hierClust: hierClust

In eprifti/momr: Mining Metaomics Data (MetaOMineR)

hierClust

Description

This function computes the pairwise distance between samples and computes a hierarchical clustering that is further depicted as a heatmap graphic. The distance is computed as 1-correlation.

Usage

hierClust(
  data,
  side = "col",
  dist = "correlation",
  cor.type = "spearman",
  hclust.method = "ward.D",
  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.D method
side.col.c	: a vector of colors to be applied in the columns, usually depicting a class
side.col.r	: a vector of colors to be applied in the rows, usually depicting a class
plot	: logical default TRUE. It will plot the heatmap of the similarity with the hierarchical 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

eprifti/momr documentation built on Dec. 11, 2024, 3:06 p.m.