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The W-filament AAS instrumentation used was based on a prototype design that utilized self-reversal background correction scheme and peak area measurements.
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All arrays were background corrected using local background correction and normalized using Lowess normalization [ 87].
Background correction, normalization and probe set summarization were performed using the robust multi array algorithm with background adjustment (gcrma, [35]).
The preprocessing procedure for the raw microarray data consists of background correction, normalization, and summarization.
The processing steps include background correction, normalization and probeset summarization.
In addition, Ritchie et al. [ 18] only compare background correction methods and do not demonstrate how normalization methods will affect and interact with different background correction methods.
After background correction, normalization, and fitting a linear model, down-regulated genes were recovered.
We compared three background correction and normalization methods, MAS5, Robust Multi-array Average, and gcRMA.
We used RMA and Bioconductor in R [70] for background correction and normalization [71], [72].
VSN is a protocol that combines the background correction and across array normalization [40].
Background correction and normalization was performed using the robust multi-array average (RMA) algorithm.
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