genomeSidekick: A user-friendly epigenomics data analysis tool

被引:0
|
作者
Chen, Junjie [1 ]
Zhu, Ashley J. [2 ]
Packard, Rene R. S. [1 ,3 ,4 ,5 ]
Vondriska, Thomas M. [1 ,2 ,3 ]
Chapski, Douglas J. [2 ]
机构
[1] Univ Calif Los Angeles, David Geffen Sch Med, Dept Med, Div Cardiol, Los Angeles, CA USA
[2] Univ Calif Los Angeles, David Geffen Sch Med, Dept Anesthesiol & Perioperat Med, Los Angeles, CA 90095 USA
[3] Univ Calif Los Angeles, David Geffen Sch Med, Dept Physiol, Los Angeles, CA USA
[4] Ronald Reagan UCLA Med Ctr, Los Angeles, CA USA
[5] West Los Angeles Vet Affairs Med Ctr, Los Angeles, CA USA
来源
FRONTIERS IN BIOINFORMATICS | 2022年 / 2卷
关键词
epigenomics; chromatin; data visualization; Shiny app; bioinformatics;
D O I
10.3389/fbinf.2022.831025
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Recent advances in epigenomics measurements have resulted in a preponderance of genomic sequencing datasets that require focused analyses to discover mechanisms governing biological processes. In addition, multiple epigenomics experiments are typically performed within the same study, thereby increasing the complexity and difficulty of making meaningful inferences from large datasets. One gap in the sequencing data analysis pipeline is the availability of tools to efficiently browse genomic data for scientists that do not have bioinformatics training. To bridge this gap, we developed genomeSidekick, a graphical user interface written in R that allows researchers to perform bespoke analyses on their transcriptomic and chromatin accessibility or chromatin immunoprecipitation data without the need for command line tools. Importantly, genomeSidekick outputs lists of up- and downregulated genes or chromatin features with differential accessibility or occupancy; visualizes omics data using interactive volcano plots; performs Gene Ontology analyses locally; and queries PubMed for selected gene candidates for further evaluation. Outputs can be saved using the user interface and the code underlying genomeSidekick can be edited for custom analyses. In summary, genomeSidekick brings wet lab scientists and bioinformaticians into a shared fluency with the end goal of driving mechanistic discovery.
引用
收藏
页数:7
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