MCPcounter返回的分数以任意单位表示。这些分数与样本中估计的细胞数量成比例。每个种群具有不同的任意单位。因此，它不能用来比较一个样本中不同种群的丰度。然而，这些分数允许比较队列中样本之间单个细胞群体的丰度。这与其他去卷积方法（如CIBERSORT）是一个根本性的区别，这些方法估计了整体免疫浸润中的相对成分，因此允许在样本内的群体之间进行比较，但不能在样本之间进行比较。

####MCPcounter ######## 下载超时，安装不成功
#利用devtools包的install_github函数进行安装
# install.packages(c('devtools','curl'))
# library(curl)
# library(devtools)
# install_github("ebecht/MCPcounter",ref="master", subdir="Source")
# library(MCPcounter)############# 直接拷贝R脚本文件########################## Rd
## description >> Takes as input an expression matrix and a list of marker features and return summarized expression values
## argument
## item >> xp >> An expression matrix with features in rows and samples in columns
## item >> markers >> a list whose names are cellular populations' names and elements are character vectors of features
## value >> matrix with the summarized expression of each marker features sets in rows
## author >> Etienne Becht
## keyword >> methods
## endappendSignatures=function(xp,markers){res=as.data.frame(do.call(cbind,lapply(markers,function(x){apply(xp[intersect(row.names(xp),x),,drop=F],2,mean,na.rm=T)})))res
}## Rd
## description >> this function produces a matrix with abundance estimates from an expression matrix
## argument
## item >> expression >> matrix or data.frame with features in rows and samples in columns
## item >> featuresType >> type of identifiers for expression features. Defaults to "affy133P2_probesets" for Affymetrix Human Genome 133 Plus 2.0 probesets. Other options are "HUGO_symbols" (Official gene symbols), "ENTREZ_ID" (Entrez Gene ID) or "ENSEMBL_ID" (ENSEMBL Gene ID)
## value >> matrix with cell populations in rows and samples in columns
## author >> Etienne Becht
## keyword >> methods
## examples >> ExampleEstimates=MCPcounter.estimate(MCPcounterExampleData,featuresType="affy133P2_probesets")
## examples >> heatmap(as.matrix(ExampleEstimates),col=colorRampPalette(c("blue","white","red"))(100))
## endMCPcounter.estimate=function(expression,featuresType=c("affy133P2_probesets","HUGO_symbols","ENTREZ_ID","ENSEMBL_ID")[1],probesets=read.table(curl:::curl("https://raw.githubusercontent.com/ebecht/MCPcounter/master/Signatures/probesets.txt"),sep="\t",stringsAsFactors=FALSE,colClasses="character"),genes=read.table(curl:::curl("https://raw.githubusercontent.com/ebecht/MCPcounter/master/Signatures/genes.txt"),sep="\t",stringsAsFactors=FALSE,header=TRUE,colClasses="character",check.names=FALSE)
){## marker.names=c("T cells","CD8 T cells","Cytotoxic lymphocytes","NK cells","B lineage","Monocytic lineage","Myeloid dendritic cells","Neutrophils","Endothelial cells","Fibroblasts")if(featuresType=="affy133P2_probesets"){features=probesetsmarkers.names = unique(features[, 2])features=split(features[,1],features[,2])features=lapply(features,intersect,x=rownames(expression))features=features[sapply(features,function(x)length(x)>0)]missing.populations=setdiff(markers.names,names(features))features=features[intersect(markers.names,names(features))]} else {markersG=genes}if(featuresType=="HUGO_symbols"){features=subset(markersG,get("HUGO symbols")%in%rownames(expression))markers.names = unique(features[, "Cell population"])features=split(features[,"HUGO symbols"],features[,"Cell population"])missing.populations=setdiff(markers.names,names(features))features=features[intersect(markers.names,names(features))]}if(featuresType=="ENTREZ_ID"){features=subset(markersG,ENTREZID%in%rownames(expression))markers.names = unique(features[, "Cell population"])features=split(features[,"ENTREZID"],features[,"Cell population"])missing.populations=setdiff(markers.names,names(features))features=features[intersect(markers.names,names(features))]}if(featuresType=="ENSEMBL_ID"){features=subset(markersG,get("ENSEMBL ID")%in%rownames(expression))markers.names = unique(features[, "Cell population"])features=split(features[,"ENSEMBL ID"],features[,"Cell population"])missing.populations=setdiff(markers.names,names(features))features=features[intersect(markers.names,names(features))]}if(length(missing.populations)>0){warning(paste("Found no markers for population(s):",paste(missing.populations,collapse=", ")))}t(appendSignatures(expression,features))
}## Rd
## description >> this function returns a matrix whose elements are p-value corresponding to the null hypothesis that samples are not infiltrated by the corresponding cell population.
## argument
## item >> MCPcounterMatrix >> A matrix, usually a return from the MCPcounter.estimate method
## item >> platform >> Expression platform used to produce the data. Supported are "133P2" (Affymetrix Human Genome 133 Plus 2.0), "133A" (Affymetrix Human Genome 133A), "HG1" (Affymetrix Human Gene 1.0ST). Other platforms are not supported. Data should ideally be log2-transformed and normalized with the fRMA bioconductor package. MCP-counter estimates from Affymetrix Human Genome 133 Plus 2.0 and 133A arrays should be computed using "affy_133P2_probesets" as identifiers, and "HUGO_symbols" or "ENTREZ_ID" for Affymetrix Human Gene 1.0ST.
## value >> matrix with samples in rows and cell populations in columns. Elements are p-values
## author >> Etienne Becht
## keyword >> methods
## endtest_for_infiltration=function(MCPcounterMatrix,platform=c("133P2","133A","HG1")[1]){MCPcounterMatrix=t(MCPcounterMatrix)params=null_models[grep(platform,colnames(null_models))]rownames(params)=null_models[,"Cell.population"]colnames(params)=sub(platform,"",colnames(params),fixed=T)res=sapply(colnames(MCPcounterMatrix),function(x){pnorm(MCPcounterMatrix[,x],mean=params[x,"mu."],sd=params[x,"sigma."],lower.tail=F)})rownames(res)=rownames(MCPcounterMatrix)res
}############# 直接拷贝R脚本文件########################setwd("/Users/zhengxueming/scripts/R_scripts")
genes <- data.table::fread("/Users/zhengxueming/software/MCPcounter-master/Signatures/genes.txt",data.table = F)
genes[1:5,]probesets <- data.table::fread("/Users/zhengxueming/software/MCPcounter-master/Signatures/probesets.txt",data.table = F,header = F)
probesets[1:5,]# 准备基因表达数据rna_seq数据
# 行名为HUGO_symbols，ENTREZ_ID或 ENSEMBL_ID
exprs_df <- read.delim("/Users/zhengxueming/test/test_mRNA_exprs.tsv", header=T, sep="\t", check.names=F,row.names = 1)
exprs_df[1:3,1:5]library(stringr)
# ENSG00000242268.2 =》ENSG00000242268
names_short <- word(rownames(exprs_df),1,sep=fixed("."))  # 提取点号前面的部分
rownames(exprs_df) <- names_short
dim(exprs_df)
results<- MCPcounter.estimate(exprs_df,featuresType= "ENSEMBL_ID", probesets=probesets,genes=genes)class(results) # [1] "matrix" "array"
results # 行为十种细胞类型，列为样本
dim(results)
rownames(results)
colnames(results)
results[1:3,1:5]

参考：

http://134.157.229.105:3838/webMCP/

https://github.com/ebecht/MCPcounter

https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-1070-5