学习一个R包——免疫浸润MCP-counter
save(results,file = 'MCPcounter.rdata') 导出的结果是以sample为colname(第一行),以细胞类型(8种免疫细胞和2种基质细胞)为rownames(第一列)的matrix。
学习一个R包——免疫浸润xCell MCP-counter(Microenvironment Cell Populations-counter)包由Becht团队于2016年开发,原文题目为:Estimating the population abundance of tissue-infiltrating immune and stromal cell populations using gene expression 这是个很常用的包,在我们公众号中多次提到,目前已经被引用200+次。 本...
学习一个R包——免疫浸润xCell MCP-counter(Microenvironment Cell Populations-counter)包由Becht团队于2016年开发,原文题目为:Estimating the population abundance of tissue-infiltrating immune and stromal cell populations using gene expression 这是个很常用的包,在我们公众号中多次提到,目前已经被引用200+次。 本...
To do so, open an R session and enter install.packages(c("devtools","curl")) ##Installs devtools and the MCPcounter dependancy 'curl' library(devtools) install_github("ebecht/MCPcounter",ref="master", subdir="Source") Examples on how to run the algorithm on your data are shown in...
load("TCGA-LIHC_sur_model.Rdata") head(exprSet)[1:4,1:4] # TCGA-FV-A495-01A TCGA-ED-A7PZ-01A TCGA-ED-A97K-01A TCGA-ED-A7PX-01A # WASH7P 1.913776 1.2986076 1.967382 1.586170 # AL627309.6 3.129116 0.5606928 3.831265 1.363539
conda install -c grst -c bioconda -c conda-forge r-immunedeconv condawill automatically install the package and all dependencies. You can then open anRinstance within the environment and use the package. We highly recommend usingconda, as it will avoid incompatibilities between different package...