Package: gprege
Version: 1.12.0
Date: 2013-10-08
Title: Gaussian Process Ranking and Estimation of Gene Expression
        time-series
Authors@R: c(person(c("Alfredo"), "Kalaitzis", role =
        c("aut","cre","trl"), email = "alkalait@gmail.com"))
Author: Alfredo Kalaitzis <alkalait@gmail.com>
Maintainer: Alfredo Kalaitzis <alkalait@gmail.com>
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
BugReports: alkalait@gmail.com
Packaged: 2015-04-17 04:03:07 UTC; biocbuild
biocViews: Microarray, Preprocessing, DifferentialExpression,
        TimeCourse
NeedsCompilation: no
Built: R 3.2.0; ; 2015-04-17 09:33:37 UTC; windows
