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genomeSidekick: A user-friendly epigenomics data analysis tool

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 increa...

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Autores principales: Chen, Junjie, Zhu, Ashley J., Packard, René R. S., Vondriska, Thomas M., Chapski, Douglas J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9580848/
https://www.ncbi.nlm.nih.gov/pubmed/36304311
http://dx.doi.org/10.3389/fbinf.2022.831025
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author Chen, Junjie
Zhu, Ashley J.
Packard, René R. S.
Vondriska, Thomas M.
Chapski, Douglas J.
author_facet Chen, Junjie
Zhu, Ashley J.
Packard, René R. S.
Vondriska, Thomas M.
Chapski, Douglas J.
author_sort Chen, Junjie
collection PubMed
description 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.
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spelling pubmed-95808482022-10-26 genomeSidekick: A user-friendly epigenomics data analysis tool Chen, Junjie Zhu, Ashley J. Packard, René R. S. Vondriska, Thomas M. Chapski, Douglas J. Front Bioinform Bioinformatics 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. Frontiers Media S.A. 2022-07-18 /pmc/articles/PMC9580848/ /pubmed/36304311 http://dx.doi.org/10.3389/fbinf.2022.831025 Text en Copyright © 2022 Chen, Zhu, Packard, Vondriska and Chapski. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Bioinformatics
Chen, Junjie
Zhu, Ashley J.
Packard, René R. S.
Vondriska, Thomas M.
Chapski, Douglas J.
genomeSidekick: A user-friendly epigenomics data analysis tool
title genomeSidekick: A user-friendly epigenomics data analysis tool
title_full genomeSidekick: A user-friendly epigenomics data analysis tool
title_fullStr genomeSidekick: A user-friendly epigenomics data analysis tool
title_full_unstemmed genomeSidekick: A user-friendly epigenomics data analysis tool
title_short genomeSidekick: A user-friendly epigenomics data analysis tool
title_sort genomesidekick: a user-friendly epigenomics data analysis tool
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9580848/
https://www.ncbi.nlm.nih.gov/pubmed/36304311
http://dx.doi.org/10.3389/fbinf.2022.831025
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