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NASQAR: a web-based platform for high-throughput sequencing data analysis and visualization

BACKGROUND: As high-throughput sequencing applications continue to evolve, the rapid growth in quantity and variety of sequence-based data calls for the development of new software libraries and tools for data analysis and visualization. Often, effective use of these tools requires computational ski...

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Autores principales: Yousif, Ayman, Drou, Nizar, Rowe, Jillian, Khalfan, Mohammed, Gunsalus, Kristin C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7322916/
https://www.ncbi.nlm.nih.gov/pubmed/32600310
http://dx.doi.org/10.1186/s12859-020-03577-4
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author Yousif, Ayman
Drou, Nizar
Rowe, Jillian
Khalfan, Mohammed
Gunsalus, Kristin C.
author_facet Yousif, Ayman
Drou, Nizar
Rowe, Jillian
Khalfan, Mohammed
Gunsalus, Kristin C.
author_sort Yousif, Ayman
collection PubMed
description BACKGROUND: As high-throughput sequencing applications continue to evolve, the rapid growth in quantity and variety of sequence-based data calls for the development of new software libraries and tools for data analysis and visualization. Often, effective use of these tools requires computational skills beyond those of many researchers. To ease this computational barrier, we have created a dynamic web-based platform, NASQAR (Nucleic Acid SeQuence Analysis Resource). RESULTS: NASQAR offers a collection of custom and publicly available open-source web applications that make extensive use of a variety of R packages to provide interactive data analysis and visualization. The platform is publicly accessible at http://nasqar.abudhabi.nyu.edu/. Open-source code is on GitHub at https://github.com/nasqar/NASQAR, and the system is also available as a Docker image at https://hub.docker.com/r/aymanm/nasqarall. NASQAR is a collaboration between the core bioinformatics teams of the NYU Abu Dhabi and NYU New York Centers for Genomics and Systems Biology. CONCLUSIONS: NASQAR empowers non-programming experts with a versatile and intuitive toolbox to easily and efficiently explore, analyze, and visualize their Transcriptomics data interactively. Popular tools for a variety of applications are currently available, including Transcriptome Data Preprocessing, RNA-seq Analysis (including Single-cell RNA-seq), Metagenomics, and Gene Enrichment.
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spelling pubmed-73229162020-06-30 NASQAR: a web-based platform for high-throughput sequencing data analysis and visualization Yousif, Ayman Drou, Nizar Rowe, Jillian Khalfan, Mohammed Gunsalus, Kristin C. BMC Bioinformatics Software BACKGROUND: As high-throughput sequencing applications continue to evolve, the rapid growth in quantity and variety of sequence-based data calls for the development of new software libraries and tools for data analysis and visualization. Often, effective use of these tools requires computational skills beyond those of many researchers. To ease this computational barrier, we have created a dynamic web-based platform, NASQAR (Nucleic Acid SeQuence Analysis Resource). RESULTS: NASQAR offers a collection of custom and publicly available open-source web applications that make extensive use of a variety of R packages to provide interactive data analysis and visualization. The platform is publicly accessible at http://nasqar.abudhabi.nyu.edu/. Open-source code is on GitHub at https://github.com/nasqar/NASQAR, and the system is also available as a Docker image at https://hub.docker.com/r/aymanm/nasqarall. NASQAR is a collaboration between the core bioinformatics teams of the NYU Abu Dhabi and NYU New York Centers for Genomics and Systems Biology. CONCLUSIONS: NASQAR empowers non-programming experts with a versatile and intuitive toolbox to easily and efficiently explore, analyze, and visualize their Transcriptomics data interactively. Popular tools for a variety of applications are currently available, including Transcriptome Data Preprocessing, RNA-seq Analysis (including Single-cell RNA-seq), Metagenomics, and Gene Enrichment. BioMed Central 2020-06-29 /pmc/articles/PMC7322916/ /pubmed/32600310 http://dx.doi.org/10.1186/s12859-020-03577-4 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Software
Yousif, Ayman
Drou, Nizar
Rowe, Jillian
Khalfan, Mohammed
Gunsalus, Kristin C.
NASQAR: a web-based platform for high-throughput sequencing data analysis and visualization
title NASQAR: a web-based platform for high-throughput sequencing data analysis and visualization
title_full NASQAR: a web-based platform for high-throughput sequencing data analysis and visualization
title_fullStr NASQAR: a web-based platform for high-throughput sequencing data analysis and visualization
title_full_unstemmed NASQAR: a web-based platform for high-throughput sequencing data analysis and visualization
title_short NASQAR: a web-based platform for high-throughput sequencing data analysis and visualization
title_sort nasqar: a web-based platform for high-throughput sequencing data analysis and visualization
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7322916/
https://www.ncbi.nlm.nih.gov/pubmed/32600310
http://dx.doi.org/10.1186/s12859-020-03577-4
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