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


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2014-12

AUTHORS

Li Shen, Ningyi Shao, Xiaochuan Liu, Eric Nestler

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. More... »

PAGES

284

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/1471-2164-15-284

    DOI

    http://dx.doi.org/10.1186/1471-2164-15-284

    DIMENSIONS

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    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/24735413


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