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Open Access Highly Accessed Software

ngs.plot: Quick mining and visualization of next-generation sequencing data by integrating genomic databases

Li Shen*, Ningyi Shao, Xiaochuan Liu and Eric Nestler

Author Affiliations

Fishberg Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA

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BMC Genomics 2014, 15:284  doi:10.1186/1471-2164-15-284

Published: 15 April 2014

Abstract

Background

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.

Results

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.

Conclusions

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.

Keywords:
Next-generation sequencing; Visualization; Epigenomics; Data mining; Genomic databases