如何从topgo中从r？

Question

我如何检索R中的GO富集分析结果中提到的重要基因？我使用TopGo软件包运行以下内容：

library("topGO")  
#list with transcripts ID and one or more associated GO terms    
contig2GO=readMappings(file="C:/Users/Documents/transcripts_topGO.txt")
str(head(contig2GO))
names_contig=names(contig2GO)
        
my_list <- factor(as.integer(names_contig %in% list_of_interest$id))
names(my_list)=names_contig
GOdata_BP = new("topGOdata",ontology="BP",allGenes = my_list,annot=annFUN.gene2GO,gene2GO=contig2GO)
> GOdata_BP

------------------------- topGOdata object -------------------------
    
Description:
   -   
    
 Ontology:
   -  BP 
    
 12532 available genes (all genes from the array):
   - symbol:  tr1 tr2 tr3  ...
   - 73  significant genes. 
    
 5255 feasible genes (genes that can be used in the analysis):
   - symbol:  tr1 tr2 tr3  ...
   - 38  significant genes. 

 GO graph (nodes with at least  1  genes):
   - a graph with directed edges
   - number of nodes = 2340 
   - number of edges = 4702 
    
------------------------- topGOdata object -------------------------

resultsFisher_BP=runTest(GOdata_BP,algorithm = "classic",statistic = "fisher")
> print(resultsFisher_BP)

Description:  
Ontology: BP 
'classic' algorithm with the 'fisher' test
2340 GO terms scored: 35 terms with p < 0.01
Annotation data:
    Annotated genes: 5255 
    Significant genes: 38 
    Min. no. of genes annotated to a GO: 1 
    Nontrivial nodes: 228

topGO_results_BP <- GenTable(GOdata_BP, classicFisher = resultsFisher_BP, topNodes = 100)

因此，我有35个与p

my_list <- factor(as.integer(names_contig %in% list_of_interest$id))< 0.01. Now I want to find which are the genes in

相关的术语。
有没有直接的方法来获取它们？

现在，我对此进行了交叉的态度：

topGO_results_BP$classicFisher <- as.numeric(topGO_results_BP$classicFisher)
topGO_results_BP$classicFisher <- round(topGO_results_BP$classicFisher,10)
significant_GO_BP <- topGO_results_BP %>% filter(classicFisher < 0.01)

list_of_interest_filt <- list_of_interest %>% filter(!is.na(GO)) %>% mutate(GO_list = str_split(GO, ",")) %>% filter(
                                  sapply(GO_list, function(go_terms) any(go_terms %in% significant_GO_BP$GO.ID))) %>% dplyr::select(-GO_list) 

是间接的。我想知道是否有一些事情可以更好地做这项工作？

我知道我提供了代码，而不是可重复的示例。 Transcripts_topgo就像：

genesInTerm

和list_of_interest是一个较大的数据框架，但其中包含Transcripts_topgo的子集，带有成绩单名称和关联的go。

是的，有一种更直接的方法可以使用GenesInterm（）提取与富集的GO术语相关的重要基因。此功能使您可以检索映射到topgodata对象中特定go术语的基因。
try：

> set.seed(42)
> transcripts <- paste0("tr", 1:10)
> go_terms <- c("GO:0005515", "GO:0007616", "GO:0016021", "GO:0043226", "GO:46872")
> go_column <- sapply(1:10, function(x) paste(sample(go_terms, sample(1:4, 1), replace = TRUE), collapse = ","))
> transcripts_topGO <- data.frame(Sample = samples, GO = go_column, stringsAsFactors = FALSE)
> transcripts_topGO
   transcripts                                   GO
    1     tr1                              GO:46872
    2     tr2                            GO:0005515
    3     tr3                 GO:0043226,GO:0007616
    4     tr4                 GO:0005515,GO:0043226
    5     tr5                              GO:46872
    6     tr6                 GO:0043226,GO:0007616
    7     tr7                 GO:0016021,GO:0005515
    8     tr8                            GO:0016021
    9     tr9 GO:46872,GO:46872,GO:46872,GO:0043226
    10   tr10                 GO:0043226,GO:0016021

Answer 1

这种方法避免手动交叉镜头，并直接从topgodata中提取相关数据。

说实话，我不是Go术语的忠实拥护者。他们太简单了。他们通常不会告诉我们我们不知道的任何事情。