print ('\n---------\nNow working with leaf ' + leaf.name)
tree.mark_tree([leaf.node_id], marks=['#1'])
print (tree.write())
# to organize a bit, we name model with the name of the marked node
# any character after the dot, in model name, is not taken into account
# for computation. (have a look in /tmp/ete3.../bsA.. directory)
print ('running model bsA and bsA1')
tree.run_model('bsA.'+ leaf.name)
tree.run_model('bsA1.' + leaf.name)
print ('p-value of positive selection for sites on this branch is: ')
ps = tree.get_most_likely('bsA.' + leaf.name, 'bsA1.'+ leaf.name)
rx = tree.get_most_likely('bsA1.'+ leaf.name, 'M0')
print (str(ps))
print ('p-value of relaxation for sites on this branch is: ')
print (str(rx))
if ps < 0.05 and float(tree.get_model("bsA." + leaf.name).wfrg2a) > 1:
print ('we have positive selection on sites on this branch')
elif rx<0.05 and ps>=0.05:
print ('we have relaxation on sites on this branch')
else:
print ('no signal detected on this branch, best fit for M0')
print ('\nclean tree, remove marks')
tree.mark_tree(map(lambda x: x.node_id, tree.get_descendants()),
marks=[''] * len(tree.get_descendants()), verbose=True)
# nothing working yet to get which sites are under positive selection/relaxation,
# have to look at the main outfile or rst outfile
print ('The End.')
print('\n---------\nNow working with leaf ' + leaf.name)
tree.mark_tree([leaf.node_id], marks=['#1'])
print(tree.write())
# to organize a bit, we name model with the name of the marked node
# any character after the dot, in model name, is not taken into account
# for computation. (have a look in /tmp/ete3.../bsA.. directory)
print('running model bsA and bsA1')
tree.run_model('bsA.' + leaf.name)
tree.run_model('bsA1.' + leaf.name)
print('p-value of positive selection for sites on this branch is: ')
ps = tree.get_most_likely('bsA.' + leaf.name, 'bsA1.' + leaf.name)
rx = tree.get_most_likely('bsA1.' + leaf.name, 'M0')
print(str(ps))
print('p-value of relaxation for sites on this branch is: ')
print(str(rx))
if ps < 0.05 and float(tree.get_model("bsA." + leaf.name).wfrg2a) > 1:
print('we have positive selection on sites on this branch')
elif rx < 0.05 and ps >= 0.05:
print('we have relaxation on sites on this branch')
else:
print('no signal detected on this branch, best fit for M0')
print('\nclean tree, remove marks')
tree.mark_tree(map(lambda x: x.node_id, tree.get_descendants()),
marks=[''] * len(tree.get_descendants()),
verbose=True)
# nothing working yet to get which sites are under positive selection/relaxation,
# have to look at the main outfile or rst outfile
print('The End.')
