NormalizeBeta: Normalize gene beta scores

In MAGeCKFlute: Integrative Analysis Pipeline for Pooled CRISPR Functional Genetic Screens

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)

MAGeCKFlute documentation built on Nov. 8, 2020, 5:40 p.m.