title: Exploring the cooccurrence patterns of multiple sets of genomic intervals.
abstract: BACKGROUND
  Exploring the spatial relationship of different genomic features has been of great interest since the early days of genomic research. The relationship sometimes provides useful information for understanding certain biological processes. Recent advances in high-throughput technologies such as ChIP-seq produce large amount of data in the form of genomic intervals. Most of the existing methods for assessing spatial relationships among the intervals are designed for pairwise comparison and cannot be easily scaled up.
  
  
  RESULTS
  We present a statistical method and software tool to characterize the cooccurrence patterns of multiple sets of genomic intervals. The occurrences of genomic intervals are described by a simple finite mixture model, where each component represents a distinct cooccurrence pattern. The model parameters are estimated via an EM algorithm and can be viewed as sufficient statistics of the cooccurrence patterns. Simulation and real data results show that the model can accurately capture the patterns and provide biologically meaningful results. The method is implemented in a freely available R package giClust.
  
  
  CONCLUSIONS
  The method and the software provide a convenient way for biologists to explore the cooccurrence patterns among a relatively large number of sets of genomic intervals.
authors.affiliation: Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, USA.
authors.forename: Hao
authors.initials: H
authors.lastname: Wu
authors.forename: Zhaohui S
authors.initials: ZS
authors.lastname: Qin
mesh_terms: D000818:Animals; D016000:Cluster Analysis; D053595:Embryonic Stem Cells / Q000378:metabolism; D005786:Gene Expression Regulation; D016678:Genome / Q000235:genetics*; D023281:Genomics; D006657:Histones / Q000378:metabolism; D006801:Humans; D020014:K562 Cells; D008239:Lysine / Q000378:metabolism; D051379:Mice; D008957:Models, Genetic; D011485:Protein Binding; D011499:Protein Processing, Post-Translational; D012984:Software
chemical_list: D006657:Histones; D008239:Lysine