自定义富集分析结果的term顺序

大家好，元旦过得还好吗？之前我们聊过如果富集分析结果不理想，如何选择富集分析的terms，如果不记得，可以看看这三个推文和视频。

1. ?富集分析结果不理想：如何从上千个term中找到自己想要所有term？

2. 直播五：单细胞GO、KEGG富集分析

3. 手动选择富集分析结果，真的不合理吗？

• 今天我们聊聊富集分析的图如何美化

我们手动选择tems之后，画图如下

 ggplot(xx.all  %>%          dplyr::filter(stringr::str_detect(pattern = "apopto",Description))  %>%        #  dplyr::mutate(Description = factor(Description, levels = unique(.$Description))) %>%                    dplyr::filter(stringr::str_detect(negate = TRUE,pattern = "regulation of lymphocyte apop",Description) )  %>%                              group_by(Description) %>%          add_count()  %>%          dplyr::arrange(dplyr::desc(n),dplyr::desc(Description)) %>%          mutate(Description =forcats:: fct_inorder(Description))                , #fibri|matrix|colla        aes(Cluster, Description)) +   geom_point(aes(fill=p.adjust, size=Count), shape=21)+   theme_bw()+   theme(axis.text.x=element_text(angle=90,hjust = 1,vjust=0.5),         axis.text.y=element_text(size = 12),         axis.text = element_text(color = 'black', size = 12)   )+   scale_fill_gradient(low="red",high="blue")+   labs(x=NULL,y=NULL) # coord_flip()

美化富集分析结果

有人说这图不好看，有点乱。那我稍微更改一下，富集分析的结果会更好看点。主要是Description列变成因子就行啦，这样看上去确实清爽很多：

? ggplot(xx.all  %>%          dplyr::filter(stringr::str_detect(pattern = "apopto",Description))  %>%          dplyr::mutate(Description = factor(Description, levels = unique(.$Description))) %>%                    dplyr::filter(stringr::str_detect(negate = TRUE,pattern = "regulation of lymphocyte apop",Description) )  %>%                              group_by(Description) %>%          add_count()  %>%          dplyr::arrange(dplyr::desc(n),dplyr::desc(Description)) %>%          mutate(Description =forcats:: fct_inorder(Description))                , #fibri|matrix|colla        aes(Cluster, Description)) +   geom_point(aes(fill=p.adjust, size=Count), shape=21)+   theme_bw()+   theme(axis.text.x=element_text(angle=90,hjust = 1,vjust=0.5),         axis.text.y=element_text(size = 12),         axis.text = element_text(color = 'black', size = 12)   )+   scale_fill_gradient(low="red",high="blue")+   labs(x=NULL,y=NULL) # coord_flip()