normalizeCounts: Normalize counts

In plbaldoni/epigraHMM: Epigenomic R-based analysis with hidden Markov models

Normalize counts

Description

This function performs a non-linear normalization of counts with respect to a reference sample (geometric mean)

Usage

normalizeCounts(object, control, span = 1, ...)

Arguments

object	an epigraHMMDataSet
control	list of control arguments from controlEM()
span	the span parameter of loessFit (default is 1)
...	arguments to be passed to loessFit for loess calculation

Details

This function 'limma::loessFit', which simply a wrapper for the 'stats::lowess' smoother.

Value

An epigraHMMDataSet with an 'offsets' assay filled in.

Author(s)

Pedro L. Baldoni, [e-mail]

References

https://github.com/plbaldoni/epigraHMM

Examples

# Creating dummy object
countData <- list('counts' = matrix(rpois(1e5,10),ncol = 2),
'controls' = matrix(rpois(1e5,5),ncol = 2))
colData <- data.frame(condition = c('A','A'), replicate = c(1,2))
object <- epigraHMMDataSetFromMatrix(countData,colData)

# Normalizing counts
object <- normalizeCounts(object = object,control = controlEM(), span = 1)

plbaldoni/epigraHMM documentation built on Oct. 15, 2023, 7:53 p.m.