Package: GPrank
Title: Gaussian Process Ranking of Multiple Time Series
Version: 0.1.4
Date: 2018-08-17
Authors@R: c(person("Hande", "Topa", role = c("aut", "cre"),
                     email = "hande.topa@helsinki.fi"),
	     person("Antti", "Honkela", role = c("aut"),
                     email = "antti.honkela@helsinki.fi"))
Depends: R (>= 2.14.0)
Imports: gptk, matrixStats, tigreBrowserWriter, RColorBrewer
LazyData: true
Description: Implements a Gaussian process (GP)-based ranking method
    which can be used to rank multiple time series according to their
    temporal activity levels. An example is the case when expression
    levels of all genes are measured over a time course and the main
    concern is to identify the most active genes, i.e. genes which
    show significant non-random variation in their expression levels.
    This is achieved by computing Bayes factors for each time series
    by comparing the marginal likelihoods under time-dependent and
    time-independent GP models. Additional variance information from
    pre-processing of the observations is incorporated into the GP
    models, which makes the ranking more robust against model
    overfitting. The package supports exporting the results to
    'tigreBrowser' for visualisation, filtering or ranking.
License: MIT + file LICENSE
URL: https://github.com/PROBIC/GPrank
BugReports: https://github.com/PROBIC/GPrank/issues
RoxygenNote: 6.0.1
NeedsCompilation: no
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Packaged: 2018-08-17 14:33:07 UTC; topah
Author: Hande Topa [aut, cre],
  Antti Honkela [aut]
Maintainer: Hande Topa <hande.topa@helsinki.fi>
Repository: CRAN
Date/Publication: 2018-08-17 15:00:03 UTC
Built: R 4.0.2; ; 2020-07-16 14:38:27 UTC; unix
