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ngs.plot: Quick mining and visualization of next-generation sequencing data by integrating genomic databases.
Li Shen1, Ningyi Shao, Xiaochuan Liu
1Fishberg Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA. li.shen@mssm.edu.
BMC Genomics
|April 17, 2014
Summary
ngs.plot visualizes DNA-protein interactions from next-generation sequencing data. This powerful, user-friendly tool helps interpret large genomic datasets for mammalian genome research.
Area of Science:
- Genomics
- Bioinformatics
- Molecular Biology
Background:
- Understanding functional DNA elements and protein regulators is crucial for mammalian genome research.
- Next-generation sequencing (NGS) is widely used for genome-wide profiling of protein-DNA interactions and gene expression.
- Interpreting the vast amounts of data generated by NGS presents a significant challenge.
Purpose of the Study:
- To develop a standalone program for visualizing DNA-protein interaction enrichment patterns.
- To provide a tool for analyzing next-generation sequencing data at functionally important genomic regions.
Main Methods:
- Development of ngs.plot, a standalone software tool.
- Utilizing next-generation sequencing data to identify and visualize protein-DNA enrichment patterns.
- Demonstration of efficiency, scalability, and ease of use through examples.
Main Results:
- ngs.plot effectively visualizes enrichment patterns of DNA-interacting proteins.
- The program is demonstrated to be efficient, scalable, and user-friendly.
- Publication-ready figures can be generated using ngs.plot.
Conclusions:
- ngs.plot serves as a valuable tool for bridging the gap between large sequencing datasets and genomic information.
- The tool aids researchers in the era of big sequencing data.
- Facilitates interpretation of complex genomic data.
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