Viewing RNA-seq data on the entire human genome

Eric M Weitz; Lorena Pantano; Jingzhi Zhu; Bennett Upton; Ben Busby

doi:10.12688/f1000research.9762.1

Viewing RNA-seq data on the entire human genome

F1000Res. 2017 Apr 28:6:596. doi: 10.12688/f1000research.9762.1. eCollection 2017.

Authors

Eric M Weitz¹, Lorena Pantano², Jingzhi Zhu³, Bennett Upton⁴, Ben Busby¹

Affiliations

¹ National Center for Biotechnology Information, U.S. National Library of Medicine, Bethesda, MD, 20894, USA.
² Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA.
³ Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
⁴ LSU Shreveport Laboratory for Advanced Biomedical Informatics, Shreveport, LA, 71105, USA.

Abstract

RNA-Seq Viewer is a web application that enables users to visualize genome-wide expression data from NCBI's Sequence Read Archive (SRA) and Gene Expression Omnibus (GEO) databases. The application prototype was created by a small team during a three-day hackathon facilitated by NCBI at Brandeis University. The backend data pipeline was developed and deployed on a shared AWS EC2 instance. Source code is available at https://github.com/NCBI-Hackathons/rnaseqview.

Keywords: RNA-seq; ideogram; javascript; next generation sequencing.

Grants and funding

Work on this project by Eric Weitz and Ben Busby was supported by the Intramural Research Program of the National Institutes of Health (NIH)/National Library of Medicine (NLM)/National Center for Biotechnology Information (NCBI).