coef=2,adjust='BH')bp=function(g){library(ggpubr)df=data.frame(gene=g,stage=group_list)p<-ggboxplot(df,x="stage",y="gene",color="stage",palette="jco",add="jitter")# Add p-valuep+stat_compare_means()}deg=topTable(fit,coef=2,adjust='BH',number=Inf)head...
geneList <- DEG_up$logFC ## 2.命名 names(geneList) = DEG_up$ENTREZID ## 3.排序很重要 geneList = sort(geneList, decreasing = TRUE) head(geneList) cnetplot(enrichKK, categorySize="pvalue", foldChange=geneList,colorEdge = TRUE) cnetplot(enrichKK, foldChange=geneList, circular = TRUE...
coef=2,adjust='BH')bp=function(g){library(ggpubr)df=data.frame(gene=g,stage=group_list)p<-ggboxplot(df,x="stage",y="gene",color="stage",palette="jco",add="jitter")# Add p-value
The coefficient of variation (CV) was defined as the ratio of the standard deviation to the mean expression of each gene across replicate samples within each of the 20 PDX models. The median CV, as well as the interquartile range, were documented for each PDX model. Intraclass correlation co...
scale_size(range=c(2,12))+ scale_x_discrete(labels=function(ego_bp)str_wrap(ego_bp,width =25)) ggsave("ego_bp_up_barplot.png") ego_up_goplot.png ego_up_barplot.png 同样的方式看看下调基因的GO_BP: down_regulated_genes.png 和文献中的GO_BP比较一下©...
根据原文文献中:Differential gene expression was defined if the fold change >1.5 and P < 0.05 between tumor and normal samples找差异基因 ## 不同的阈值,筛选到的差异基因数量就不一样,后面的超几何分布检验结果就大相径庭。 if(T){ logFC_t=1.5 ...