Add python script for pairwise comparison

#!/usr/bin/env python2

# Pairwise comparison of contigs and assessment of shared gene content

from __future__ import division

import scipy.stats as stats

import re

import math

import sys

clusters = sys.argv[1]

families = {}

names2 = []

with open(clusters) as file2:

    for line in file2:

        dat = line.strip().split('\t')

        for i in dat:

            contig = re.search('(\S+)_\d+', i).group(1)

            families[contig] = set()

            names2.append(contig)

names = list(set(names2))

with open(clusters) as file1:

    count = 1

    for line in file1:

        dat = line.strip().split('\t')

        for i in dat:

            k = re.search('(\S+)_\d+', i).group(1)

            if k in families:

                families[k].add('family_' + str(count))

        count += 1

total = []

file_out = open('genome_graphs.txt', 'w')

for i in range(len(names)):

    for j in range(len(names)):

        if names[i] != names[j]:

            common = len(families[names[i]].intersection(families[names[j]]))

            c = max(len(families[names[i]]), len(families[names[j]]))

            b = min(len(families[names[i]]), len(families[names[j]]))

            p = stats.hypergeom.sf(common - 1, count - 1, c, b)

            if p != 0:

                link_strength = - math.log10(p * (len(names) * (len(names) - 1) / 2))

                if link_strength > 0 and names[i] != names[j]:

                    l = [names[i], names[j], str(link_strength)]

                    file_out.write('\t'.join(l) + '\n')

            else:

                l = [names[i], names[j], "100"]

                file_out.write('\t'.join(l) + '\n')

file_out.close()