humburg/tileHMM: Hidden Markov Models for ChIP-on-Chip Analysis
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.
Getting started
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Package details |
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| Maintainer | |
| License | GPL (>= 2) |
| Version | 1.0-7 |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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