Package: gprege
Version: 1.4.1
Date: 2012-02-27
Title: Gaussian Process Ranking and Estimation of Gene Expression
        time-series
Authors@R: c(person(c("Alfredo"), "Kalaitzis", role =
        c("aut","cre","trl"), email = "a.kalaitzis@ucl.ac.uk"))
Author: Alfredo Kalaitzis <a.kalaitzis@ucl.ac.uk>
Maintainer: Alfredo Kalaitzis <a.kalaitzis@ucl.ac.uk>
Depends: R (>= 2.8.0), gptk
Suggests: spam
Description: The gprege package implements the methodology described in
  Kalaitzis & Lawrence (2011) "A simple approach to ranking differentially
  expressed gene expression time-courses through Gaussian process regression".
  The software fits two GPs with the an RBF (+ noise diagonal) kernel on each
  profile. One GP kernel is initialised wih a short lengthscale hyperparameter,
  signal variance as the observed variance and a zero noise variance. It is
  optimised via scaled conjugate gradients (netlab). A second GP has fixed
  hyperparameters: zero inverse-width, zero signal variance and noise
  variance as the observed variance. The log-ratio of marginal likelihoods of
  the two hypotheses acts as a score of differential expression for the profile.
  Comparison via ROC curves is performed against BATS (Angelini et.al, 2007).
  A detailed discussion of the ranking approach and dataset used can be found in
  the paper (http://www.biomedcentral.com/1471-2105/12/180).
License: AGPL-3
biocViews: Microarray, Preprocessing, Bioinformatics,
        DifferentialExpression, TimeCourse
URL:
BugReports: a.kalaitzis@ucl.ac.uk
Packaged: 2013-10-03 07:28:10 UTC; biocbuild
Built: R 3.0.1; ; 2013-10-03 12:07:56 UTC; windows
