ggsave(gop, filename = "goplot.pdf", width=10, height=10) 4.3 barplot与dotplot——最常用的可视化图形 barplot与dotplot展示富集通路的p.adj,generatio,count信息。 如果enrichGO的ont为'ALL',barplot与dotplot还可以设置使不同ont项目通路分隔开展示 ### barplot barp <- barplot(go_enrich_results, f...
write.csv(summary(ego),"GO-enrich_p.adj0.05.csv",row.names=FALSE)##可视化--点图pdf("Enrichment-GO-bubble.pdf")dotplot(ego,title="Enrichment-GO")#点图,按富集的数从大到小的 dev.off()##可视化--条形图pdf("Enrichment-GO.pdf")barplot(ego,showCategory=20,title="Enrichment-GO")#条状图,...
##数据载入和目录设置setwd("C:/Users/Lenovo/Desktop/test")source('FUNCTIONS.R')load(file= '1.counts.Rdata')load(list.files(path= "./3.DEG",pattern = 'DEG_results.Rdata',full.names = T))dir.create("4.Enrichment_KEGG_GO")setwd("4.Enrichment_KEGG_GO") ### 筛选条件设置 ###log2...
The GOCircle plot emphasizes this fact. #Generate a circular visualization of the results of gene- annotation enrichment analysis GOCircle(circ) The outer circle shows a scatter plot for each term of the logFC of the assigned genes. Red circles display up- regulation and blue ones down- ...
p <- ggplot(dat,aes(y=Fold_Enrichment,x=Term,fill=PValue)) + geom_bar(stat="identity",position = "dodge") + facet_grid(Category~.,scales = "free",space = "free") + coord_flip() + theme_bw() + theme(plot.title = element_text(hjust = 0.5), ...
Enrichment Analysis Functional Interpretation Read More Evaluate Blast2GO within OmicsBox Selected publications featuring Blast2GO Blast2GO is used by more than hundred labs worldwide and has contributed to the many annotation efforts in genomics and transcriptomics studies covering taxa from microorganisms...
down_kegg<-kk_gse[kk_gse$pvalue<0.05& kk_gse$enrichmentScore <0,];down_kegg$group=-1up_kegg<-kk_gse[kk_gse$pvalue<0.05& kk_gse$enrichmentScore >0,];up_kegg$group=1g_kegg=kegg_plot(up_kegg,down_kegg) print(g_kegg) ggsave(g_kegg,filename ='kegg_up_down_gsea.png') ...
labs(title="Custom GO Enrichment Bubble Plot", x="GO Term", y="Gene Count") 总结和建议 在R语言中绘制GO图的步骤包括:1、安装和加载必要的包;2、准备数据;3、进行GO富集分析;4、使用enrichplot和ggplot2进行可视化。通过这些步骤,你可以生成各种形式的GO图来展示基因功能富集结果。为了更好的理解和应用...
指定为生物过程 pAdjustMethod = "BH", pvalueCutoff = 0.05, qvalueCutoff = 0.2) # 查看结果 print(go_bp_result) # 可视化结果 dotplot(go_bp_result, showCategory=20) + ggtitle("GO-BP Enrichment Dot Plot") barplot(go_bp_result, showCategory=20) + ggtitle("GO-BP Enrichment Bar Plot")...
富集图(Enrichment Map): emapplot(ego) 热图(Heatmap): heatplot(ego) 三、结果解释和展示 每种可视化方法都有其独特的优势和适用场景。以下是对几种常用方法的详细解释: 条形图(Bar Plot): 条形图展示了显著富集的GO条目及其富集分数。通过条形图,可以直观地看到哪些GO条目在基因列表中富集程度较高。以下是一...