Exploring the Cooccurrence Patterns of Multiple Sets of Genomic Intervals. (28th May 2013)

• Record Type: Journal Article
• Authors: Wu, Hao; Qin, Zhaohui S.
• Other Names: Zhao Zhongming Academic Editor.
• Is Part Of: BioMed research international. Volume 2013(2013)
• Publication Date: 2013-05-28
• Subjects: Medicine -- Periodicals; Biology -- Periodicals; Biotechnology -- Periodicals; Life sciences -- Periodicals; 610.5
• DOI: 10.1155/2013/617545
• Languages: English
• ISSNs: 2314-6133

Abstract

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.