DaMiR.Clustplot: Expression data clustering and heatmap

In BioinfoMonzino/DaMiRseq: Data Mining for RNA-seq data: normalization, feature selection and classification

Description

The function helps to draw a clustering dendrogram and a heatmap of expression data.

Usage

DaMiR.Clustplot(
  data,
  df,
  type_row = c("euclidean", "correlation"),
  type_col = c("euclidean", "correlation")
)

Arguments

data	A SummarizedExperiment object or a matrix or a data.frame where rows and cols should be, respectively, observations and features
df	A data frame with class and (optionally) known variables; at least one column with 'class' label must be included
type_row	The metric to be used to cluster rows. Either "euclidean" or "correlation" is allowed; default is "euclidean"
type_col	The metric to be used to cluster cols. Either "euclidean" or "correlation" is allowed; default is "euclidean"

Value

A clustering dendrogram and heatmap.

Author(s)

Mattia Chiesa, Luca Piacentini

Examples

# use example data:
data(data_norm)
data(df)
# use the first 100 genes:
data_norm_red<-data_norm[1:100,]
# Draw heatmap: samples (cols) per genes (rows)
# and use variable annotation:
DaMiR.Clustplot(data=data_norm_red,
df=df, type_row="correlation", type_col="correlation")

BioinfoMonzino/DaMiRseq documentation built on Aug. 22, 2021, 3:11 p.m.