RefPlus

RefPlus stabilizes probeset intensity estimation for Affymetrix gene expression microarray data by applying extrapolation algorithms that extend RMA (Robust Multi-array Average) pre-processing to reduce variability when additional microarrays are incorporated.

Key Features:

• Extrapolation Strategy and Extrapolation Averaging Algorithms: Introduces Extrapolation Strategy and Extrapolation Averaging Algorithms to stabilize probeset intensity calculations across datasets of varying sizes and maintain consistency when new microarrays are added.
• Integration with RMA, RMA+ and RMA++ Methods: Builds on and integrates with RMA (Robust Multi-array Average), RMA+ and RMA++ pre-processing techniques for normalization and summarization of Affymetrix microarray data.

Scientific Applications:

• Large-scale Affymetrix gene expression studies: Ensures that the inclusion of additional samples does not introduce variability in probeset intensity calculations, preserving comparability across experimental conditions and time points.

Methodology:

Implements the Extrapolation Strategy and Extrapolation Averaging Algorithms in the R programming language and integrates these methods with RMA, RMA+ and RMA++ pre-processing to produce stabilized probeset intensity estimates.