我有一个约700个密钥的默认字典。密钥的格式为A_B_STRING。我需要做的是将键分成'_',并比较每个键的'STRING'之间的距离,如果A和B相同的话。如果距离<= 2,我想将这些键的列表分组到一个defaultdict键:值组中。将有多个密钥应匹配并进行分组。我还想保留新的组合defaultdict,所有关键:没有成为组的值对。
输入文件是FASTA格式,其中标题是键,值是序列(因为多个序列根据原始fasta文件的blast报告具有相同的标题,因此使用defaultdict) 。
这是我到目前为止所做的:
!/usr/bin/env python
import sys
from collections import defaultdict
import itertools
inp = sys.argv[1] # input fasta file; format '>header'\n'sequence'
with open(inp, 'r') as f:
h = []
s = []
for line in f:
if line.startswith(">"):
h.append(line.strip().split('>')[1]) # append headers to list
else:
s.append(line.strip()) # append sequences to list
seqs = dict(zip(h,s)) # create dictionary of headers:sequence
print 'Total Sequences: ' + str(len(seqs)) # Numb. total sequences in input file
groups = defaultdict(list)
for i in seqs:
groups['_'.join(i.split('_')[1:])].append(seqs[i]) # Create defaultdict with sequences in lists with identical headers
def hamming(str1, str2):
""" Simple hamming distance calculator """
if len(str1) == len(str2):
diffs = 0
for ch1, ch2 in zip(str1,str2):
if ch1 != ch2:
diffs += 1
return diff
keys = [x for x in groups]
combos = list(itertools.combinations(keys,2)) # Create tupled list with all comparison combinations
combined = defaultdict(list) # Defaultdict in which to place groups
for i in combos: # Combo = (A1_B1_STRING2, A2_B2_STRING2)
a1 = i[0].split('_')[0]
a2 = i[1].split('_')[0]
b1 = i[0].split('_')[1] # Get A's, B's, C's
b2 = i[1].split('_')[1]
c1 = i[0].split('_')[2]
c2 = i[1].split('_')[2]
if a1 == a2 and b1 == b2: # If A1 is equal to A2 and B1 is equal to B2
d = hamming(c1, c2) # Get distance of STRING1 vs STRING2
if d <= 2: # If distance is less than or equal to 2
combined[i[0]].append(groups[i[0]] + groups[i[1]]) # Add to defaultdict by combo 1 key
print len(combined)
for c in sorted(combined):
print c, '\t', len(combined[c])
问题是此代码无法正常工作。在组合的defaultdict中打印键时;我清楚地看到有许多可以结合起来。但是,组合defaultdict的长度大约是原始大小的一半。
修改
替代方案没有itertools.combinbin:
for a in keys:
tocombine = []
tocombine.append(a)
tocheck = [x for x in keys if x != a]
for b in tocheck:
i = (a,b) # Combo = (A1_B1_STRING2, A2_B2_STRING2)
a1 = i[0].split('_')[0]
a2 = i[1].split('_')[0]
b1 = i[0].split('_')[1] # Get A's, B's, C's
b2 = i[1].split('_')[1]
c1 = i[0].split('_')[2]
c2 = i[1].split('_')[2]
if a1 == a2 and b1 == b2: # If A1 is equal to A2 and B1 is equal to B2
if len(c1) == len(c2): # If length of STRING1 is equal to STRING2
d = hamming(c1, c2) # Get distance of STRING1 vs STRING2
if d <= 2:
tocombine.append(b)
for n in range(len(tocombine[1:])):
keys.remove(tocombine[n])
combined[tocombine[0]].append(groups[tocombine[n]])
final = defaultdict(list)
for i in combined:
final[i] = list(itertools.chain.from_iterable(combined[i]))
然而,使用这些方法,我仍然缺少一些与其他人不匹配的方法。
答案 0 :(得分:1)
我认为我看到您的代码存在一个问题,请考虑这种情况:
0: A_B_DATA1
1: A_B_DATA2
2: A_B_DATA3
All the valid comparisons are:
0 -> 1 * Combines under key 'A_B_DATA1'
0 -> 2 * Combines under key 'A_B_DATA1'
1 -> 2 * Combines under key 'A_B_DATA2' **opps
我想你会希望所有这三个在1键下合并。但请考虑以下情况:
0: A_B_DATA111
1: A_B_DATA122
2: A_B_DATA223
All the valid comparisons are:
0 -> 1 * Combines under key 'A_B_DATA111'
0 -> 2 * Combines under key 'A_B_DATA111'
1 -> 2 * Combines under key 'A_B_DATA122'
现在它变得有点棘手,因为第0行是第1行的距离2,第1行是第2行的第2距离,但是你可能不希望它们全部在一起,因为第0行距第2行的距离为3!
这是一个工作解决方案的示例,假设您希望输出看起来像这样:
def unpack_key(key):
data = key.split('_')
return '_'.join(data[:2]), '_'.join(data[2:])
combined = defaultdict(list)
for key1 in groups:
combined[key1] = []
key1_ab, key1_string = unpack_key(key1)
for key2 in groups:
if key1 != key2:
key2_ab, key2_string = unpack_key(key2)
if key1_ab == key2_ab and len(key1_string) == len(key2_string):
if hamming(key1_string, key2_string) <= 2:
combined[key1].append(key2)
在我们的第二个例子中,这将产生以下字典,如果这不是您正在寻找的答案,您是否可以输入该示例的最终字典应该是什么?
A_B_DATA111: ['A_B_DATA122']
A_B_DATA122: ['A_B_DATA111', 'A_B_DATA223']
A_B_DATA223: ['A_B_DATA122']
请记住,这是一个O(n ^ 2)算法,这意味着当您的密钥集变大时,它不可扩展。