def main(argv):
parser = argparse.ArgumentParser(
description=__DESCRIPTION__,
formatter_class=argparse.RawDescriptionHelpFormatter)
# name or flags - Either a name or a list of option strings, e.g. foo or -f, --foo.
# action - The basic type of action to be taken when this argument is encountered at the command line. (store, store_const, store_true, store_false, append, append_const, version)
# nargs - The number of command-line arguments that should be consumed. (N, ? (one or default), * (all 1 or more), + (more than 1) )
# const - A constant value required by some action and nargs selections.
# default - The value produced if the argument is absent from the command line.
# type - The type to which the command-line argument should be converted.
# choices - A container of the allowable values for the argument.
# required - Whether or not the command-line option may be omitted (optionals only).
# help - A brief description of what the argument does.
# metavar - A name for the argument in usage messages.
# dest - The name of the attribute to be added to the object returned by parse_args().
parser.add_argument("--show",
dest="show_tree",
action="store_true",
help="""Display tree after the analysis.""")
parser.add_argument("--render",
dest="render",
action="store_true",
help="""Render tree.""")
parser.add_argument("--dump",
dest="dump",
action="store_true",
help="""Dump analysis""")
parser.add_argument(
"--explore",
dest="explore",
type=str,
help="""Reads a previously analyzed tree and visualize it""")
input_args = parser.add_mutually_exclusive_group()
input_args.required = True
input_args.add_argument("-t",
"--tree",
dest="target_tree",
nargs="+",
type=str,
help="""Tree file in newick format""")
input_args.add_argument("-tf",
dest="tree_list_file",
type=str,
help="File with the list of tree files")
parser.add_argument("--tax",
dest="tax_info",
type=str,
help="If the taxid attribute is not set in the"
" newick file for all leaf nodes, a tab file file"
" with the translation of name and taxid can be"
" provided with this option.")
parser.add_argument(
"--sp_delimiter",
dest="sp_delimiter",
type=str,
help=
"If taxid is part of the leaf name, delimiter used to split the string"
)
parser.add_argument(
"--sp_field",
dest="sp_field",
type=int,
default=0,
help="field position for taxid after splitting leaf names")
parser.add_argument("--ref",
dest="ref_tree",
type=str,
help="Uses ref tree to compute robinson foulds"
" distances of the different subtrees")
parser.add_argument("--rf-only",
dest="rf_only",
action="store_true",
help="Skip ncbi consensus analysis")
parser.add_argument(
"--outgroup",
dest="outgroup",
type=str,
nargs="+",
help="A list of node names defining the trees outgroup")
parser.add_argument("--is_sptree",
dest="is_sptree",
action="store_true",
help="Assumes no duplication nodes in the tree")
parser.add_argument("-o",
dest="output",
type=str,
help="Writes result into a file")
parser.add_argument("--tax2name", dest="tax2name", type=str, help="")
parser.add_argument("--tax2track", dest="tax2track", type=str, help="")
parser.add_argument("--dump_tax_info",
dest="dump_tax_info",
action="store_true",
help="")
args = parser.parse_args(argv)
if args.sp_delimiter:
GET_TAXID = lambda x: x.split(args.sp_delimiter)[args.sp_field]
else:
GET_TAXID = None
reftree_name = os.path.basename(args.ref_tree) if args.ref_tree else ""
if args.explore:
print >> sys.stderr, "Reading tree from file:", args.explore
t = cPickle.load(open(args.explore))
ts = TreeStyle()
ts.force_topology = True
ts.show_leaf_name = False
ts.layout_fn = ncbi_layout
ts.mode = "r"
t.show(tree_style=ts)
print >> sys.stderr, "dumping color config"
cPickle.dump(name2color, open("ncbi_colors.pkl", "w"))
sys.exit()
if args.output:
OUT = open(args.output, "w")
else:
OUT = sys.stdout
print >> sys.stderr, "Dumping results into", OUT
target_trees = []
if args.tree_list_file:
target_trees = [line.strip() for line in open(args.tree_list_file)]
if args.target_tree:
target_trees += args.target_tree
prev_tree = None
if args.tax2name:
tax2name = cPickle.load(open(args.tax2name))
else:
tax2name = {}
if args.tax2track:
tax2track = cPickle.load(open(args.tax2track))
else:
tax2track = {}
print len(tax2track), len(tax2name)
header = ("TargetTree", "Subtrees", "Ndups", "Broken subtrees",
"Broken clades", "Clade sizes", "RF (avg)", "RF (med)",
"RF (std)", "RF (max)", "Shared tips")
print >> OUT, '|'.join([h.ljust(15) for h in header])
if args.ref_tree:
print >> sys.stderr, "Reading ref tree from", args.ref_tree
reft = Tree(args.ref_tree, format=1)
else:
reft = None
SHOW_TREE = False
if args.show_tree or args.render:
SHOW_TREE = True
prev_broken = set()
ENTRIES = []
ncbi.connect_database()
for tfile in target_trees:
#print tfile
t = PhyloTree(tfile, sp_naming_function=None)
if GET_TAXID:
for n in t.iter_leaves():
n.name = GET_TAXID(n.name)
if args.outgroup:
if len(args.outgroup) == 1:
out = t & args.outgroup[0]
else:
out = t.get_common_ancestor(args.outgroup)
if set(out.get_leaf_names()) ^ set(args.outgroup):
raise ValueError("Outgroup is not monophyletic")
t.set_outgroup(out)
t.ladderize()
if prev_tree:
tree_compare(t, prev_tree)
prev_tree = t
if args.tax_info:
tax2name, tax2track = annotate_tree_with_taxa(
t, args.tax_info, tax2name, tax2track)
if args.dump_tax_info:
cPickle.dump(tax2track, open("tax2track.pkl", "w"))
cPickle.dump(tax2name, open("tax2name.pkl", "w"))
print "Tax info written into pickle files"
else:
for n in t.iter_leaves():
spcode = n.name
n.add_features(taxid=spcode)
n.add_features(species=spcode)
tax2name, tax2track = annotate_tree_with_taxa(
t, None, tax2name, tax2track)
# Split tree into species trees
#subtrees = t.get_speciation_trees()
if not args.rf_only:
#print "Calculating tree subparts..."
t1 = time.time()
if not args.is_sptree:
subtrees = t.split_by_dups()
#print "Subparts:", len(subtrees), time.time()-t1
else:
subtrees = [t]
valid_subtrees, broken_subtrees, ncbi_mistakes, broken_branches, total_rf, broken_clades, broken_sizes = analyze_subtrees(
t, subtrees, show_tree=SHOW_TREE)
#print valid_subtrees, broken_subtrees, ncbi_mistakes, total_rf
else:
subtrees = []
valid_subtrees, broken_subtrees, ncbi_mistakes, broken_branches, total_rf, broken_clades, broken_sizes = 0, 0, 0, 0, 0, 0
ndups = 0
nsubtrees = len(subtrees)
rf = 0
rf_max = 0
rf_std = 0
rf_med = 0
common_names = 0
max_size = 0
if reft and len(subtrees) == 1:
rf = t.robinson_foulds(reft, attr_t1="realname")
rf_max = rf[1]
rf = rf[0]
rf_med = rf
elif reft:
#print "Calculating avg RF..."
nsubtrees, ndups, subtrees = t.get_speciation_trees(
map_features=["taxid"])
#print len(subtrees), "Sub-Species-trees found"
avg_rf = []
rf_max = 0.0 # reft.robinson_foulds(reft)[1]
sum_size = 0.0
print nsubtrees, "subtrees", ndups, "duplications"
for ii, subt in enumerate(subtrees):
print "\r%d" % ii,
sys.stdout.flush()
try:
partial_rf = subt.robinson_foulds(reft, attr_t1="taxid")
except ValueError:
pass
else:
sptree_size = len(
set([n.taxid for n in subt.iter_leaves()]))
sum_size += sptree_size
avg_rf.append(
(partial_rf[0] / float(partial_rf[1])) * sptree_size)
common_names = len(partial_rf[3])
max_size = max(max_size, sptree_size)
rf_max = max(rf_max, partial_rf[1])
#print partial_rf[:2]
rf = numpy.sum(avg_rf) / float(sum_size) # Treeko dist
rf_std = numpy.std(avg_rf)
rf_med = numpy.median(avg_rf)
sizes_info = "%0.1f/%0.1f +- %0.1f" % (numpy.mean(broken_sizes),
numpy.median(broken_sizes),
numpy.std(broken_sizes))
iter_values = [
os.path.basename(tfile), nsubtrees, ndups, broken_subtrees,
ncbi_mistakes, broken_branches, sizes_info, rf, rf_med, rf_std,
rf_max, common_names
]
print >> OUT, '|'.join(
map(lambda x: str(x).strip().ljust(15), iter_values))
fixed = sorted([n for n in prev_broken if n not in broken_clades])
new_problems = sorted(broken_clades - prev_broken)
fixed_string = color(', '.join(fixed), "green") if fixed else ""
problems_string = color(', '.join(new_problems),
"red") if new_problems else ""
OUT.write(" Fixed clades: %s\n" % fixed_string) if fixed else None
OUT.write(" New broken: %s\n" %
problems_string) if new_problems else None
prev_broken = broken_clades
ENTRIES.append([
os.path.basename(tfile), nsubtrees, ndups, broken_subtrees,
ncbi_mistakes, broken_branches, sizes_info, fixed_string,
problems_string
])
OUT.flush()
if args.show_tree or args.render:
ts = TreeStyle()
ts.force_topology = True
#ts.tree_width = 500
ts.show_leaf_name = False
ts.layout_fn = ncbi_layout
ts.mode = "r"
t.dist = 0
if args.show_tree:
#if args.hide_monophyletic:
# tax2monophyletic = {}
# n2content = t.get_node2content()
# for node in t.traverse():
# term2count = defaultdict(int)
# for leaf in n2content[node]:
# if leaf.lineage:
# for term in leaf.lineage:
# term2count[term] += 1
# expected_size = len(n2content)
# for term, count in term2count.iteritems():
# if count > 1
print "Showing tree..."
t.show(tree_style=ts)
else:
t.render("img.svg", tree_style=ts, dpi=300)
print "dumping color config"
cPickle.dump(name2color, open("ncbi_colors.pkl", "w"))
if args.dump:
cPickle.dump(t, open("ncbi_analysis.pkl", "w"))
print
print
HEADER = ("TargetTree", "Subtrees", "Ndups", "Broken subtrees",
"Broken clades", "Broken branches", "Clade sizes",
"Fixed Groups", "New Broken Clades")
print_table(ENTRIES, max_col_width=50, row_line=True, header=HEADER)
if args.output:
OUT.close()
def main(argv):
parser = ArgumentParser(description=__DESCRIPTION__)
parser.add_argument("--db", dest="dbfile",
type=str,
help="""NCBI sqlite3 db file.""")
parser.add_argument("-t", "--taxid", dest="taxid", nargs="+",
type=int,
help="""taxids (space separated)""")
parser.add_argument("-tf", "--taxid_file", dest="taxid_file",
type=str,
help="""file containing a list of taxids (one per line)""")
parser.add_argument("-r", "--reftree", dest="reftree",
type=str,
help="""tree file containing taxids as node names.""")
parser.add_argument("--reftree_attr", dest="reftree_attr",
type=str, default="name",
help="""Where taxid should be read from""")
parser.add_argument("-n", "--name", dest="names", nargs="+",
type=str,
help="""species or taxa names (comma separated)""")
parser.add_argument("-nf", "--names_file", dest="names_file",
type=str,
help="""file containing a list of taxids (one per line)""")
parser.add_argument("-x", "--taxonomy", dest="taxonomy",
action="store_true",
help=("returns a pruned version of the NCBI taxonomy"
" tree containing target species"))
parser.add_argument("--show_tree", dest="show_tree",
action="store_true",
help="""shows the NCBI taxonomy tree of the provided species""")
parser.add_argument("--collapse_subspecies", dest="collapse_subspecies",
action="store_true",
help=("When used, all nodes under the the species rank"
" are collapsed, so all species and subspecies"
" are seen as sister nodes"))
parser.add_argument("--rank_limit", dest="rank_limit",
type=str,
help=("When used, all nodes under the provided rank"
" are discarded"))
parser.add_argument("--full_lineage", dest="full_lineage",
action="store_true",
help=("When used, topology is not pruned to avoid "
" one-child-nodes, so the complete lineage"
" track leading from root to tips is kept."))
parser.add_argument("-i", "--info", dest="info",
action="store_true",
help="""shows NCBI information about the species""")
parser.add_argument("--fuzzy", dest="fuzzy", type=float,
help=("Tries a fuzzy (and SLOW) search for those"
" species names that could not be translated"
" into taxids. A float number must be provided"
" indicating the minimum string similarity."))
args = parser.parse_args(argv)
if not args.taxonomy and not args.info and not args.reftree:
parser.print_usage()
sys.exit(0)
if args.fuzzy:
import pysqlite2.dbapi2 as sqlite3
c = sqlite3.connect(os.path.join(MODULE_PATH, args.dbfile))
else:
ncbi.connect_database(args.dbfile)
all_names = set([])
all_taxids = []
if args.names_file:
all_names.update(map(strip, open(args.names_file, "rU").read().split("\n")))
if args.names:
all_names.update(map(strip, " ".join(args.names).split(",")))
all_names.discard("")
#all_names = set([n.lower() for n in all_names])
not_found = set()
name2realname = {}
name2score = {}
if all_names:
log.info("Dumping name translations:")
name2id = ncbi.get_name_translator(all_names)
not_found = all_names - set(name2id.keys())
if args.fuzzy and not_found:
log.info("%s unknown names", len(not_found))
for name in not_found:
# enable extension loading
c.enable_load_extension(True)
c.execute("select load_extension('%s')" % os.path.join(module_path,
"SQLite-Levenshtein/levenshtein.sqlext"))
tax, realname, sim = ncbi.get_fuzzy_name_translation(name, args.fuzzy)
if tax:
name2id[name] = tax
name2realname[name] = realname
name2score[name] = "Fuzzy:%0.2f" %sim
for name in all_names:
taxid = name2id.get(name, "???")
realname = name2realname.get(name, name)
score = name2score.get(name, "Exact:1.0")
print "\t".join(map(str, [score, name, realname.capitalize(), taxid]))
if args.taxid_file:
all_taxids.extend(map(strip, open(args.taxid_file, "rU").read().split("\n")))
if args.taxid:
all_taxids.extend(args.taxid)
reftree = None
if args.reftree:
reftree = PhyloTree(args.reftree)
all_taxids.extend(list(set([getattr(n, args.reftree_attr) for n in reftree.iter_leaves()])))
if all_taxids and args.info:
all_taxids = set(all_taxids)
all_taxids.discard("")
all_taxids, merge_conversion = ncbi.translate_merged(all_taxids)
log.info("Dumping %d taxid translations:" %len(all_taxids))
all_taxids.discard("")
translator = ncbi.get_taxid_translator(all_taxids)
for taxid, name in translator.iteritems():
lineage = ncbi.get_sp_lineage(taxid)
named_lineage = ','.join(ncbi.translate_to_names(lineage))
lineage = ','.join(map(str, lineage))
print "\t".join(map(str, [merge_conversion.get(int(taxid), taxid), name, named_lineage, lineage ]))
for notfound in set(map(str, all_taxids)) - set(str(k) for k in translator.iterkeys()):
print >>sys.stderr, notfound, "NOT FOUND"
if all_taxids and args.taxonomy:
all_taxids = set(all_taxids)
all_taxids.discard("")
log.info("Dumping NCBI taxonomy of %d taxa:" %len(all_taxids))
t = ncbi.get_topology(all_taxids, args.full_lineage, args.rank_limit)
id2name = ncbi.get_taxid_translator([n.name for n in t.traverse()])
for n in t.traverse():
n.add_features(taxid=n.name)
n.add_features(sci_name=str(id2name.get(int(n.name), "?")))
if n.rank in COLOR_RANKS:
n.add_features(bgcolor=COLOR_RANKS[n.rank])
n.name = "%s{%s}" %(id2name.get(int(n.name), n.name), n.name)
lineage = ncbi.get_sp_lineage(n.taxid)
n.add_features(named_lineage = '|'.join(ncbi.translate_to_names(lineage)))
if args.collapse_subspecies:
species_nodes = [n for n in t.traverse() if n.rank == "species"
if int(n.taxid) in all_taxids]
for sp_node in species_nodes:
bellow = sp_node.get_descendants()
if bellow:
# creates a copy of the species node
connector = sp_node.__class__()
for f in sp_node.features:
connector.add_feature(f, getattr(sp_node, f))
connector.name = connector.name + "{species}"
for n in bellow:
n.detach()
n.name = n.name + "{%s}" %n.rank
sp_node.add_child(n)
sp_node.add_child(connector)
sp_node.add_feature("collapse_subspecies", "1")
if args.show_tree:
t.show()
print "\n\n ===== Newick files saved as 'your_taxa_query.*' ===== "
t.write(format=9, outfile="your_ncbi_query.nw")
t.write(format=8, outfile="your_ncbi_query.named.nw")
t.write(format=9, features=["taxid", "name", "rank", "bgcolor", "sci_name", "collapse_subspecies", "named_lineage"],
outfile="your_ncbi_query.extended.nw")
for i in t.iter_leaves():
i.name = i.taxid
t.write(format=9, outfile="your_ncbi_query.taxids.nw")
if all_taxids and reftree:
translator = ncbi.get_taxid_translator(all_taxids)
for n in reftree.iter_leaves():
if not hasattr(n, "taxid"):
n.add_features(taxid=int(getattr(n, args.reftree_attr)))
n.add_features(sci_name = translator.get(int(n.taxid), n.name))
lineage = ncbi.get_sp_lineage(n.taxid)
named_lineage = '|'.join(ncbi.translate_to_names(lineage))
n.add_features(ncbi_track=named_lineage)
print reftree.write(features=["taxid", "sci_name", "ncbi_track"])
def main(argv):
global args
#test()
parser = argparse.ArgumentParser(
description=__DESCRIPTION__,
formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument("target_trees",
type=str,
nargs="+",
help='a list of target tree files')
parser.add_argument("-r",
dest='reftree',
type=str,
help='The reference tree to compare with')
parser.add_argument(
"--ref_attr",
dest="ref_attr",
default="name",
help=("Defines the attribute in REFERENCE tree that will be used"
" to perform the comparison"))
parser.add_argument(
"--target_attr",
dest="target_attr",
default="name",
help=("Defines the attribute in TARGET tree that will be used"
" to perform the comparison"))
parser.add_argument(
"--fullsearch",
dest="fullsearch",
action="store_false",
help=("Enable this option if duplicated attributes (i.e. name)"
"exist in reference or target trees."))
parser.add_argument("--quite",
dest="quite",
action="store_true",
help="Do not show process information")
parser.add_argument("--report",
dest="report",
choices=["topology", "diffs", "diffs_tab", "summary"],
default="topology",
help="Different format for the comparison results")
parser.add_argument(
"--ncbi",
dest="ncbi",
action="store_true",
help=
"If enabled, it will use the ETE ncbi_taxonomy module to for ncbi taxid translation"
)
parser.add_argument(
"--color",
dest="color",
action="store_true",
help="If enabled, it will use colors in some of the report")
args = parser.parse_args(argv)
if args.quite:
logging.basicConfig(format='%(message)s', level=logging.WARNING)
else:
logging.basicConfig(format='%(message)s', level=logging.INFO)
log = logging
t1 = Tree(args.reftree)
if args.ncbi:
from common import ncbi
ncbi.connect_database()
for ttree in args.target_trees:
t2 = Tree(ttree)
if args.ncbi:
taxids = set(
[getattr(leaf, args.ref_attr) for leaf in t1.iter_leaves()])
taxids.update(
[getattr(leaf, args.target_attr) for leaf in t2.iter_leaves()])
taxid2name = ncbi.get_taxid_translator(taxids)
for leaf in t1.get_leaves() + t2.get_leaves():
try:
leaf.name = taxid2name.get(int(leaf.name), leaf.name)
except ValueError:
pass
difftable = treediff(t1,
t2,
args.ref_attr,
args.target_attr,
reduce_matrix=args.fullsearch)
if args.report == "topology":
show_difftable_topo(difftable,
args.ref_attr,
args.target_attr,
usecolor=args.color)
elif args.report == "diffs":
show_difftable(difftable)
elif args.report == "diffs_tab":
show_difftable_tab(difftable)
elif args.report == 'table':
rf, rf_max, _, _, _, _, _ = t1.robinson_foulds(
t2, attr_t1=args.ref_attr, attr_t2=args.target_attr)[:2]
show_difftable_summary(difftable, rf, rf_max)
def main(argv):
global args
# test()
parser = argparse.ArgumentParser(description=__DESCRIPTION__, formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument("target_trees", type=str, nargs="+", help="a list of target tree files")
parser.add_argument("-r", dest="reftree", type=str, help="The reference tree to compare with")
parser.add_argument(
"--ref_attr",
dest="ref_attr",
default="name",
help=("Defines the attribute in REFERENCE tree that will be used" " to perform the comparison"),
)
parser.add_argument(
"--target_attr",
dest="target_attr",
default="name",
help=("Defines the attribute in TARGET tree that will be used" " to perform the comparison"),
)
parser.add_argument(
"--fullsearch",
dest="fullsearch",
action="store_false",
help=("Enable this option if duplicated attributes (i.e. name)" "exist in reference or target trees."),
)
parser.add_argument("--quite", dest="quite", action="store_true", help="Do not show process information")
parser.add_argument(
"--report",
dest="report",
choices=["topology", "diffs", "diffs_tab", "summary"],
default="topology",
help="Different format for the comparison results",
)
parser.add_argument(
"--ncbi",
dest="ncbi",
action="store_true",
help="If enabled, it will use the ETE ncbi_taxonomy module to for ncbi taxid translation",
)
parser.add_argument(
"--color", dest="color", action="store_true", help="If enabled, it will use colors in some of the report"
)
args = parser.parse_args(argv)
if args.quite:
logging.basicConfig(format="%(message)s", level=logging.WARNING)
else:
logging.basicConfig(format="%(message)s", level=logging.INFO)
log = logging
t1 = Tree(args.reftree)
if args.ncbi:
from common import ncbi
ncbi.connect_database()
for ttree in args.target_trees:
t2 = Tree(ttree)
if args.ncbi:
taxids = set([getattr(leaf, args.ref_attr) for leaf in t1.iter_leaves()])
taxids.update([getattr(leaf, args.target_attr) for leaf in t2.iter_leaves()])
taxid2name = ncbi.get_taxid_translator(taxids)
for leaf in t1.get_leaves() + t2.get_leaves():
try:
leaf.name = taxid2name.get(int(leaf.name), leaf.name)
except ValueError:
pass
difftable = treediff(t1, t2, args.ref_attr, args.target_attr, reduce_matrix=args.fullsearch)
if args.report == "topology":
show_difftable_topo(difftable, args.ref_attr, args.target_attr, usecolor=args.color)
elif args.report == "diffs":
show_difftable(difftable)
elif args.report == "diffs_tab":
show_difftable_tab(difftable)
elif args.report == "table":
rf, rf_max, _, _, _, _, _ = t1.robinson_foulds(t2, attr_t1=args.ref_attr, attr_t2=args.target_attr)[:2]
show_difftable_summary(difftable, rf, rf_max)
def main(argv):
parser = ArgumentParser(description=__DESCRIPTION__)
parser.add_argument("--db",
dest="dbfile",
type=str,
help="""NCBI sqlite3 db file.""")
parser.add_argument("-t",
"--taxid",
dest="taxid",
nargs="+",
type=int,
help="""taxids (space separated)""")
parser.add_argument(
"-tf",
"--taxid_file",
dest="taxid_file",
type=str,
help="""file containing a list of taxids (one per line)""")
parser.add_argument("-r",
"--reftree",
dest="reftree",
type=str,
help="""tree file containing taxids as node names.""")
parser.add_argument("--reftree_attr",
dest="reftree_attr",
type=str,
default="name",
help="""Where taxid should be read from""")
parser.add_argument("-n",
"--name",
dest="names",
nargs="+",
type=str,
help="""species or taxa names (comma separated)""")
parser.add_argument(
"-nf",
"--names_file",
dest="names_file",
type=str,
help="""file containing a list of taxids (one per line)""")
parser.add_argument("-x",
"--taxonomy",
dest="taxonomy",
action="store_true",
help=("returns a pruned version of the NCBI taxonomy"
" tree containing target species"))
parser.add_argument(
"--show_tree",
dest="show_tree",
action="store_true",
help="""shows the NCBI taxonomy tree of the provided species""")
parser.add_argument("--collapse_subspecies",
dest="collapse_subspecies",
action="store_true",
help=("When used, all nodes under the the species rank"
" are collapsed, so all species and subspecies"
" are seen as sister nodes"))
parser.add_argument("--rank_limit",
dest="rank_limit",
type=str,
help=("When used, all nodes under the provided rank"
" are discarded"))
parser.add_argument("--full_lineage",
dest="full_lineage",
action="store_true",
help=("When used, topology is not pruned to avoid "
" one-child-nodes, so the complete lineage"
" track leading from root to tips is kept."))
parser.add_argument("-i",
"--info",
dest="info",
action="store_true",
help="""shows NCBI information about the species""")
parser.add_argument("--fuzzy",
dest="fuzzy",
type=float,
help=("Tries a fuzzy (and SLOW) search for those"
" species names that could not be translated"
" into taxids. A float number must be provided"
" indicating the minimum string similarity."))
args = parser.parse_args(argv)
if not args.taxonomy and not args.info and not args.reftree:
parser.print_usage()
sys.exit(0)
if args.fuzzy:
import pysqlite2.dbapi2 as sqlite3
c = sqlite3.connect(os.path.join(MODULE_PATH, args.dbfile))
else:
ncbi.connect_database(args.dbfile)
all_names = set([])
all_taxids = []
if args.names_file:
all_names.update(
map(strip,
open(args.names_file, "rU").read().split("\n")))
if args.names:
all_names.update(map(strip, " ".join(args.names).split(",")))
all_names.discard("")
#all_names = set([n.lower() for n in all_names])
not_found = set()
name2realname = {}
name2score = {}
if all_names:
log.info("Dumping name translations:")
name2id = ncbi.get_name_translator(all_names)
not_found = all_names - set(name2id.keys())
if args.fuzzy and not_found:
log.info("%s unknown names", len(not_found))
for name in not_found:
# enable extension loading
c.enable_load_extension(True)
c.execute("select load_extension('%s')" % os.path.join(
module_path, "SQLite-Levenshtein/levenshtein.sqlext"))
tax, realname, sim = ncbi.get_fuzzy_name_translation(
name, args.fuzzy)
if tax:
name2id[name] = tax
name2realname[name] = realname
name2score[name] = "Fuzzy:%0.2f" % sim
for name in all_names:
taxid = name2id.get(name, "???")
realname = name2realname.get(name, name)
score = name2score.get(name, "Exact:1.0")
print "\t".join(
map(str,
[score, name, realname.capitalize(), taxid]))
if args.taxid_file:
all_taxids.extend(
map(strip,
open(args.taxid_file, "rU").read().split("\n")))
if args.taxid:
all_taxids.extend(args.taxid)
reftree = None
if args.reftree:
reftree = PhyloTree(args.reftree)
all_taxids.extend(
list(
set([
getattr(n, args.reftree_attr)
for n in reftree.iter_leaves()
])))
if all_taxids and args.info:
all_taxids = set(all_taxids)
all_taxids.discard("")
all_taxids, merge_conversion = ncbi.translate_merged(all_taxids)
log.info("Dumping %d taxid translations:" % len(all_taxids))
all_taxids.discard("")
translator = ncbi.get_taxid_translator(all_taxids)
for taxid, name in translator.iteritems():
lineage = ncbi.get_sp_lineage(taxid)
named_lineage = ','.join(ncbi.translate_to_names(lineage))
lineage = ','.join(map(str, lineage))
print "\t".join(
map(str, [
merge_conversion.get(int(taxid), taxid), name,
named_lineage, lineage
]))
for notfound in set(map(str, all_taxids)) - set(
str(k) for k in translator.iterkeys()):
print >> sys.stderr, notfound, "NOT FOUND"
if all_taxids and args.taxonomy:
all_taxids = set(all_taxids)
all_taxids.discard("")
log.info("Dumping NCBI taxonomy of %d taxa:" % len(all_taxids))
t = ncbi.get_topology(all_taxids, args.full_lineage, args.rank_limit)
id2name = ncbi.get_taxid_translator([n.name for n in t.traverse()])
for n in t.traverse():
n.add_features(taxid=n.name)
n.add_features(sci_name=str(id2name.get(int(n.name), "?")))
if n.rank in COLOR_RANKS:
n.add_features(bgcolor=COLOR_RANKS[n.rank])
n.name = "%s{%s}" % (id2name.get(int(n.name), n.name), n.name)
lineage = ncbi.get_sp_lineage(n.taxid)
n.add_features(
named_lineage='|'.join(ncbi.translate_to_names(lineage)))
if args.collapse_subspecies:
species_nodes = [
n for n in t.traverse() if n.rank == "species"
if int(n.taxid) in all_taxids
]
for sp_node in species_nodes:
bellow = sp_node.get_descendants()
if bellow:
# creates a copy of the species node
connector = sp_node.__class__()
for f in sp_node.features:
connector.add_feature(f, getattr(sp_node, f))
connector.name = connector.name + "{species}"
for n in bellow:
n.detach()
n.name = n.name + "{%s}" % n.rank
sp_node.add_child(n)
sp_node.add_child(connector)
sp_node.add_feature("collapse_subspecies", "1")
if args.show_tree:
t.show()
print "\n\n ===== Newick files saved as 'your_taxa_query.*' ===== "
t.write(format=9, outfile="your_ncbi_query.nw")
t.write(format=8, outfile="your_ncbi_query.named.nw")
t.write(format=9,
features=[
"taxid", "name", "rank", "bgcolor", "sci_name",
"collapse_subspecies", "named_lineage"
],
outfile="your_ncbi_query.extended.nw")
for i in t.iter_leaves():
i.name = i.taxid
t.write(format=9, outfile="your_ncbi_query.taxids.nw")
if all_taxids and reftree:
translator = ncbi.get_taxid_translator(all_taxids)
for n in reftree.iter_leaves():
if not hasattr(n, "taxid"):
n.add_features(taxid=int(getattr(n, args.reftree_attr)))
n.add_features(sci_name=translator.get(int(n.taxid), n.name))
lineage = ncbi.get_sp_lineage(n.taxid)
named_lineage = '|'.join(ncbi.translate_to_names(lineage))
n.add_features(ncbi_track=named_lineage)
print reftree.write(features=["taxid", "sci_name", "ncbi_track"])
def main(argv):
parser = argparse.ArgumentParser(description=__DESCRIPTION__,
formatter_class=argparse.RawDescriptionHelpFormatter)
# name or flags - Either a name or a list of option strings, e.g. foo or -f, --foo.
# action - The basic type of action to be taken when this argument is encountered at the command line. (store, store_const, store_true, store_false, append, append_const, version)
# nargs - The number of command-line arguments that should be consumed. (N, ? (one or default), * (all 1 or more), + (more than 1) )
# const - A constant value required by some action and nargs selections.
# default - The value produced if the argument is absent from the command line.
# type - The type to which the command-line argument should be converted.
# choices - A container of the allowable values for the argument.
# required - Whether or not the command-line option may be omitted (optionals only).
# help - A brief description of what the argument does.
# metavar - A name for the argument in usage messages.
# dest - The name of the attribute to be added to the object returned by parse_args().
parser.add_argument("--show", dest="show_tree",
action="store_true",
help="""Display tree after the analysis.""")
parser.add_argument("--render", dest="render",
action="store_true",
help="""Render tree.""")
parser.add_argument("--dump", dest="dump",
action="store_true",
help="""Dump analysis""")
parser.add_argument("--explore", dest="explore",
type=str,
help="""Reads a previously analyzed tree and visualize it""")
input_args = parser.add_mutually_exclusive_group()
input_args.required=True
input_args.add_argument("-t", "--tree", dest="target_tree", nargs="+",
type=str,
help="""Tree file in newick format""")
input_args.add_argument("-tf", dest="tree_list_file",
type=str,
help="File with the list of tree files")
parser.add_argument("--tax", dest="tax_info", type=str,
help="If the taxid attribute is not set in the"
" newick file for all leaf nodes, a tab file file"
" with the translation of name and taxid can be"
" provided with this option.")
parser.add_argument("--sp_delimiter", dest="sp_delimiter", type=str,
help="If taxid is part of the leaf name, delimiter used to split the string")
parser.add_argument("--sp_field", dest="sp_field", type=int, default=0,
help="field position for taxid after splitting leaf names")
parser.add_argument("--ref", dest="ref_tree", type=str,
help="Uses ref tree to compute robinson foulds"
" distances of the different subtrees")
parser.add_argument("--rf-only", dest="rf_only",
action = "store_true",
help="Skip ncbi consensus analysis")
parser.add_argument("--outgroup", dest="outgroup",
type=str, nargs="+",
help="A list of node names defining the trees outgroup")
parser.add_argument("--is_sptree", dest="is_sptree",
action = "store_true",
help="Assumes no duplication nodes in the tree")
parser.add_argument("-o", dest="output", type=str,
help="Writes result into a file")
parser.add_argument("--tax2name", dest="tax2name", type=str,
help="")
parser.add_argument("--tax2track", dest="tax2track", type=str,
help="")
parser.add_argument("--dump_tax_info", dest="dump_tax_info", action="store_true",
help="")
args = parser.parse_args(argv)
if args.sp_delimiter:
GET_TAXID = lambda x: x.split(args.sp_delimiter)[args.sp_field]
else:
GET_TAXID = None
reftree_name = os.path.basename(args.ref_tree) if args.ref_tree else ""
if args.explore:
print >>sys.stderr, "Reading tree from file:", args.explore
t = cPickle.load(open(args.explore))
ts = TreeStyle()
ts.force_topology = True
ts.show_leaf_name = False
ts.layout_fn = ncbi_layout
ts.mode = "r"
t.show(tree_style=ts)
print >>sys.stderr, "dumping color config"
cPickle.dump(name2color, open("ncbi_colors.pkl", "w"))
sys.exit()
if args.output:
OUT = open(args.output, "w")
else:
OUT = sys.stdout
print >>sys.stderr, "Dumping results into", OUT
target_trees = []
if args.tree_list_file:
target_trees = [line.strip() for line in open(args.tree_list_file)]
if args.target_tree:
target_trees += args.target_tree
prev_tree = None
if args.tax2name:
tax2name = cPickle.load(open(args.tax2name))
else:
tax2name = {}
if args.tax2track:
tax2track = cPickle.load(open(args.tax2track))
else:
tax2track = {}
print len(tax2track), len(tax2name)
header = ("TargetTree", "Subtrees", "Ndups", "Broken subtrees", "Broken clades", "Clade sizes", "RF (avg)", "RF (med)", "RF (std)", "RF (max)", "Shared tips")
print >>OUT, '|'.join([h.ljust(15) for h in header])
if args.ref_tree:
print >>sys.stderr, "Reading ref tree from", args.ref_tree
reft = Tree(args.ref_tree, format=1)
else:
reft = None
SHOW_TREE = False
if args.show_tree or args.render:
SHOW_TREE = True
prev_broken = set()
ENTRIES = []
ncbi.connect_database()
for tfile in target_trees:
#print tfile
t = PhyloTree(tfile, sp_naming_function=None)
if GET_TAXID:
for n in t.iter_leaves():
n.name = GET_TAXID(n.name)
if args.outgroup:
if len(args.outgroup) == 1:
out = t & args.outgroup[0]
else:
out = t.get_common_ancestor(args.outgroup)
if set(out.get_leaf_names()) ^ set(args.outgroup):
raise ValueError("Outgroup is not monophyletic")
t.set_outgroup(out)
t.ladderize()
if prev_tree:
tree_compare(t, prev_tree)
prev_tree = t
if args.tax_info:
tax2name, tax2track = annotate_tree_with_taxa(t, args.tax_info, tax2name, tax2track)
if args.dump_tax_info:
cPickle.dump(tax2track, open("tax2track.pkl", "w"))
cPickle.dump(tax2name, open("tax2name.pkl", "w"))
print "Tax info written into pickle files"
else:
for n in t.iter_leaves():
spcode = n.name
n.add_features(taxid=spcode)
n.add_features(species=spcode)
tax2name, tax2track = annotate_tree_with_taxa(t, None, tax2name, tax2track)
# Split tree into species trees
#subtrees = t.get_speciation_trees()
if not args.rf_only:
#print "Calculating tree subparts..."
t1 = time.time()
if not args.is_sptree:
subtrees = t.split_by_dups()
#print "Subparts:", len(subtrees), time.time()-t1
else:
subtrees = [t]
valid_subtrees, broken_subtrees, ncbi_mistakes, broken_branches, total_rf, broken_clades, broken_sizes = analyze_subtrees(t, subtrees, show_tree=SHOW_TREE)
#print valid_subtrees, broken_subtrees, ncbi_mistakes, total_rf
else:
subtrees = []
valid_subtrees, broken_subtrees, ncbi_mistakes, broken_branches, total_rf, broken_clades, broken_sizes = 0, 0, 0, 0, 0, 0
ndups = 0
nsubtrees = len(subtrees)
rf = 0
rf_max = 0
rf_std = 0
rf_med = 0
common_names = 0
max_size = 0
if reft and len(subtrees) == 1:
rf = t.robinson_foulds(reft, attr_t1="realname")
rf_max = rf[1]
rf = rf[0]
rf_med = rf
elif reft:
#print "Calculating avg RF..."
nsubtrees, ndups, subtrees = t.get_speciation_trees(map_features=["taxid"])
#print len(subtrees), "Sub-Species-trees found"
avg_rf = []
rf_max = 0.0 # reft.robinson_foulds(reft)[1]
sum_size = 0.0
print nsubtrees, "subtrees", ndups, "duplications"
for ii, subt in enumerate(subtrees):
print "\r%d" %ii,
sys.stdout.flush()
try:
partial_rf = subt.robinson_foulds(reft, attr_t1="taxid")
except ValueError:
pass
else:
sptree_size = len(set([n.taxid for n in subt.iter_leaves()]))
sum_size += sptree_size
avg_rf.append((partial_rf[0]/float(partial_rf[1])) * sptree_size)
common_names = len(partial_rf[3])
max_size = max(max_size, sptree_size)
rf_max = max(rf_max, partial_rf[1])
#print partial_rf[:2]
rf = numpy.sum(avg_rf) / float(sum_size) # Treeko dist
rf_std = numpy.std(avg_rf)
rf_med = numpy.median(avg_rf)
sizes_info = "%0.1f/%0.1f +- %0.1f" %( numpy.mean(broken_sizes), numpy.median(broken_sizes), numpy.std(broken_sizes))
iter_values = [os.path.basename(tfile), nsubtrees, ndups,
broken_subtrees, ncbi_mistakes, broken_branches, sizes_info, rf, rf_med,
rf_std, rf_max, common_names]
print >>OUT, '|'.join(map(lambda x: str(x).strip().ljust(15), iter_values))
fixed = sorted([n for n in prev_broken if n not in broken_clades])
new_problems = sorted(broken_clades - prev_broken)
fixed_string = color(', '.join(fixed), "green") if fixed else ""
problems_string = color(', '.join(new_problems), "red") if new_problems else ""
OUT.write(" Fixed clades: %s\n" %fixed_string) if fixed else None
OUT.write(" New broken: %s\n" %problems_string) if new_problems else None
prev_broken = broken_clades
ENTRIES.append([os.path.basename(tfile), nsubtrees, ndups,
broken_subtrees, ncbi_mistakes, broken_branches, sizes_info, fixed_string, problems_string])
OUT.flush()
if args.show_tree or args.render:
ts = TreeStyle()
ts.force_topology = True
#ts.tree_width = 500
ts.show_leaf_name = False
ts.layout_fn = ncbi_layout
ts.mode = "r"
t.dist = 0
if args.show_tree:
#if args.hide_monophyletic:
# tax2monophyletic = {}
# n2content = t.get_node2content()
# for node in t.traverse():
# term2count = defaultdict(int)
# for leaf in n2content[node]:
# if leaf.lineage:
# for term in leaf.lineage:
# term2count[term] += 1
# expected_size = len(n2content)
# for term, count in term2count.iteritems():
# if count > 1
print "Showing tree..."
t.show(tree_style=ts)
else:
t.render("img.svg", tree_style=ts, dpi=300)
print "dumping color config"
cPickle.dump(name2color, open("ncbi_colors.pkl", "w"))
if args.dump:
cPickle.dump(t, open("ncbi_analysis.pkl", "w"))
print
print
HEADER = ("TargetTree", "Subtrees", "Ndups", "Broken subtrees", "Broken clades", "Broken branches", "Clade sizes", "Fixed Groups", "New Broken Clades")
print_table(ENTRIES, max_col_width = 50, row_line=True, header=HEADER)
if args.output:
OUT.close()