def load_parameters():
descendant_dict = defaultdict()
with open(input_file, 'r') as f:
all_lines = f.readlines()
aln_file = all_lines[0].strip()
if not os.path.exists(aln_file):
logger.error('Invalid cDNA alignment file: {0}'.format(aln_file))
sys.exit(1)
logger.info('Input cDNA alignment file: {0}'.format(aln_file))
seq_id_dict = defaultdict()
seq_id_list = []
for seq_record in AlignIO.read(aln_file, 'fasta'):
seq_id_dict[str(seq_record.id)] = 1
seq_id_list.append(str(seq_record.id))
tree_file = all_lines[1].strip()
if not os.path.exists(tree_file):
logger.error('Invalid tree file: {0}'.format(tree_file))
sys.exit(1)
logger.info('Input tree file: {0}'.format(tree_file))
tmp_t = Tree(tree_file, format=0)
node_id_dict = defaultdict()
for node in tmp_t:
node_id_dict[str(node.name)] = 1
if seq_id_dict != node_id_dict:
if len(seq_id_dict) < len(node_id_dict):
logger.warning('Sequences is less than tree nodes.')
logger.info('Trim input tree file.')
tree_file = trim_tree(tree_file, seq_id_list)
else:
logger.error('Sequences is falsely greater than tree nodes.')
sys.exit(1)
t = EvolTree(tree_file, format=1)
for descendant in t.iter_descendants():
descendant_dict[descendant.node_id] = str(descendant)
root = t.get_tree_root()
id_list = []
for leaf in t.traverse('preorder'):
id_list.append(leaf.node_id)
select_nodes = []
if len(all_lines) > 2:
for each_line in all_lines[2:]:
s = each_line.strip()
if s:
select_nodes.append(s)
if select_nodes:
nodes_line = ', '.join(select_nodes)
logger.info('Input nodes: {0}'.format(nodes_line))
for node in select_nodes:
if node not in t:
logger.error('Error node: {0}'.format(node))
sys.exit(1)
if not t.check_monophyly(values=select_nodes, target_attr='name'):
logger.error('Some nodes are not monophyletic.')
sys.exit(1)
common_ancestor = t.get_common_ancestor(select_nodes)
else:
common_ancestor = root
logger.info('No specific node')
run_list = []
for s in common_ancestor.iter_descendants():
run_list.append(s.node_id)
logger.info('These node ids will be checked: {0}'.format(
str(run_list)))
return run_list, aln_file, tree_file, descendant_dict
tree.prune(taxa_in_alignment, preserve_branch_length=True)
test_taxa = []
with open(test_taxa_file, 'r') as test_taxa_list:
for taxon in test_taxa_list:
taxon = taxon.rstrip()
test_taxa.append(taxon)
nodes_to_mark = set() # set since we want it to be all unique ids
# Mark the test taxa
for taxon in test_taxa:
taxon_node = tree & taxon # ete3 notation for finding a node within a tree
taxon_id = taxon_node.node_id # mark_tree only takes node_ids, not labels
nodes_to_mark.add(taxon_id)
# Find internal nodes below the test taxa and mark them
for i in range(len(test_taxa), 1, -1):
taxa_groups = [x for x in combinations(test_taxa, i)]
for group in taxa_groups:
common_node = tree.get_common_ancestor(*group)
taxon_id = common_node.node_id
nodes_to_mark.add(taxon_id)
#TODO change the names of the nodes
for mark_id in nodes_to_mark:
test_node = tree.search_nodes(node_id=mark_id)[0]
test_node.name += '{test}'
tree.write(outfile=out_tree_name, format=1)
import sys, os, subprocess
import argparse
from ete3 import EvolTree
tree = EvolTree("tree.nw",
binpath="/home/edu/miniconda3/envs/ete3/bin/ete3_apps/bin")
tree.link_to_alignment("infile.phy", alg_format="phylip")
tree.workdir = os.getcwd()
print(tree)
print('running model M0, for comparison with branch-site models...')
tree.run_model('M0', keep=True)
#tree.link_to_evol_model("/home/edu/Desktop/Bioinformatica/Mitogenomics/Chondrichthyes/Phylogenetic_Tree","M0")
chimaeriformes = tree.get_common_ancestor("HM147138.1", "HM147135.1")
#chimaeriformes =tree.get_common_ancestor("Human_ECP","Goril_ECP")
for leaf in chimaeriformes:
tree.mark_tree([leaf.node_id], marks=["#1"])
#tree.run_model("bsA." + chimaeriformes)
#tree.mark_tree([leaf.node_id], marks = ["#1"])
print("Running")
print(tree.write())
tree.run_model('bsA.Chimaeriformes')
tree.run_model("bsA1.Chimaeriformes")
print('p-value of positive selection for sites on this branch is: ')
ps = tree.get_most_likely('bsA.Chimaeriformes', 'bsA1.Chimaeriformes')
print(str(ps))
rx = tree.get_most_likely('bsA1.Chimaeriformes', 'M0')
