
truncate_fasta_qual(self.fasta_fp, self.qual_fp, output_dir, base_pos)
actual_trunc_fasta_fp = output_dir +\
basename(self.fasta_fp).replace(".fasta", "_filtered.fasta")
actual_trunc_fasta_fp = open(actual_trunc_fasta_fp, "U")
actual_trunc_fasta = [line.strip() for line in actual_trunc_fasta_fp]
self.assertEqual(actual_trunc_fasta, expected_fasta_seqs)
actual_trunc_qual_fp = output_dir +\
basename(self.qual_fp).replace(".qual", "_filtered.qual")
actual_trunc_qual_fp = open(actual_trunc_qual_fp, "U")
actual_trunc_qual = [line.strip() for line in actual_trunc_qual_fp]
self.assertEqual(actual_trunc_qual, expected_qual_scores)
def test_plot_rank_abundance_graphs_dense(self):
"""plot_rank_abundance_graphs works with any number of samples (DenseOTUTable)"""
self.otu_table = parse_biom_table_str(otu_table_dense)
self.dir = get_tmp_filename(tmp_dir=self.tmp_dir,
prefix="test_plot_rank_abundance",
suffix="/")
create_dir(self.dir)
self._dirs_to_remove.append(self.dir)
#test empty sample name
self.assertRaises(ValueError, plot_rank_abundance_graphs, '',
self.otu_table, self.dir)
#test invalid sample name
self.assertRaises(ValueError, plot_rank_abundance_graphs,
'Invalid_sample_name',
self.otu_table, self.dir)
#test with two samples
file_type="pdf"
plot_rank_abundance_graphs('S3,S5', self.otu_table, self.dir,
file_type=file_type)
tmp_file = abspath(self.dir+"rank_abundance_cols_0_2."+file_type)
self.assertTrue(exists(tmp_file))
self.files_to_remove.append(tmp_file)
# test with all samples
plot_rank_abundance_graphs('*', self.otu_table, self.dir,
file_type=file_type)
tmp_file = abspath(self.dir+"rank_abundance_cols_0_1_2."+file_type)
self.files_to_remove.append(tmp_file)
self.assertTrue(exists(tmp_file))
def main():
option_parser, opts, args =\
parse_command_line_parameters(suppress_verbose=True, **script_info)
mapping_fp = opts.mapping_fp
has_barcodes = not opts.not_barcoded
variable_len_barcodes = opts.variable_len_barcodes
output_dir = opts.output_dir + "/"
char_replace = opts.char_replace
verbose = opts.verbose
disable_primer_check = opts.disable_primer_check
added_demultiplex_field = opts.added_demultiplex_field
# Create output directory, check path/access to mapping file
create_dir(output_dir)
# Test for valid replacement characters
valid_replacement_chars = digits + letters + "_" + "."
if char_replace not in valid_replacement_chars:
option_parser.error('-c option requires alphanumeric, period, or '+\
'underscore character.')
if len(char_replace) != 1:
option_parser.error('-c parameter must be a single character.')
check_mapping_file(mapping_fp, output_dir, has_barcodes, char_replace,\
verbose, variable_len_barcodes,
disable_primer_check, added_demultiplex_field)
def test_make_plots(self):
"""make_plots: tests whether the average plots are generated and if
dictionary for the html generation is properly formatted"""
filename1='/tmp/test/testcol_0_row_0_ave.png'
filename2='/tmp/test/testcol_0_row_0_raw.png'
folder1='/tmp/test/'
self._paths_to_clean_up = [filename1,filename2]
self._folders_to_cleanup=[folder1]
exp1={'SampleID': {'Sample1': {'test': {'ave': [' 7.000', ' 2.052'], 'err': [' nan', ' 0.000']}}}}
exp2={'test': {'groups': {'SampleID': {'Sample1': {'groupcolor': '#ff0000', 'raw_link': 'html_plots/testcol_0_row_0_raw.png', 'groupsamples': ['Sample1'], 'ave_link': 'html_plots/testcol_0_row_0_ave.png'}}}, 'samples': {'Sample1': {'color': '#ff0000', 'link': 'html_plots/testcol_0_row_0.png'}}}}
create_dir('/tmp/test/',False)
obs1,obs2 = make_plots(self.background_color,self.label_color, \
self.rare_data,self.ymax, self.xmax,'/tmp/test/', \
self.resolution, self.imagetype,self.groups,\
self.colors,self.data_colors,self.metric_name,\
self.labelname,self.rarefaction_data_mat, \
self.rarefaction_legend_mat,self.sample_dict, \
self.data_colors,self.colors2,self.mapping_lookup)
self.assertEqual(obs1,exp1)
self.assertEqual(obs2,exp2)
self.assertTrue(exists(filename1))
self.assertTrue(exists(filename2))
self.assertTrue(exists(folder1))
def test_plot_rank_abundance_graphs_dense(self):
"""plot_rank_abundance_graphs works with any number of samples (DenseOTUTable)"""
self.otu_table = parse_biom_table_str(otu_table_dense)
self.dir = get_tmp_filename(tmp_dir=self.tmp_dir,
prefix="test_plot_rank_abundance",
suffix="/")
create_dir(self.dir)
self._dirs_to_remove.append(self.dir)
tmp_fname = get_tmp_filename(tmp_dir=self.dir)
#test empty sample name
self.assertRaises(ValueError, plot_rank_abundance_graphs, tmp_fname,'',
self.otu_table)
#test invalid sample name
self.assertRaises(ValueError, plot_rank_abundance_graphs, tmp_fname,
'Invalid_sample_name',
self.otu_table)
#test with two samples
file_type="pdf"
tmp_file = abspath(self.dir+"rank_abundance_cols_0_2."+file_type)
plot_rank_abundance_graphs(tmp_file, 'S3,S5', self.otu_table,
file_type=file_type)
self.assertTrue(exists(tmp_file))
self.files_to_remove.append(tmp_file)
# test with all samples
tmp_file = abspath(self.dir+"rank_abundance_cols_0_1_2."+file_type)
plot_rank_abundance_graphs(tmp_file,'*', self.otu_table,file_type=file_type)
self.files_to_remove.append(tmp_file)
self.assertTrue(exists(tmp_file))
def main():
option_parser, opts, args =\
parse_command_line_parameters(suppress_verbose=True, **script_info)
mapping_fp = opts.mapping_fp
has_barcodes = not opts.not_barcoded
variable_len_barcodes = opts.variable_len_barcodes
output_dir = opts.output_dir + "/"
char_replace = opts.char_replace
verbose = opts.verbose
disable_primer_check = opts.disable_primer_check
added_demultiplex_field = opts.added_demultiplex_field
suppress_html = opts.suppress_html
# Create output directory, check path/access to mapping file
create_dir(output_dir)
# Test for valid replacement characters
valid_replacement_chars = digits + letters + "_" + "."
if char_replace not in valid_replacement_chars:
option_parser.error('-c option requires alphanumeric, period, or ' +
'underscore character.')
if len(char_replace) != 1:
option_parser.error('-c parameter must be a single character.')
check_mapping_file(mapping_fp, output_dir, has_barcodes, char_replace,
verbose, variable_len_barcodes, disable_primer_check,
added_demultiplex_field, suppress_html)
def test_truncate_fasta_qual(self):
""" Test for overall module functionality """
base_pos = 80
output_dir = '/tmp/truncate_fasta_qual_test/'
create_dir(output_dir)
truncate_fasta_qual(self.fasta_fp, self.qual_fp, output_dir, base_pos)
actual_trunc_fasta_fp = output_dir +\
basename(self.fasta_fp).replace(".fasta", "_filtered.fasta")
actual_trunc_fasta_fp = open(actual_trunc_fasta_fp, "U")
actual_trunc_fasta = [line.strip() for line in actual_trunc_fasta_fp]
self.assertEqual(actual_trunc_fasta, expected_fasta_seqs)
actual_trunc_qual_fp = output_dir +\
basename(self.qual_fp).replace(".qual", "_filtered.qual")
actual_trunc_qual_fp = open(actual_trunc_qual_fp, "U")
actual_trunc_qual = [line.strip() for line in actual_trunc_qual_fp]
self.assertEqual(actual_trunc_qual, expected_qual_scores)
def __call__(self,
query_fasta_fp,
database_fasta_fp,
output_dir,
observation_metadata_fp=None,
params=None,
HALT_EXEC=False):
if params is None:
params = {}
""" Call the DatabaseMapper """
create_dir(output_dir)
raw_output_fp = self._get_raw_output_fp(output_dir, params)
output_observation_map_fp = '%s/observation_map.txt' % output_dir
output_biom_fp = '%s/observation_table.biom' % output_dir
log_fp = '%s/observation_table.log' % output_dir
self._assign_dna_reads_to_database(query_fasta_fp=query_fasta_fp,
database_fasta_fp=database_fasta_fp,
raw_output_fp=raw_output_fp,
temp_dir=get_qiime_temp_dir(),
params=params,
HALT_EXEC=HALT_EXEC)
self._process_raw_output(raw_output_fp, log_fp,
output_observation_map_fp)
self._generate_biom_output(output_observation_map_fp, output_biom_fp,
observation_metadata_fp)
def main():
option_parser, opts, args =\
parse_command_line_parameters(**script_info)
create_dir(opts.output_dir, fail_on_exist=False)
post_process(opts.fasta_fp, opts.denoiser_map_file, opts.denoised_fasta_fp,
opts.otu_picker_map_file, opts.output_dir)
def setUp(self):
# create the temporary input files that will be used
self._files_to_remove = []
self.sample_fasta_file1_data = sample_fasta_file1
self.sample_fasta_file_bad_labels_data =\
sample_fasta_file_bad_labels
self.sample_mapping_file1_data = sample_mapping_file1
self.sample_mapping_file_no_revprimer_header =\
sample_mapping_file_no_revprimer_header
self.sample_mapping_file_bad_revprimer =\
sample_mapping_file_bad_revprimer
self.expected_truncation_default_settings =\
expected_truncation_default_settings
self.expected_truncation_zero_mismatches =\
expected_truncation_zero_mismatches
self.expected_truncation_zero_mismatches_truncate_remove =\
expected_truncation_zero_mismatches_truncate_remove
self.fasta_fp = get_tmp_filename(prefix='fasta_seqs_', suffix='.fna')
seq_file = open(self.fasta_fp, 'w')
seq_file.write(self.sample_fasta_file1_data)
seq_file.close()
self.fasta_badlabels_fp = get_tmp_filename(
prefix="fasta_seqs_badlabels_", suffix=".fna")
seq_file = open(self.fasta_badlabels_fp, "w")
seq_file.write(self.sample_fasta_file_bad_labels_data)
seq_file.close()
self.mapping_fp = get_tmp_filename(prefix='sample_mapping_',
suffix='.txt')
mapping_file = open(self.mapping_fp, "w")
mapping_file.write(self.sample_mapping_file1_data)
mapping_file.close()
self.mapping_bad_header_fp = get_tmp_filename(
prefix='sample_mapping_badheader_', suffix=".txt")
mapping_file = open(self.mapping_bad_header_fp, "w")
mapping_file.write(self.sample_mapping_file_no_revprimer_header)
mapping_file.close()
self.mapping_bad_primer_fp = get_tmp_filename(
prefix='sample_mapping_badprimer_', suffix=".txt")
mapping_file = open(self.mapping_bad_primer_fp, "w")
mapping_file.write(self.sample_mapping_file_bad_revprimer)
mapping_file.close()
self.output_dir = mkdtemp()
self.output_dir += '/'
create_dir(self.output_dir)
self._files_to_remove =\
[self.fasta_fp, self.mapping_fp, self.mapping_bad_header_fp,
self.mapping_bad_primer_fp, self.fasta_badlabels_fp]
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
biom_table_fp = opts.biom_table_fp
mapping_fp = opts.mapping_fp
fields = opts.fields.split(',')
output_dir = opts.output_dir
suppress_mf = opts.suppress_mapping_file_output
# column_rename_ids = opts.column_rename_ids
# include_repeat_cols = opts.include_repeat_cols
bt = load_table(biom_table_fp)
mdata, mheaders, mcomments = parse_mapping_file(mapping_fp)
mdata = array(mdata)
# check that biom file and mapping file have matching sample names. discard
# those samples that do not appear in both.
shared_samples = list(set(mdata[:, 0]).intersection(bt.ids(axis='sample')))
if len(shared_samples) == 0:
raise ValueError('Mapping file and biom table share no samples.')
elif len(shared_samples) == len(mdata[:, 0]):
mdata = array(mdata)
else:
# we want to preserve the order of the samples in the biom table
ss_bt_order = [s for s in bt.ids(axis='sample') if s in
shared_samples]
bt = bt.filter(ss_bt_order, axis='sample', inplace=True)
mdata = subset_mapping_data(mdata, shared_samples)
# check that headers in mapping data
if not all([i in mheaders for i in fields]):
raise ValueError('One or more of the specified fields was not found ' +\
'in the mapping file.')
# create output directory and create base names
create_dir(output_dir)
mf_base_name = join(output_dir, splitext(split(mapping_fp)[1])[0])
bt_base_name = join(output_dir, splitext(split(biom_table_fp)[1])[0])
# run code and append output
sample_groups, value_groups = make_non_empty_sample_lists(fields, mheaders,
mdata)
for sg, vg in zip(sample_groups, value_groups):
name_base = '__' + '%s_%s_' * len(vg) + '_'
name_tmp = []
for f, v in zip(fields, vg):
name_tmp.extend([f, v])
nb = name_base % tuple(name_tmp)
tmp_mf_data = subset_mapping_data(mdata, sg)
tmp_mf_str = format_mapping_file(mheaders, tmp_mf_data, mcomments)
write_biom_table(bt.filter(sg, axis='sample', inplace=False),
bt_base_name + nb + '.biom')
if not suppress_mf:
o = open(mf_base_name + nb + '.txt', 'w')
o.writelines(tmp_mf_str)
o.close()
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
biom_table_fp = opts.biom_table_fp
mapping_fp = opts.mapping_fp
fields = opts.fields.split(',')
output_dir = opts.output_dir
suppress_mf = opts.suppress_mapping_file_output
# column_rename_ids = opts.column_rename_ids
# include_repeat_cols = opts.include_repeat_cols
bt = load_table(biom_table_fp)
mdata, mheaders, mcomments = parse_mapping_file(mapping_fp)
mdata = array(mdata)
# check that biom file and mapping file have matching sample names. discard
# those samples that do not appear in both.
shared_samples = list(set(mdata[:, 0]).intersection(bt.ids(axis='sample')))
if len(shared_samples) == 0:
raise ValueError('Mapping file and biom table share no samples.')
elif len(shared_samples) == len(mdata[:, 0]):
mdata = array(mdata)
else:
# we want to preserve the order of the samples in the biom table
ss_bt_order = [s for s in bt.ids(axis='sample') if s in
shared_samples]
bt = bt.filter(ss_bt_order, axis='sample', inplace=True)
mdata = subset_mapping_data(mdata, shared_samples)
# check that headers in mapping data
if not all([i in mheaders for i in fields]):
raise ValueError('One or more of the specified fields was not found ' +\
'in the mapping file.')
# create output directory and create base names
create_dir(output_dir)
mf_base_name = join(output_dir, splitext(split(mapping_fp)[1])[0])
bt_base_name = join(output_dir, splitext(split(biom_table_fp)[1])[0])
# run code and append output
sample_groups, value_groups = make_non_empty_sample_lists(fields, mheaders,
mdata)
for sg, vg in zip(sample_groups, value_groups):
name_base = '__' + '%s_%s_' * len(vg) + '_'
name_tmp = []
for f, v in zip(fields, vg):
name_tmp.extend([f, v])
nb = name_base % tuple(name_tmp)
tmp_mf_data = subset_mapping_data(mdata, sg)
tmp_mf_str = format_mapping_file(mheaders, tmp_mf_data, mcomments)
write_biom_table(bt.filter(sg, axis='sample', inplace=False),
bt_base_name + nb + '.biom')
if not suppress_mf:
o = open(mf_base_name + nb + '.txt', 'w')
o.writelines(tmp_mf_str)
o.close()
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
mapping_fp = opts.mapping_fp
alpha_diversity_fp = opts.alpha_diversity_fp
categories = opts.categories.split(',')
depth = opts.depth
output_dir = opts.output_dir
correction_method = opts.correction_method
test_type = opts.test_type
num_permutations = opts.num_permutations
if num_permutations < 10:
option_parser.error('Number of permuations must be greater than or '
'equal to 10.')
create_dir(output_dir)
for category in categories:
stat_output_fp = join(output_dir, '%s_stats.txt' % category)
boxplot_output_fp = join(output_dir, '%s_boxplots.pdf' % category)
alpha_diversity_f = open(alpha_diversity_fp, 'U')
mapping_f = open(mapping_fp, 'U')
ttest_result, alphadiv_avgs = \
compare_alpha_diversities(alpha_diversity_f,
mapping_f,
category,
depth,
test_type,
num_permutations)
alpha_diversity_f.close()
mapping_f.close()
corrected_result = _correct_compare_alpha_results(
ttest_result, correction_method)
# write stats results
stat_output_f = open(stat_output_fp, 'w')
header = ('Group1\tGroup2\tGroup1 mean\tGroup1 std\tGroup2 mean\t'
'Group2 std\tt stat\tp-value')
lines = [header]
for (t0, t1), v in corrected_result.items():
lines.append('\t'.join(
map(str, [
t0, t1, alphadiv_avgs[t0][0], alphadiv_avgs[t0][1],
alphadiv_avgs[t1][0], alphadiv_avgs[t1][1], v[0], v[1]
])))
stat_output_f.write('\n'.join(lines) + '\n')
stat_output_f.close()
# write box plots
alpha_diversity_f = open(alpha_diversity_fp, 'U')
mapping_f = open(mapping_fp, 'U')
boxplot = generate_alpha_diversity_boxplots(alpha_diversity_f,
mapping_f, category, depth)
alpha_diversity_f.close()
mapping_f.close()
boxplot.savefig(boxplot_output_fp)
def main():
"""run denoiser on input flowgrams"""
option_parser, opts, args = parse_command_line_parameters(**script_info)
sff_files = opts.sff_fps
for f in sff_files:
if (not exists(f)):
option_parser.error(('Flowgram file path does not exist:\n %s \n' +
'Pass a valid one via -i.') % f)
outdir = opts.output_dir
create_dir(outdir, fail_on_exist=not opts.force)
log_fh = None
if (not (opts.primer or opts.map_fname)):
raise ApplicationError("Either mapping file or primer required")
# Read primer from Meta data file if not set on command line
if not opts.primer:
mapping_data, header, comments = \
parse_mapping_file(open(opts.map_fname, "U"))
index = header.index("LinkerPrimerSequence")
all_primers = set(array(mapping_data)[:, index])
if len(all_primers) != 1:
raise ValueError(
"Currently only data sets with one primer are allowed.\n" +
"Make separate mapping files with only one primer, re-run split_libraries and\n"
+ "denoise with each split_library output separately.")
primer = list(all_primers)[0]
last_char = primer[-1]
if (last_char not in "ACGT"):
raise ValueError("We currently do not support primer with " +
"degenerate bases at it's 3' end.")
else:
primer = opts.primer
centroids, cluster_mapping = fast_denoiser(opts.sff_fps,
opts.fasta_fp,
outdir,
opts.num_cpus,
primer,
titanium=opts.titanium)
# store mapping file and centroids
result_otu_path = '%s/denoised_clusters.txt' % outdir
of = open(result_otu_path, 'w')
for i, cluster in cluster_mapping.iteritems():
of.write('%s\t%s\n' % (str(i), '\t'.join(cluster)))
of.close()
result_fasta_path = '%s/denoised_seqs.fasta' % outdir
oh = open(result_fasta_path, 'w')
write_Fasta_from_name_seq_pairs(centroids, oh)
def main():
option_parser, opts, args =\
parse_command_line_parameters(**script_info)
otu_table_fp = opts.otu_table_fp
mapping_fp = opts.mapping_fp
tree_fp = opts.tree_fp
output_dir = opts.out_fp
output_basename = splitext(split(otu_table_fp)[1])[0]
if not output_dir:
output_dir = 'make_tep_output/'
create_dir(output_dir)
tep_fp = '%s/%s.tep' % (output_dir,output_basename) # opts.out_fp+'.tep'
jnlp_fp = '%s/%s.jnlp' % (output_dir,output_basename)
tepfile = open(tep_fp, 'w')
otu_lines = open(otu_table_fp, 'U').readlines()
sample_ids, otu_ids, otu_table, metadata = parse_otu_table(otu_lines)
mapping_lines = open(mapping_fp, 'U')
tree_lines = open(tree_fp, 'U')
lines = ['>>tre\n']
lines += tree_lines.readlines()
lines += '\n'
if(metadata):
lines += '>>otm\n#OTU ID\tOTU Metadata\n'
for i in range(len(otu_ids)):
lines += otu_ids[i] + '\t'
for m in metadata[i]:
lines += m + ';'
# lines = lines[:len(lines)-1]
lines += '\n'
lines += '>>osm\n'
lines += otu_lines
lines += '\n>>sam\n'
lines += mapping_lines.readlines()
tepfile.writelines(lines)
jnlpfile = open(jnlp_fp, 'w')
lines = [jnlp_top_block]
if(opts.web_flag):
lines += 'http://topiaryexplorer.sourceforge.net/app/'
else:
lines += 'file:'+load_qiime_config()['topiaryexplorer_project_dir']
lines += jnlp_middle_block
if(opts.url):
lines += opts.url
else:
lines += os.path.abspath(tep_fp)
# lines += os.path.abspath(tep_fp)
lines += jnlp_bottom_block
jnlpfile.writelines(lines)
def run_process_illumina_through_split_lib(study_id,run_prefix,input_fp,
mapping_fp, output_dir,
command_handler, params, qiime_config,
write_to_all_fasta=False,
status_update_callback=print_to_stdout):
""" NOTE: Parts of this function are a directly copied from the
run_qiime_data_preparation function from the workflow.py library file
in QIIME.
The steps performed by this function are:
1) De-multiplex sequences. (split_libraries_fastq.py)
"""
# Prepare some variables for the later steps
filenames=input_fp.split(',')
commands = []
create_dir(output_dir)
python_exe_fp = qiime_config['python_exe_fp']
script_dir = get_qiime_scripts_dir()
logger = WorkflowLogger(generate_log_fp(output_dir),
params=params,
qiime_config=qiime_config)
# copy the mapping file
copied_mapping=split(mapping_fp)[-1]
mapping_input_fp_copy=join(output_dir, copied_mapping)
copy_mapping_cmd='cp %s %s' % (mapping_fp,mapping_input_fp_copy)
commands.append([('CopyMapping', copy_mapping_cmd)])
# sort the filenames
filenames.sort()
# determine which file is seq-file and which is barcode-file and associate
# to mapping file
if len(filenames) == 1:
try:
# Format of sample_id needs to be seqs_<sample_name>.<sequence_prep_id>.fastq
data_access = data_access_factory(ServerConfig.data_access_type)
sql = """
select s.sample_name || '.' || sp.sequence_prep_id
from sample s
inner join sequence_prep sp
on s.sample_id = sp.sample_id
where s.study_id = {0}
and sp.run_prefix = '{1}'
""".format(study_id, run_prefix[:-1])
sample_and_prep = data_access.dynamicMetadataSelect(sql).fetchone()[0]
input_str = '-i {0} --sample_id {1}'.format(filenames[0], sample_and_prep)
except Exception, e:
error = 'Failed to obtain sample and sequence prep info for study_id {0} and run_prefix {1}\n'.format(study_id, run_prefix)
error += 'SQL was: \n {0} \n'.format(sql)
error += 'Original exception was: \n {0}'.format(str(e))
raise Exception(error)
def setUp(self):
# create the temporary input files that will be used
self.iupac = {'A':'A', 'T':'T', 'G':'G', 'C':'C', 'R':'[AG]',
'Y':'[CT]', 'S':'[GC]', 'W':'[AT]', 'K':'[GT]', 'M':'[AC]',
'B':'[CGT]','D':'[AGT]', 'H':'[ACT]', 'V':'[ACG]', 'N':'[ACGT]'}
self.output_dir = get_random_directory_name(prefix = '/tmp/')
self.output_dir += '/'
create_dir(self.output_dir)
def main():
# parse command line parameters
option_parser, opts, args = parse_command_line_parameters(**script_info)
# Create local copy of options
forward_reads_fp = opts.forward_reads_fp
reverse_reads_fp = opts.reverse_reads_fp
pe_join_method = opts.pe_join_method
output_dir = opts.output_dir
# fastq-join only options:
perc_max_diff = opts.perc_max_diff
# SeqPrep only options:
max_ascii_score = opts.max_ascii_score
min_frac_match = opts.min_frac_match
max_good_mismatch = opts.max_good_mismatch
phred_64 = opts.phred_64
# both fastq-join & SeqPrep options
min_overlap = opts.min_overlap
create_dir(output_dir, fail_on_exist=False)
# send parameters to appropriate join method
# currently only two join methods exist:
# 'fastq-join' and 'SeqPrep'
if pe_join_method == "fastq-join":
join_func = join_method_names["fastq-join"]
paths = join_func(
forward_reads_fp,
reverse_reads_fp,
perc_max_diff=perc_max_diff,
min_overlap=min_overlap,
working_dir=output_dir,
)
if pe_join_method == "SeqPrep":
join_func = join_method_names["SeqPrep"]
paths = join_func(
forward_reads_fp,
reverse_reads_fp,
max_overlap_ascii_q_score=max_ascii_score,
min_overlap=min_overlap,
max_mismatch_good_frac=max_good_mismatch,
min_frac_matching=min_frac_match,
phred_64=phred_64,
working_dir=output_dir,
)
# If index / barcode file is supplied, filter unused barcode reads
# and write them to a new file. Name based on joined-pairs / assembled
# outfile
if opts.index_reads_fp:
index_reads = opts.index_reads_fp
assembly_fp = paths["Assembled"] # grab joined-pairs output path
write_synced_barcodes_fastq(assembly_fp, index_reads)
def make_per_sample_fasta(input_seqs_fp, mapping_file, output_dir):
""" Creates per-sample fasta files from a multiplexed fasta file and a mapping file """
mapping_data, header, comments = parse_mapping_file(mapping_file, suppress_stripping=False)
for item in mapping_data:
negate = False
create_dir(output_dir)
seqs_to_keep = item[0]
output_file = join(output_dir, seqs_to_keep + '.fna')
seqs_to_keep_lookup = get_seqs_to_keep_lookup_from_prefix(open(input_seqs_fp), seqs_to_keep)
filter_fasta_fp(input_seqs_fp, output_file, seqs_to_keep_lookup, negate)
def main():
option_parser, options, args = parse_command_line_parameters(**script_info)
create_dir(options.output_dir, fail_on_exist=False)
master_tree, support_trees = load_tree_files(options.master_tree,
options.support_dir)
# get support of each node in master
new_master, bootstraps = bootstrap_support(master_tree, support_trees)
write_bootstrap_support_files(new_master, bootstraps, options.output_dir,
len(support_trees))
def main():
"""run denoiser on input flowgrams"""
option_parser, opts, args = parse_command_line_parameters(**script_info)
sff_files = opts.sff_fps
for f in sff_files:
if (not exists(f)):
option_parser.error(('Flowgram file path does not exist:\n %s \n' +
'Pass a valid one via -i.') % f)
outdir = opts.output_dir
create_dir(outdir, fail_on_exist=not opts.force)
log_fh = None
if (not (opts.primer or opts.map_fname)):
raise ApplicationError("Either mapping file or primer required")
# Read primer from Meta data file if not set on command line
if not opts.primer:
mapping_data, header, comments = \
parse_mapping_file(open(opts.map_fname, "U"))
index = header.index("LinkerPrimerSequence")
all_primers = set(array(mapping_data)[:, index])
if len(all_primers) != 1:
raise ValueError("Currently only data sets with one primer are allowed.\n" +
"Make separate mapping files with only one primer, re-run split_libraries and\n"
+ "denoise with each split_library output separately.")
primer = list(all_primers)[0]
last_char = primer[-1]
if(last_char not in "ACGT"):
raise ValueError("We currently do not support primer with " +
"degenerate bases at it's 3' end.")
else:
primer = opts.primer
centroids, cluster_mapping = fast_denoiser(opts.sff_fps, opts.fasta_fp,
outdir, opts.num_cpus, primer,
titanium=opts.titanium)
# store mapping file and centroids
result_otu_path = '%s/denoised_clusters.txt' % outdir
of = open(result_otu_path, 'w')
for i, cluster in cluster_mapping.iteritems():
of.write('%s\t%s\n' % (str(i), '\t'.join(cluster)))
of.close()
result_fasta_path = '%s/denoised_seqs.fasta' % outdir
oh = open(result_fasta_path, 'w')
write_Fasta_from_name_seq_pairs(centroids, oh)
def main():
option_parser, options, args = parse_command_line_parameters(**script_info)
create_dir(options.output_dir, fail_on_exist=False)
master_tree, support_trees = load_tree_files(options.master_tree,
options.support_dir)
# get support of each node in master
new_master, bootstraps = bootstrap_support(master_tree, support_trees)
write_bootstrap_support_files(new_master, bootstraps, options.output_dir,
len(support_trees))
def test_generate_heatmap_plots(self):
"""generate_heatmap_plots: create default output files"""
# create directories and move js files to verify everything works
# in the script file
dir_path = join(self.output_dir, 'test')
create_dir(dir_path)
js_dir_path = join(dir_path, 'js')
create_dir(js_dir_path)
self._folders_to_cleanup.append(dir_path)
qiime_dir = get_qiime_project_dir()
js_path = join(qiime_dir, 'qiime/support_files/js')
shutil.copyfile(join(js_path, 'overlib.js'),
join(js_dir_path, 'overlib.js'))
shutil.copyfile(join(js_path, 'otu_count_display.js'),
join(js_dir_path, 'otu_count_display.js'))
shutil.copyfile(join(js_path, 'jquery.js'),
join(js_dir_path, 'jquery.js'))
shutil.copyfile(join(js_path, 'jquery.tablednd_0_5.js'),
join(js_dir_path, 'jquery.tablednd_0_5.js'))
# generate otu_table object
orig_data = array([[0, 1, 2], [1000, 0, 0]])
orig_otu_table = table_factory(orig_data,
['Sample1', 'Sample2', 'Sample3'],
['OTU1', 'OTU2'], [None, None, None], [{
"taxonomy": ["Bacteria"]
}, {
"taxonomy": ["Archaea"]
}])
# put in an OTU sort order and sample order
otu_sort = ['OTU2', 'OTU1']
sample_sort = ['Sample2', 'Sample1', 'Sample3']
num_otu_hits = 3
# generate test files
generate_heatmap_plots(num_otu_hits,
orig_otu_table,
otu_sort,
sample_sort,
dir_path,
js_dir_path,
'test',
fractional_values=False)
self.assertEqual(
open(join(js_dir_path, 'test.js'), 'U').read(), exp_js_output_file)
def main():
option_parser, opts, args =\
parse_command_line_parameters(**script_info)
fasta_fp = opts.fasta_fp
qual_fp = opts.qual_fp
output_dir = opts.output_dir
base_pos = int(opts.base_pos)
create_dir(output_dir)
truncate_fasta_qual(fasta_fp, qual_fp, output_dir, base_pos)
def main():
option_parser, opts, args =\
parse_command_line_parameters(**script_info)
fasta_fp = opts.fasta_fp
qual_fp = opts.qual_fp
output_dir = opts.output_dir
base_pos = int(opts.base_pos)
create_dir(output_dir)
truncate_fasta_qual(fasta_fp, qual_fp, output_dir, base_pos)
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
create_dir(opts.output_dir, fail_on_exist=False)
levels = map(int, opts.levels.split(','))
results = generate_taxa_compare_table(opts.root_dir, opts.key_dir, levels)
results = format_output(results, opts.separator)
for level in levels:
with open(join(opts.output_dir, 'compare_table_L' + str(level) + '.txt'), 'w') as f:
f.writelines(results[level])
def main():
# parse command line parameters
option_parser, opts, args = parse_command_line_parameters(**script_info)
# Create local copy of options
input_fp = opts.input_fp
output_dir = opts.output_dir
forward_read_identifier = opts.forward_read_identifier
reverse_read_identifier = opts.reverse_read_identifier
create_dir(output_dir, fail_on_exist=False)
extract_reads_from_interleaved(input_fp, forward_read_identifier,
reverse_read_identifier, output_dir)
def main():
# parse command line parameters
option_parser, opts, args = parse_command_line_parameters(**script_info)
# Create local copy of options
forward_reads_fp = opts.forward_reads_fp
reverse_reads_fp = opts.reverse_reads_fp
pe_join_method = opts.pe_join_method
output_dir = opts.output_dir
# fastq-join only options:
perc_max_diff = opts.perc_max_diff
# SeqPrep only options:
max_ascii_score = opts.max_ascii_score
min_frac_match = opts.min_frac_match
max_good_mismatch = opts.max_good_mismatch
phred_64 = opts.phred_64
# both fastq-join & SeqPrep options
min_overlap = opts.min_overlap
create_dir(output_dir, fail_on_exist=False)
# send parameters to appropriate join method
# currently only two join methods exist:
# 'fastq-join' and 'SeqPrep'
if pe_join_method == "fastq-join":
join_func = join_method_names["fastq-join"]
paths = join_func(forward_reads_fp,
reverse_reads_fp,
perc_max_diff=perc_max_diff,
min_overlap=min_overlap,
working_dir=output_dir)
if pe_join_method == "SeqPrep":
join_func = join_method_names["SeqPrep"]
paths = join_func(forward_reads_fp,
reverse_reads_fp,
max_overlap_ascii_q_score=max_ascii_score,
min_overlap=min_overlap,
max_mismatch_good_frac=max_good_mismatch,
min_frac_matching=min_frac_match,
phred_64=phred_64,
working_dir=output_dir)
# If index / barcode file is supplied, filter unused barcode reads
# and write them to a new file. Name based on joined-pairs / assembled
# outfile
if opts.index_reads_fp:
index_reads = opts.index_reads_fp
assembly_fp = paths['Assembled'] # grab joined-pairs output path
write_synced_barcodes_fastq(assembly_fp, index_reads)
def setUp(self):
""" Creates variables and tmp filepaths for use in unit testing """
self.sample_fasta_fp = get_tmp_filename(prefix="sample_fasta_",
suffix=".fna")
seq_file = open(self.sample_fasta_fp, 'w')
seq_file.write(sample_fasta_file)
seq_file.close()
self.sample_fasta_invalid_fp = get_tmp_filename(prefix="sample_fasta_",
suffix=".fna")
seq_file = open(self.sample_fasta_invalid_fp, 'w')
seq_file.write(sample_fasta_file_invalid)
seq_file.close()
self.sample_mapping_fp = get_tmp_filename(prefix="sample_mapping_",
suffix=".txt")
map_file = open(self.sample_mapping_fp, "w")
map_file.write(sample_mapping_file)
map_file.close()
self.sample_tree_3tips_fp = get_tmp_filename(
prefix="sample_tree3tips_", suffix=".tre")
tree_file = open(self.sample_tree_3tips_fp, "w")
tree_file.write(sample_tree_file_3tips)
tree_file.close()
self.sample_tree_5tips_fp = get_tmp_filename(
prefix="sample_tree3tips_", suffix=".tre")
tree_file = open(self.sample_tree_5tips_fp, "w")
tree_file.write(sample_tree_file_5tips)
tree_file.close()
self.sample_mapping_file_errors_fp =\
get_tmp_filename(prefix="error_mapping_", suffix=".txt")
map_file = open(self.sample_mapping_file_errors_fp, "w")
map_file.write(sample_mapping_file_errors)
map_file.close()
self._files_to_remove = [
self.sample_fasta_fp, self.sample_fasta_invalid_fp,
self.sample_mapping_fp, self.sample_tree_3tips_fp,
self.sample_tree_5tips_fp, self.sample_mapping_file_errors_fp
]
self.output_dir =\
get_tmp_filename(prefix="validate_demultiplexed_fasta_",
suffix="/")
create_dir(self.output_dir)
