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

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Ayman Yousif ◽  
Nizar Drou ◽  
Jillian Rowe ◽  
Mohammed Khalfan ◽  
Kristin C. Gunsalus
Genomics ◽  
2017 ◽  
Vol 109 (2) ◽  
pp. 83-90 ◽  
Author(s):  
Yan Guo ◽  
Yulin Dai ◽  
Hui Yu ◽  
Shilin Zhao ◽  
David C. Samuels ◽  
...  

PLoS ONE ◽  
2014 ◽  
Vol 9 (1) ◽  
pp. e85879 ◽  
Author(s):  
Fabrice P. A. David ◽  
Julien Delafontaine ◽  
Solenne Carat ◽  
Frederick J. Ross ◽  
Gregory Lefebvre ◽  
...  

PLoS ONE ◽  
2019 ◽  
Vol 14 (10) ◽  
pp. e0222512
Author(s):  
Edoardo Morandi ◽  
Matteo Cereda ◽  
Danny Incarnato ◽  
Caterina Parlato ◽  
Giulia Basile ◽  
...  

2012 ◽  
Vol 12 (6) ◽  
pp. 1058-1067 ◽  
Author(s):  
Pierre Wit ◽  
Melissa H. Pespeni ◽  
Jason T. Ladner ◽  
Daniel J. Barshis ◽  
François Seneca ◽  
...  

2019 ◽  
Author(s):  
Ayman Yousif ◽  
Nizar Drou ◽  
Jillian Rowe ◽  
Mohammed Khalfan ◽  
Kristin C Gunsalus

AbstractBackgroundAs 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).ResultsNASQAR 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.ConclusionsNASQAR 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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