}
}
if __name__=="__main__":
parser = collect_args()
params = parser.parse_args()
if params.clean:
config["clean"] = True
if params.json:
config["in"] = params.json
config["newick_tree_options"]["raxml"] = not params.no_raxml
runner = process(config)
runner.align()
runner.build_tree()
runner.timetree_setup_filter_run()
runner.run_geo_inference()
runner.save_as_nexus()
runner.auspice_export()
# plot an approximate skyline - needs testing
plot_skyline = False
if plot_skyline: # plot an approximate skyline
from matplotlib import pyplot as plt
T = runner.tree.tt
plt.figure()
skyline, confidence = T.merger_model.skyline_inferred(gen = 50, confidence=2.0)
plt.fill_between(skyline.x, confidence[0], confidence[1], color=(0.8, 0.8, 0.8))
else: # Look for serotype-specific JSONs in the ./prepared/ directory
if 'multiple' in args.serotypes: # "multiple" = run all 5 builds
args.serotypes = ['denv1', 'denv2', 'denv3', 'denv4', 'all']
else:
args.serotypes = args.serotypes
args.json = ['./prepared/dengue_%s.json'%s for s in args.serotypes] # Look for ./prepared/dengue_SEROTYPE.json if no file paths given
for j in args.json: # validate input JSONs exist
assert os.path.isfile(j)
### Run analyses ###
for prepared_json in args.json:
try:
print("Processing %s"%prepared_json)
runner = process(make_config(prepared_json, args)) # parse
runner.align() # run alignment with mafft
runner.build_tree() # build tree with fasttree -> raxml
runner.timetree_setup_filter_run() # infer ML ancestral states (geo traits, node dates, mutations)
runner.run_geo_inference() # run mugration model to infer transmissions
# estimate mutation frequencies here.
if runner.config["estimate_mutation_frequencies"]:
pivots = runner.get_pivots_via_spacing()
runner.estimate_mutation_frequencies(pivots=pivots, min_freq=0.02, inertia=np.exp(-1.0/12), stiffness=2)
# estimate tree frequencies here.
if runner.config["estimate_tree_frequencies"]: # methods @ [ref]
pivots = runner.get_pivots_via_spacing()
runner.estimate_tree_frequencies(pivots=pivots, stiffness=2) # stiffness ~= amount of smoothing
def parse(xml, debug=False):
handler = Handler(debug)
process(xml, handler)
return handler.props
# "auspice": { ## settings for auspice JSON export
# "extra_attr": ['serum', 'clade', 'dTiter', 'cTiter'], # keys from tree.tree.clade['attr'] to include in export
# "color_options": { # which traits to color the tree by in auspice; titer colorbys are added in dengue_titers
# "country":{"key":"country", "legendTitle":"Country", "menuItem":"country", "type":"discrete"},
# "region":{"key":"region", "legendTitle":"Region", "menuItem":"region", "type":"discrete"},
# "gt":{"key":"genotype", "legendTitle":"Genotype", "menuItem":"genotype", "type":"discrete"},
# },
# "controls": {'authors':['authors']},
# "defaults": {'geoResolution': 'region', 'colorBy': 'region', 'distanceMeasure': 'div', 'mapTriplicate': True}
# },
##### Parse input files/params and run #####
### Run analyses ###
print("Processing %s" % args.json)
runner = process(config) # parse
runner.align() # run alignment with mafft
runner.build_tree() # build tree with fasttree -> raxml
runner.timetree_setup_filter_run(
) # infer ML ancestral states (geo traits, node dates, mutations)
runner.run_geo_inference() # run mugration model to infer transmissions
# estimate tree frequencies here.
if runner.config["estimate_tree_frequencies"]:
pivots = runner.get_pivots_via_spacing()
runner.estimate_tree_frequencies(region='southeast_asia', stiffness=2)
# titers
if runner.config["fit_titer_model"] and runner.config[
"titers"]: # methods @ Neher et al., PNAS 2016
if args.titer_model == 'tree':
<image size="extralarge">http://userserve-ak.last.fm/serve/300x300/27272219.jpg</image>
</album>
<toptags>
<tag>
<name>electronic</name>
<url>http://www.last.fm/tag/electronic</url>
</tag>
<tag>
<name>new wave</name>
<url>http://www.last.fm/tag/new%20wave</url>
</tag>
<tag>
<name>synthpop</name>
<url>http://www.last.fm/tag/synthpop</url>
</tag>
<tag>
<name>80s</name>
<url>http://www.last.fm/tag/80s</url>
</tag>
<tag>
<name>depeche mode</name>
<url>http://www.last.fm/tag/depeche%20mode</url>
</tag>
</toptags>
</track></lfm>
"""
handler = Handler(debug=False)
process(r_test, handler)
print handler.props
