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NASQAR: a web-based platform for high-throughput sequencing data analysis and visualization.
Yousif, Ayman; Drou, Nizar; Rowe, Jillian; Khalfan, Mohammed; Gunsalus, Kristin C.
Afiliação
  • Yousif A; NYU Abu Dhabi Center for Genomics & Systems Biology, Division of Biological Sciences, Abu Dhabi, United Arab Emirates.
  • Drou N; NYU Abu Dhabi Center for Genomics & Systems Biology, Division of Biological Sciences, Abu Dhabi, United Arab Emirates.
  • Rowe J; NYU Abu Dhabi Center for Genomics & Systems Biology, Division of Biological Sciences, Abu Dhabi, United Arab Emirates.
  • Khalfan M; Center for Genomics & Systems Biology, Department of Biology, New York University, New York, 10003, United States.
  • Gunsalus KC; NYU Abu Dhabi Center for Genomics & Systems Biology, Division of Biological Sciences, Abu Dhabi, United Arab Emirates. kcg1@nyu.edu.
BMC Bioinformatics ; 21(1): 267, 2020 Jun 29.
Article em En | MEDLINE | ID: mdl-32600310
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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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Sequenciamento de Nucleotídeos em Larga Escala Idioma: En Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Emirados Árabes Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Sequenciamento de Nucleotídeos em Larga Escala Idioma: En Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Emirados Árabes Unidos