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

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          Abstract

          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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          Most cited references13

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          Pathview: an R/Bioconductor package for pathway-based data integration and visualization

          Summary: Pathview is a novel tool set for pathway-based data integration and visualization. It maps and renders user data on relevant pathway graphs. Users only need to supply their data and specify the target pathway. Pathview automatically downloads the pathway graph data, parses the data file, maps and integrates user data onto the pathway and renders pathway graphs with the mapped data. Although built as a stand-alone program, Pathview may seamlessly integrate with pathway and functional analysis tools for large-scale and fully automated analysis pipelines. Availability: The package is freely available under the GPLv3 license through Bioconductor and R-Forge. It is available at http://bioconductor.org/packages/release/bioc/html/pathview.html and at http://Pathview.r-forge.r-project.org/. Contact: luo_weijun@yahoo.com Supplementary information: Supplementary data are available at Bioinformatics online.
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            Docker: lightweight linux containers for consistent development and deployment

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              • Article: not found

              Multiplex chromatin interactions with single-molecule precision

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                Author and article information

                Contributors
                ay21@nyu.edu
                nd48@nyu.edu
                jdr400@nyu.edu
                mkhalfan@nyu.edu
                kcg1@nyu.edu
                Journal
                BMC Bioinformatics
                BMC Bioinformatics
                BMC Bioinformatics
                BioMed Central (London )
                1471-2105
                29 June 2020
                29 June 2020
                2020
                : 21
                : 267
                Affiliations
                [1 ]GRID grid.440573.1, NYU Abu Dhabi Center for Genomics & Systems Biology, ; Division of Biological Sciences, Abu Dhabi, United Arab Emirates
                [2 ]Center for Genomics & Systems Biology, Department of Biology, New York University, New York, 10003 United States
                Author information
                http://orcid.org/0000-0001-9769-4624
                Article
                3577
                10.1186/s12859-020-03577-4
                7322916
                32600310
                09055004-5d9b-4bad-8e3d-c307786a730a
                © 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.

                History
                : 8 September 2019
                : 1 June 2020
                Categories
                Software
                Custom metadata
                © The Author(s) 2020

                Bioinformatics & Computational biology
                transcriptomics,graphical user interface,interactive visualization,exploratory data analysis

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