adele/omicsMA: Variance-Preserving Estimation and Normalization of M-A Values

This package provides methods for estimating and normalizing the M (intensity log-ratio) and A (mean log intensity) values from two-channel (or two-color) microarrays. Unlike conventional estimation methods which take into account only measures of location (e.g., mean and median) of the pixel intensities of each channel, the provided estimation method takes into account pixel-level variability, which may reflects uncertainties due noise and systematic artifacts. To remove array-specific effects, intensity-dependent dye biases, and other systematic trends of the microarray data, the M and A values have to be subjected to a within-slide normalization. The most used within-slide normalization technique is LOWESS. However, the choice of the LOWESS parameters, particularly the smoothing neighborhood parameter (or bandwidth), critically affects the quality of the microarray data normalization. Thus, to preserve relevant variation that may be removed in LOWESS normalization with arbitrarily chosen parameters, it is provided a parameter selection method that is parsimonious and considers intrinsic characteristics of microarray data, such as heteroskedasticity.

Getting started

Package details

AuthorAdèle Helena Ribeiro
MaintainerAdèle Helena Ribeiro <[email protected]>
LicenseGPL (>= 2)
Version1.0
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("adele/omicsMA")
adele/omicsMA documentation built on April 10, 2019, 7:26 p.m.