CRAN
tileHMM 1.0-7
Hidden Markov Models for ChIP-on-Chip Analysis
Released Jul 3, 2015 by Peter Humburg
This package can be loaded by Renjin but 18 out 28 tests failed.
Dependencies
Methods and classes to build HMMs that are suitable for the analysis of ChIP-chip data. The provided parameter estimation methods include the Baum-Welch algorithm and Viterbi training as well as a combination of both.
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>tileHMM</artifactId>
<version>1.0-7-b76</version>
</dependency>
</dependencies>
<repositories>
<repository>
<id>bedatadriven</id>
<name>bedatadriven public repo</name>
<url>https://nexus.bedatadriven.com/content/groups/public/</url>
</repository>
</repositories>
Renjin CLI
If you're using Renjin from the command line, you load this library by invoking:
library('org.renjin.cran:tileHMM')
Test Results
This package was last tested against Renjin 0.9.2709 on Nov 8, 2018.
- baumWelch-examples
- contDist-class-examples
- contHMM-access-examples
- contHMM-class-examples
- discDist-class-examples
- dist-access-examples
- dist-class-examples
- forward-examples
- getHMM-examples
- gff2index-examples
- hmm-class-examples
- hmm.setup-examples
- logSum-examples
- plot-examples
- posterior-examples
- reg2gff-examples
- region.length-examples
- region.position-examples
- remove.short-examples
- sampleObs-examples
- sampleSeq-examples
- shrinkt.st-examples
- simChIP-examples
- states-examples
- tDist-class-examples
- viterbi-examples
- viterbiEM-examples
- viterbiTraining-examples