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Epiviz File Server: Query, transform and interactively explore data from indexed genomic files

MOTIVATION: Genomic data repositories like The Cancer Genome Atlas, Encyclopedia of DNA Elements, Bioconductor’s AnnotationHub and ExperimentHub etc., provide public access to large amounts of genomic data as flat files. Researchers often download a subset of data files from these repositories to pe...

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Detalles Bibliográficos
Autores principales: Kancherla, Jayaram, Yang, Yifan, Chae, Hyeyun, Corrada Bravo, Hector
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7695125/
https://www.ncbi.nlm.nih.gov/pubmed/32618995
http://dx.doi.org/10.1093/bioinformatics/btaa591
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author Kancherla, Jayaram
Yang, Yifan
Chae, Hyeyun
Corrada Bravo, Hector
author_facet Kancherla, Jayaram
Yang, Yifan
Chae, Hyeyun
Corrada Bravo, Hector
author_sort Kancherla, Jayaram
collection PubMed
description MOTIVATION: Genomic data repositories like The Cancer Genome Atlas, Encyclopedia of DNA Elements, Bioconductor’s AnnotationHub and ExperimentHub etc., provide public access to large amounts of genomic data as flat files. Researchers often download a subset of data files from these repositories to perform exploratory data analysis. We developed Epiviz File Server, a Python library that implements an in situ data query system for local or remotely hosted indexed genomic files, not only for visualization but also data transformation. The File Server library decouples data retrieval and transformation from specific visualization and analysis tools and provides an abstract interface to define computations independent of the location, format or structure of the file. We demonstrate the File Server in two use cases: (i) integration with Galaxy workflows and (ii) using Epiviz to create a custom genome browser from the Epigenome Roadmap dataset. AVAILABILITY AND IMPLEMENTATION: Epiviz File Server is open source and is available on GitHub at http://github.com/epiviz/epivizFileServer. The documentation for the File Server library is available at http://epivizfileserver.rtfd.io.
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spelling pubmed-76951252020-12-02 Epiviz File Server: Query, transform and interactively explore data from indexed genomic files Kancherla, Jayaram Yang, Yifan Chae, Hyeyun Corrada Bravo, Hector Bioinformatics Original Papers MOTIVATION: Genomic data repositories like The Cancer Genome Atlas, Encyclopedia of DNA Elements, Bioconductor’s AnnotationHub and ExperimentHub etc., provide public access to large amounts of genomic data as flat files. Researchers often download a subset of data files from these repositories to perform exploratory data analysis. We developed Epiviz File Server, a Python library that implements an in situ data query system for local or remotely hosted indexed genomic files, not only for visualization but also data transformation. The File Server library decouples data retrieval and transformation from specific visualization and analysis tools and provides an abstract interface to define computations independent of the location, format or structure of the file. We demonstrate the File Server in two use cases: (i) integration with Galaxy workflows and (ii) using Epiviz to create a custom genome browser from the Epigenome Roadmap dataset. AVAILABILITY AND IMPLEMENTATION: Epiviz File Server is open source and is available on GitHub at http://github.com/epiviz/epivizFileServer. The documentation for the File Server library is available at http://epivizfileserver.rtfd.io. Oxford University Press 2020-07-03 /pmc/articles/PMC7695125/ /pubmed/32618995 http://dx.doi.org/10.1093/bioinformatics/btaa591 Text en © The Author(s) 2020. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Papers
Kancherla, Jayaram
Yang, Yifan
Chae, Hyeyun
Corrada Bravo, Hector
Epiviz File Server: Query, transform and interactively explore data from indexed genomic files
title Epiviz File Server: Query, transform and interactively explore data from indexed genomic files
title_full Epiviz File Server: Query, transform and interactively explore data from indexed genomic files
title_fullStr Epiviz File Server: Query, transform and interactively explore data from indexed genomic files
title_full_unstemmed Epiviz File Server: Query, transform and interactively explore data from indexed genomic files
title_short Epiviz File Server: Query, transform and interactively explore data from indexed genomic files
title_sort epiviz file server: query, transform and interactively explore data from indexed genomic files
topic Original Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7695125/
https://www.ncbi.nlm.nih.gov/pubmed/32618995
http://dx.doi.org/10.1093/bioinformatics/btaa591
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