Article abstract
Nature Biotechnology 26, 1293 - 1300 (2008)
Published online: 2 November 2008 | doi:10.1038/nbt.1505
An integrated software system for analyzing ChIP-chip and ChIP-seq data
Hongkai Ji1, Hui Jiang2, Wenxiu Ma3, David S Johnson4,8, Richard M Myers5 & Wing H Wong6,7
Abstract
We present CisGenome, a software system for analyzing genome-wide chromatin immunoprecipitation (ChIP) data. CisGenome is designed to meet all basic needs of ChIP data analyses, including visualization, data normalization, peak detection, false discovery rate computation, gene-peak association, and sequence and motif analysis. In addition to implementing previously published ChIP–microarray (ChIP-chip) analysis methods, the software contains statistical methods designed specifically for ChlP sequencing (ChIP-seq) data obtained by coupling ChIP with massively parallel sequencing. The modular design of CisGenome enables it to support interactive analyses through a graphic user interface as well as customized batch-mode computation for advanced data mining. A built-in browser allows visualization of array images, signals, gene structure, conservation, and DNA sequence and motif information. We demonstrate the use of these tools by a comparative analysis of ChIP-chip and ChIP-seq data for the transcription factor NRSF/REST, a study of ChIP-seq analysis with or without a negative control sample, and an analysis of a new motif in Nanog- and Sox2-binding regions.
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, Maryland 21205, USA.
- Institute for Computational and Mathematical Engineering, Stanford University, Durand Building, 496 Lomita Mall, Stanford, California 94305, USA.
- Department of Computer Science, Stanford University, 353 Serra Mall, Stanford, California 94305, USA.
- Department of Genetics, Stanford University School of Medicine, 300 Pasteur Drive, Stanford, California 94305, USA.
- HudsonAlpha Institute for Biotechnology, 601 Genome Way, Huntsville, Alabama 35806, USA.
- Department of Statistics, Stanford University, Sequoia Hall, 390 Serra Mall, Stanford, California 94305, USA.
- Department of Health Research and Policy, Stanford University, Sequoia Hall, 390 Serra Mall, Stanford, California 94305, USA.
- Present address: Gene Security Network, Inc., 1442 Cortland Avenue, San Francisco, California 94110, USA.
Correspondence to: Wing H Wong6,7 e-mail: whwong@stanford.edu
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