根据数据帧切换 fasta seq

Question

我实际上有 2 个名为：

的 fasta 文件

result1_aa.fasta
result2_aa.fasta

在这些文件中，我有这样的序列：

文件result1_aa.fasta:

>gene1_B
ATTGGACCA
>gene2_A
ATTAGGAC
>gene90_B
ATTAGCCACA
>gene65_B
ATTGAG

文件result2_aa.fasta:

>gene78_A
ATTGGACCA
>gene45_B
ATTAGGAC
>gene93_B
ATTAGCCACA
>gene54_A
ATTGACA

我有一个这样的数据框：

geneA      geneB
gene78_A   gene1_B
gene2_A    gene45_B
gene90_A   gene93_B
gene54_A   gene65_B

它们实际上是有序的（参见 _number）我想要的是获得 2 个新的 fasta 文件，其顺序与上面的数据框相同，这里是：

文件result1_aa_new.fasta:

>gene78_A
ATTGGACCA
>gene2_A
ATTAGGAC
>gene90_A
ATTAGCCACA
>gene54_A
ATTGACA

文件result2_new_aa.fasta:

>gene1_B
ATTGGACCA
>gene45_B
ATTAGGAC
>gene93_B
ATTAGCCACA
>gene65_B
ATTGAG

我尝试了一些解决方案，但我无法将顺序作为数据框保存在我的 fasta 文件中...

用阿美的解决方法：

    from Bio import SeqIO
    import sys
    from Bio.SeqRecord import SeqRecord
    import pandas as pd

    seq_0042_aa=open("seq_0042_aa.fasta","w")
    seq_0042_dna=open("seq_0042_dna.fasta","w")
    seq_0035_aa=open("seq_0035_aa.fasta","w")
    seq_0035_dna=open("seq_0035_dna.fasta","w")

    dN_dS_sorted=pd.read_table("dn_ds.out_sorted",sep='\t')

    seq1_id=dN_dS_sorted["seq1_id"] #first row
    seq2_id=dN_dS_sorted["seq2_id"] #second row


    from Bio import SeqIO
    results1 = list(SeqIO.parse("result1_aa.fasta", "fasta"))
    results1 = pd.DataFrame({'f_id': [r.id for r in results1], 'f_seq': results1})

    results1 = pd.merge(dN_dS_sorted, results1, left_on="seq1_id", right_on='f_id', how='left').dropna()
    results1 = list(results1.f_seq.values)

    with open("out.fasta", "w") as output_handle:
        SeqIO.write(results1, output_handle, "fasta")

    results2 = list(SeqIO.parse("result2_aa.fasta", "fasta"))
    results2 = pd.DataFrame({'f_id': [r.id for r in results2], 'f_seq': results2})

    results2 = pd.merge(dN_dS_sorted, results2, left_on="seq2_id", right_on='f_id', how='left').dropna()
    results2 = list(results2.f_seq.values)

    with open("out2.fasta", "w") as output_handle:
        SeqIO.write(results2, output_handle, "fasta")

这是我的数据框的头部：

seq1_id             seq2_id              dN               dS
g66097.t1_0035_0035 g13600.t1_0042_0042 0.10455938989199982 0.3122332927029104
g45594.t1_0035_0035 g1464.t1_0042_0042  0.5208761055250978  5.430485421797574
g50055.t1_0035_0035 g34744.t1_0042_0035 0.08040473491714645 0.4233916132491867
g34020.t1_0035_0035 g12096.t1_0042_0042 0.4385191689737516  26.834927363887587
g28436.t1_0035_0042 g35222.t1_0042_0035 0.055299811368483165    0.1181241496387666

然后，在输出中我应该得到：

输出1：

>g66097.t1_0035_0035
ATTGGAGATA
>g45594.t1_0035_0035    
TAGGAGGAGA
>g34020.t1_0035_0035
ATGGGAT
>g28436.t1_0035_0042
ATTGGAGA

和输出2：

>g13600.t1_0042_0042    
ATGGGAGAGA
>g1464.t1_0042_0042 
ATGGAGGAGA
>g12096.t1_0042_0042    
ATGGAGGAA
>g35222.t1_0042_0035
ATGGAGAG

但我实际上得到：输出 1：

>g28436.t1_0035_0042
ATGAGAGAGA
>g1005.t1_0035_0035
ATAGGAGATA
>g28456.t1_0035_0035
ATGGAGATA
>g30148.t1_0035_0042
ATGGAGA

和输出2：

>g35222.t1_0042_0035
ATAGGAGA
>g11524.t1_0042_0042
ATAGGAGA
>g31669.t1_0042_0035
ATGAGAGA
>g37790.t1_0042_0035
ATGAGGAGA

这是 fastafile1 的头部：

>g13600.t1_0042_0042
AGATAGAGA
>g1464.t1_0042_0042
AGATTAGA
>g34744.t1_0042_0035
ATAGAGGA
>g12096.t1_0042_0042
AGATATGA

这里是 fastafile2 的头部：

>g66097.t1_0035_0035
AGATTAGAGA
>g45594.t1_0035_0035
AGTATAGAGA
>g50055.t1_0035_0035
ATAGGAGAGA
>g34020.t1_0035_0035
ATAGGAGAG

Answer 1

让我们做第一个文件。再次使用 BioPython、

from Bio import SeqIO
results1 = list(SeqIO.parse("result1_aa.fasta", "fasta"))
results1 = pd.DataFrame({'f_id': [r.id for r in results1], 'f_seq': results1})

现在合并它们：

results1 = pd.merge(df, results1, left_on='results_on', right_on='id', how='left').dropna()

（假设列名是 results_on - 你没有指定它。

现在获取排序的记录：

results1 = list(results1.f_seq.values)

写出来：

with open("out.fasta", "w") as output_handle:
    SeqIO.write(results1, output_handle, "fasta")

根据数据帧切换 fasta seq

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