HeatmapCell: Heatmap of single cell based on top cluster specific genes

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

Usage

HeatmapCell(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")
HeatmapCell(obj=res,10)
## The function is currently defined as
function (obj, top) 
{
    feature = obj$clustergene
    topmarker = as.data.frame(feature %>% group_by(clusts) %>% 
        top_n(top, auroc))
    topmarker = topmarker[order(topmarker$clusts), ]
    method = obj$method
    if (method == "Seurat") {
        cluster = obj$seuratCluster
        cluster = cluster[order(cluster)]
    }
    else if (method == "dbscan") {
        cluster = obj$dbscanCluster
        cluster = cluster[order(cluster)]
    }
    clustertype = unique(cluster)
    data = obj$rawdata[topmarker$gene, names(cluster)]
    clustercount = table(cluster)
    gapIndex = c()
    for (i in 2:(length(clustertype) - 1)) {
        gapIndex = c(gapIndex, sum(clustercount[1:i]))
    }
    pheatmap(data, cluster_cols = F, cluster_rows = F, show_colnames = F, 
        gaps_col = gapIndex)
  }

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