cellNorm: Data normalization

In OperaMate: An R package of Data Importing, Processing and Analysis for Opera High Content Screening System

Description

Normalizes raw data based on different normalization methods.

Usage

cellNorm(object, norm.method)

## S4 method for signature 'cellData'
cellNorm(object,
  norm.method = getOption("opm.normalization.method"))

Arguments

object	a cellData object
norm.method	getOption("opm.normalization.method")

Details

Method description: "MP" employes the median polish algorithm which divides data by the median of their plates and wells recursively, while "PMed" only divides data by the median of their plates; "Z" substracts data by their plate medians, and then divides by the median absolute deviations; "Ctr" divides data by the mean of their plate negative controls; "None" avoids the data normalization in this step. The first three methods are based on the assumption that most samples display no biological effects in the assay be analyzed. They are often more effective than "Ctr" method as to the high throughput screening.

Value

a celldata object with initialized slot norm.data

Examples

data(demoCell)
oneCell <- cellNorm(oneCell, norm.method = "MP")
str(oneCell["norm.data"])

OperaMate documentation built on Nov. 17, 2017, 1:55 p.m.