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CENTIPEDE: CENTIPEDE learns a DNaseI footprint of a transcription factor and predicts its binding sites
Centipede fits a bayesian hierarchical mixture model to learn TF-specific distribution of experimental data on a particular cell-type for a set of candidate binding sites described by a motif. More documentation is under preparation and will be make available soon at http://centipede.uchicago.edu
Getting started
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Package details |
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| Author | Jacob F Degner, Roger Pique-Regi |
| Maintainer | Roger Pique-Regi <rpique@uchicago.edu> |
| License | GPL |
| Version | 1.2 |
| Package repository | View on R-Forge |
| Installation |
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