Intensity.Norm: Function to compute normalized intensity for each channel

In anapuce: Tools for Microarray Data Analysis

Description

Computes normalized intensity for each channel and each array from the file containing normalized data.

Usage

Intensity.Norm(fileIN = "resNorm.txt", n = 3, ind.array = NULL, 
name.A = "A", name.M = "M.norm", sep = "\t", center = FALSE, 
log.transf = TRUE, ...)

Arguments

fileIN	input dataframe.
n	number of identificant columns.
ind.array	indices of arrays to use.
name.A	character string containing a regular expression contained in the columnames corresponding to the A values.
name.M	character string containing a regular expression contained in the columnames corresponding to the M values.
sep	the field separator string to use in the read.table function.
center	logical indicating wether data will be centered by array.
log.transf	logical indicating wether data will stay log-transformed.
...	Further arguments to be passed to read.table.

Value

A R dataframe containing the n first columns of the input dataframe and the "normalized" intensity for the red and green channels of each chosen array.

Author(s)

J. Aubert

References

Thorne, N.P. (2004) Single-channel normalisation and analysis of twocolour cDNA microarray data, PhD thesis

See Also

normalisation

anapuce documentation built on May 2, 2019, 9:44 a.m.