hierClust

Description

This function computes the pairwise distance between samples and computes a hierarchical clustering that is further depicted as a heatmap graphic

Usage

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hierClust(data, side = "col", dist = "correlation", cor.type = "spearman",
  hclust.method = "ward", side.col.c = NULL, side.col.r = NULL,
  plot = TRUE)

Arguments

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 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

Details

hierClust

Value

it will return a list of three variables, the correlation matrix, the distance matrix and the hclust object

Note

updated hierClust functions by elechat april 7th 2015 added options SideColors added + spearman == pearson(rank)

Author(s)

Edi Prifti

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