使用Biopython从gff文件提取gene的位置以及gene的id，再从fna文件提取gene序列

需要注意的是 Biopython存储到parse里面的并不是和文件的 染色体的顺序一致，在这里对字典嵌套列表，保存基因的位置以及其他信息，biopython读取的序列切片是从0开始的，这里它读取的基因的位置整体偏移1位

头部几个和NcBI里面的对比一下

对比一下尾部几个碱基

from Bio import SeqIO
from BCBio import GFF
import re

def get_geneLocation_geneId(in_file,gene_len):
    """
        本函数主要应用于从gff文件提取gene的location以及gene的id
        in_file 为 输入的 gff文件
        gene_len 为 需要提取的基因长度
    """
    in_handle = open(in_file)
    gene_information =dict()
    for rec in GFF.parse(in_handle):
        j=0
        i=0
        while j<len(rec.features):
            if rec.features[j].type=='region':
                tem = str(rec.features[j].id.split(':')[0])
                gene_information[tem]=[]
            if rec.features[j].type=='gene':               
                gene_location_t=[int(s) for s in re.findall(r'-?\d+\.?\d*', str(rec.features[j].location))]
                if gene_location_t[1]-gene_location_t[0] < gene_len :
                    gene_information[tem].append([gene_location_t[0],gene_location_t[1],\
                                                 str(rec.features[j].qualifiers['ID']),\
                                             str(rec.features[j].qualifiers['gene_biotype']),\
                                             str(rec.features[j].location)])
                    i+=1
            j+=1
    in_handle.close()
    return gene_information

def get_gene_gff_fna(file_path_gff,file_path_fna,save_path='./',gene_len=10000):#"GCF_904848185.1_fAcaLat1.1_genomic.gbff"
    '''
        本函数主要是用来从fna文件里面提取gene序列的
    '''
    return_gene=[]
    gene_information= get_geneLocation_geneId(file_path_gff,gene_len)
    with open(save_path+'.fasta','w',encoding='utf-8') as f:
        for seq_record in SeqIO.parse(file_path_fna, "fasta"):
            tem = str(seq_record.description.split()[0])
            for j in range(len(gene_information[tem])):
                return_gene.append(str(seq_record.seq[gene_information[tem][j]

下面的代码是添加的文件操作，把提取到的gene保存到*.fasta文件里面，，，具体的保存格式上图对比图有

from Bio import SeqIO
from BCBio import GFF
import re
import os
def get_geneLocation_geneId(in_file,gene_len):
    """
        本函数主要应用于从gff文件提取gene的location以及gene的id
        in_file 为 输入的 gff文件
        gene_len 为 需要提取的基因长度
    """
    in_handle = open(in_file)
    gene_information =dict()
    for rec in GFF.parse(in_handle):
        j=0
        i=0
        while j<len(rec.features):
            if rec.features[j].type=='region':
                tem = str(rec.features[j].id.split(':')[0])
                gene_information[tem]=[]
            if rec.features[j].type=='gene':               
                gene_location_t=[int(s) for s in re.findall(r'-?\d+\.?\d*', str(rec.features[j].location))]
                if gene_location_t[1]-gene_location_t[0] < gene_len :
                    gene_information[tem].append([gene_location_t[0],gene_location_t[1],\
                                                 str(rec.features[j].qualifiers['ID']),\
                                             str(rec.features[j].qualifiers['gene_biotype']),\
                                             str(rec.features[j].location)])
                    i+=1
            j+=1
    in_handle.close()
    return gene_information

def get_gene_gff_fna(file_path_gff,file_path_fna,save_path='./',gene_len=10000):#"GCF_904848185.1_fAcaLat1.1_genomic.gbff"
    '''
        本函数主要是用来从fna文件里面提取gene序列的
    '''
    return_gene=[]
    gene_information= get_geneLocation_geneId(file_path_gff,gene_len)
    i=0
    with open(save_path+'.fasta','w',encoding='utf-8') as f:
        c=0
        ge=0
        for seq_record in SeqIO.parse(file_path_fna, "fasta"):
            tem = str(seq_record.description.split()[0])
            for j in range(len(gene_information[tem])):
                f.write('>')
                f.write(seq_record.description.split()[0])
                f.write(' ')
                f.write(str(seq_record.description.split()[1]))
                f.write(' ')
                f.write(str(seq_record.description.split()[2]))
                f.write(' ')
                f.write('chr')
                for aa in seq_record.description.split()[5:-4]:
                    f.write(str(aa))
                    f.write(' ')
                f.write(gene_information[tem][j][2])
                f.write(' ')
                f.write(gene_information[tem][j][3])
                f.write(' ')
                f.write(gene_information[tem][j][4])
                f.write('\n')
                return_gene.append(str(seq_record.seq[gene_information[tem][j][0]:gene_information[tem][j][1]]))
                n=0
                for m in return_gene[-1]:
                    if n<80:
                        f.write(m)
                        n+=1
                    else:
                        f.write('\n')
                        n=0
                f.write('\n')
                c+=1
            print(c)
            i+=1
    print('extra gene over')
    return return_gene,gene_information