ptreegen.distance_functions Namespace Reference

Functions
def	p_distance
	Computation of the uncorrected p-distance.
def	poisson_corrected
	Poisson corrected p-distance.
def	jukes_cantor
	Distance according to the Jukes-Cantor model.

Function Documentation

def ptreegen.distance_functions.jukes_cantor	(		seq1,
			seq2,
			args,
			kwargs
	)

Distance according to the Jukes-Cantor model.

For more info see: http://goo.gl/upr3wR

Parameters

seq1	first sequence
seq2	second sequence
*args	positional arguments
**kwargs	keyword arguments ("sequence_type" option is used to determine the parameters for the formula)

Returns

distance as a single value

Definition at line 66 of file distance_functions.py.

References ptreegen.distance_functions.p_distance().

def jukes_cantor(seq1, seq2, *args, **kwargs):
    p_dist = p_distance(seq1, seq2, *args, **kwargs)
    if kwargs["sequence_type"] == SeqTypes.AA:
        return (-19.0/20.0) * math.log(1 - (20.0/19.0) * p_dist)
    elif kwargs["sequence_type"] == SeqTypes.DNA or kwargs["sequence_type"] == SeqTypes.RNA:
        return (-3.0/4.0) * math.log(1 - (4.0/3.0) * p_dist)
    else:
        assert False

def ptreegen.distance_functions.p_distance	(		seq1,
			seq2,
			args,
			kwargs
	)

Computation of the uncorrected p-distance.

The formula is similar to the one used in EMBOSS (see http://emboss.sourceforge.net/apps/release/6.6/emboss/apps/distmat.html).

Parameters

seq1	first sequence
seq2	second sequence
*args	positional arguments
**kwargs	keyword arguments (the "gap_penalty" argument is used to determine the gap penalty)

Returns

distance as a single value

Definition at line 22 of file distance_functions.py.

Referenced by ptreegen.distance_functions.jukes_cantor(), and ptreegen.distance_functions.poisson_corrected().

def p_distance(seq1, seq2, *args, **kwargs):
    assert len(seq1) == len(seq2)
    gap_penalty = 0
    if kwargs.has_key("gap_penalty"):
        gap_penalty = kwargs["gap_penalty"]
    positions_all = len(seq1)
    matches = 0
    gaps = 0
    for idx in range(positions_all):
        res1 = seq1[idx]
        res2 = seq2[idx]
        if res1 == res2 and not(res1 == "-" and res2 == "-"):
            matches+=1
        elif res1 == "-" or res2 == "-" and not(res1 == "-" and res2 == "-"):
            gaps+=1
    return 1 - float(matches) / ((positions_all - gaps) + gaps * gap_penalty)