HeatmapCluster: Heatmap of cluster based on top cluster specific genes

In Fang0828/SCMarker: What the package does (short line)

Usage

HeatmapCluster(obj, top)

Arguments

obj	The list objective from the function getClusterGene
top	The number of gene which showed top cluster specificity

Examples

data(melanoma)
melanoma1=as.matrix(melanoma[,2:dim(melanoma)[2]])
row.names(melanoma1)=melanoma[,1]
res=ModalFilter(data=melanoma1,geneK=10,cellK=10)
res=GeneFilter(obj=res)
res=getMarker(obj=res,MNN=200,MNNIndex=20)
res=SCcluster(obj=res)
res=getClusterGene(obj=res,method="Seurat")
HeatmapCluster(obj=res,top=10)
## The function is currently defined as
HeatmapCluster<-function(obj,top,scale="none"){
    feature=obj$clustergene
    topmarker=as.data.frame(feature 
    topmarker=topmarker[order(topmarker$clusts),]
    method=obj$method
    if (method=="Seurat"){
        cluster=obj$seuratCluster
    }else if (method=="dbscan"){
        cluster=obj$dbscanCluster
    }
    clustertype=levels(factor(cluster))
    genemean=c()
    for (i in clustertype){
        cell=names(cluster[cluster==i])
        subdata=obj$rawdata[topmarker$gene,cell]
        genemean=cbind(genemean,apply(subdata,1,mean))
    }
    row.names(genemean)=topmarker$gene
    colnames(genemean)=clustertype
    
    mat_col <- data.frame(cluster=levels(factor(cluster)))
    row.names(mat_col) <- levels(factor(cluster))
    mat_colors <- list(cluster=rainbow(length(clustertype)))
    names(mat_colors$cluster)=levels(factor(cluster))
    pheatmap(genemean,cluster_cols = F,scale=scale,cluster_rows = F,show_colnames=F,annotation_col = mat_col,annotation_colors = mat_colors)
}


{ ~kwd1 }
{ ~kwd2 }

Fang0828/SCMarker documentation built on May 13, 2019, 12:51 p.m.