Chromdmm: a dirichlet-multinomial mixture model for clustering heterogeneous epigenetic data

HIGHLIGHTS

  • who: Bioinformatics and collaborators from the Department of Computer Science, Aalto University, Espoo, Finland and Klarman Cell Observatory, Broad Institute of Harvard have published the research: ChromDMM: a Dirichlet-multinomial mixture model for clustering heterogeneous epigenetic data, in the Journal: (JOURNAL)
  • what: With simulated data the authors demonstrate that ChromDMM clusters shifts and strand-orients the profiles more accurately than previous methods. With ENCODE data the authors show that the clustering of enhancer regions in the human genome reveals distinct patterns in several chromatin features. Compared with the standard Dirichlet-multinomial mixture model (Holmes et_al . . .

     

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