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#!/usr/bin/env python
# File created on 09 Feb 2010
#file make_otu_heatmap_html.py
from __future__ import division
__author__ = "Jesse Stombaugh"
__copyright__ = "Copyright 2011, The QIIME Project"
__credits__ = ["Jesse Stombaugh"]
__license__ = "GPL"
__version__ = "1.4.0"
__maintainer__ = "Jesse Stombaugh"
__email__ = "jesse.stombaugh@colorado.edu"
__status__ = "Release"
from qiime.util import parse_command_line_parameters, get_options_lookup
from qiime.util import make_option
from qiime.make_otu_heatmap_html import generate_heatmap_plots,get_otu_counts,\
get_log_transform
import os
import shutil
import os
from qiime.util import get_qiime_project_dir
from qiime.parse import parse_mapping_file
from qiime.parse import parse_newick, PhyloNode
from sys import exit
options_lookup = get_options_lookup()
#make_otu_heatmap_html.py
script_info={}
script_info['brief_description']="""Make heatmap of OTU table"""
script_info['script_description']="""Once the OTU table has been generated, the user can create an interactive OTU heatmap. This script parses the OTU count table and filters the table by counts per otu (user-specified), then converts the table into a javascript array, which can be loaded into a web application. The OTU heatmap displays raw OTU counts per sample, where the counts are colored based on the contribution of each OTU to the total OTU count present in that sample (blue: contributes low percentage of OTUs to sample; red: contributes high percentage of OTUs). This web application allows the user to filter the otu table by number of counts per otu. The user also has the ability to view the table based on taxonomy assignment. Additional features include: the ability to drag rows (up and down) by clicking and dragging on the row headers; and the ability to zoom in on parts of the heatmap by clicking on the counts within the heatmap."""
script_info['script_usage']=[]
script_info['script_usage'].append(("""Examples:""","""By using the default values ("-n 5), you can then use the code as follows:""","""%prog -i otu_table.txt"""))
script_info['script_usage'].append(("","""If you would like to filter the OTU table by a different number of counts per OTU (i.e., 10), you can use the following code:""","""%prog -i otu_table.txt -n 10"""))
script_info['script_usage'].append(("","""If you would like to specify a different output directory (i.e., "otu_heatmap"), you can use the following code:""","""%prog -i otu_table.txt -o otu_heatmap"""))
script_info['script_usage'].append(("","""If you would like to sort the heatmap by Sample ID's then you should supply the mapping file, as follows:""","""%prog -i otu_table.txt -o otu_heatmap -m mapping_file.txt"""))
script_info['script_usage'].append(("","""If you would like to sort the heatmap by Sample ID's and the tips in the tree, you can supply a tree as follows:""","""%prog -i otu_table.txt -o otu_heatmap -m mapping_file.txt -t tree_file.txt"""))
script_info['output_description']="""The interactive heatmap is located in a randomly generated folder where the name of the folder starts with "otu_table". The resulting folder contains the interactive heatmap (html file) along with a javascript library folder. This web application has been tested in Mozilla Firefox and Safari. Safari is recommended for viewing the OTU Heatmap, since the HTML table generation is much faster."""
script_info['required_options']=[\
options_lookup['otu_table_as_primary_input']
]
script_info['optional_options']=[\
options_lookup['output_dir'],
make_option('-n', '--num_otu_hits',
help='Only include OTUs with at least this many sequences.' +\
' [default: %default]',default=5, type='int'),
make_option('-t','--tree',
help='Path to newick tree where OTUs are tips, used for sorting' +\
' OTUs in the heatmap',default=None,
type='existing_filepath'),
make_option('-m', '--map_fname',
help='Input metadata mapping filepath, used for sorting' +\
' samples in the heatmap',default=None,
type='existing_filepath'),
make_option('--sample_tree',
help='Path to newick tree where samples are tips' +\
' (e.g, output from upgma_cluster.py) used for sorting samples in' +\
' the heatmap. If both this and the metadata' +\
' mapping file are provided, the mapping file will be ignored.',
default=None,
type='existing_filepath'),
make_option('--log_transform', action="store_true",
help='Log-transform the data. All zeros will be set' +\
' to a small value (default is 1/2 of the smallest non-zero entry).' +\
' Data will be translated to be non-negative after log transform and' +\
' the num_otu_hits will be set to 0.',
default=False),
make_option('--log_eps', type="float",
help='Small value to replace zeros when performing log' +\
' transformation. [default: 1/2 the smallest non-zero entry].',
default=None),
]
script_info['option_label']={'otu_table_as_primary_input':'OTU table filepath',
'map_fname':'QIIME-formatted mapping filepath',
'num_otu_hits': '# of sequences',
'output_dir': 'Output directory',
'tree': 'Newick tree filepath',
'sample_tree': 'Newick tree filepath (containing samples on tips)',
'log_transform':'Perform log transformation',
'log_eps': 'Replace zeros w this value x smallest non-zero value'}
script_info['version'] = __version__
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
data = {}
#Open and get coord data
data['otu_counts'] = list(get_otu_counts(opts.otu_table_fp, data))
# determine whether fractional values are present in OTU table
if opts.log_transform:
if not opts.log_eps is None and opts.log_eps <= 0:
print "Parameter 'log_eps' must be positive. Value was", opts.log_eps
exit(1)
data['otu_counts'][2] = get_log_transform(data['otu_counts'][2], opts.log_eps)
opts.num_otu_hits = 0
# test: if using relative abundances, and opts.num_otu_hits > 0
# print warning and set to 0
fractional_values = ((data['otu_counts'][2] > 0) & \
(data['otu_counts'][2] < 1)).any()
if fractional_values and (data['otu_counts'][2]).max() <= 1:
if opts.num_otu_hits > 0:
print "Warning: OTU table appears to be using relative abundances",\
"and num_otu_hits was set to %d. Setting num_otu_hits to 0."\
%(opts.num_otu_hits)
opts.num_otu_hits = 0
filepath=opts.otu_table_fp
filename=filepath.strip().split('/')[-1].split('.')[0]
if opts.output_dir:
if os.path.exists(opts.output_dir):
dir_path=opts.output_dir
else:
try:
os.mkdir(opts.output_dir)
dir_path=opts.output_dir
except OSError:
pass
else:
dir_path='./'
js_dir_path = os.path.join(dir_path,'js')
try:
os.mkdir(js_dir_path)
except OSError:
pass
qiime_dir=get_qiime_project_dir()
js_path=os.path.join(qiime_dir,'qiime/support_files/js')
shutil.copyfile(os.path.join(js_path,'overlib.js'), os.path.join(js_dir_path,'overlib.js'))
shutil.copyfile(os.path.join(js_path,'otu_count_display.js'), os.path.join(js_dir_path,'otu_count_display.js'))
shutil.copyfile(os.path.join(js_path,'jquery.js'), os.path.join(js_dir_path,'jquery.js'))
shutil.copyfile(os.path.join(js_path,'jquery.tablednd_0_5.js'), os.path.join(js_dir_path,'jquery.tablednd_0_5.js'))
# load tree for sorting OTUs
ordered_otu_names = None
if not opts.tree is None:
try:
f = open(opts.tree, 'U')
except (TypeError, IOError):
raise TreeMissingError, \
"Couldn't read tree file at path: %s" % tree_source
tree = parse_newick(f, PhyloNode)
f.close()
ordered_otu_names = [tip.Name for tip in tree.iterTips()]
ordered_sample_names = None
# load tree for sorting Samples
if not opts.sample_tree is None:
try:
f = open(opts.sample_tree, 'U')
except (TypeError, IOError):
raise TreeMissingError, \
"Couldn't read tree file at path: %s" % tree_source
tree = parse_newick(f, PhyloNode)
f.close()
ordered_sample_names = [tip.Name for tip in tree.iterTips()]
# if there's no sample tree, load sample map for sorting samples
elif not opts.map_fname is None:
lines = open(opts.map_fname,'U').readlines()
map = parse_mapping_file(lines)[0]
ordered_sample_names = [row[0] for row in map]
data['otu_order'] = ordered_otu_names
data['sample_order'] = ordered_sample_names
try:
action = generate_heatmap_plots
except NameError:
action = None
#Place this outside try/except so we don't mask NameError in action
if action:
action(opts,data, dir_path,js_dir_path,filename, fractional_values)
if __name__ == "__main__":
main()
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