def run_core_diversity_analyses(
biom_fp,
mapping_fp,
sampling_depth,
output_dir,
qiime_config,
command_handler=call_commands_serially,
tree_fp=None,
params=None,
categories=None,
arare_min_rare_depth=10,
arare_num_steps=10,
parallel=False,
status_update_callback=print_to_stdout):
"""
"""
if categories != None:
# Validate categories provided by the users
mapping_data, mapping_comments = \
parse_mapping_file_to_dict(open(mapping_fp,'U'))
metadata_map = MetadataMap(mapping_data, mapping_comments)
for c in categories:
if c not in metadata_map.CategoryNames:
raise ValueError, ("Category '%s' is not a column header "
"in your mapping file. "
"Categories are case and white space sensitive. Valid "
"choices are: (%s)" % (c,', '.join(metadata_map.CategoryNames)))
if metadata_map.hasSingleCategoryValue(c):
raise ValueError, ("Category '%s' contains only one value. "
"Categories analyzed here require at least two values." % c)
else:
categories= []
# prep some variables
if params == None:
params = parse_qiime_parameters([])
create_dir(output_dir)
index_fp = '%s/index.html' % output_dir
index_links = []
commands = []
python_exe_fp = qiime_config['python_exe_fp']
script_dir = get_qiime_scripts_dir()
# begin logging
log_fp = generate_log_fp(output_dir)
index_links.append(('Master run log',log_fp,'Log files'))
logger = WorkflowLogger(log_fp,
params=params,
qiime_config=qiime_config)
input_fps = [biom_fp,mapping_fp]
if tree_fp != None:
input_fps.append(tree_fp)
log_input_md5s(logger,input_fps)
bdiv_even_output_dir = '%s/bdiv_even%d/' % (output_dir,sampling_depth)
even_dm_fps = run_beta_diversity_through_plots(
otu_table_fp=biom_fp,
mapping_fp=mapping_fp,
output_dir=bdiv_even_output_dir,
command_handler=command_handler,
params=params,
qiime_config=qiime_config,
sampling_depth=sampling_depth,
# force suppression of distance histograms - boxplots work better
# in this context, and are created below.
histogram_categories=[],
tree_fp=tree_fp,
parallel=parallel,
logger=logger,
status_update_callback=status_update_callback)
for bdiv_metric, dm_fp in even_dm_fps:
for category in categories:
boxplots_output_dir = '%s/%s_boxplots/' % (bdiv_even_output_dir,bdiv_metric)
try:
params_str = get_params_str(params['make_distance_boxplots'])
except KeyError:
params_str = ''
boxplots_cmd = \
'make_distance_boxplots.py -d %s -f %s -o %s -m %s -n 999 %s' %\
(dm_fp, category, boxplots_output_dir, mapping_fp, params_str)
commands.append([('Boxplots (%s)' % category,
boxplots_cmd)])
index_links.append(('Distance boxplots (%s)' % bdiv_metric,
'%s/%s_Distances.pdf' % \
(boxplots_output_dir,category),
'Beta diversity results (even sampling: %d)' % sampling_depth))
index_links.append(('Distance boxplots statistics (%s)' % bdiv_metric,
'%s/%s_Stats.txt' % \
(boxplots_output_dir,category),
'Beta diversity results (even sampling: %d)' % sampling_depth))
index_links.append(('3D plot (%s, continuous coloring)' % bdiv_metric,
'%s/%s_3d_continuous/%s_pc_3D_PCoA_plots.html' % \
(bdiv_even_output_dir,bdiv_metric,bdiv_metric),
'Beta diversity results (even sampling: %d)' % sampling_depth))
index_links.append(('3D plot (%s, discrete coloring)' % bdiv_metric,
'%s/%s_3d_discrete/%s_pc_3D_PCoA_plots.html' % \
(bdiv_even_output_dir,bdiv_metric,bdiv_metric),
'Beta diversity results (even sampling: %d)' % sampling_depth))
index_links.append(('2D plot (%s, continuous coloring)' % bdiv_metric,
'%s/%s_2d_continuous/%s_pc_2D_PCoA_plots.html' % \
(bdiv_even_output_dir,bdiv_metric,bdiv_metric),
'Beta diversity results (even sampling: %d)' % sampling_depth))
index_links.append(('2D plot (%s, discrete coloring)' % bdiv_metric,
'%s/%s_2d_discrete/%s_pc_2D_PCoA_plots.html' % \
(bdiv_even_output_dir,bdiv_metric,bdiv_metric),
'Beta diversity results (even sampling: %d)' % sampling_depth))
index_links.append(('Distance matrix (%s)' % bdiv_metric,
'%s/%s_dm.txt' % \
(bdiv_even_output_dir,bdiv_metric),
'Beta diversity results (even sampling: %d)' % sampling_depth))
index_links.append(('Principal coordinate matrix (%s)' % bdiv_metric,
'%s/%s_pc.txt' % \
(bdiv_even_output_dir,bdiv_metric),
'Beta diversity results (even sampling: %d)' % sampling_depth))
## Alpha rarefaction workflow
arare_full_output_dir = '%s/arare_max%d/' % (output_dir,sampling_depth)
run_qiime_alpha_rarefaction(
otu_table_fp=biom_fp,
mapping_fp=mapping_fp,
output_dir=arare_full_output_dir,
command_handler=command_handler,
params=params,
qiime_config=qiime_config,
tree_fp=tree_fp,
num_steps=arare_num_steps,
parallel=parallel,
logger=logger,
min_rare_depth=arare_min_rare_depth,
max_rare_depth=sampling_depth,
status_update_callback=status_update_callback)
index_links.append(('Alpha rarefaction plots',
'%s/alpha_rarefaction_plots/rarefaction_plots.html'\
% arare_full_output_dir,
"Alpha rarefaction results"))
collated_alpha_diversity_fps = \
glob('%s/alpha_div_collated/*txt' % arare_full_output_dir)
try:
params_str = get_params_str(params['compare_alpha_diversity'])
except KeyError:
params_str = ''
for c in categories:
for collated_alpha_diversity_fp in collated_alpha_diversity_fps:
alpha_metric = splitext(split(collated_alpha_diversity_fp)[1])[0]
alpha_comparison_output_fp = '%s/%s_%s.txt' % \
(arare_full_output_dir,c,alpha_metric)
compare_alpha_cmd = \
'compare_alpha_diversity.py -i %s -m %s -c %s -d %s -o %s -n 999 %s' %\
(collated_alpha_diversity_fp, mapping_fp, c,
sampling_depth, alpha_comparison_output_fp, params_str)
commands.append([('Compare alpha diversity (%s, %s)' %\
(category,alpha_metric),
compare_alpha_cmd)])
index_links.append(
('Alpha diversity statistics (%s, %s)' % (category,alpha_metric),
alpha_comparison_output_fp,
"Alpha rarefaction results"))
taxa_plots_output_dir = '%s/taxa_plots/' % output_dir
run_summarize_taxa_through_plots(
otu_table_fp=biom_fp,
mapping_fp=mapping_fp,
output_dir=taxa_plots_output_dir,
mapping_cat=None,
sort=True,
command_handler=command_handler,
params=params,
qiime_config=qiime_config,
logger=logger,
status_update_callback=status_update_callback)
index_links.append(('Taxa summary bar plots',
'%s/taxa_summary_plots/bar_charts.html'\
% taxa_plots_output_dir,
"Taxonomic summary results"))
index_links.append(('Taxa summary area plots',
'%s/taxa_summary_plots/area_charts.html'\
% taxa_plots_output_dir,
"Taxonomic summary results"))
for c in categories:
taxa_plots_output_dir = '%s/taxa_plots_%s/' % (output_dir,c)
run_summarize_taxa_through_plots(
otu_table_fp=biom_fp,
mapping_fp=mapping_fp,
output_dir=taxa_plots_output_dir,
mapping_cat=c,
sort=True,
command_handler=command_handler,
params=params,
qiime_config=qiime_config,
logger=logger,
status_update_callback=status_update_callback)
index_links.append(('Taxa summary bar plots',
'%s/taxa_summary_plots/bar_charts.html'\
% taxa_plots_output_dir,
"Taxonomic summary results (by %s)" % c))
index_links.append(('Taxa summary area plots',
'%s/taxa_summary_plots/area_charts.html'\
% taxa_plots_output_dir,
"Taxonomic summary results (by %s)" % c))
# OTU category significance
for category in categories:
category_signifance_fp = \
'%s/category_significance_%s.txt' % (output_dir, category)
try:
params_str = get_params_str(params['otu_category_significance'])
except KeyError:
params_str = ''
# Build the OTU cateogry significance command
category_significance_cmd = \
'otu_category_significance.py -i %s -m %s -c %s -o %s %s' %\
(biom_fp, mapping_fp, category,
category_signifance_fp, params_str)
commands.append([('OTU category significance (%s)' % category,
category_significance_cmd)])
index_links.append(('Category significance (%s)' % category,
category_signifance_fp,
"Category results"))
command_handler(commands, status_update_callback, logger)
generate_index_page(index_links,index_fp)
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
verbose = opts.verbose
otu_table_fp = opts.otu_table_fp
output_dir = opts.output_dir
mapping_fp = opts.mapping_fp
tree_fp = opts.tree_fp
num_steps = opts.num_steps
verbose = opts.verbose
print_only = opts.print_only
parallel = opts.parallel
min_rare_depth = opts.min_rare_depth
max_rare_depth = opts.max_rare_depth
if opts.parameter_fp:
try:
parameter_f = open(opts.parameter_fp)
except IOError:
raise IOError,\
"Can't open parameters file (%s). Does it exist? Do you have read access?"\
% opts.parameter_fp
params = parse_qiime_parameters(parameter_f)
else:
params = parse_qiime_parameters([])
# empty list returns empty defaultdict for now
jobs_to_start = opts.jobs_to_start
default_jobs_to_start = qiime_config['jobs_to_start']
validate_and_set_jobs_to_start(params,
jobs_to_start,
default_jobs_to_start,
parallel,
option_parser)
try:
makedirs(output_dir)
except OSError:
if opts.force:
pass
else:
# Since the analysis can take quite a while, I put this check
# in to help users avoid overwriting previous output.
option_parser.error("Output directory already exists. Please choose"
" a different directory, or force overwrite with -f.")
if print_only:
command_handler = print_commands
else:
command_handler = call_commands_serially
if verbose:
status_update_callback = print_to_stdout
else:
status_update_callback = no_status_updates
run_qiime_alpha_rarefaction(otu_table_fp=otu_table_fp,\
mapping_fp=mapping_fp,\
output_dir=output_dir,\
command_handler=command_handler,\
params=params,
qiime_config=qiime_config,\
tree_fp=tree_fp,\
num_steps=num_steps,\
parallel=parallel,\
min_rare_depth=min_rare_depth,
max_rare_depth=max_rare_depth,
status_update_callback=status_update_callback)
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
verbose = opts.verbose
otu_table_fp = opts.otu_table_fp
output_dir = opts.output_dir
mapping_fp = opts.mapping_fp
tree_fp = opts.tree_fp
num_steps = opts.num_steps
verbose = opts.verbose
print_only = opts.print_only
parallel = opts.parallel
min_rare_depth = opts.min_rare_depth
max_rare_depth = opts.max_rare_depth
if opts.parameter_fp:
try:
parameter_f = open(opts.parameter_fp)
except IOError:
raise IOError,\
"Can't open parameters file (%s). Does it exist? Do you have read access?"\
% opts.parameter_fp
params = parse_qiime_parameters(parameter_f)
else:
params = parse_qiime_parameters([])
# empty list returns empty defaultdict for now
jobs_to_start = opts.jobs_to_start
default_jobs_to_start = qiime_config['jobs_to_start']
validate_and_set_jobs_to_start(params, jobs_to_start,
default_jobs_to_start, parallel,
option_parser)
try:
makedirs(output_dir)
except OSError:
if opts.force:
pass
else:
# Since the analysis can take quite a while, I put this check
# in to help users avoid overwriting previous output.
print "Output directory already exists. Please choose "+\
"a different directory, or force overwrite with -f."
exit(1)
if print_only:
command_handler = print_commands
else:
command_handler = call_commands_serially
if verbose:
status_update_callback = print_to_stdout
else:
status_update_callback = no_status_updates
run_qiime_alpha_rarefaction(otu_table_fp=otu_table_fp,\
mapping_fp=mapping_fp,\
output_dir=output_dir,\
command_handler=command_handler,\
params=params,
qiime_config=qiime_config,\
tree_fp=tree_fp,\
num_steps=num_steps,\
parallel=parallel,\
min_rare_depth=min_rare_depth,
max_rare_depth=max_rare_depth,
status_update_callback=status_update_callback)