読んだ BMC Bioinformatics. 2010 Jan 22;11:45.
NeatMap というパッケージで使える。
data(mtcars) # heatmap1 NeatMap::heatmap1(mtcars) # circularmap make.circularmap(as.matrix(mtcars), metric="euclidean", cluster.method="complete.linkage", normalize.profiles=FALSE) mtcars.nMDS <- nMDS(as.matrix(mtcars), metric="euclidean") mtcars.cluster <- hclust(dist(mtcars), method="complete") circularmap(mtcars.nMDS$x, as.matrix(mtcars), normalize.profiles=FALSE, cluster.result=mtcars.cluster) # lineplot mtcars.PCA <- prcomp(mtcars) lineplot(mtcars.PCA$x, mtcars) # draw.dendrogram3d mtcars.nMDS<-nMDS(mtcars, metric="euclidean") mtcars.cluster<-hclust(dist(mtcars), method="complete") draw.dendrogram3d(mtcars.cluster, mtcars.nMDS$x, labels=rownames(mtcars), label.size=0.5) # profileplot3d make.profileplot3d(mtcars, row.method="PCA", column.method="average.linkage") mtcars.PCA <- prcomp(mtcars) mtcars.col.cluster <- hclust(dist(t(mtcars)), method="average") mtcars.row.cluster <- hclust(as.dist(1-cor(t(mtcars))), method="average") profileplot3d(mtcars.PCA$x, mtcars, column.order=mtcars.col.cluster$order, row.cluster=mtcars.row.cluster, column.cluster=mtcars.col.cluster) # stereo.profileplot3d mtcars.PCA <- prcomp(mtcars) mtcars.col.cluster <- hclust(dist(t(mtcars)), method="average") mtcars.row.cluster <- hclust(as.dist(1-cor(t(mtcars))), method="average") stereo.profileplot3d(mtcars.PCA$x, mtcars, column.order=mtcars.col.cluster$order, row.cluster=mtcars.row.cluster, column.cluster=mtcars.col.cluster)
