GO术语的生物信息检索及与用户特定术语的比较

Question

我有以下函数(属于类)：

import Bio
from bioservices import KEGGParser, UniProt, QuickGO

def locate_common_GO(self,list_of_genes,GO_term):
    
    #initialize variables and classes
    q = QuickGO()
    a = Retrieve_Data()
    b=[]

    #get the uniprot IDS using hugo2uniprot. hugo2uniprot is a custom method of my Retrieve_Data class (which uses bioservices module) simply for getting a uniprot ID from a gene symbol. 
    for i in range(0,len(list_of_genes)):
        b.append(a.hugo2uniprot(list_of_genes[i],'hsa'))
        print 'Gene: {} \t UniProtID: {}'.format(list_of_genes[i],b[i])


    #search for GO terms and store as dictionary. Keys are the gene name and a list of GO terms are values. 
    GO_dict = {}
    for i in range(0,len(b)):
        q = QuickGO()
        GO_dict[list_of_genes[i]]= q.Annotation(protein=b[i], frmt="tsv", _with=True,tax=9606, source="UniProt", col="goName")
    keys = GO_dict.keys()

    #This bit should search the dictionary values for a term supplied by the user (stored in the variable 'GO_Term'). 
    #If the user supplied term is present in the retrieved list of GO terms I want it to add the dictionary key (i.e. the gene name) to a list named 'matches'. 
    matches = []
    for gene in range(0,len(keys)):
        if GO_term in GO_dict[keys[gene]].splitlines():
            matches.append(keys[i])
    return matches 

问题是，尽管提供了一个已知通用基因术语的基因列表，但该功能的输出始终是相同的基因名称。例如，'TGFB1'和'COL9A2'都有一个GO术语'proteinaceous extracellular matrix'，但是输出是list，['COL9A2','COL9A2']应该是['COL9A2','TGFB1']。有谁对如何修改这个程序有任何建议吗？我想我已经接近了，但我找不到解决办法。

Answer 1

您总是将keys[i]附加到matches，但是i在该循环中不会更改，所以您总是追加相同的项。您可能需要追加keys[gene]。