normalizeCounts {epigraHMM} | R Documentation

## 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, pedrobaldoni@gmail.com

### 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)

[Package epigraHMM version 1.0.8 Index]