NOISY_FUN {bayNorm} | R Documentation

## Noisy gene detection

### Description

This function detects noisy genes using trends observed in a set of synthetic controls. Input bayNorm normalized data of real data (`bay_array_N`) and synthetic control (`bay_array_C`) respectively.

### Usage

    NOISY_FUN(bay_array_N, bay_array_C, plot.out = FALSE)

### Arguments

`bay_array_N` | A 2D matrix or 3D array of normalized data(real cells).
`bay_array_C` | A 2D matrix or 3D array of normalized data(synthetic control).
`plot.out` | If TRUE, show CV^2 vs Mean expression plot. Default is FALSE.

### Details

`bay_array_N` and `bay_array_C` should be of the same dimension.

### Value

A vector of adjusted P-values.

### Examples

    bay_array_N<-array(rpois(1000*50*2,17),dim=c(1000,50,2))
    bay_array_C<-array(rpois(1000*50*2,58),dim=c(1000,50,2))
    noisy_output<-NOISY_FUN(bay_array_N,bay_array_C)

[Package bayNorm version 1.6.0 Index]