在 Python 中连接两个 fasta 文件
Concatenate two fasta files in Python
我有两个数据文件 (FASTA)，每个文件代表一个基因，序列按物种和本地标识。我想将这些文件连接成一个，例如：
psbki.fas:
>E_oleracea_Docas_de_Belm
AACCT
ycf1b.fas:
>E_oleracea_Docas_de_B
GGTTC
output:
>E_oleracea_Docas_de_Belm
AACCTGGTTC
如果您查看这两个文件中的物种名称，它们在编写时存在一些语法问题，使它们彼此不同。另外，我还有一个问题：有些物种不在两个文件中。
为了解决这些问题，我写了下面的代码：
ids, sequences = parse_fasta(open('psbki.fas', 'r').read().split('\n'))
ids2, sequences2 = parse_fasta(open('ycf1b.fas', 'r').read().split('\n'))
for i, j, z, h in zip(ids, sequences, sequences2, ids2):
if i != h:
print(">"+i + "\n"+j)
else:
print(">"+i + "\n"+j+z)
前两个序列的输出没问题。但是对于其他序列，代码只打印一个文件中的文件，但它们在两个文件中。
我的代码有什么问题？
我是 python
的初学者
输出是：
>E_edulis_I1
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTTTGGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAAG----ATCTTGAATTGGTATTATTCTCATTATCAGCATAAATTATCACACGTCTGGCTCTTCTTGAACGAATTTCAATATCTTCTATCGGTTTTTCCTCATTTTCTTCCTCCTGTTCTTCCAGAAGATTGGTCAATTTATATGACCATCGAGAAACCTTTTTACTGATTTCTTCTATTCCAATAGATTCATTTCTAGTTGTTTTATCATTTGGATCAATTGTCATTATATCGAATACAAATTTCAAAGATTTTGCTTGACTTTCTGAATCCATTTTTCTTTGTTCTGCCAATAAAGAACAGTTTTTCAAACAAAAATTGGGTGTGAATTCAAAAGAAAATGAAGTTAAGGAATTACCGATATAATTCAAAAATGATTTACCACCACCAAGTGAATTCTTTTGATGTTCAAATTCTCTGAAATTATTAGGAAGTAGCTCATGGATCTTATTTATCCAAAGACTTTTTATGGAATCCTCCATATAAGGGAAAAAATCATTTATGATTGTACGTAAATCAAAATCTTTTATTGCTCCACGGCATGGTCCGCTCAATAAAGGATCATATGTTTTGGTCAAGCATTTTTGTTTATTCTCATGATTGCAAAATCTAGTCTTTTTTTCGAGCATATCTAGAGCAAGAAATCCCTTTTCTTTTTTTTCTTTTTCTAGAGCTTTTATTCGACTTATTAATTCATTGCTCAAGTTGTATTTTTTTTGTTCATTGGTAAAAACCCAAAAATTATACAGGTCTCCATGGGATAATTTTTT-GTCGTGTACAAAAACATTTTTCGTTCTATCATTTCC
>E_edulis_I2
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTTTGGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAAG----ATCTTGAATTGGTATTATTCTCATTATCAGCATAAATTATCACACGTCTGGCTCTTCTTGAACGAATTTCAATATCTTCTATCGGTTTTTCCTCAATTTCTTCCTCCTGTTCTTCCAGAAGATTGGTCAATTTATATGACCATCGAGAAACCTTTTTACTGATTTCTTCTATTCCAATAGATTCATTTCTAGTTGTTTTATCATTTGGATCAATTGTCATTATATCGAATACAAATTTCAAAGATTTTGCTTGACTTTCTGAATCCATTTTTCTTTGTTCTGCCAATAAAGAACAGTTTTTCAAACAAAAATTGGGTGTGAATTCAAAAGAAAATGAAGTTAAGGAATTACCGATATAATTCAAAAATGATTTACCACCACCAAGTGAATTCTTTTGATGTTCAAATTCTCTGAAATTATTAGGAAGTAGCTCATGGATCTTATTTATCCAAAGACTTTTTATGGAATCCTCCATATAAGGGAAAAAATCATTTATGATTGTACGTAAATCAAAATCTTTTATTGCTCCACGGCATGGTCCGCTCAATAAAGGATCATATGTTTTGGTCAAGCATTTTTGTTTATTCTCATGATTGCAAAATCTAGTCTTTTTTTCGAGCATATCTAGAGCAAGAAATCCCTTTTCTTTTTTTTCTTTTTCTAGAGCTTTTATTCGACTTATTAATTCATTGCTCAAGTTGTATTTTTTTTGTTCATTGGTAAAAACCCAAAAATTATACAGGTCTCCATGGGATAATTTTTTTGTCGTGTACAAAAACATTTTTCGTTCTATCATTTCC
>E_edulis_F7
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCTTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAA-G----ATCTTG
>E_edulis_R10
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTTTGGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAAG----ATCTTG
>E_edulis_R11
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTTTGGGGGTGTCATGTCAAAACAAAATAGKGTATGTGGTAAAGTAAAAAATAASTAACCTATTCCCTTTTTCAAAAAAAAAAG----ATCTTG
>E_edulis_R12
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTTTGGGGGWGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAAA----ATCTTG
>E_edulis_IFES
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGARCAAAGACTTTATTAGGTTGCTTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAA-G----ATCTTG
>E_oleracea_Ilha_do_combu_1
AAATCGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAGATCTTATCTTG
>E_oleracea_Ilha_do_combu_2
AAATCGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAGATCTTATCTTG
>E_oleracea_Ilha_do_combu_3
AAATCGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAGATCTTATCTTG
>E_oleracea_Ilha_do_combu_5
AAATCGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAGATCTTATCTTG
>E_oleracea_Ilha_do_combu_10
AAATCGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAGATCTTATCTTG
>E_oleracea_Mangal_2
AAATCGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAGATCTTATCTTG
>E_oleracea_Mangal_3
AAATCGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAGATCTTATCTTG
>E_oleracea_Docas_de_Belm
AAATCGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAGATCTTATCTTG
>E_oleracea_Utinga
AAATCGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAGATCTTATCTTG
>E_oleracea_Canto_de_Roa_1
AAATCGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAGATCTTATCTTG
>E_oleracea_Canto_de_Roa_2
AAATCGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAGATCTTATCTTG
>E_oleracea_Canto_de_Roa_3
AAATCGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAGATCTTATCTTG
>E_oleracea_IFES
AAATCGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAGATCTTATCTTG
换句话说，我想连接两个文件中的基因而不是打印并且不连接仅出现在一个文件中的物种。我不知道如何解决物种写得有一些小错误的问题。
编辑 1：
我改了代码，用Levenshtein ratio解决了一些种名写错的问题，结果还是一样。
新密码是：
import Levenshtein as lev
Str1 = str(ids)
Str2 = str(ids2)
Ratio = lev.ratio(Str1.lower(),Str2.lower())
for i, j, z, h in zip(ids, sequences, sequences2, ids2):
if lev.ratio(i,h) > 0.70 and i in h:
print(">"+i + "\n"+j+z)
else:
print(">"+i + "\n"+j)
编辑 2
Input File1: gene 1
>E_edulis_I1
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTTTGGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAAG----ATCTTG
>E_edulis_I2
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTTTGGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAAG----ATCTTG
>E_edulis_F7
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCTTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAA-G----ATCTTG
Input File 2: gene 2
>E_edulis_I1
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTTTGGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAAG----ATCTTG
>E_ed_I2
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTTTGGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAAG----ATCTTG
My desired output:
>E_edulis_I1
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTTTGGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAAG----ATCTTGAAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTTTGGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAAG----ATCTTG
>E_edulis_I2
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTTTGGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAAG----ATCTTGAAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTTTGGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAAG----ATCTTG
P.S。在第二个文件中，我有相同的物种 E_edulis_I2，但名称不完整 -> E_ed_I2。我希望脚本能够识别并将序列与第一个序列连接起来（文件 1 = E_edulis_I2）。另一个问题是 E_edulis_F7 specie 只出现在文件 1 中，所以我不想在我的输出中出现 thar specie。
这比我预期的要复杂一些。问题是，例如 "E_edulis_I1" 比 "E_ed_I" 更接近 "E_edulis_I2" 。我认为最好的解决方案是比较两个文件之间的每一对名称，并确定它们是否相似到可以称为匹配项。然后，一旦你有了这组匹配的名称和它们的相似度，你就可以按照最相似到最不相似的顺序检查它，并在你进行时将结果添加到组合的 FASTA 文件中。因此，由于两个文件之间 "E_edulis_I1" 完全匹配，因此将首先放入组合的 FASTA 中。然后当我们到达匹配名称 "E_edulis_I1" 和 "E_edulis_I2" 时，我们会看到我们已经使用了 "E_edulis_I1"，所以这对不能匹配。
这对我来说还是有点脆弱。你只需要注意你的相似函数和相似阈值是什么。您可能会添加的一件事是，只要完成匹配而相似度为 1，就打印出名字。这样，您可以快速扫描这些（希望没有太多）并确定是否匹配了任何不应该匹配的名字。没去过。
无论如何，这是代码。它至少适用于您提供的示例。
from pathlib import Path
from typing import Dict
import Levenshtein as lev
def fasta_to_dict(path: str) -> Dict[str, str]:
"""Read in a fasta file and return a dict mapping names to sequences."""
fasta = Path(path).read_text().split("\n")
return {fasta[i]: fasta[i + 1] for i in range(0, len(fasta) - 1, 2)}
# put in the paths to your fasta files here
fasta1 = fasta_to_dict("f1.fasta")
fasta2 = fasta_to_dict("f2.fasta")
def get_similarity(name1: str, name2: str) -> float:
"""Return a number describing how similar the names are."""
# this could be any string comparison function you want
return lev.ratio(name1, name2)
similarity_threshold = 0.7 # must be at least this similar to be called a match
def get_correct_name(name1: str, name2: str) -> str:
"""Determine which of 2 close-match names is the correct one."""
# this can also be whatever function makes sense in your application
# I'm just using the longer name as the "correct" one
return name1 if len(name1) > len(name2) else name2
possible_matches = []
for name1 in fasta1:
for name2 in fasta2:
similarity = get_similarity(name1, name2)
if similarity > similarity_threshold:
possible_matches.append((name1, name2, similarity))
# sort by most similar matches first
possible_matches = sorted(possible_matches, key=lambda match: -match[-1])
combined_fasta = {}
used_names1 = set()
used_names2 = set()
for name1, name2, _ in possible_matches:
if name1 in used_names1 or name2 in used_names2:
continue
correct_name = get_correct_name(name1, name2)
combined_fasta[correct_name] = fasta1[name1] + fasta2[name2]
used_names1.add(name1)
used_names2.add(name2)
# put the path to your output fasta file here
with open("combined.fasta", "w") as f:
for name, seq in combined_fasta.items():
f.write(name + "\n")
f.write(seq + "\n")
我有两个数据文件 (FASTA)，每个文件代表一个基因，序列按物种和本地标识。我想将这些文件连接成一个，例如：
psbki.fas:
>E_oleracea_Docas_de_Belm
AACCT
ycf1b.fas:
>E_oleracea_Docas_de_B
GGTTC
output:
>E_oleracea_Docas_de_Belm
AACCTGGTTC
如果您查看这两个文件中的物种名称，它们在编写时存在一些语法问题，使它们彼此不同。另外，我还有一个问题：有些物种不在两个文件中。
为了解决这些问题，我写了下面的代码：
ids, sequences = parse_fasta(open('psbki.fas', 'r').read().split('\n'))
ids2, sequences2 = parse_fasta(open('ycf1b.fas', 'r').read().split('\n'))
for i, j, z, h in zip(ids, sequences, sequences2, ids2):
if i != h:
print(">"+i + "\n"+j)
else:
print(">"+i + "\n"+j+z)
前两个序列的输出没问题。但是对于其他序列，代码只打印一个文件中的文件，但它们在两个文件中。 我的代码有什么问题？ 我是 python
的初学者输出是：
>E_edulis_I1
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTTTGGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAAG----ATCTTGAATTGGTATTATTCTCATTATCAGCATAAATTATCACACGTCTGGCTCTTCTTGAACGAATTTCAATATCTTCTATCGGTTTTTCCTCATTTTCTTCCTCCTGTTCTTCCAGAAGATTGGTCAATTTATATGACCATCGAGAAACCTTTTTACTGATTTCTTCTATTCCAATAGATTCATTTCTAGTTGTTTTATCATTTGGATCAATTGTCATTATATCGAATACAAATTTCAAAGATTTTGCTTGACTTTCTGAATCCATTTTTCTTTGTTCTGCCAATAAAGAACAGTTTTTCAAACAAAAATTGGGTGTGAATTCAAAAGAAAATGAAGTTAAGGAATTACCGATATAATTCAAAAATGATTTACCACCACCAAGTGAATTCTTTTGATGTTCAAATTCTCTGAAATTATTAGGAAGTAGCTCATGGATCTTATTTATCCAAAGACTTTTTATGGAATCCTCCATATAAGGGAAAAAATCATTTATGATTGTACGTAAATCAAAATCTTTTATTGCTCCACGGCATGGTCCGCTCAATAAAGGATCATATGTTTTGGTCAAGCATTTTTGTTTATTCTCATGATTGCAAAATCTAGTCTTTTTTTCGAGCATATCTAGAGCAAGAAATCCCTTTTCTTTTTTTTCTTTTTCTAGAGCTTTTATTCGACTTATTAATTCATTGCTCAAGTTGTATTTTTTTTGTTCATTGGTAAAAACCCAAAAATTATACAGGTCTCCATGGGATAATTTTTT-GTCGTGTACAAAAACATTTTTCGTTCTATCATTTCC
>E_edulis_I2
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTTTGGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAAG----ATCTTGAATTGGTATTATTCTCATTATCAGCATAAATTATCACACGTCTGGCTCTTCTTGAACGAATTTCAATATCTTCTATCGGTTTTTCCTCAATTTCTTCCTCCTGTTCTTCCAGAAGATTGGTCAATTTATATGACCATCGAGAAACCTTTTTACTGATTTCTTCTATTCCAATAGATTCATTTCTAGTTGTTTTATCATTTGGATCAATTGTCATTATATCGAATACAAATTTCAAAGATTTTGCTTGACTTTCTGAATCCATTTTTCTTTGTTCTGCCAATAAAGAACAGTTTTTCAAACAAAAATTGGGTGTGAATTCAAAAGAAAATGAAGTTAAGGAATTACCGATATAATTCAAAAATGATTTACCACCACCAAGTGAATTCTTTTGATGTTCAAATTCTCTGAAATTATTAGGAAGTAGCTCATGGATCTTATTTATCCAAAGACTTTTTATGGAATCCTCCATATAAGGGAAAAAATCATTTATGATTGTACGTAAATCAAAATCTTTTATTGCTCCACGGCATGGTCCGCTCAATAAAGGATCATATGTTTTGGTCAAGCATTTTTGTTTATTCTCATGATTGCAAAATCTAGTCTTTTTTTCGAGCATATCTAGAGCAAGAAATCCCTTTTCTTTTTTTTCTTTTTCTAGAGCTTTTATTCGACTTATTAATTCATTGCTCAAGTTGTATTTTTTTTGTTCATTGGTAAAAACCCAAAAATTATACAGGTCTCCATGGGATAATTTTTTTGTCGTGTACAAAAACATTTTTCGTTCTATCATTTCC
>E_edulis_F7
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCTTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAA-G----ATCTTG
>E_edulis_R10
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTTTGGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAAG----ATCTTG
>E_edulis_R11
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTTTGGGGGTGTCATGTCAAAACAAAATAGKGTATGTGGTAAAGTAAAAAATAASTAACCTATTCCCTTTTTCAAAAAAAAAAG----ATCTTG
>E_edulis_R12
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTTTGGGGGWGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAAA----ATCTTG
>E_edulis_IFES
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGARCAAAGACTTTATTAGGTTGCTTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAA-G----ATCTTG
>E_oleracea_Ilha_do_combu_1
AAATCGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAGATCTTATCTTG
>E_oleracea_Ilha_do_combu_2
AAATCGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAGATCTTATCTTG
>E_oleracea_Ilha_do_combu_3
AAATCGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAGATCTTATCTTG
>E_oleracea_Ilha_do_combu_5
AAATCGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAGATCTTATCTTG
>E_oleracea_Ilha_do_combu_10
AAATCGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAGATCTTATCTTG
>E_oleracea_Mangal_2
AAATCGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAGATCTTATCTTG
>E_oleracea_Mangal_3
AAATCGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAGATCTTATCTTG
>E_oleracea_Docas_de_Belm
AAATCGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAGATCTTATCTTG
>E_oleracea_Utinga
AAATCGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAGATCTTATCTTG
>E_oleracea_Canto_de_Roa_1
AAATCGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAGATCTTATCTTG
>E_oleracea_Canto_de_Roa_2
AAATCGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAGATCTTATCTTG
>E_oleracea_Canto_de_Roa_3
AAATCGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAGATCTTATCTTG
>E_oleracea_IFES
AAATCGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAGATCTTATCTTG
换句话说，我想连接两个文件中的基因而不是打印并且不连接仅出现在一个文件中的物种。我不知道如何解决物种写得有一些小错误的问题。
编辑 1： 我改了代码，用Levenshtein ratio解决了一些种名写错的问题，结果还是一样。
新密码是：
import Levenshtein as lev
Str1 = str(ids)
Str2 = str(ids2)
Ratio = lev.ratio(Str1.lower(),Str2.lower())
for i, j, z, h in zip(ids, sequences, sequences2, ids2):
if lev.ratio(i,h) > 0.70 and i in h:
print(">"+i + "\n"+j+z)
else:
print(">"+i + "\n"+j)
编辑 2
Input File1: gene 1
>E_edulis_I1
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTTTGGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAAG----ATCTTG
>E_edulis_I2
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTTTGGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAAG----ATCTTG
>E_edulis_F7
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCTTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTT-GGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAA-G----ATCTTG
Input File 2: gene 2
>E_edulis_I1
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTTTGGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAAG----ATCTTG
>E_ed_I2
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTTTGGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAAG----ATCTTG
My desired output:
>E_edulis_I1
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTTTGGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAAG----ATCTTGAAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTTTGGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAAG----ATCTTG
>E_edulis_I2
AAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTTTGGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAAG----ATCTTGAAATAGAAATTCTTGTATATTGAATAACCGCGGCGATGAATTTTGATCAACTTATTTCCTCGTTCTGACCTTACAGTGAGCAAAGACTTTATTAGGTTGCCTACAATACCTAATTATTCATATGACAAGAAATTTTTGATAACGAAGGAATCAAAATCTTATTCCAAAGAAATTCGTGAAAATGACTTTCTTTTCAAAAAACACTTCATTTTTTTTGGGGGTGTCATGTCAAAACAAAATAGTGTATGTGGTAAAGTAAAAAATAAGTAACCTATTCCCTTTTTCAAAAAAAAAAG----ATCTTG
P.S。在第二个文件中，我有相同的物种 E_edulis_I2，但名称不完整 -> E_ed_I2。我希望脚本能够识别并将序列与第一个序列连接起来（文件 1 = E_edulis_I2）。另一个问题是 E_edulis_F7 specie 只出现在文件 1 中，所以我不想在我的输出中出现 thar specie。
这比我预期的要复杂一些。问题是，例如 "E_edulis_I1" 比 "E_ed_I" 更接近 "E_edulis_I2" 。我认为最好的解决方案是比较两个文件之间的每一对名称，并确定它们是否相似到可以称为匹配项。然后，一旦你有了这组匹配的名称和它们的相似度，你就可以按照最相似到最不相似的顺序检查它，并在你进行时将结果添加到组合的 FASTA 文件中。因此，由于两个文件之间 "E_edulis_I1" 完全匹配，因此将首先放入组合的 FASTA 中。然后当我们到达匹配名称 "E_edulis_I1" 和 "E_edulis_I2" 时，我们会看到我们已经使用了 "E_edulis_I1"，所以这对不能匹配。
这对我来说还是有点脆弱。你只需要注意你的相似函数和相似阈值是什么。您可能会添加的一件事是，只要完成匹配而相似度为 1，就打印出名字。这样，您可以快速扫描这些（希望没有太多）并确定是否匹配了任何不应该匹配的名字。没去过。
无论如何，这是代码。它至少适用于您提供的示例。
from pathlib import Path
from typing import Dict
import Levenshtein as lev
def fasta_to_dict(path: str) -> Dict[str, str]:
"""Read in a fasta file and return a dict mapping names to sequences."""
fasta = Path(path).read_text().split("\n")
return {fasta[i]: fasta[i + 1] for i in range(0, len(fasta) - 1, 2)}
# put in the paths to your fasta files here
fasta1 = fasta_to_dict("f1.fasta")
fasta2 = fasta_to_dict("f2.fasta")
def get_similarity(name1: str, name2: str) -> float:
"""Return a number describing how similar the names are."""
# this could be any string comparison function you want
return lev.ratio(name1, name2)
similarity_threshold = 0.7 # must be at least this similar to be called a match
def get_correct_name(name1: str, name2: str) -> str:
"""Determine which of 2 close-match names is the correct one."""
# this can also be whatever function makes sense in your application
# I'm just using the longer name as the "correct" one
return name1 if len(name1) > len(name2) else name2
possible_matches = []
for name1 in fasta1:
for name2 in fasta2:
similarity = get_similarity(name1, name2)
if similarity > similarity_threshold:
possible_matches.append((name1, name2, similarity))
# sort by most similar matches first
possible_matches = sorted(possible_matches, key=lambda match: -match[-1])
combined_fasta = {}
used_names1 = set()
used_names2 = set()
for name1, name2, _ in possible_matches:
if name1 in used_names1 or name2 in used_names2:
continue
correct_name = get_correct_name(name1, name2)
combined_fasta[correct_name] = fasta1[name1] + fasta2[name2]
used_names1.add(name1)
used_names2.add(name2)
# put the path to your output fasta file here
with open("combined.fasta", "w") as f:
for name, seq in combined_fasta.items():
f.write(name + "\n")
f.write(seq + "\n")