R——PCA+correlation matrix library("FactoMineR","factoextra") library("ggplot2","tidyverse","corrplot") #加载5个包,如果没有,先使用语句 install.package("..."),然后运行library(“”) concentration4_pca<- read.table("clipboard", header = T) #用复制粘贴将数据赋值给concentration4_pca名称,会在...
其实correlation matrix就是数据两两比较,算出一个相关性数值,在根据数值的大小和正负方向来画热图,把数据可视化。 其实出了相关性结果数值,应该还有一个p-value的(即相关性结果数值随即得到的概率有多大),严谨一点的实验需要连同p-value一起考虑。接下来如果你想查看有多少是正相关,有多少是负相关的,可以用以下代码...
Interestingly, by comparing the results of corGSEA between BRCA1 and NQO1, we found differential enrichment of several pathways implicated in cancer progression, such as “Hallmark Epithelial Mesenchymal Transition” and “Reactome Extracellular Matrix Organization” (Fig.3c). This suggests the possibility...