Additive partially linear models for differential gene
expression analysis
Description
A set of tools for identifying genes whose differential
expression is associated with measurements of other covariates
on a continuous scale. These methods rely on generalized
additive partially linear models which can be fitted
efficiently using a B-spline basis approximation. Still under
development: methods for interfacing with objects extending the
eSet class and a function to pass linear models in edgeR and
DEseq format.