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GsmPlot: a web server to visualize epigenome data in NCBI.


ABSTRACT: BACKGROUND:Epigenetic regulation is essential in regulating gene expression across a variety of biological processes. Many high-throughput sequencing technologies have been widely used to generate epigenetic data, such as histone modification, transcription factor binding sites, DNA modifications, chromatin accessibility, and etc. A large scale of epigenetic data is stored in NCBI Gene Expression Omnibus (GEO). However, it is a great challenge to reanalyze these large scale and complex data, especially for researchers who do not specialize in bioinformatics skills or do not have access to expensive computational infrastructure. RESULTS:GsmPlot can simply accept GSM IDs to automatically download NCBI data or can accept user's private bigwig files as input to plot the concerned data on promoters, exons or any other user-defined genome locations and generate UCSC visualization tracks. By linking public data repository and private data, GsmPlot can spark data-driven ideas and hence promote the epigenetic research. CONCLUSIONS:GsmPlot web server allows convenient visualization and efficient exploration of any NCBI epigenetic data in any genomic region without need of any bioinformatics skills or special computing resources. GsmPlot is freely available at https://gsmplot.deqiangsun.org/.

SUBMITTER: Li J 

PROVIDER: S-EPMC7017537 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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GsmPlot: a web server to visualize epigenome data in NCBI.

Li Jia J   Yin Yue Y   Zhang Mutian M   Cui Jie J   Zhang Zhenhai Z   Zhang Zhiyong Z   Sun Deqiang D  

BMC bioinformatics 20200212 1


<h4>Background</h4>Epigenetic regulation is essential in regulating gene expression across a variety of biological processes. Many high-throughput sequencing technologies have been widely used to generate epigenetic data, such as histone modification, transcription factor binding sites, DNA modifications, chromatin accessibility, and etc. A large scale of epigenetic data is stored in NCBI Gene Expression Omnibus (GEO). However, it is a great challenge to reanalyze these large scale and complex d  ...[more]

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