12 Overlap Graphs - 爱码网

Problem

A graph whose nodes have all been labeled can be represented by an adjacency list, in which each row of the list contains the two node labels corresponding to a unique edge.

A directed graph (or digraph) is a graph containing directed edges, each of which has an orientation. That is, a directed edge is represented by an arrow instead of a line segment; the starting and ending nodes of an edge form its tail and head, respectively. The directed edge with tail directed loop is a directed edge of the form (v,v).

For a collection of strings and a positive integer overlap graph for the strings is a directed graph suffix of prefix of s≠t to prevent directed loops in the overlap graph (although directed cycles may be present).

Given: A collection of DNA strings in FASTA format having total length at most 10 kbp.

Return: The adjacency list corresponding to O3. You may return edges in any order.

Sample Dataset

>Rosalind_0498
AAATAAA
>Rosalind_2391
AAATTTT
>Rosalind_2323
TTTTCCC
>Rosalind_0442
AAATCCC
>Rosalind_5013
GGGTGGG

Sample Output

Rosalind_0498 Rosalind_2391
Rosalind_0498 Rosalind_0442
Rosalind_2391 Rosalind_2323


方法一

# coding=utf-8

# method1
data ={'Rosalind_0442': 'AAATCCC',
 'Rosalind_0498': 'AAATAAA',
 'Rosalind_2323': 'TTTTCCC',
 'Rosalind_2391': 'AAATTTT',
 'Rosalind_5013': 'GGGTGGG'}

def is_k_overlap(s1, s2, k):
    return s1[-k:] == s2[:k]


import itertools
def k_edges(data, k):
    edges = []
    for u,v in itertools.combinations(data, 2):  # data 里面任意取两个比较
        u_dna, v_dna = data[u], data[v]
        print u_dna, v_dna
        if is_k_overlap(u_dna, v_dna, k):
            edges.append((u,v))

        if is_k_overlap(v_dna, u_dna, k):
            edges.append((v,u))

    return edges

print k_edges(data, 3)

　　方法二：

# coding=utf-8
### 12. Overlap Graphs ###
from collections import OrderedDict
import re


def overlap_graph(dna, n):
    edges = []
    for ke1, val1 in dna:
        for ke2, val2 in dna:
            if ke1 != ke2 and val1[-n:] == val2[:n]:
                edges.append(ke1 + '\t' + ke2)
    return edges


dna = OrderedDict()
with open('12.txt') as f:
    for line in f:
        line = line.rstrip()
        if line.startswith('>'):
            seqName = re.sub('>', '', line)
            dna[seqName] = ''
            continue
        dna[seqName] += line.upper()

fh = open('rosalind_grph_output.txt', 'wt')
for x in overlap_graph(dna.items(), 3):
    fh.write(x + '\n')

fh.close()

　　方法三

# coding=utf-8
seq_list = []
stseq = ''
for line in open('12.txt'):
    if line[0] == '>':
        if stseq != '':
            seq_list.append([stname, stseq])
            stseq = ''
        stname = line[1:-1]
    else:
        stseq = stseq + line.strip('\n')
seq_list.append([stname, stseq])
l = len(seq_list)

for i in range(0, l):
    for j in range(0, i):
        if seq_list[i][1] == seq_list[j][1]:
            continue
        if seq_list[i][1][0:3] == seq_list[j][1][-3:]:
            print seq_list[j][0], seq_list[i][0]
        if seq_list[i][1][-3:] == seq_list[j][1][0:3]:
            print seq_list[i][0], seq_list[j][0]