qsmooth

qsmooth generalizes quantile normalization by averaging two assumptions about the data generation process: quantile normalization and quantile normalization between groups.

Key Features:

• Smooth quantile normalization: Combines quantile normalization and quantile normalization between groups as a weighted average based on data characteristics.

Scientific Applications:

• Between-group normalization: Enables normalization that accounts for both global distributional assumptions and group-specific structure in high-dimensional data.

Methodology:

The method computes a weighted average of quantile normalization and quantile normalization between groups, with weights determined by the data generation process assumptions.