hierClust | R Documentation |
This function computes the pairwise distance between samples and computes a hierarchical clustering that is further depicted as a heatmap graphic
hierClust( data, side = "col", dist = "correlation", cor.type = "spearman", hclust.method = "ward.D", side.col.c = NULL, side.col.r = NULL, plot = TRUE )
data |
: frequency matrix with gene_ids in the rownames |
side |
: the distance can be performed on the columns or on the rows |
dist |
: the type of distance used. By default this is correlation based similarity |
cor.type |
: when correlation matrix, the default is spearman |
hclust.method |
: the hierarchical clustering method, by default it is the ward.D method |
side.col.c |
: a vector of colors to be applied in the columns, usually depincting a class |
side.col.r |
: a vector of colors to be applied in the rows, usually depincting a class |
plot |
: logical default TRUE. It will plot the heatmap of the similarity with the hierchical clustering |
hierClust
it will return a list of three variables, the correlation matrix, the distance matrix and the hclust object
updated hierClust functions by elechat april 7th 2015 added options SideColors added + spearman == pearson(rank)
Edi Prifti
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