Alignment tools like mafft, muscle etc. does this for you if you are not comfortable with writing a script to compare all possible k-mers/aligned bases between all pairwise sequences to construct a distance matrix.

Follow the steps given in this link: http://mafft.cbrc.jp/alignment/software/treeout.html

(keep in mind that your input should be the raw fasta sequences)

Other wise you could use (slight modification required) this python code to do all possible pairwise comparisons in your alignment file to get the distance matrix:

import numpy as np
import matplotlib.pylab as plt

def get_difference(x,y):
    return sum(ele_x != ele_y for ele_x, ele_y in zip(x,y))

my_list = []

f3= open("GBSraw_6lines.txt", "r")
lines3 = f3.readlines()
for line in lines3:
                line=line.split('\t')
                #line=line.split('\t')

                if not line[0].startswith("Taxa"):
                                #print line [1:-1]
                                #print(''.join(line[1:-1]))
                                #print line
                                my_list.append(''.join(line[1:-1]))
#print my_list

n = len(my_list)
l= len(my_list[0])

my_array = np.zeros((n,n))
#
for i, ele_1 in enumerate(my_list):
    for j, ele_2 in enumerate(my_list):
        if j >= i:
            break # Since the matrix is symmetrical we don't need to
                  # calculate everything
        #difference = 1.0-((int(l))-(int(get_difference(ele_1, ele_2)))/int(l))
        difference = 1-((l-get_difference(ele_1, ele_2))/float(l))
        print difference
        #print (int(n))
        my_array[i, j] = difference
        my_array[j, i] = difference

line_names = ['','B73','CML277','HP301','Mo17','P39','Tx303']

#line_names2 = ['','Tx303','P39','Mo17','HP301','CML277','B73'] 
print my_array

fig = plt.figure()
ax = fig.add_subplot(1,1,1)
ax.set_aspect('equal')
plt.imshow(my_array, interpolation='nearest', cmap=plt.cm.ocean)

for y in range(my_array.shape[0]):
    for x in range(my_array.shape[1]):
        plt.text(x , y , '%.4f' % my_array[y, x],
                 horizontalalignment='center',
                 verticalalignment='center',
                 )

plt.colorbar()
ax.xaxis.set_ticks_position('top')
ax.set_xticklabels(line_names, minor=False)
ax.set_yticklabels(line_names, minor=False)
plt.show()

f3.close()