Iterative rank-order normalization of gene expression microarray data.

ABSTRACT:

Background

Many gene expression normalization algorithms exist for Affymetrix GeneChip microarrays. The most popular of these is RMA, primarily due to the precision and low noise produced during the process. A significant strength of this and similar approaches is the use of the entire set of arrays during both normalization and model-based estimation of signal. However, this leads to differing estimates of expression based on the starting set of arrays, and estimates can change when a single, additional chip is added to the set. Additionally, outlier chips can impact the signals of other arrays, and can themselves be skewed by the majority of the population.

Results

We developed an approach, termed IRON, which uses the best-performing techniques from each of several popular

SUBMITTER: Welsh EA 

PROVIDER: S-EPMC3651355 | biostudies-literature | 2013 May

REPOSITORIES: biostudies-literature