def work(name, params):
cmp_dir = '%s/%s/upgma_cmp' % (params['out_dir'], name)
tree = '%s/master_tree.tre' % cmp_dir
support = '%s/color_support.txt' % cmp_dir
get_support_file(params['group'], tree_file=tree, support_file=support)
pdf = '%s/%s_cluster.pdf' % (params['out_dir'], name)
png = '%s/%s_cluster.png' % (params['out_dir'], name)
command = '%s -m %s -s %s -o %s' % (params['bootstrap_soft'],
tree,
support,
pdf)
os.system(command)
image_trans(pdf, png)
return command
def work(r_job, name, params):
file = os.popen('ls %s/%s*.txt' % (params['beta_dir'], name)).read().strip()
pdf_file = '%s/%s.heatmap.pdf' % (params['out_dir'], name)
png_file = '%s/%s.heatmap.png' % (params['out_dir'], name)
R_file = '%s/%s.heatmap.R' % (params['out_dir'], name)
distance_name = name.replace('_', ' ').title()
vars = {'for_plot': file,
'group_file': params['group_file'],
'pdf_file': pdf_file,
'distance_name': distance_name}
r_job.format(vars)
r_job.write(R_file)
r_job.run()
image_trans(pdf_file, png_file)
def work(r_job, name, params):
file_name = os.popen('ls %s/%s*.txt' % (params['beta_dir'], name)).read().strip()
file_pdf = '%s/%s.anosim.pdf' % (params['out_dir'], name)
file_png = '%s/%s.anosim.png' % (params['out_dir'], name)
file_R = '%s/%s.anosim.R' % (params['out_dir'], name)
distance_name = name.replace('_', ' ').title()
vars_in = {'distance_table': file_name,
'group_file': params['group_file'],
'pdf_file': file_pdf,
'distance_name': distance_name
}
r_job.format(vars_in)
r_job.write(file_R)
r_job.run()
image_trans(file_pdf, file_png)
def plot_one_tree(newick_file, profile_dict, node_dict, params, prefix=''):
t = Tree(newick_file, format=1)
ts = get_tree_style()
set_node_default(t, node_dict=node_dict)
suf = ''
if params['with_branch_circle']:
add_node_circle(t, node_dict=node_dict)
suf += '_circle'
if params['with_leaf_pie'] and not params['with_branch_circle']:
remove_node_circle(t, node_dict=node_dict)
if params['with_leaf_pie']:
add_pie_face(t, ts, profile_dict, group=params['group'])
suf += '_pie'
add_branch_text(t, tree_style=ts, node_dict=node_dict)
set_node_style(t, node_dict=node_dict)
if prefix:
prefix += '_'
pdf_file = '%s/%stax_tree%s.pdf' % (params['outdir'], prefix, suf)
png_file = '%s/%stax_tree%s.png' % (params['outdir'], prefix, suf)
t.render(pdf_file, tree_style=ts, dpi=100)
image_trans(pdf_file, png_file)
search_name[value] = outlevel_name
with open(outfile,"w") as fqout:
for key,value in search_name.items():
fqout.write("%s\t%s\n" %(key.split("__")[1],value.split("__")[1]))
mkdir(params['out_dir'])
if params['for_plot'] is None:
params['for_plot'] = params['out_dir'] + '/for_plot.txt'
tax_profile_filter(params['otu_table'], params['for_plot'], params['level'])
pdf_file = params['out_dir'] + '/heatmap.pdf'
png_file = params['out_dir'] + '/heatmap.png'
vars = {'row_group':outfile,
'heatmap_profile': params['for_plot'],
'pdf_file': pdf_file,
'group': params['group'],
'top': params['top'],
'dendrogram': params['dendrogram']}
r_job = rp.Rparser()
r_job.open(this_script_path + '/../src/template/03_tax_heatmap_twolegend.Rtp')
r_job.format(vars)
r_job.write(params['out_dir'] + '/heatmap.R')
r_job.run()
image_trans(pdf_file, png_file)
mkdir(params['upload_dir'])
subject = mg.Subject(infile_list=params['infile_list'],
upload_dir=params['upload_dir'],
out_fasta_file=params['out_fasta_file'],
out_stat_file=params['out_stat_file'],
upload_stat=params['upload_stat'],
required_data=params['required'],
out_length_file=params['length_stat_file'],
max_length=params['max_length'],
min_length=params['min_length'],
length_step=params['length_step'],
name_table_file=params['name_table'],
required_data_file=params['required_file'],)
subject.read_name_table()
subject.merge()
subject.write_stat()
subject.upload_stat()
subject.write_length()
# R works
r_job = rp.Rparser()
r_job.open(this_script_path + '/../src/template/00_sum_length.Rtp')
vars = {'pdf_out': params['outdir'] + '/length_distrubution.pdf',
'length_stat': params['length_stat_file'],
}
r_job.format(vars)
r_job.write(params['outdir'] + '/length_distrubution.R')
r_job.run()
image_trans(params['outdir'] + '/length_distrubution.pdf', params['outdir'] + '/length_distrubution.png')
help="set the work dir")
parser.add_argument('-g',
'--group',
dest='group',
metavar='FILE',
type=str,
required=True,
help="set the group file")
args = parser.parse_args()
params = vars(args)
return params
if __name__ == '__main__':
params = read_params(sys.argv)
mkdir(params['outdir'])
r_job = rp.Rparser()
r_job.open(this_script_path + '/../src/template/05_diff_pca.Rtp')
r_file = params['outdir'] + '/diff_pca.R'
pdf_file = params['outdir'] + '/diff_pca.pdf'
png_file = params['outdir'] + '/diff_pca.png'
var = {
'input_file': params['infile'],
'group_file': params['group'],
'pdf_file': pdf_file
}
r_job.format(var)
r_job.write(r_file)
r_job.run()
image_trans(pdf_file, png_file)
print "sample %s no in group" % samples[ind]
return otu_in_group
def write(otu_in_group, outfile):
with open(outfile, 'w') as fp:
for group, otus in otu_in_group.iteritems():
otus = sorted(list(otus), cmp=lambda a, b: cmp(int(a), int(b)))
fp.write('%s\t%s\n' % (group, ' '.join(otus)))
if __name__ == '__main__':
params = read_params(sys.argv)
mkdir(params['out_dir'])
for_plot = params['out_dir'] + '/for_plot.txt'
tiff_file = params['out_dir'] + '/venn.tiff'
png_file = params['out_dir'] + '/venn.png'
vars = {'for_plot': for_plot,
'tiff_file': tiff_file,
'group_file': params['group_dir']}
otu_in_group = read(params['otu_table'], params['group'], vars)
write(otu_in_group, for_plot)
r_job = rp.Rparser()
r_job.open(this_script_path + '/../src/template/03_otu_venn.Rtp')
r_job.format(vars)
r_job.write(params['out_dir'] + '/otu_venn.R')
r_job.run()
image_trans(tiff_file, png_file)