hierClust: hierClust

In momr: Mining Metaomics Data (MetaOMineR)

Description

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

Usage

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

momr documentation built on May 2, 2019, 4:21 a.m.