CRAN

GPrank 0.1.4

Gaussian Process Ranking of Multiple Time Series

Released Aug 17, 2018 by Hande Topa

This package can be loaded by Renjin but 3 out 14 tests failed.

Dependencies

tigreBrowserWriter 0.1.5 gptk 1.08 RColorBrewer 1.1-2 matrixStats 0.54.0

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.

Installation

Maven

This package can be included as a dependency from a Java or Scala project by including the following your project's pom.xml file. Read more about embedding Renjin in JVM-based projects.

<dependencies>
  <dependency>
    <groupId>org.renjin.cran</groupId>
    <artifactId>GPrank</artifactId>
    <version>0.1.4-b1</version>
  </dependency>
</dependencies>
<repositories>
  <repository>
    <id>bedatadriven</id>
    <name>bedatadriven public repo</name>
    <url>https://nexus.bedatadriven.com/content/groups/public/</url>
  </repository>
</repositories>

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Renjin CLI

If you're using Renjin from the command line, you load this library by invoking:

library('org.renjin.cran:GPrank')

Test Results

This package was last tested against Renjin 0.9.2675 on Aug 22, 2018.

Source

R

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Release History