BMC BioinformaticsBioinformaticsPeer-reviewed journal article
NASQAR: A web-based platform for High-throughput sequencing data analysis and visualization
Ayman Yousif, Nizar DrouiD, Jillian D Rowe, Mohammed Khalfan, Kristin C. GunsalusiD
- Citations
- 57
- FWCI
- 3.24
- Field percentile
- top 6%
Abstract
BackgroundAs 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.
- assay: bulk RNA-seq
- assay: metagenomics
- assay: scRNA-seq
- research focus: software / tool
- research focus: database / resource
- research focus: benchmarking
- approach: experimental assay
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Rnalys: An Interactive Web Application for Transcriptomic Data Analysis and Visualization
Christoffer Frisk·bioRxiv·Feb 12, 2025
- VizR: An Interactive Web Platform for End-to-End RNA-Seq Analysis and Visualization in Plant Biology
Woo-Taek Jeon, Hoon Jung, … Yuree Lee·bioRxiv·Jul 24, 2026
- RNAlysis: analyze your RNA sequencing data without writing a single line of code
Guy Teichman, Dror Cohen, … Oded Rechavi·BMC BiologyPeer-reviewed·Apr 6, 2023
- ASAP: a Web-based platform for the analysis and inter-active visualization of single-cell RNA-seq data
Vincent Gardeux, Fabrice P.A. David, … Bart Deplancke·BioinformaticsPeer-reviewed·May 23, 2017
- HTSeq - A Python framework to work with high-throughput sequencing data
Simon Anders, Paul Theodor Pyl, Wolfgang Huber·BioinformaticsPeer-reviewed·Sep 25, 2014
- SPEAQeasy: a Scalable Pipeline for Expression Analysis and Quantification for R/Bioconductor-powered RNA-seq analyses
Nicholas J. Eagles, Emily E. Burke, … Leonardo Collado‐Torres·BMC BioinformaticsPeer-reviewed·May 1, 2021