def main(argv):
parser = argparse.ArgumentParser(
description=__DESCRIPTION__,
formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument("--tf",
dest='target_trees_file',
type=str,
help='target_trees')
parser.add_argument("-t",
dest='target_trees',
type=str,
nargs="+",
help='target_trees')
parser.add_argument(
"--unique",
dest='unique',
type=str,
help=
'When used, all the provided trees are compared and unique topologies are dumped in the specified file.'
)
parser.add_argument("--stats",
dest='stats',
type=str,
help='Show general stats for the provided trees')
parser.add_argument(
"--distmatrix",
dest='distmatrix',
type=str,
help='Dump a distance matrix (robinson foulds) among all topologies')
args = parser.parse_args(argv)
print __DESCRIPTION__
unique_topo = {}
stats_table = []
for tfile in itertrees(args.target_trees, args.target_trees_file):
t = Tree(tfile)
if args.unique:
tid = t.get_topology_id()
if tid not in unique_topo:
unique_topo[tid] = t
if args.stats:
most_distance_node, tree_length = t.get_farthest_leaf()
supports = []
names = []
distances = []
leaves = 0
for n in t.traverse():
names.append(n.name)
if n.up:
supports.append(n.support)
distances.append(n.dist)
if n.is_leaf():
leaves += 1
min_support, max_support = min(supports), max(supports)
mean_support, std_support = mean_std_dev(supports)
min_dist, max_dist = min(distances), max(distances)
mean_dist, std_dist = mean_std_dev(distances)
stats_table.append([
str(t.children <= 2),
leaves,
tree_length,
most_distance_node.name,
min_support,
max_support,
mean_support,
std_support,
min_dist,
max_dist,
mean_dist,
std_dist,
])
if stats_table:
header = [
'rooted', '#tips', 'tree length', 'most distant tip',
'min support', 'max support', 'min support', 'std support',
'max dist', 'min dist', 'mean dist', 'std dist'
]
print_table(stats_table, header=header, max_col_width=12)
if unique_topo:
print '%d unique topologies found' % len(unique_topo)
topos = unique_topo.values()
open(args.unique + '.trees',
'w').write('\n'.join([topo.write(format=9)
for topo in topos]) + '\n')
import itertools
for a, b in itertools.product(topos, topos):
print a.diff(b, output='diffs_tab')
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().
input_gr = parser.add_argument_group(
"TREE INPUT OPTIONS\n=================")
input_gr.add_argument(
'tree',
metavar='tree_file',
type=str,
nargs=1,
help='A tree file (or text string) in newick format.')
input_gr.add_argument("--raxml",
dest="raxml",
action="store_true",
help="""Process newick as raxml bootstrap values""")
img_gr = parser.add_argument_group("TREE IMAGE OPTIONS\n=================")
img_gr.add_argument("-m",
"--mode",
dest="mode",
choices=["c", "r"],
default="r",
help="""(r)ectangular or (c)ircular visualization""")
img_gr.add_argument(
"-i",
"--image",
dest="image",
type=str,
help="Render tree image instead of showing it. A filename "
" should be provided. PDF, SVG and PNG file extensions are"
" supported (i.e. -i tree.svg)")
img_gr.add_argument(
"--Iw",
"--width",
dest="width",
type=int,
default=0,
help="width of the rendered image in pixels (see --size-units).")
img_gr.add_argument(
"--Ih",
"--height",
dest="height",
type=int,
default=0,
help="height of the rendered image in pixels (see --size-units).")
img_gr.add_argument("--Ir",
"--resolution",
dest="resolution",
type=int,
default=300,
help="Resolution if the tree image (DPI)")
img_gr.add_argument("--Iu",
"--size-units",
dest="size_units",
choices=["px", "mm", "in"],
default="px",
help="Units used to specify the size of the image."
" (px:pixels, mm:millimeters, in:inches). ")
img_gr.add_argument(
"-mbs",
"--min-branch-separation",
dest="branch_separation",
type=int,
default=3,
help="Min number of pixels to separate branches vertically.")
img_gr.add_argument("--ss",
"--show-support",
dest="show_support",
action="store_true",
help="""Shows branch bootstrap/support values""")
img_gr.add_argument("--sbl",
"--branch-length",
dest="show_branch_length",
action="store_true",
help="""Show branch lengths.""")
img_gr.add_argument(
"--ft",
"--force-topology",
dest="force_topology",
action="store_true",
help="""Force branch length to have a minimum length in the image""")
img_gr.add_argument("--hln",
"--hide-leaf-names",
dest="hide_leaf_names",
action="store_true",
help="""Hide leaf names.""")
img_gr.add_argument(
"--sin",
"--show-internal-names",
dest="show_internal_names",
action="store_true",
help="""Show the name attribute of all internal nodes.""")
edit_gr = parser.add_argument_group("TREE EDIT OPTIONS\n=================")
edit_gr.add_argument(
"-r",
"--root",
dest="root",
type=str,
nargs="*",
help="Roots the tree to the node grouping the list"
" of node names provided (space separated). In example:"
"'--root human rat mouse'")
edit_gr.add_argument("-s",
"--sort-branches",
dest="sort",
action="store_true",
help="""Sort branches according to node names.""")
edit_gr.add_argument("-l",
"--ladderize",
dest="ladderize",
action="store_true",
help="""Sort branches by partition size.""")
edit_gr.add_argument("--color_by_rank",
dest="color_by_rank",
type=str,
nargs="+",
help="""If the attribute rank is present in nodes """)
phylo_gr = parser.add_argument_group(
"PHYLOGENETIC OPTIONS\n=================")
phylo_gr.add_argument("--alg",
dest="alg",
type=str,
help="""Multiple sequence alignment.""")
phylo_gr.add_argument(
"--alg-format",
dest="alg_format",
type=str,
default="fasta",
help="""fasta, phylip, iphylip, relaxed_iphylip, relaxed_phylip.""")
phylo_gr.add_argument(
"--sp-discovery",
dest="species_discovery_regexp",
type=str,
default="^[^_]+_(.+)",
help="Perl regular expression to capture species"
" code from node names. By default, node names"
" are expected to follow the NAME_SPCODE format = '^[^_]+_(.+)' ")
phylo_gr.add_argument(
"--dump-subtrees",
dest="subtrees_output_file",
type=str,
help="Returns a file containing all possible species subtrees"
" contained in a given gene tree ")
phylo_gr.add_argument(
"--newick",
dest="newick",
type=str,
help="dumps newick file after applying editing options")
args = parser.parse_args(argv)
tfile = args.tree[0]
if args.ladderize and args.sort:
raise ValueError(
"--sort-branches and --ladderize options are mutually exclusive")
if args.raxml:
nw = re.sub(":(\d+\.\d+)\[(\d+)\]", ":\\1[&&NHX:support=\\2]",
open(tfile).read())
t = PhyloTree(nw)
#for n in t.traverse():
#n.support = getattr(n, "bootstrap", -1)
#
else:
t = PhyloTree(tfile)
if args.alg:
t.link_to_alignment(args.alg, alg_format=args.alg_format)
LEAF_ATTRIBUTES["sequence"] = 1
if args.species_discovery_regexp:
SPCODE_REGEXP = re.compile(args.species_discovery_regexp)
t.set_species_naming_function(user_species_naming_function)
if args.ladderize:
t.ladderize()
if args.sort:
t.sort_descendants()
if args.root:
if len(args.root) > 1:
outgroup = t.get_common_ancestor(args.root)
else:
outgroup = t & args.root[0]
t.set_outgroup(outgroup)
# EXTRACT INFO
if args.subtrees_output_file:
ntrees, ndups, treeiter = t.get_speciation_trees()
print >> sys.stderr, "Found %d duplication nodes. Dumping %d sutrees..." % (
ndups, ntrees)
OUT = open(args.subtrees_output_file, "w")
for tree in treeiter:
print >> OUT, tree.write()
OUT.close()
# VISUALIZATION
ts = TreeStyle()
ts.mode = args.mode
ts.show_leaf_name = False
ts.branch_vertical_margin = args.branch_separation
if args.show_support:
ts.show_branch_support = True
if args.show_branch_length:
ts.show_branch_length = True
if args.force_topology:
ts.force_topology = True
if args.hide_leaf_names:
del LEAF_ATTRIBUTES["name"]
if args.show_internal_names:
INTERNAL_ATTRIBUTES["name"] = 1
# scale the tree
if not args.height:
args.height = None
if not args.width:
args.width = None
ts.layout_fn = master_layout
if args.image:
t.render(args.image,
tree_style=ts,
w=args.width,
h=args.height,
units=args.size_units)
else:
t.show(None, tree_style=ts)
if args.newick:
t.write(features=[], outfile=args.newick)
print "Processed Newick dumped into", args.newick
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 = argparse.ArgumentParser(
description=__DESCRIPTION__,
formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument("target_trees",
metavar='target_trees',
type=str,
nargs="*",
help='a list of target tree files')
parser.add_argument(
"--targets_file",
dest="targets_file",
type=str,
help="""path to a file containing target trees, one per line""")
parser.add_argument("-o",
dest="output",
type=str,
help="""Path to the tab delimited report file""")
parser.add_argument("-r",
dest="reftree",
type=str,
required=True,
help="""Reference tree""")
parser.add_argument(
"--outgroup",
dest="outgroup",
nargs="+",
help=
"""outgroup used to root reference and target trees before distance computation"""
)
parser.add_argument("--expand_polytomies",
dest="polytomies",
action="store_true",
help="""expand politomies if necessary""")
parser.add_argument("--unrooted",
dest="unrooted",
action="store_true",
help="""compare trees as unrooted""")
parser.add_argument(
"--min_support",
dest="min_support",
type=float,
default=0.0,
help=
("min support value for branches to be counted in the distance computation (RF, treeko and refTree/targeGene compatibility)"
))
parser.add_argument(
"--extract_species",
dest="extract_species",
action="store_true",
help=
"""When used, reference tree is assumed to contain species names, while target trees as expected to be gene trees. Species name will be extracted from gene tree nodes and treeko will be used if duplication events are found."""
)
parser.add_argument("--spname_delimiter",
dest="spname_delimiter",
type=str,
default="_",
help=("species code delimiter in node names"))
parser.add_argument(
"--spname_field",
dest="spname_field",
type=int,
default=-1,
help=
("position of the species code extracted from node names. -1 = last field"
))
parser.add_argument("--collateral",
dest="collateral",
action='store_true',
help=(""))
parser.add_argument("--ref_attr",
dest="ref_attr",
type=str,
help=("attribute in ref tree used as leaf name"))
parser.add_argument("--target_attr",
dest="target_attr",
type=str,
help=("attribute in target tree used as leaf name"))
args = parser.parse_args(argv)
print __DESCRIPTION__
reftree = args.reftree
if args.targets_file and args.target_trees:
print >> sys.stderr, 'The use of targets_file and targets at the same time is not supported.'
sys.exit(1)
if args.targets_file:
target_trees = tree_iterator(args.targets_file)
else:
target_trees = args.target_trees
t = Tree(reftree)
if args.ref_attr:
for lf in t.iter_leaves():
lf._origname = lf.name
if args.ref_attr not in lf.features:
print lf
lf.name = getattr(lf, args.ref_attr)
if args.outgroup:
if len(args.outgroup) > 1:
out = t.get_common_ancestor(args.outgroup)
else:
out = t.search_nodes(name=args.outgroup[0])[0]
t.set_outgroup(out)
ref_names = set(t.get_leaf_names())
reftree_len = len(t)
reftree_edges = (reftree_len * 2) - 2
ncollapsed_branches = len([
n for n in t.traverse() if n.children and n.support < args.min_support
])
#reftree_edges -= ncollapsed_branches
#if ncollapsed_branches:
# print '%d branches collapsed in reference tree' %ncollapsed_branches
HEADER = ("target tree", 'dups', 'subtrees', 'used trees', 'treeko', "RF",
"maxRF", 'normRF', "%reftree", "%genetree", "avgSize", "minSize",
"common tips", "refSize", "targetSize")
if args.output:
OUT = open(args.output, "w")
print >> OUT, '# ' + ctime()
print >> OUT, '# ' + ' '.join(sys.argv)
print >> OUT, '#' + '\t'.join(HEADER)
else:
print '# ' + ctime()
print '# ' + ' '.join(sys.argv)
COL_WIDTHS = [20, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7]
print_table([HEADER], fix_col_width=COL_WIDTHS, wrap_style='wrap')
prev_tree = None
for counter, tfile in enumerate(target_trees):
if args.targets_file:
seedid, tfile = tfile
else:
seedid = None
if args.extract_species:
tt = PhyloTree(tfile,
sp_naming_function=lambda name: name.split(
args.spname_delimiter)[args.spname_field])
else:
tt = Tree(tfile)
if args.target_attr:
for lf in tt.iter_leaves():
lf._origname = lf.name
lf.name = getattr(lf, args.target_attr)
if args.outgroup:
if len(args.outgroup) > 1:
out = tt.get_common_ancestor(args.outgroup)
else:
out = tt.search_nodes(name=args.outgroup[0])[0]
tt.set_outgroup(out)
if args.target_trees:
fname = os.path.basename(tfile)
else:
fname = '%05d' % counter
max_size, min_size, avg_size, common = -1, -1, -1, -1
total_rf, max_rf, norm_rf = -1, -1, -1
treeko_d = -1
ref_branches_in_target, target_branches_in_ref = -1, -1
target_tree_len = -1
used_subtrees = -1
if args.extract_species:
orig_target_size = len(tt)
ntrees, ndups, sp_trees = tt.get_speciation_trees(
autodetect_duplications=True, newick_only=True)
if ntrees < 1000:
all_rf = []
ref_found = []
target_found = []
tree_sizes = []
all_max_rf = []
common_names = 0
for subtree_nw in sp_trees:
if seedid and not args.collateral and (seedid
not in subtree_nw):
continue
subtree = PhyloTree(
subtree_nw,
sp_naming_function=lambda name: name.split(
args.spname_delimiter)[args.spname_field])
# only necessary if rf function is going to filter by support value. It slows downs the analysis, obviously
if args.min_support:
subtree_content = subtree.get_cached_content(
store_attr='name')
for n in subtree.traverse():
if n.children:
n.support = tt.get_common_ancestor(
subtree_content[n]).support
rf, maxr, common, p1, p2, d1, d2 = t.robinson_foulds(
subtree,
expand_polytomies=args.polytomies,
unrooted_trees=args.unrooted,
attr_t2='species',
min_support_t2=args.min_support)
if maxr > 0 and p1 and p2:
all_rf.append(rf)
tree_sizes.append(len(common))
all_max_rf.append(maxr)
common_names = max(common_names, len(common))
ref_found.append(float(len(p2 & p1)) / reftree_edges)
p2bis = set([
p for p in (p2 - d2)
if len(p[0]) > 1 and len(p[1]) > 1
]) # valid edges in target not leaves
if p2bis:
incompatible_target_branches = float(
len((p2 - d2) - p1))
target_found.append(1 -
(incompatible_target_branches /
(len(p2 - d2))))
# valid_target = p2-d2
# valid_ref = p1-d1
# ref_found.append(float(len(valid_target & valid_ref)) / reftree_edges)
# p2bis = set([p for p in (p2-d2) if len(p[0])>1 and len(p[1])>1])
# if p2bis-d2:
# incompatible_target_branches = float(len((p2-d2) - p1))
# target_found.append(1 - (incompatible_target_branches / (len(p2-d2))))
if all_rf:
# Treeko speciation distance
alld = [(all_rf[i] / float(all_max_rf[i]))
for i in xrange(len(all_rf))]
a = numpy.sum(
[alld[i] * tree_sizes[i] for i in xrange(len(all_rf))])
b = float(numpy.sum(tree_sizes))
treeko_d = a / b
total_rf = numpy.mean(all_rf)
norm_rf = numpy.mean([(all_rf[i] / float(all_max_rf[i]))
for i in xrange(len(all_rf))])
max_rf = numpy.max(all_max_rf)
ref_branches_in_target = numpy.mean(ref_found)
target_branches_in_ref = numpy.mean(
target_found) if target_found else -1
target_tree_len = numpy.mean(tree_sizes)
used_subtrees = len(all_rf)
else:
target_tree_len = len(tt)
ndups, ntrees, used_subtrees = 0, 1, 1
treeko_d = -1
total_rf, max_rf, common, p1, p2, d1, d2 = tt.robinson_foulds(
t,
expand_polytomies=args.polytomies,
unrooted_trees=args.unrooted)
common_names = len(common)
if max_rf:
norm_rf = total_rf / float(max_rf)
if p1 and p2:
sizes = [len(p) for p in p2 ^ p1]
if sizes:
avg_size = sum(sizes) / float(len(sizes))
max_size, min_size = max(sizes), min(sizes)
else:
max_size, min_size, avg_size = 0, 0, 0
ref_branches_in_target = float(len(p2 & p1)) / reftree_edges
#if p2-d2:
# incompatible_target_branches = float(len((p2-d2) - p1))
# target_found.append(1 - (incompatible_target_branches / (len(p2-d2))))
else:
ref_branches_in_target = 0.0
target_branches_in_ref = 0.0
max_size, min_size, avg_size = -1, -1, -1
if args.output:
print >> OUT, '\t'.join(
map(str, (fname, ndups, ntrees, used_subtrees, treeko_d,
total_rf, max_rf, norm_rf, ref_branches_in_target,
target_branches_in_ref, avg_size, min_size,
common_names, reftree_len, target_tree_len)))
else:
print_table([
map(istr,
(fname[-30:], ndups, ntrees, used_subtrees, treeko_d,
total_rf, max_rf, norm_rf,
'%0.4f' % ref_branches_in_target,
'%0.4f' % target_branches_in_ref, avg_size, min_size,
common_names, reftree_len, target_tree_len))
],
fix_col_width=COL_WIDTHS,
wrap_style='cut')
if args.output:
OUT.close()
def main(argv):
parser = argparse.ArgumentParser(
description=__DESCRIPTION__,
formatter_class=argparse.RawDescriptionHelpFormatter)
input_args = parser.add_argument_group("INPUT OPTIONS")
input_args.add_argument("source_trees",
metavar='source_trees',
type=str,
nargs="*",
help='a list of source tree files')
input_args.add_argument(
"--source_file",
dest="source_file",
type=str,
help="""path to a file containing many source trees, one per line""")
input_args.add_argument("-r",
dest="reftree",
type=str,
required=True,
help="""Reference tree""")
input_args.add_argument("--ref_tree_attr",
dest="ref_tree_attr",
type=str,
default="name",
help=("attribute in ref tree used as leaf name"))
input_args.add_argument(
"--src_tree_attr",
dest="src_tree_attr",
type=str,
default="name",
help=("attribute in source tree used as leaf name"))
input_args.add_argument(
"--min_support_ref",
type=float,
default=0.0,
help=("min support for branches to be considered from the ref tree"))
input_args.add_argument(
"--min_support_src",
type=float,
default=0.0,
help=(
"min support for branches to be considered from the source tree"))
output_args = parser.add_argument_group("OUTPUT OPTIONS")
output_args.add_argument("-o",
dest="output",
type=str,
help="""Path to the tab delimited report file""")
opt_args = parser.add_argument_group("DISTANCE OPTIONS")
opt_args.add_argument(
"--outgroup",
dest="outgroup",
nargs="+",
help=
"""outgroup used to root reference and source trees before distance computation"""
)
opt_args.add_argument("--expand_polytomies",
dest="polytomies",
action="store_true",
help="""expand politomies if necessary""")
opt_args.add_argument("--unrooted",
dest="unrooted",
action="store_true",
help="""compare trees as unrooted""")
opt_args.add_argument(
"--min_support",
dest="min_support",
type=float,
default=0.0,
help=
("min support value for branches to be counted in the distance computation (RF, treeko and refTree/targeGene compatibility)"
))
opt_args = parser.add_argument_group("PHYLOGENETICS OPTIONS")
opt_args.add_argument(
"--extract_species",
action="store_true",
help=
"When used, leaf names in the reference and source trees are assumed to represent species."
" If target trees are gene-trees whose species information is encoded as a part of the leaf sequence name,"
" it can be automatically extracted by providing a Perl regular expression that extract a "
" valid species code (see --sp_regexp). Such information will be also used to detect duplication"
" events. ")
opt_args.add_argument(
"--sp_regexp",
type=str,
help=
("Specifies a Perl regular expression to automatically extract species names"
" from the name string in source trees. If not used, leaf names are assumed to represent species names."
" Example: use this expression '[^_]+_(.+)' to extract HUMAN from the string 'P53_HUMAN'."
))
opt_args.add_argument("--collateral", action='store_true', help=(""))
args = parser.parse_args(argv)
print __DESCRIPTION__
reftree = args.reftree
if args.source_file and args.source_trees:
print >> sys.stderr, 'The use of targets_file and targets at the same time is not supported.'
sys.exit(1)
if args.source_file:
source_trees = tree_iterator(args.source_file)
else:
source_trees = args.source_trees
ref_tree = Tree(reftree)
if args.ref_tree_attr:
for lf in ref_tree.iter_leaves():
lf._origname = lf.name
if args.ref_tree_attr not in lf.features:
print lf
lf.name = getattr(lf, args.ref_tree_attr)
if args.outgroup:
if len(args.outgroup) > 1:
out = ref_tree.get_common_ancestor(args.outgroup)
else:
out = ref_tree.search_nodes(name=args.outgroup[0])[0]
ref_tree.set_outgroup(out)
HEADER = ("source tree", 'ref tree', 'common\ntips', 'normRF', 'RF',
'maxRF', "%reftree", "%genetree", "subtrees", "treeko\ndist")
if args.output:
OUT = open(args.output, "w")
print >> OUT, '# ' + ctime()
print >> OUT, '# ' + ' '.join(sys.argv)
print >> OUT, '#' + '\t'.join(HEADER)
else:
print '# ' + ctime()
print '# ' + ' '.join(sys.argv)
COL_WIDTHS = [20, 20] + [9] * 10
print_table([HEADER], fix_col_width=COL_WIDTHS, wrap_style='wrap')
prev_tree = None
ref_fname = os.path.basename(args.reftree)
for counter, tfile in enumerate(source_trees):
if args.source_file:
seedid, tfile = tfile
else:
seedid = None
if args.extract_species:
if args.sp_regexp:
SPMATCHER = re.compile(args.sp_regexp)
get_sp_name = lambda x: re.search(SPMATCHER, x).groups()[0]
else:
get_sp_name = lambda x: x
tt = PhyloTree(tfile, sp_naming_function=get_sp_name)
else:
tt = Tree(tfile)
if args.src_tree_attr:
for lf in tt.iter_leaves():
lf._origname = lf.name
lf.name = getattr(lf, args.src_tree_attr)
if args.outgroup:
if len(args.outgroup) > 1:
out = tt.get_common_ancestor(args.outgroup)
else:
out = tt.search_nodes(name=args.outgroup[0])[0]
tt.set_outgroup(out)
if args.source_trees:
fname = os.path.basename(tfile)
else:
fname = '%05d' % counter
r = tt.compare(ref_tree,
ref_tree_attr=args.ref_tree_attr,
source_tree_attr=args.src_tree_attr,
min_support_ref=args.min_support_ref,
min_support_source=args.min_support_src,
unrooted=args.unrooted,
has_duplications=args.extract_species)
print_table([
map(istr, [
fname[-30:], ref_fname[-30:], r['effective_tree_size'],
r['norm_rf'], r['rf'], r['max_rf'], r["source_edges_in_ref"],
r["ref_edges_in_source"], r['source_subtrees'],
r['treeko_dist']
])
],
fix_col_width=COL_WIDTHS,
wrap_style='cut')
if args.output:
OUT.close()
def main(argv):
global args
parser = argparse.ArgumentParser(
description=__DESCRIPTION__,
formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument("-r",
dest="reftree",
type=str,
required=True,
help="""Reference tree""")
parser.add_argument(
"--source_trees",
dest="source_trees",
type=str,
required=True,
help=
("A list of *rooted* genetrees, one per line, in the format: TreeID/SeedID [TAB] newick "
))
parser.add_argument("--plot_newick",
dest="plot_newick",
type=str,
help=(""))
parser.add_argument("--spname_delimiter",
dest="spname_delimiter",
type=str,
default="_",
help=("species code delimiter in node names"))
parser.add_argument(
"--spname_field",
dest="spname_field",
type=int,
default=-1,
help=
("position of the species code extracted from node names. -1 = last field"
))
parser.add_argument(
"--collateral",
dest="use_collateral",
action="store_true",
help=("If enabled, collateral information will be used as"
" equally qualified data. Otherwise, such data will"
" be reported separatedly. Use this if your set of"
" trees are not overlaping. "))
parser.add_argument(
"--skip_dup_detection",
dest="skip_dup_detection",
action="store_true",
help=('If used, duplications will be expected to be annotated'
' in the source gene trees with the evoltype="D" tag.'
' Otherwise they will be inferred on the fly using'
' the species overlap algorithm.'))
parser.add_argument(
"--spoverlap",
dest="species_overlap",
type=float,
default=0.0,
help=("Species overlap cutoff. A number between 0 and 1 "
"representing the percentage of species that should be "
"shared between two sister partitions to be considered a"
" duplication. 0 = any overlap represents a duplication. "))
parser.add_argument(
"--debug",
dest="debug",
action="store_true",
help=
("generate an image of every input gene tree tree, so the result can be inspected"
))
parser.add_argument(
"--snapshot_step",
dest="snapshot_step",
type=int,
default=1000,
help=("How many trees should be processed between snapshots dumps?"))
parser.add_argument(
"--reftree_constraint",
dest="reftree_constraint",
type=str,
help=("A python module from from which a function called "
"*is_valid_treeid(treeid, refbranch)* should be importable. "
"The function will be used to decide if the info of a given "
"source tree is informative or not for each reftree branch. "))
parser.add_argument("-o",
dest="output",
type=str,
required=True,
help=("output tag name (extensions will be added)"))
parser.add_argument("--cpu",
dest="cpu",
type=int,
default=1,
help=("enable parallel computation"))
parser.add_argument(
"--img_report",
dest="img_report",
action="store_true",
help=
("If true, it generates a summary image results with all the computed data"
))
parser.add_argument(
"--report_supports",
dest="report_supports",
action="store_true",
help=
("If used, supported ref tree branches are individually reported for each gene tree "
))
args = parser.parse_args(argv)
if args.plot_newick:
t = Tree(args.plot_newick)
ts = TreeStyle()
ts.layout_fn = info_layout
t.render("tree_analysis.png", tree_style=ts)
sys.exit(0)
SPNAME_FIELD, SPNAME_DELIMITER = args.spname_field, args.spname_delimiter
USE_COLLATERAL = args.use_collateral
DETECT_DUPLICATIONS = True if not args.skip_dup_detection else False
REPORT_PER_TREE_SUPPORTS = True if args.report_supports else False
SP_OVERLAP = args.species_overlap
DEBUG = args.debug
IMG_REPORT = args.img_report
reftree = PhyloTree(args.reftree, sp_naming_function=None)
for nid, n in enumerate(reftree.traverse()):
n.add_features(nid=nid)
REFTREE_SPECIES = set(reftree.get_leaf_names())
print __DESCRIPTION__
if REPORT_PER_TREE_SUPPORTS:
REPORT_SUPPORT_FILE = open("%s.gentree_supports" % args.output, "w")
print >> REPORT_SUPPORT_FILE, '#' + '\t'.join(
map(str, [
"treeId", "spCoverage", "mean_support", "mean_coll_support",
"tested_branches", 'tested_coll_branches'
]))
TOTAL_TREES = int(
commands.getoutput("wc -l %s" % args.source_trees).split()[0]) + 1
print >> sys.stderr, "Processing %d source trees" % TOTAL_TREES
if args.reftree_constraint:
import imp
constraint = imp.load_source('constraint', args.reftree_constraint)
IS_VALID_TREEID = constraint.is_valid_treeid
else:
IS_VALID_TREEID = None
if args.cpu > 1:
MONITOR_STEP = 0
#return (informed_branches, dup_per_branch, losses_per_branch, losses_per_dup_branch, refbranch_supports,
# coll_dup_per_branch, coll_losses_per_branch, coll_losses_per_dup_branch, coll_refbranch_supports)
# The output of the process_trees function are 9 dictionaries in which keys are refbranches
target_dicts = [{} for x in range(9)]
def merge_dict_results(target, source):
def merge_dict(target, source):
for k, v in source.iteritems():
if k not in target:
target[k] = v
elif isinstance(v, list):
target[k].extend(v)
elif isinstance(v, set):
target[k].update(v)
elif isinstance(v, int):
target[k] += v
else:
raise ValueError("Impossible to merge str results")
for index in xrange(len(target)):
merge_dict(target[index], out[index])
from multiprocessing import Process, Queue
from Queue import Empty as QueueEmpty
outputs_queue = Queue()
if TOTAL_TREES > args.cpu:
trees_per_cpu = TOTAL_TREES / args.cpu
trees_per_cpu += 1 if TOTAL_TREES % args.cpu else 0
else:
trees_per_cpu = 1
args.cpu = TOTAL_TREES
all_workers = set()
for cpu_num in xrange(args.cpu):
sline = (cpu_num * trees_per_cpu)
eline = (cpu_num * trees_per_cpu) + trees_per_cpu
data_iter = tree_iterator(args.source_trees,
restrict_species=REFTREE_SPECIES,
start_line=sline,
end_line=eline)
print >> sys.stderr, "Launching worker %d from %d to %d" % (
cpu_num, sline, eline)
worker = Process(target=run_parallel,
args=(cpu_num, outputs_queue, process_trees,
data_iter, reftree, trees_per_cpu))
worker.name = "Worker_%d" % cpu_num
all_workers.add(worker)
worker.start()
while all_workers:
# clear done threads
for w in list(all_workers):
if not w.is_alive():
print >> sys.stderr, "%s thread is done!" % w.name
all_workers.discard(w)
# get and merge results
while 1:
try:
out = outputs_queue.get(False)
except QueueEmpty:
break
else:
# This merge depends on process_trees return output!!!!!
merge_dict_results(target_dicts, out)
# Dump a snapshot
dump_results(reftree, *target_dicts)
time.sleep(0.1)
if all_workers:
time.sleep(1)
# collected data
(informed_branches, dup_per_branch, losses_per_branch,
losses_per_dup_branch, refbranch_supports, coll_dup_per_branch,
coll_losses_per_branch, coll_losses_per_dup_branch,
coll_refbranch_supports) = target_dicts
else:
MONITOR_STEP = args.snapshot_step
data_iter = tree_iterator(args.source_trees,
restrict_species=REFTREE_SPECIES)
(informed_branches, dup_per_branch, losses_per_branch,
losses_per_dup_branch, refbranch_supports, coll_dup_per_branch,
coll_losses_per_branch, coll_losses_per_dup_branch,
coll_refbranch_supports) = process_trees(data_iter, reftree,
TOTAL_TREES)
if REPORT_PER_TREE_SUPPORTS:
REPORT_SUPPORT_FILE.close()
dump_results(reftree, informed_branches, dup_per_branch, losses_per_branch,
losses_per_dup_branch, refbranch_supports,
coll_dup_per_branch, coll_losses_per_branch,
coll_losses_per_dup_branch, coll_refbranch_supports)
print >> sys.stderr, "Dumping full analysis..."
# Full dump, including duplication details
cPickle.dump(reftree, open("%s.pkl" % args.output, "w"))
def main(argv):
parser = argparse.ArgumentParser(description=__DESCRIPTION__,
formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument("-r", dest="reftree",
type=str, required=True,
help="""Reference tree""")
parser.add_argument("source_trees", metavar='source_trees',
type=str, nargs="+",
help='A list of newick tree files used as a source for node annotations')
parser.add_argument("--discard", dest="discard",
type=str, nargs="+", default=[],
help=("A list of attributes that should be ignored from source trees. "
"Node dist, name and support values are always ignored unless they"
" are explicitly passed as target features"))
parser.add_argument("--features", dest="features",
type=str, nargs="+", default = [],
help=("A list of attributes that should be transferred from source trees."))
parser.add_argument("-o", dest="output",
type=str, required=True,
help=("output file name for the annotated tree"))
args = parser.parse_args(argv)
ref = Tree(args.reftree)
TARGET_FEATURES = args.features
DISCARD_FEATURES = args.discard + ["support", "name", "dist"]
key2node = {}
for node in ref.traverse():
nodekey = frozenset(node.get_leaf_names())
key2node[nodekey] = node
out = ref.children[0].get_leaf_names()
out2 = ref.children[1].get_leaf_names()
transferred_features = defaultdict(int)
for target in args.source_trees:
print target
tt = Tree(target)
tt.prune(ref.get_leaf_names())
if len(out) > 1:
try:
tt.set_outgroup(tt.get_common_ancestor(out))
except ValueError:
tt.set_outgroup(tt.get_common_ancestor(out2))
else:
tt.set_outgroup(tt.search_nodes(name=out[0])[0])
for node in tt.traverse():
nodekey = frozenset([n.name for n in node.get_leaves()])
target_node = key2node.get(nodekey, None)
if target_node:
for f in node.features:
if f in DISCARD_FEATURES and not TARGET_FEATURES:
continue
elif TARGET_FEATURES and f not in TARGET_FEATURES:
continue
else:
transferred_features[f] += 1
target_node.add_feature(f, getattr(node, f))
ref.write(outfile=args.output, features=[], format_root_node=True)
print
print_table(transferred_features.items(), header=["feature name", "#nodes"])
def main(argv):
parser = argparse.ArgumentParser(
description=__DESCRIPTION__,
formatter_class=argparse.RawDescriptionHelpFormatter)
input_gr = parser.add_argument_group(
"TREE INPUT OPTIONS\n=================")
input_gr.add_argument(
'tree',
metavar='tree_file',
type=str,
nargs=1,
help='A tree file (or text string) in newick format.')
input_gr.add_argument("--raxml",
dest="raxml",
action="store_true",
help="""Process newick as raxml bootstrap values""")
img_gr = parser.add_argument_group("TREE IMAGE OPTIONS\n=================")
img_gr.add_argument("-m",
"--mode",
dest="mode",
choices=["c", "r"],
default="r",
help="""(r)ectangular or (c)ircular visualization""")
img_gr.add_argument(
"-i",
"--image",
dest="image",
type=str,
help="Render tree image instead of showing it. A filename "
" should be provided. PDF, SVG and PNG file extensions are"
" supported (i.e. -i tree.svg)")
img_gr.add_argument("--text",
dest="text_mode",
action="store_true",
help="Shows the tree using ASCII characters")
img_gr.add_argument(
"--attr",
"--show_attributes",
dest="show_attributes",
nargs="+",
help="Display the value of the specified attributes, if available")
img_gr.add_argument(
"--Iw",
"--width",
dest="width",
type=int,
default=0,
help="width of the rendered image in pixels (see --size-units).")
img_gr.add_argument(
"--Ih",
"--height",
dest="height",
type=int,
default=0,
help="height of the rendered image in pixels (see --size-units).")
img_gr.add_argument("--Ir",
"--resolution",
dest="resolution",
type=int,
default=300,
help="Resolution if the tree image (DPI)")
img_gr.add_argument("--Iu",
"--size_units",
dest="size_units",
choices=["px", "mm", "in"],
default="px",
help="Units used to specify the size of the image."
" (px:pixels, mm:millimeters, in:inches). ")
img_gr.add_argument(
"-mbs",
"--min_branch_separation",
dest="branch_separation",
type=int,
default=3,
help="Min number of pixels to separate branches vertically.")
img_gr.add_argument("--ss",
"--show_support",
dest="show_support",
action="store_true",
help="""Shows branch bootstrap/support values""")
img_gr.add_argument("--sbl",
"--show_branch_length",
dest="show_branch_length",
action="store_true",
help="""Show branch lengths.""")
img_gr.add_argument(
"--ft",
"--force_topology",
dest="force_topology",
action="store_true",
help="""Force branch length to have a minimum length in the image""")
img_gr.add_argument("--hln",
"--hide_leaf_names",
dest="hide_leaf_names",
action="store_true",
help="""Hide leaf names.""")
img_gr.add_argument(
"--sin",
"--show_internal_names",
dest="show_internal_names",
action="store_true",
help="""Show the name attribute of all internal nodes.""")
edit_gr = parser.add_argument_group("TREE EDIT OPTIONS\n=================")
edit_gr.add_argument(
"-r",
"--root",
dest="root",
type=str,
nargs="*",
help="Roots the tree to the node grouping the list"
" of node names provided (space separated). In example:"
"'--root human rat mouse'")
edit_gr.add_argument("-s",
"--sort_branches",
dest="sort",
action="store_true",
help="""Sort branches according to node names.""")
edit_gr.add_argument("-l",
"--ladderize",
dest="ladderize",
action="store_true",
help="""Sort branches by partition size.""")
edit_gr.add_argument("--color_by_rank",
dest="color_by_rank",
type=str,
nargs="+",
help="""If the attribute rank is present in nodes """)
edit_gr.add_argument(
"--ncbi",
dest="ncbi",
action="store_true",
help=""" Annotate tree using the NCBI taxonomy database""")
edit_gr.add_argument(
"--taxid_attr",
dest="taxid_attr",
type=str,
default="name",
help="node attribute encoding for valid taxid numbers.")
edit_gr.add_argument(
"--taxid_attr_regexp",
dest="taxid_attr_regexp",
type=str,
help=
"If taxid number is encoded as part of another text string, i.e. gene name, use this argument to define a Perl regular expression to extract taxid numbers."
)
phylo_gr = parser.add_argument_group(
"PHYLOGENETIC OPTIONS\n=================")
phylo_gr.add_argument(
"--alg",
dest="alg",
type=str,
help="""Link tree to a multiple sequence alignment.""")
phylo_gr.add_argument(
"--alg_format",
dest="alg_format",
type=str,
default="fasta",
help="""fasta, phylip, iphylip, relaxed_iphylip, relaxed_phylip.""")
phylo_gr.add_argument(
"--sp_discovery",
dest="species_discovery_regexp",
type=str,
default="^[^_]+_(.+)",
help="Perl regular expression used to capture species"
" code from node names. By default, node names"
" are expected to follow the NAME_SPCODE format = '^[^_]+_(.+)' ")
args = parser.parse_args(argv)
tfile = args.tree[0]
if args.ladderize and args.sort:
raise ValueError(
"--sort-branches and --ladderize options are mutually exclusive")
if args.raxml:
nw = re.sub(":(\d+\.\d+)\[(\d+)\]", ":\\1[&&NHX:support=\\2]",
open(tfile).read())
t = PhyloTree(nw)
else:
t = PhyloTree(tfile)
if args.ncbi:
if args.taxid_attr_regexp:
TAXIDMATCHER = re.compile(args.taxid_attr_regexp)
for lf in t:
if args.taxid_attr_regexp:
lf.taxid = re.search(TAXIDMATCHER,
getattr(lf, args.taxid_attr)).groups()[0]
else:
lf.taxid = getattr(lf, args.taxid_attr)
t.annotate_ncbi_taxa(taxid_attr="taxid")
if args.alg:
t.link_to_alignment(args.alg, alg_format=args.alg_format)
LEAF_ATTRIBUTES["sequence"] = 1
if args.species_discovery_regexp:
SPCODE_REGEXP = re.compile(args.species_discovery_regexp)
t.set_species_naming_function(user_species_naming_function)
if args.ladderize:
t.ladderize()
if args.sort:
t.sort_descendants()
if args.root:
if len(args.root) > 1:
outgroup = t.get_common_ancestor(args.root)
else:
outgroup = t & args.root[0]
t.set_outgroup(outgroup)
# VISUALIZATION
ts = TreeStyle()
ts.mode = args.mode
ts.show_leaf_name = False
ts.branch_vertical_margin = args.branch_separation
if args.show_support:
ts.show_branch_support = True
if args.show_branch_length:
ts.show_branch_length = True
if args.force_topology:
ts.force_topology = True
if args.hide_leaf_names:
del LEAF_ATTRIBUTES["name"]
if args.show_internal_names:
INTERNAL_ATTRIBUTES["name"] = 1
# scale the tree
if not args.height:
args.height = None
if not args.width:
args.width = None
if args.text_mode:
print t.get_ascii(show_internal=args.show_internal_names,
attributes=args.show_attributes)
else:
ts.layout_fn = master_layout
if args.image:
t.render(args.image,
tree_style=ts,
w=args.width,
h=args.height,
units=args.size_units)
else:
t.show(None, tree_style=ts)
def main(argv):
parser = argparse.ArgumentParser(
description=__DESCRIPTION__,
formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument('tree',
metavar='tree_file',
type=str,
nargs=1,
help='A tree file (or text string) in newick format.')
parser.add_argument(
"--sp_delimiter",
dest="species_delimiter",
type=str,
default="_",
help=("When species names are guessed from node names,"
" this argument specifies how to split node name to guess"
" the species code"))
parser.add_argument(
"--sp_field",
dest="species_field",
type=int,
default=1,
help=("When species names are guessed from node names,"
" this argument specifies the position of the species"
" name code relative to the name splitting delimiter"))
parser.add_argument(
"--root",
dest="root",
type=str,
nargs="*",
help="Roots the tree to the node grouping the list"
" of node names provided (space separated). In example:"
"'--root human rat mouse'")
parser.add_argument(
"--skip_ortholog_detection",
dest="skip_ortholog_detection",
action="store_true",
help=
("Skip automatic detection of"
" speciation and duplication events, thus relying in the"
" correct annotation of the provided tree using"
" the extended newick format (i.e. '((A, A)[&&NHX:evoltype=D], B)[&&NHX:evoltype=S];')"
))
parser.add_argument(
"--evoltype_attr",
dest="evoltype_attr",
type=str,
default="evoltype",
help=(
"When orthology detection is disabled,"
" the attribute name provided here will be expected to exist"
" in all internal nodes and read from the extended newick format"))
parser.add_argument("--database",
dest="database",
type=str,
default="",
help=("Database name"))
parser.add_argument(
"--show",
dest="show",
action="store_true",
default="",
help=(
"Show the tree and its evolutionary events before orthoXML export"
))
parser.add_argument(
"--ascii",
dest="ascii",
action="store_true",
default="",
help=(
"Show the tree using ASCII representation and all its evolutionary"
" events before orthoXML export"))
parser.add_argument(
"--newick",
dest="newick",
action="store_true",
default="",
help=("print the extended newick format for provided tree using"
" ASCII representation and all its evolutionary events"
" before orthoXML export"))
args = parser.parse_args()
newick = args.tree[0]
SPECIES_NAME_POS = args.species_field
SPECIES_NAME_DELIMITER = args.species_delimiter
# load a phylomeDB Tree provided as a newick file in the command line
t = PhyloTree(newick, sp_naming_function=extract_spname)
if args.root:
if len(args.root) > 1:
outgroup = t.get_common_ancestor(args.root)
else:
outgroup = t & args.root[0]
t.set_outgroup(outgroup)
if not args.skip_ortholog_detection:
# detect speciation and duplication events using the species overlap
# algorithm used in phylomeDB
t.get_descendant_evol_events()
if args.ascii:
print t.get_ascii(attributes=[args.evoltype_attr, "name"],
show_internal=True)
if args.newick:
print t.write(features=[args.evoltype_attr], format_root_node=True)
if args.show:
t.show()
export_as_orthoXML(t, args.database, args.evoltype_attr)