title: DANPOS: dynamic analysis of nucleosome position and occupancy by sequencing.
abstract: Recent developments in next-generation sequencing have enabled whole-genome profiling of nucleosome organizations. Although several algorithms for inferring nucleosome position from a single experimental condition have been available, it remains a challenge to accurately define dynamic nucleosomes associated with environmental changes. Here, we report a comprehensive bioinformatics pipeline, DANPOS, explicitly designed for dynamic nucleosome analysis at single-nucleotide resolution. Using both simulated and real nucleosome data, we demonstrated that bias correction in preliminary data processing and optimal statistical testing significantly enhances the functional interpretation of dynamic nucleosomes. The single-nucleotide resolution analysis of DANPOS allows us to detect all three categories of nucleosome dynamics, such as position shift, fuzziness change, and occupancy change, using a uniform statistical framework. Pathway analysis indicates that each category is involved in distinct biological functions. We also analyzed the influence of sequencing depth and suggest that even 200-fold coverage is probably not enough to identify all the dynamic nucleosomes. Finally, based on nucleosome data from the human hematopoietic stem cells (HSCs) and mouse embryonic stem cells (ESCs), we demonstrated that DANPOS is also robust in defining functional dynamic nucleosomes, not only in promoters, but also in distal regulatory regions in the mammalian genome.
authors.affiliation: Division of Biostatistics, Dan L Duncan Cancer Center and Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas 77030, USA.
authors.forename: Kaifu
authors.initials: K
authors.lastname: Chen
authors.forename: Yuanxin
authors.initials: Y
authors.lastname: Xi
authors.forename: Xuewen
authors.initials: X
authors.lastname: Pan
authors.forename: Zhaoyu
authors.initials: Z
authors.lastname: Li
authors.forename: Klaus
authors.initials: K
authors.lastname: Kaestner
authors.forename: Jessica
authors.initials: J
authors.lastname: Tyler
authors.forename: Sharon
authors.initials: S
authors.lastname: Dent
authors.forename: Xiangwei
authors.initials: X
authors.lastname: He
authors.forename: Wei
authors.initials: W
authors.lastname: Li
mesh_terms: D000465:Algorithms; D000818:Animals; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D004247:DNA / Q000378:metabolism*; D030541:Databases, Genetic; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D051379:Mice; D009707:Nucleosomes / Q000378:metabolism*; D011401:Promoter Regions, Genetic; D011485:Protein Binding; D012372:ROC Curve
chemical_list: D009707:Nucleosomes; D004247:DNA