Dataset Information

Exploring the cooccurrence patterns of multiple sets of genomic intervals.

ABSTRACT: 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.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.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.

SUBMITTER: Wu H

PROVIDER: S-EPMC3679813 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Exploring the cooccurrence patterns of multiple sets of genomic intervals.

Wu Hao H Qin Zhaohui S ZS

BioMed research international 20130528

<h4>Background</h4>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 compa ...[more]

PMID: 23781505

Similar Datasets

Project description:Picocyanobacteria Prochlorococcus and Synechococcus are abundant in the global oceans and subject to active viral infection. In this study, the genetic diversity of picocyanobacteria and the genetic diversity of cyanopodoviruses were synchronously investigated along water columns in the equatorial Indian Ocean and over a seasonal time course in the coastal Sanya Bay, South China Sea. Using the 16S-23S rRNA internal transcribed spacer (ITS)-based clone library and quantitative PCR (qPCR) analyses, the picocyanobacterial community composition and abundance were determined. Sanya Bay was dominated by clade II Synechococcus during all the seasons, and a typical population shift from high-light-adapted Prochlorococcus to low-light-adapted Prochlorococcus was found along the vertical profiles. Strikingly, the DNA polymerase gene sequences of cyanopodoviruses revealed a much greater genetic diversity than we expected. Nearly one-third of the phylogenetic groups were newly described here. No apparent seasonal pattern was observed for the Sanya Bay picocyanobacterial or cyanopodoviral communities. Different dominant cyanopodovirus lineages were identified for the coastal area, upper euphotic zone, and middle-to-lower euphotic zone of the open ocean. Diversity indices of both picocyanobacteria and cyanopodoviruses were highest in the middle euphotic zone and both were lower in the upper euphotic zone, reflecting a host-virus interaction. Cyanopodoviral communities differed significantly between the upper euphotic zone and the middle-to-lower euphotic zone, showing a vertical pattern similar to that of picocyanobacteria. However, in the surface waters of the open ocean, cyanopodoviruses exhibited no apparent biogeographic pattern, differing from picocyanobacteria. This study demonstrates correlated distribution patterns of picocyanobacteria and cyanopodoviruses, as well as the complex biogeography of cyanopodoviruses.IMPORTANCE Picocyanobacteria are highly diverse and abundant in the ocean and display remarkable global biogeography and a vertical distribution pattern. However, how the diversity and distribution of picocyanobacteria affect those of the viruses that infect them remains largely unknown. Here we synchronously analyzed the community structures of cyanopodoviruses and picocyanobacteria at spatial and temporal scales. Both spatial and temporal variations of cyanopodoviral communities can be linked to those of picocyanobacteria. The coastal area, upper euphotic zone, and middle-to-lower euphotic zone of the open ocean have distinct cyanopodoviral communities, showing horizontal and vertical variation patterns closely related to those of picocyanobacteria. These findings emphasize the driving force of host community in shaping the biogeographic structure of viruses. Our work provides important information for future assessments of the ecological roles of viruses and hosts for each other.

Dataset Information

Exploring the cooccurrence patterns of multiple sets of genomic intervals.

Publications

Exploring the cooccurrence patterns of multiple sets of genomic intervals.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets