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10.1186/s13059-015-0708-z

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suck abstract from ncbi


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pmid26206277
      Genome+Biol 2015 ; 16 (1 ): 151
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  • Chromatin segmentation based on a probabilistic model for read counts explains a large portion of the epigenome #MMPMID26206277
  • Mammana A ; Chung HR
  • Genome Biol 2015[Jul]; 16 (1 ): 151 PMID26206277 show ga
  • Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is an increasingly common experimental approach to generate genome-wide maps of histone modifications and to dissect the complexity of the epigenome. Here, we propose EpiCSeg: a novel algorithm that combines several histone modification maps for the segmentation and characterization of cell-type specific epigenomic landscapes. By using an accurate probabilistic model for the read counts, EpiCSeg provides a useful annotation for a considerably larger portion of the genome, shows a stronger association with validation data, and yields more consistent predictions across replicate experiments when compared to existing methods.The software is available at http://github.com/lamortenera/epicseg.
  • |*Algorithms [MESH]
  • |*Models, Statistical [MESH]
  • |Chromatin/*metabolism [MESH]
  • |Epigenesis, Genetic [MESH]
  • |Epigenomics/*methods [MESH]
  • |Histone Code [MESH]
  • |Humans [MESH]


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