NormalizeBeta {MAGeCKFlute} | R Documentation

## Normalize gene beta scores

### Description

Two normalization methods are available. `cell_cycle` method normalizes gene beta scores based on positive control genes in CRISPR screening. `loess` method normalizes gene beta scores using loess.

### Usage

    NormalizeBeta(
      beta,
      id = 1,
      method = "cell_cycle",
      posControl = NULL,
      samples = NULL
    )

### Arguments

`beta` | Data frame.
`id` | An integer specifying the column of gene.
`method` | Character, one of 'cell_cycle'(default) and 'loess'. or character string giving the name of the table column containing the gene names.
`posControl` | A character vector, specifying a list of positive control genes.
`samples` | Character vector, specifying the sample names in beta columns. If NULL (default), take all beta columns as samples.

### Details

In CRISPR screens, cells treated with different conditions (e.g., with or without drug) may have different proliferation rates. So it's necessary to normalize the proliferation rate based on defined positive control genes among samples. After normalization, the beta scores are comparable across samples. `loess` is another optional normalization method, which is used to normalize array data before.

### Value

A data frame with same format as input data beta.

### Author(s)

Wubing Zhang

### Examples

    file3 = file.path(system.file("extdata", package = "MAGeCKFlute"),
    "testdata/mle.gene_summary.txt")
    dd = ReadBeta(file3)
    #Cell Cycle normalization
    dd_essential = NormalizeBeta(dd, samples=c("dmso", "plx"), method="cell_cycle")
    head(dd_essential)

    #Optional loess normalization (not recommended)
    dd_loess = NormalizeBeta(dd, samples=c("dmso", "plx"), method="loess")
    head(dd_loess)

[Package MAGeCKFlute version 1.12.0 Index]