GPrank-package

<p>GPrank package implements our Gaussian-process-based ranking method,
which can be used to rank multiple time series according to their temporal activity
levels. GPrank incorporates available variance information on the observations
into the GP models and achieves a higher performance than the standard GP-based
ranking methods.</p>

package

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.

Hande Topa

GPrank

Package:	GPrank
Type:	Package
Version:	0.1.2
Date:	2016-12-21
License:	MIT

GPrank-package: GPrank - Gaussian Process ranking of multiple time series

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