Orthogonal projections to latent structures as a strategy for microarray data normalization.

ABSTRACT:

Background

During generation of microarray data, various forms of systematic biases are frequently introduced which limits accuracy and precision of the results. In order to properly estimate biological effects, these biases must be identified and discarded.

Results

We introduce a normalization strategy for multi-channel microarray data based on orthogonal projections to latent structures (OPLS); a multivariate regression method. The effect of applying the normalization methodology on single-channel Affymetrix data as well as dual-channel cDNA data is illustrated. We provide a parallel comparison to a wide range of commonly employed normalization methods with diverse properties and strengths based on sensitivity and specificity from external (spike-in) controls. On the illus

SUBMITTER: Bylesjo M 

PROVIDER: S-EPMC1906839 | biostudies-literature | 2007 Jun

REPOSITORIES: biostudies-literature