normaliseOtherEnds: Normalise Other Ends
In Chicago: CHiCAGO: Capture Hi-C Analysis of Genomic Organization

Description Usage Arguments Details Value Warning Author(s) Examples

Compute s_i normalisation factors for other ends, and normalised counts.

1	normaliseOtherEnds(cd, Ncol = "NNb", normNcol = "NNboe", plot = TRUE, outfile = NULL)

`cd`	A `chicagoData` object.
`Ncol`	The name of an input column in `intData(cd)` that contains counts normalised by bait (i.e. it is output from `normaliseBaits`.
`normNcol`	The name of an output column that will contain counts normalised by other ends (in addition to any normalisation already performed on the `Ncol` column). Useful for plotting.
`plot`	If `TRUE`, output a diagnostic plot.
`outfile`	`NULL`, or a character string. If `NULL`, the diagnostic plot is outputted to the current plotting device. If a character string, e.g. `outfile="tech.pdf"`, then the plot will be outputted to that file.

A chicagoData object: intData(cd) gains new columns s_i, and normalised output NNboe (unless the normNcol parameter is altered).

An object of class chicagoData.

The object intData(cd) is updated by reference. Thus, intData(cd) will be altered. See vignette for further information.

Mikhail Spivakov, Jonathan Cairns, Paula Freire Pritchett

##FIXME: example can be run by loading data package if it is installed, once it exists

if("PCHiCdata" %in% rownames(installed.packages()))
{
  library(PCHiCdata)
  data(smESC)
  
  ##modifiy smESC to use correct design directory
  designDir <- file.path(system.file("extdata", package="PCHiCdata"), "mm9TestDesign")
  smESC <- modifySettings(cd=smESC, designDir=designDir)
  
  ##normalise here...
  normaliseOtherEnds(smESC)
  
} else {
  warning("Please install the PCHiCdata package to run this example.")
}