TY - JOUR
T1 - NASQAR
T2 - A web-based platform for high-throughput sequencing data analysis and visualization
AU - Yousif, Ayman
AU - Drou, Nizar
AU - Rowe, Jillian
AU - Khalfan, Mohammed
AU - Gunsalus, Kristin C.
AU - Gunsalus, Kristin C.
N1 - Publisher Copyright:
© 2020 The Author(s).
PY - 2020/6/29
Y1 - 2020/6/29
N2 - 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.
AB - 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.
KW - Exploratory data analysis
KW - Graphical user interface
KW - Interactive visualization
KW - Transcriptomics
UR - http://www.scopus.com/inward/record.url?scp=85087426047&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85087426047&partnerID=8YFLogxK
U2 - 10.1186/s12859-020-03577-4
DO - 10.1186/s12859-020-03577-4
M3 - Article
C2 - 32600310
AN - SCOPUS:85087426047
SN - 1471-2105
VL - 21
JO - BMC bioinformatics
JF - BMC bioinformatics
IS - 1
M1 - 267
ER -