BMC Genomics · 2014 · 951 citations · 58 references
Life SciencesBioinformaticsMolecular BiologyData VisualizationGenomic Data AnalysisGenomicsDna SequencingFunctional GenomicsGenomic Data IntegrationGenomic Data VisualizationGenomic DatabasesNext-generation SequencingEnrichmentEnrichment Plot VisualizationNext-generation Sequencing Data AnalysisProtein-dna InteractionsRegulatory Protein-dna InteractionsScalable Genomic Data Visualization
Understanding how millions of functional DNA elements and their protein regulators interact to produce diverse phenotypes is essential, yet the growing volume of next‑generation sequencing data makes interpretation increasingly challenging. We developed ngs.plot, a standalone program that visualizes enrichment patterns of DNA‑interacting proteins at functionally important regions using next‑generation sequencing data, and demonstrate its efficiency and scalability. The tool is easy to use and can generate publication‑ready figures from NGS data, as illustrated by several examples. ngs.plot effectively bridges the gap between massive sequencing datasets and genomic information, making it a valuable resource for researchers.
Understanding the relationship between the millions of functional DNA elements and their protein regulators, and how they work in conjunction to manifest diverse phenotypes, is key to advancing our understanding of the mammalian genome. Next-generation sequencing technology is now used widely to probe these protein-DNA interactions and to profile gene expression at a genome-wide scale. As the cost of DNA sequencing continues to fall, the interpretation of the ever increasing amount of data generated represents a considerable challenge. We have developed ngs.plot – a standalone program to visualize enrichment patterns of DNA-interacting proteins at functionally important regions based on next-generation sequencing data. We demonstrate that ngs.plot is not only efficient but also scalable. We use a few examples to demonstrate that ngs.plot is easy to use and yet very powerful to generate figures that are publication ready. We conclude that ngs.plot is a useful tool to help fill the gap between massive datasets and genomic information in this era of big sequencing data.
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