normalizeVmat {VplotR} | R Documentation

## A function to normalized a Vmat

### Description

This function normalizes a Vmat. Several different approaches have been implemented to normalize the Vmats.

### Usage

    normalizeVmat(
      Vmat,
      bam_granges,
      granges,
      normFun = c("zscore"),
      s = 0.99,
      roll = 1,
      verbose = TRUE
    )

### Arguments

`Vmat` | A Vmat, usually output of computeVmat
`bam_granges` | GRanges, the paired-end fragments
`granges` | GRanges, the regions to map the fragments onto
`normFun` | character. A Vmat should be scaled either by: 'libdepth+nloci', e.g. the library depth and the number of loci used to compute the Vmat; zscore, if relative patterns of fragment density are more important than density per se; Alternatively, the Vmat can be scaled to a chosen quantile ('quantile') or to the max Vmat value ('max').
`s` | A float indicating which quantile to use if 'quantile' normalization is chosen
`roll` | integer, to use as the window to smooth the Vmat rows by rolling mean.
`verbose` | Boolean

### Value

A normalized Vmat object

### Examples

    data(bam_test)
    data(ce11_all_REs)
    Vmat <- computeVmat(bam_test, ce11_all_REs)
    Vmat <- normalizeVmat(
        Vmat,
        bam_test,
        ce11_all_REs,
        normFun = c('libdepth+nloci')
    )

[Package VplotR version 1.0.0 Index]