if not args.output:
parser.error("An output directory is required.")
elif not exists(args.output):
mkdir(args.output)
output_dir = args.output
# Parses the category argument
if not args.categories:
categories = {}
else:
cat_set = [c for c in args.categories.split(',')]
category_fp = {
c.strip().split(':')[0]: c.strip().split(':')[1]
for c in cat_set
}
categories = load_category_files(category_files=category_fp)
# Deals with the sample list
if args.samples_to_plot:
samples = args.samples_to_plot
samples = samples.split(',')
else:
samples = None
# Checks the sample type is sane
if args.sample_type:
if args.sample_type in SAMPLE_TYPES:
sample_type = args.sample_type
else:
parser.error('%s is not a supported sample type.' %
args.sample_type)
parser.error("An input mapping file is required.")
elif not isfile(args.mapping):
parser.error('he supplied file does not exist in the path')
else:
mapping = open(args.mapping, 'U')
# Checks the output directory is sane
if not args.output:
parser.error("An output directory is required.")
elif not exists(args.output):
mkdir(args.output)
output_dir = args.output
# Parses the category argument
if not args.categories:
categories = {}
else:
category_fp = dict([c.strip().split(':') \
for c in args.categories.split(',')])
categories = load_category_files(category_fp, LEVEL)
# Deals with the sample list
if args.samples_to_plot:
samples = args.samples_to_plot
samples = samples.split(',')
else:
samples = None
main(otu_table, mapping, output_dir = output_dir, \
categories = categories, samples_to_plot = samples)
def main(otu_table, mapping_data, categories, output_dir, \
samples_to_plot = None, legend = False, xaxis = True):
"""Creates stacked bar plots for an otu table
INPUTS:
otu_table -- an open OTU table
mapping_data -- a tab delimited string containing the mapping data
passed from the mapping file.
categories -- a dictionary keying a mapping category to the
corresponding sample IDs and taxonomy for a collapsed
biom table
output_dir -- the location of the directory where output files should be
saved. If this directory does not exist, it will be created.
samples_to_plot -- a list of sample ids to plot. If no value is passed,
then all samples in the biom table are analyzed.
OUTPUTS:
A pdf of stacked taxonomy will be generated for each sample and saved
in the output directory. These will follow the file name format
Figure_4_<SAMPLEID>.pdf
"""
# Sets constants
LEVEL = 2
FILEPREFIX = 'Figure_4_'
MICHAEL_POLLAN = '000007108.1075657'
NUM_TAXA = 9
NUM_CATS_TO_PLOT = 7
# Loads the mapping file
map_dict = map_to_2D_dict(mapping_data)
(common_taxa, whole_sample_ids, whole_summary) = \
summarize_human_taxa(otu_table, LEVEL)
# Converts final taxa to a clean list
common_phyla = []
for taxon in common_taxa:
common_phyla.append(taxon[1].strip(' p__').strip('[').strip(']'))
common_taxa = common_phyla
# Checks that the correct sample ids are plotted
if samples_to_plot == None:
sample_ids = whole_sample_ids
else:
sample_ids = samples_to_plot
# Identifies Michael Pollan's pre-ABX sample
mp_sample_pos = whole_sample_ids.index(MICHAEL_POLLAN)
mp_sample_taxa = whole_summary[:,mp_sample_pos]
# Loads the category dictionary
categories = load_category_files(category_fp, LEVEL)
# Generates a figure for each sample
for idx, sample_id in enumerate(whole_sample_ids):
if sample_id in sample_ids:
# Preallocates a numpy array for the plotting data
tax_array = zeros((NUM_TAXA, NUM_CATS_TO_PLOT))
meta_data = map_dict[sample_id]
cat_list = ['You', 'Average', 'Similar Diet', ' Similar BMI',
'Same Gender', 'Similar Age',
'Michael Pollan', '']
#cat_list.append('Your Fecal Sample')
#cat_list.append('Average Fecal Samples')
tax_array[:,0] = whole_summary[:,idx]
tax_array[:,1] = mean(whole_summary, 1)
cat_watch = 2
# Identifies the appropriate metadata categories
for cat in categories:
# Pulls metadata for the sample and category
mapping_key = meta_data[cat]
# Pulls taxonomic summary and group descriptions for the category
tax_summary = categories[cat]['Taxa Summary']
group_descriptions = categories[cat]['Groups']
# Amends plotting tables
try:
mapping_col = group_descriptions.index(mapping_key)
except:
raise ValueError, 'The %s cannot be found in %s.' \
% (mapping_key, cat)
tax_array[:,cat_watch] = tax_summary[:,mapping_col]
cat_watch = cat_watch + 1
tax_array[:,-1] = mp_sample_taxa
# Plots the data
filename = pjoin(output_dir, '%s%s.pdf' \
% (FILEPREFIX, sample_id))
plot_american_gut(tax_array, filename)
# Checks the output directory is sane
if not args.output:
parser.error("An output directory is required.")
elif not exists(args.output):
mkdir(args.output)
output_dir = args.output
# Parses the category argument
if not args.categories:
categories = {}
else:
cat_set = [c for c in args.categories.split(',')]
category_fp = {c.strip().split(':')[0]: c.strip().split(':')[1]
for c in cat_set}
categories = load_category_files(category_files=category_fp)
# Deals with the sample list
if args.samples_to_plot:
samples = args.samples_to_plot
samples = samples.split(',')
else:
samples = None
# Checks the sample type is sane
if args.sample_type:
if args.sample_type in SAMPLE_TYPES:
sample_type = args.sample_type
else:
parser.error('%s is not a supported sample type.'
% args.sample_type)
