counts.hc: Hierarchical clustering on an spectral counts matrix.

In msmsEDA: Exploratory Data Analysis of LC-MS/MS data by spectral counts

Description

Hierarchical clustering of samples in an spectral counts matrix, coloring tree branches according to factor levels.

Usage

counts.hc(msnset, do.plot=TRUE, facs=NULL, wait=TRUE)

Arguments

msnset	A MSnSet with spectral counts in the expression matrix.
do.plot	A logical indicating whether to plot the dendrograms.
facs	NULL, or a data frame with factors. See details below.
wait	This function may draw different plots, one by given factor in facs. When in interactive mode the default is to wait for confirmation before proceeding to the next plot. When wait is FALSE and R in interactive mode, instructs not to wait for confirmation.

Details

The hierarchical clustering is done by means of hclust with default parameters. If do.plot is TRUE, a dendrogram is plotted for each factor, with branches colored as per factor level. If facs is NULL then the factors are taken from pData(msnset).

Value

Invisibly returns the the value obtained from hclust.

Author(s)

Josep Gregori

See Also

MSnSet, hclust

Examples

data(msms.dataset)
msnset <- pp.msms.data(msms.dataset)
hc <- counts.hc(msnset)
str(hc)

msmsEDA documentation built on Nov. 8, 2020, 6:55 p.m.